Arab Climate Change Assessment Report: Introduction

ARAB CLIMATE CHANGE ASSESSMENT REPORT MAIN REPORT

Regional Initiative for the Assessment of Climate Change Impacts on Water Resources and Socio-Economic Vulnerability in the Arab Region ARAB CLIMATE CHANGE ASSESSMENT REPORT MAIN REPORT

Regional Initiative for the Assessment of Climate Change Impacts on Water Resources and Socio-Economic Vulnerability in the Arab Region

RICCAR PARTNERS

DONORS ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

By the United Nations Economic and Social Commission for Western Asia (ESCWA).

All rights reserved under International Copyright Conventions. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without prior permission in writing from the publisher. Inquiries should be addressed to the Sustainable Development Policies Division, Economic and Social Commission for Western Asia, P.O. Box 11-8575, Beirut, Lebanon.

Email: [email protected] Website: www.escwa.un.org

Available through: United Nations Publication E/ESCWA/SDPD/2017/RICCAR/Report

Reference as: United Nations Economic and Social Commission for Western Asia (ESCWA) et al. 2017. Arab Climate Change Assessment Report – Main Report. Beirut, E/ESCWA/SDPD/2017/RICCAR/Report.

Authors: United Nations Economic and Social Commission for Western Asia (ESCWA) Arab Center for the Studies of Arid Zones and Dry Lands (ACSAD) of the League of Arab States Food and Agriculture Organization of the United Nations (FAO) Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ) League of Arab States Swedish Meteorological and Hydrological Institute (SMHI) United Nations Environment Programme (UN Environment) United Nations Educational, Scientific and Cultural Organization (UNESCO) Office in Cairo United Nations Office for Disaster Risk Reduction (UNISDR) United Nations University Institute for Water, Environment and Health (UNU-INWEH) World Meteorological Organization (WMO)

Disclaimer: The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

The opinions expressed in this technical material are those of the authors and do not necessarily reflect the views of the United Nations Member States, the Government of Sweden, the Government of the Federal Republic of Germany, the League of Arab States or the United Nations Secretariat.

Cover photo © Kertu – Fotolia.com #131675281

Layout: Ghazal Lababidi Marilynn Dagher

2 PREFACE

The Regional Initiative for the Assessment of Climate Change Impacts on Water Resources and Socio-Economic Vulnerability in the Arab Region (RICCAR) is a joint initiative of the United Nations and the League of Arab States launched in 2010.

RICCAR is implemented through a collaborative partnership involving 11 regional and specialized organizations, namely the United Nations Economic and Social Commission for Western Asia (ESCWA), Arab Center for the Studies of Arid Zones and Dry Lands (ACSAD), Food and Agriculture Organization of the United Nations (FAO), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), League of Arab States, Swedish Meteorological and Hydrological Institute (SMHI), United Nations Environment Programme (UN Environment), United Nations Educational, Scientific and Cultural Organization (UNESCO) Office in Cairo, United Nations Office for Disaster Risk Reduction (UNISDR), United Nations University Institute for Water, Environment and Health (UNU-INWEH), and World Meteorological Organization (WMO). ESCWA coordinates the regional initiative. Funding for RICCAR is provided by the Government of Sweden and the Government of the Federal Republic of Germany.

RICCAR is implemented under the auspices of the Arab Ministerial Water Council and derives its mandate from resolutions adopted by this council as well as the Council of Arab Ministers Responsible for the Environment, the Arab Permanent Committee for Meteorology and the 25th ESCWA Ministerial Session.

Funding for the preparation of this report and its technical annex was provided by the Swedish Government through the Swedish International Development Cooperation Agency.

3 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

CONTENTS PART I. IMPACT ASSESSMENT

PREFACE 3 FOREWORD 19 CHAPTER 1 CONTRIBUTORS AND ACKNOWLEDGEMENTS 20 PURSUING REGIONAL CLIMATE MODELLING AND HYDROLOGICAL MODELLING IN THE ARAB REGION 67 ACRONYMS AND ABBREVIATIONS 22 1.1 Global climate modelling 67 1.1.1 Reference and projection periods 68 OVERVIEW 1.1.2 Representative concentration pathways 68 1.2 Regional climate modelling 69 BACKGROUND 29 1.2.1 The Arab Domain 70 1.2.2 Regional climate modelling projections 72 1 Mandates and partnerships 30 1.3 Regional hydrological modelling 73 2 Objectives 31 1.3.1 Bias correction for hydrological modelling 73 3 Implementation framework 31 1.3.2 Hydrological models applied 74 1.4 Explanation of analysis and presentation of results 76 OVERVIEW 33 1.4.1 Ensemble analysis 76 1 Integrated assessment methodology 33 1.4.2 Regional climate modelling outputs 76 1.4.3 Regional hydrological modelling outputs 76 2 Structure of the report 34 1.4.4 Extreme event indices 78 1.4.5 Seasonal outputs 80 1.4.6 Subdomains 80 BASELINE INFORMATION AND DATASETS 35 Endnotes 82 1 Climate characteristics of the Arab region 35 References 83 1.1 Climate zones and features 35 1.2 Atmospheric patterns affecting climate variability 36 1.3 Extreme events and climate related hazards 37

2 Climate diagnostics 39 CHAPTER 2 2.1 Global observed climate trends 39 2.2 Regional climate observations 40 REGIONAL CLIMATE MODELLING RESULTS FOR THE ARAB DOMAIN AND SELECTED SUBDOMAINS 87 3 Climate indices and data sources 43 3.1 Essential climate variables 43 2.1 Projected change in climate across the 3.2 Extreme event Indices 43 Arab Domain 87 3.3 Meteorological data sources 45 2.1.1 Change in temperature 87 3.4 Water resources in the Arab region 47 2.1.2 Change in precipitation 88 2.1.3 Changes in extreme temperature indices 92 4 Topographic and terrestrial features and 2.1.4 Changes in extreme precipitation indices 94 data sources 49 4.1 Topographical features of the Arab region 49 2.2 Comparative analysis with other regional 4.2 Topographic and other terrestrial data sources 52 climate modelling assessments 97 2.2.1 IPCC AR5 findings relating to Arab States 97 5 Socio-economic data sources 53 2.2.2 Findings from other corresponding climate 5.1 Demographic datasets 53 projections 98 5.2 Economic datasets 53 5.3 Technology-related datasets 53 2.2.3 Findings from CORDEX MENA compared to 5.4 Equity-related datasets 53 CORDEX AFRICA 99 6 Disaster loss databases 53 2.3 Projected change in climate in the Moroccan 6.1 Main findings from disaster loss databases Highlands 105 in selected Arab States 54 2.4 Projected change in climate along the 6.2 Using historical disaster data for climate Mediterranean Coast 105 change analysis 55 Endnotes 108 Endnotes 56 References 109 References 58

4 CHAPTER 3 REGIONAL HYDROLOGICAL MODELLING RESULTS FOR 5.1.2 Drought events 154 THE ARAB REGION AND SELECTED SUBDOMAINS 113 5.1.3 Extreme flood events 154 3.1 Projected changes in water availability due to 5.2 Nahr el Kabir River basin – Lebanon/ climate change in the Arab region 113 Syrian Arab Republic 155 3.1.1 Changes in runoff 113 5.2.1 Extreme temperature and precipitation 155 3.1.2 Changes in evapotranspiration 113 5.2.2 Drought events 157 3.2 Moroccan Highlands 118 5.2.3 Extreme flood events 158 3.3 Mediterranean Coast 119 5.3 Wadi Diqah River basin 159 5.3.1 Extreme temperature and precipitation 159 Endnotes 120 5.3.2 Drought events 161 References 120 5.3.3 Extreme flood events 162 5.4 Medjerda River basin 163 5.4.1 Extreme temperature and precipitation 163 5.4.2 Drought events 165 CHAPTER 4 5.4.3 Extreme flood events 167 FINDINGS FOR SELECTED SHARED WATER BASINS 5.5 Summary of key findings 167 IN THE ARAB REGION 121 Endnotes 168 4.1 Nile River basin 122 References 168 4.1.1 Overview and subdomain selection 122 4.1.2 Vulnerable sectors 122 4.1.3 Regional climate modelling findings 123 4.1.4 Regional hydrological modelling findings 125 CHAPTER 6 4.2 Tigris River and Euphrates River basins 126 4.2.1 Overview and subdomain selection 126 IMPACT OF CLIMATE CHANGE ON THE 4.2.2 Vulnerable sectors 126 AGRICULTURAL SECTOR 169 4.2.3 Regional climate modelling findings 128 6.1 Impact on cropping systems 170 4.2.4 Regional hydrological modelling findings 131 6.2 Impact on livestock systems 173 4.3 Medjerda River basin 133 6.3 Impact on fisheries and aquaculture 173 4.3.1 Overview and subdomain selection 133 4.3.2 Vulnerable sectors 133 6.4 Impact on forestry 173 4.3.3 Regional climate modelling findings 134 6.5 Impact on selected crops in Egypt, 4.3.4 Regional hydrological modelling findings 136 Lebanon and Jordan 175 4.4 Jordan River basin 137 6.6 Conclusion 178 4.4.1 Overview and subdomain selection 137 Endnotes 180 4.4.2 Vulnerable sectors 137 References 180 4.4.3 Regional climate modelling findings 139 4.4.4 Regional hydrological modelling findings 141 4.5 Senegal River basin 142 4.5.1 Overview and subdomain selection 142 CHAPTER 7 4.5.2 Vulnerable sectors 142 4.5.3 Regional climate modelling findings 144 IMPACT OF CLIMATE CHANGE ON HUMAN HEALTH IN 4.5.4 Regional hydrological modelling findings 144 SELECTED AREAS 181 Endnotes 147 7.1 Heat index considerations and findings 182 References 148 7.2 Case studies of neglected tropical diseases 183 7.2.1 Conceptual framework 183 7.2.2 Leishmaniasis 184 7.2.3 Schistosomiasis 185 CHAPTER 5 7.2.4 Implications and conclusions 187 7.2.5 Limitations 188 EXTREME EVENTS IMPACT ASSESSMENT FOR SELECTED BASINS 153 Endnotes 190 References 191 5.1 Indicators and events selected for analysis 154 5.1.1 Extreme temperature and precipitation 154 5 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

PART II. INTEGRATED VULNERABILITY 11.2.1 Reference period 255 11.2.2 Future periods 259 ASSESSMENT 11.2.3 Hotspots 265 CHAPTER 8 11.3 Agriculture Sector: Overall vulnerability 265 11.3.1 Reference period 265 BACKGROUND AND METHODOLOGY 197 11.3.2 Future periods 266 8.1 Conceptual framework 197 11.3.3 Hotspots 268 8.2 Target sectors and impacts 198 Endnotes 269 8.3 Methodology development process 198 References 269 8.4 Integrated mapping methodology 199 8.5 Presentation of results 201 CHAPTER 12 Endnotes 202 References 203 INFRASTRUCTURE AND HUMAN SETTLEMENTS SECTOR – VULNERABILITY 271 12.1 Inland flooding area 271

12.1.1 Reference period 272 CHAPTER 9 12.1.2 Future periods 275 WATER SECTOR – VULNERABILITY 205 12.1.3 Hotspots 280 9.1 Water availability 205 Endnotes 281 9.1.1 Reference period 206 References 281 9.1.2 Future periods 208 9.1.3 Hotspots 213 Endnotes 214 References 214 CHAPTER 13 PEOPLE SECTOR – VULNERABILITY 283 13.1 Water available for drinking 283 13.1.1 Reference period 284 CHAPTER 10 13.1.2 Future periods 287 BIODIVERSITY AND ECOSYSTEMS SECTOR – 13.1.3 Hotspots 292 VULNERABILITY 217 13.2 Health conditions due to heat stress 292 10.1 Area covered by forests 217 13.2.1 Reference period 293 10.1.1 Reference period 218 13.2.2 Future period 295 10.1.2 Future periods 221 13.2.3 Hotspots 301 10.1.3 Hotspots 226 13.3 Employment rate for the agricultural sector 301 10.2 Area covered by wetlands 227 13.3.1 Reference period 302 10.2.1 Reference period 227 13.3.2 Future periods 305 10.2.2 Future periods 230 13.3.3 Hotspots 310 10.2.3 Hotspots 235 13.4 People Sector: Overall vulnerability 311 10.3 Biodiversity and Ecosystems Sector: 13.4.1 Reference period 311 Overall vulnerability 236 13.4.2 Future periods 311 10.3.1 Reference period 236 13.4.3 Hotspots 312 10.3.2 Future periods 237 Endnotes 315 10.3.3 Hotspots 239 References 315 Endnotes 242 References 243 CHAPTER 14 INTEGRATED VULNERABILITY ASSESSMENT – SUMMARY 317 14.1 Overview of general vulnerability trends 317 14.2 Hotspots 319 CHAPTER 11 AGRICULTURE SECTOR – VULNERABILITY 245 11.1 Water available for crops 245 CONCLUSION 11.1.1 Reference period 246 11.1.2 Future periods 248 Main findings and conclusions 325 11.1.3 Hotspots 254 Next steps 328 11.2 Water available for livestock 255 66 FIGURES

FIGURE 1: FIGURE 8: FIGURE 14: FIGURE 20: RICCAR implementation Hazard frequency by type (for the Schematic depiction of the one- Change in mean temperature (°C) framework six countries combined) way RCM nesting technique over time for the Arab Domain as a 30-year moving average for six individual climate projections

32 55 69 88

FIGURE 2: FIGURE 9: FIGURE 15: FIGURE 21: RICCAR-related consultative Combined economic losses by CORDEX domains Mean change in annual mechanisms informing integrated hazard type in US$ precipitation (mm/month) for mid- assessment and end-century for ensemble of three RCP 4.5 and RCP 8.5 projections compared to the reference period

32 55 70 89

FIGURE 3: FIGURE 10: FIGURE 16: FIGURE 22: RICCAR integrated assessment Combined economic losses by Different domain configurations Mean change in seasonal methodology country in US$ tested for the CORDEX-MENA precipitation for mid- and Domain (Arab Domain) end-century for ensemble of three RCP 4.5 projections compared to the reference period

33 55 71 90

FIGURE 4: FIGURE 17: FIGURE 23: Mean annual precipitation CORDEX-MENA Domain Mean change in seasonal distribution across the Arab precipitation for mid- and end- region (1986-2005) century for ensemble of three RCP 8.5 projections compared to CHAPTER 1 the reference period

36 71 90

FIGURE 5: FIGURE 11: FIGURE 18: FIGURE 24: Observed globally averaged Time periods considered for Location of subdomains identified Agreement on mean change in combined land- and analysis for analysis annual precipitation from the ocean-surface temperature reference period between the anomaly until 2012 ensemble of three RCP 4.5 and (relative to 1986–2005) three RCP 8.5 projections for mid- and end-century

39 68 80 91

FIGURE 6: FIGURE 12: FIGURE 25: Global mean sea-level change Representative concentration Mean change in the number of until 2010 (relative to 1986–2005) pathways summer days (SU) (days/yr) for mid- and end-century for ensemble of three RCP 4.5 and CHAPTER 2 RCP 8.5 projections compared to the reference period

39 68 92

FIGURE 7: FIGURE 13: FIGURE 19: FIGURE 26: Globally averaged observed Global temperature change Mean change in annual Mean change in the number of hot greenhouse gas projections for RCP temperature (°C) for mid- and days (SU35) (days/yr) for mid- and concentrations until 2011 scenarios under CMIP5 end-century for ensemble of three end-century for ensemble of three RCP 4.5 and RCP 8.5 projections RCP 4.5 and RCP 8.5 projections compared to the reference compared to the reference period period

39 69 88 93

7 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

FIGURE 27: FIGURE 34: FIGURE 41: FIGURE 47: Mean change in the number of Spatial boundaries of the Future changes in different Agreement on mean change in very hot days (SU40) (days/yr) geographical regions used in the variables from ALADIN-Climate annual evapotranspiration for for mid- and end-century for IPCC 5th Assessment Report projections for RCP 8.5 for the mid- and end-century between the ensemble of three RCP 4.5 and future period 2036–2065 ensemble of three RCP 4.5 RCP 8.5 projections compared to compared to the reference period and RCP 8.5 projections from the the reference period 1971–2000 reference period

93 98 103 117

FIGURE 28: FIGURE 35: FIGURE 42: FIGURE 48: Mean change in the number of Comparison between CORDEX Mean change in temperature, Mean change in runoff and tropical nights (TR) (days/yr) MENA and CORDEX AFRICA precipitation and selected evapotranspiration (using HYPE for mid- and end-century for outputs for temperature change at extreme events indices over time and VIC) over time for ensemble ensemble of three RCP 4.5 and end-century for ensemble of three RCP 4.5 of three RCP 4.5 and RCP 8.5 RCP 8.5 projections compared to and RCP 8.5 projections for the projections for the Moroccan the reference period Moroccan Highlands Highlands

94 100 106 118

FIGURE 29: FIGURE 36: FIGURE 43: FIGURE 49: Mean change in the maximum Number of CORDEX AFRICA Mean change in temperature, Comparison between 25 km length of dry spell (CDD) (days/yr) models within the range of precipitation and selected (MNA22) and 50 km (MNA44) for mid- and end-century for CORDEX MENA models for extreme event indices over time resolutions for mean change in ensemble of three RCP 4.5 and temperature at end-century for ensemble of three RCP 4.5 runoff (using HYPE) over time for RCP 8.5 projections compared to and RCP 8.5 projections for the two RCP 8.5 projections for the the reference period Mediterranean Coast Moroccan Highlands

95 100 107 118

FIGURE 30: FIGURE 37: FIGURE 50: Mean change in the maximum Comparison between CORDEX Mean change in runoff and length of wet spell (CWD) MENA and CORDEX AFRICA evapotranspiration (using HYPE (days/yr) for mid- and end-century outputs for precipitation change and VIC) over time for ensemble for ensemble of three RCP 4.5 and at end-century of three RCP 4.5 and RCP 8.5 RCP 8.5 projections compared to CHAPTER 3 projections for the Mediterranean the reference period Coast

95 101 119

FIGURE 31: FIGURE 38: FIGURE 44: FIGURE 51: Mean change in the number of Number of CORDEX Africa models Mean change in annual runoff Comparison between 25 km 10 mm precipitation days (R10) within the range of CORDEX MENA (mm/month) for mid- and (MNA22) and 50 km (MNA44) (days/yr) for mid- and end-century models for precipitation at end- end-century for the ensemble resolutions for mean change in for ensemble of three RCP 4.5 and century of three RCP 4.5 and RCP 8.5 runoff (using HYPE) over time for RCP 8.5 projections compared to projections compared to the two RCP 8.5 projections for the the reference period reference period using two Mediterranean Coast hydrological models 96 101 114 119

FIGURE 32: FIGURE 39: FIGURE 45: Mean change in the number of Spatial extent of the Domain Agreement on mean change 20 mm precipitation days (R20) considered using in annual runoff for mid- and (days/yr) for mid- and end-century ALADIN-Climate end-century between the for ensemble of three RCP 4.5 and ensemble of three RCP 4.5 and RCP 8.5 projections compared to RCP 8.5 projections from the CHAPTER 4 the reference period reference period

96 102 115

FIGURE 33: FIGURE 40: FIGURE 46: FIGURE 52: Change in the Simple Precipitation Future changes in different Mean change in annual Map of the Nile River basin and Intensity Index (SDII) (mm) variables from ALADIN-Climate evapotranspiration (mm/month) extent of subdomain for mid- and end-century for projections for RCP 4.5 for for mid- and end-century for the ensemble of three RCP 4.5 and the future period 2036–2065 ensemble of three RCP 4.5 and RCP 8.5 projections compared to compared to the reference period RCP 8.5 projections compared to the baseline period 1971–2000 the reference period using two hydrological models

97 103 116 122

8 FIGURE 53: FIGURE 60: FIGURE 67: FIGURE 74: Mean change in temperature, Comparison between 25 km Map of the Jordan River Basin and Comparison between 25 km precipitation and selected (MNA22) and 50 km (MNA44) subdomain extent (MNA22) and 50 km (MNA44) extreme events indices over time resolutions for mean change resolutions for mean change for ensemble of three RCP 4.5 and in runoff and discharge (using in runoff and discharge (using RCP 8.5 projections for the Blue HYPE) over time for two RCP 8.5 HYPE) over time for two RCP 8.5 Nile Headwaters projections for the Tigris River projections for the Senegal River Headwaters Headwaters 124 132 137 146

FIGURE 54: FIGURE 61: FIGURE 68: Mean change in runoff (using Mean change in runoff (using Mean change in temperature, HYPE and VIC) and discharge HYPE and VIC) and discharge precipitation and selected (using HYPE) over time for (using HYPE) over time for extreme events indices over time ensemble of three RCP 4.5 and ensemble of three RCP 4.5 and for ensemble of three RCP 4.5 RCP 8.5 projections for the Blue RCP 8.5 projections for the and RCP 8.5 projections for the CHAPTER 5 Nile Headwaters Euphrates River Headwaters Jordan River Basin

125 132 140

FIGURE 55: FIGURE 62: FIGURE 69: FIGURE 75: Comparison between 25 km Comparison between 25 km Mean change in runoff (using Extreme events case studies: (MNA22) and 50 km (MNA44) (MNA22) and 50 km (MNA44) HYPE and VIC) and discharge study area resolutions for mean change resolutions for mean change (using HYPE) over time for in runoff and discharge (using in runoff and discharge (using ensemble of three RCP 4.5 and HYPE) over time for two RCP HYPE) over time for two RCP 8.5 RCP 8.5 projections for the Jordan 8.5 projections for the Blue Nile projections for the Euphrates River Headwaters River Headwaters 125 132 141 153

FIGURE 56: FIGURE 63: FIGURE 70: FIGURE 76: Map of the Tigris and Euphrates Map of the Medjerda River Basin Comparison between 25 km Mean change in selected extreme river basins and subdomain and subdomain extent (MNA22) and 50 km (MNA44) events indices over time for extent resolutions for mean change ensemble of three RCP 4.5 and in runoff and discharge (using RCP 8.5 projections for the HYPE) over time for two RCP 8.5 Nahr el Kabir River basin projections for the Jordan River

126 133 141 156

FIGURE 57: FIGURE 64: FIGURE 71: FIGURE 77: Mean change in temperature, Mean change in temperature, Map of the Senegal River Basin Projected six-month SPI trends precipitation and selected precipitation and selected and subdomain extent over time for ensemble of three extreme event indices over time extreme events indices over time RCP 4.5 and RCP 8.5 projections for ensemble of three RCP 4.5 and for ensemble of three RCP 4.5 for the Nahr el Kabir River basin RCP 8.5 projections for the Tigris and RCP 8.5 projections for the River Headwaters Medjerda River basin

129 135 142 158

FIGURE 58: FIGURE 65: FIGURE 72: FIGURE 78: Mean change in temperature, Mean change in runoff (using Mean change in temperature, Projected 12-month SPI trends precipitation and selected HYPE and VIC) and discharge precipitation and selected over time for ensemble of three extreme events indices over time (using HYPE) over time for extreme events indices over time RCP 4.5 and RCP 8.5 projections for ensemble of three RCP 4.5 ensemble of three RCP 4.5 and for ensemble of three RCP 4.5 for the Nahr el Kabir River basin and RCP 8.5 projections for the RCP 8.5 projections for the and RCP 8.5 projections for the Euphrates River Headwaters Medjerda River Senegal River Headwaters

130 136 145 158

FIGURE 59: FIGURE 66: FIGURE 73: FIGURE 79: Mean change in runoff (using Comparison between 25 km Mean change in runoff (using Mean number of 90th percentile HYPE and VIC) and discharge (MNA22) and 50 km (MNA44) HYPE and VIC) and discharge high-flow days for different (using HYPE) over time for resolutions for mean change (using HYPE) over time for emission scenarios and time ensemble of three RCP 4.5 and in runoff and discharge (using ensemble of three RCP 4.5 and periods for the Nahr el Kabir River RCP 8.5 projections for the Tigris HYPE) over time for two RCP 8.5 RCP 8.5 projections for the basin River Headwaters projections for the Medjerda Senegal River Headwaters River 131 136 146 158

9 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

FIGURE 80: FIGURE 87: FIGURE 93: FIGURE 100: Mean change in the 100-year Projected six-month SPI trends Distribution (%) of major farming Simulated yield and growing- flood value (m3/s) over time for over time for ensemble of three systems in the vulnerability period duration of wheat and ensemble of three RCP 4.5 and RCP 4.5 and RCP 8.5 projections classes (end-century) barley for the reference period, RCP 8.5 projections for the Nahr for the Medjerda River basin mid-century and end-century for el Kabir River basin RCP 4.5 and RCP 8.5 in Jordan

158 166 171 178

FIGURE 81: FIGURE 88: FIGURE 94: Mean change in selected extreme Projected 12-month SPI trends Crop area distribution in events indices over time for over time for ensemble of three the vulnerability classes ensemble of three RCP 4.5 and RCP 4.5 projections for the (mid-century) RCP 8.5 projections for the Wadi Medjerda River basin Diqah River basin CHAPTER 7

160 166 172

FIGURE 82: FIGURE 89: FIGURE 95: FIGURE 101: Projected six-month SPI trends Mean number of 90th percentile Crop area distribution in Historical and projected exposure over time for ensemble of three high-flow days for different the vulnerability classes to Leishmaniasis in North Africa RCP 4.5 and RCP 8.5 projections emission scenarios and time (end-century) in November for the Wadi Diqah River basin periods for the Medjerda River basin

162 167 172 185

FIGURE 83: FIGURE 90: FIGURE 96: FIGURE 102: Projected 12-month SPI trends Mean change in the 100-year Proportion of irrigated crops Susceptibility and lack over time for ensemble of three flood value (m3/s) over time areas exposed to the highest two of adaptive capacity to RCP 4.5 and RCP 8.5 projections for ensemble of three RCP 4.5 classes of vulnerability leishmaniasis in Morocco for the Wadi Diqah River basin and RCP 8.5 projections for the Medjerda River basin

162 167 172 185

FIGURE 84: FIGURE 97: FIGURE 103: Mean number of 90th percentile Location of the pilot sites for Historical and projected exposure high-flow days for different investigating the impacts of to schistosomiasis in Egypt in emission scenarios and time climate change December periods for the Wadi Diqah River basin CHAPTER 6

162 174 186

FIGURE 85: FIGURE 91: FIGURE 98: FIGURE 104 : Mean change in the 100-year Major farming systems in the Simulated yield and growing- Susceptibility and lack flood value (m3/s) over time for Arab region period duration of maize, wheat of adaptive capacity to ensemble of three RCP 4.5 and and cotton for the reference schistosomiasis in Egypt RCP 8.5 projections for the Wadi period, mid-century and end- Diqah River basin century for RCP 4.5 and RCP 8.5 in Egypt

162 170 176 187

FIGURE 86: FIGURE 92: FIGURE 99: Mean change in selected extreme Distribution (%) of major farming Simulated yield and growing- event indices over time for systems in the vulnerability period duration of eggplant, maize ensemble of three RCP 4.5 and classes (mid-century) and potato for the reference RCP 8.5 projections for the period, mid-century and Medjerda River basin end-century for RCP 4.5 and RCP 8.5 in Lebanon

164 171 177

10 FIGURE 110: FIGURE 117: FIGURE 123: Water availability – Water availability – Area covered by forests – Adaptive capacity Mid-century RCP 8.5 – Reference period – Vulnerability Vulnerability CHAPTER 8

207 212 220

FIGURE 105: FIGURE 111: FIGURE 118: FIGURE 124: Components of vulnerability Water availability – Water availability – Area covered by forests – based on the IPCC AR4 approach Reference Period – End-century RCP 4.5 – Mid-century RCP 4.5 – Vulnerability Vulnerability Potential impact

197 208 212 221

FIGURE 106: FIGURE 112: FIGURE 119: FIGURE 125: Sectors and subsectors selected Water availability – Water availability – Area covered by forests – for the Arab region vulnerability Mid-century RCP 4.5 – End-century RCP 8.5 – Mid-century RCP 8.5 – assessment Potential impact Vulnerability Potential impact

198 209 213 222

FIGURE 107: FIGURE 113: FIGURE 126: Presentation of results Water availability – Area covered by forests – Mid-century RCP 8.5 – End-century RCP 4.5 – Potential impact Potential impact CHAPTER 10

201 209 222

FIGURE 114: FIGURE 120: FIGURE 127: Water availability – Impact chain and weights for area Area covered by forests – End-century RCP 4.5 – covered by forests End-century RCP 8.5 – Potential impact Potential impact CHAPTER 9

210 217 223

FIGURE 108: FIGURE 115: FIGURE 121: FIGURE 128: Impact chain and weights for Water availability – Area covered by forests – Area covered by forests – water availability End-century RCP 8.5 – Reference period – Mid-century RCP 4.5 – Potential impact Potential impact Vulnerability

205 210 218 224

FIGURE 109: FIGURE 116: FIGURE 122: FIGURE 129: Water availability – Water availability – Area covered by forests – Area covered by forests – Reference Period – Mid-century RCP 4.5 – Adaptive capacity Mid-century RCP 8.5 – Potential Impact Vulnerability Vulnerability

206 211 219 225

11 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

FIGURE 130: FIGURE 137: FIGURE 144: Area covered by forests – Area covered by wetlands – Biodiversity and ecosystems End-century RCP 4.5 – Mid-century RCP 8.5 – sector – Vulnerability – Vulnerability Potential impact Reference period CHAPTER 11

225 231 236

FIGURE 131: FIGURE 138: FIGURE 145: FIGURE 151: Area covered by forests – Area covered by wetlands – Biodiversity and ecosystems Impact chain and weights for End-century RCP 8.5 – End-century RCP 4.5 – sector – Vulnerability – water available for crops Vulnerability Potential impact Mid-century RCP 4.5

226 232 237 245

FIGURE 132: FIGURE 139: FIGURE 146: FIGURE 152: Impact chain and weights for area Area covered by wetlands – Biodiversity and ecosystems Water available for crops – covered by wetlands End-century RCP 8.5 – sector – Vulnerability – Reference period – Potential impact Mid-century RCP 8.5 Potential impact

227 232 238 247

FIGURE 133: FIGURE 140: FIGURE 147: FIGURE 153: Area covered by wetlands – Area covered by wetlands – Biodiversity and ecosystems Water available for crops – Reference period – Mid-century RCP 4.5 – sector – Vulnerability – Adaptive capacity Potential impact Vulnerability End-century RCP 4.5

228 233 238 247

FIGURE 134: FIGURE 141: FIGURE 148: FIGURE 154: Area covered by wetlands – Area covered by wetlands – Biodiversity and ecosystems Water available for crops – Adaptive capacity Mid-century RCP 8.5 – sector – Vulnerability – Reference period – Vulnerability End-century RCP 8.5 Vulnerability

229 234 239 248

FIGURE 135: FIGURE 142: FIGURE 149: FIGURE 155: Area covered by wetlands – Area covered by wetlands – Map of the Iraqi Marshlands Water available for crops – Reference period – End-century RCP 4.5 – highlighting the four key areas Mid-century RCP 4.5 – Vulnerability Vulnerability Potential impact

230 234 240 249

FIGURE 136: FIGURE 143: FIGURE 150: FIGURE 156: Area covered by wetlands – Area covered by wetlands – Change in the size of the southern Water available for crops – Mid-century RCP 4.5 – End-century RCP 8.5 – Marshes from 1973 to 2010 Mid-century RCP 8.5 – Potential impact Vulnerability Potential impact

231 235 240 250

12 FIGURE 157: FIGURE 164: FIGURE 171: FIGURE 178: Water available for crops – Water available for livestock – Water available for livestock – Agriculture sector – End-century RCP 4.5 – Reference Period – Mid-century RCP 4.5 – Vulnerability – Potential impact Potential impact Vulnerability End-century RCP 4.5

250 256 263 267

FIGURE 158: FIGURE 165: FIGURE 172: FIGURE 179: Water available for crops – Water available for livestock – Water available for livestock – Agriculture sector – End-century RCP 8.5 – Adaptive capacity Mid-century RCP 8.5 – Vulnerability – Potential impact Vulnerability End-century RCP 8.5

251 257 263 268

FIGURE 159: FIGURE 166: FIGURE 173: Water available for crops – Water available for livestock – Water available for livestock – Mid-century RCP 4.5 – Reference period – End-century RCP 4.5 – Vulnerability Vulnerability Vulnerability CHAPTER 12

252 258 264

FIGURE 160: FIGURE 167: FIGURE 174: FIGURE 180: Water available for crops – Water available for livestock – Water available for livestock – Impact chain and weights for Mid-century RCP 8.5 – Mid-century RCP 4.5 – End-century RCP 8.5 – inland flooding area Vulnerability Potential impact Vulnerability

253 259 264 271

FIGURE 161: FIGURE 168: FIGURE 175: FIGURE 181: Water available for crops – Water available for livestock – Agriculture sector – Inland flooding area – End-century RCP 4.5 – Mid-century RCP 8.5 – Vulnerability – Reference period – Vulnerability Potential impact Reference period Potential impact

253 260 265 273

FIGURE 162: FIGURE 169: FIGURE 176: FIGURE 182: Water available for crops – Water available for livestock – Agriculture sector – Inland flooding area – End-century RCP 8.5 – End-century RCP 4.5 – Vulnerability – Adaptive capacity Vulnerability Potential impact Mid-century RCP 4.5

254 260 266 274

FIGURE 163: FIGURE 170: FIGURE 177: FIGURE 183: Impact chain and weights for Water available for livestock – Agriculture sector – Inland flooding area – water available for livestock End-century RCP 8.5 – Vulnerability – Reference period – Potential impact Mid-century RCP 8.5 Vulnerability

255 261 267 275

13 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

FIGURE 184: FIGURE 191: FIGURE 197: FIGURE 204: Inland flooding area – Inland flooding area – Water available for drinking – Impact chain and weights for Mid-century RCP 4.5 – End-century RCP 8.5 – Mid-century RCP 8.5 – health conditions due to heat Potential impact Vulnerability Potential impact stress

276 280 288 292

FIGURE 185: FIGURE 198: FIGURE 205: Inland flooding area – Water available for drinking – Health conditions due to heat Mid-century RCP 8.5 – End-century RCP 4.5 – stress – Reference period – Potential impact Potential impact Potential impact CHAPTER 13

276 288 293

FIGURE 186: FIGURE 192: FIGURE 199: FIGURE 206: Inland flooding area – Impact chain and weights for Water available for drinking – Health conditions due to heat End-century RCP 4.5 – water available for drinking End-century RCP 8.5 – stress – Adaptive capacity Potential impact Potential impact

277 283 289 294

FIGURE 187: FIGURE 193: FIGURE 200: FIGURE 207: Inland flooding area – Water available for drinking – Water available for drinking – Health conditions due to heat End-century RCP 8.5 – Reference period – Mid-century RCP 4.5 – stress – Reference period – Potential impact Potential impact Vulnerability Vulnerability

277 285 290 295

FIGURE 188: FIGURE 194: FIGURE 201: FIGURE 208: Inland flooding area – Water available for drinking – Water available for drinking – Health conditions due to heat Mid-century RCP 4.5 – Adaptive capacity Mid-century RCP 8.5 – stress – Mid-century RCP 4.5 – Vulnerability Vulnerability Potential impact

278 285 290 296

FIGURE 189: FIGURE 195: FIGURE 202: FIGURE 209: Inland flooding area – Water available for drinking – Water available for drinking – Health conditions due to heat Mid-century RCP 8.5 – Reference period – End-century RCP 4.5 – stress – Mid-century RCP 8.5 – Vulnerability Vulnerability Vulnerability Potential impact

279 286 291 296

FIGURE 190: FIGURE 196: FIGURE 203: FIGURE 210: Inland flooding area – Water available for drinking – Water available for drinking – Health conditions due to heat End-century RCP 4.5 – Mid-century RCP 4.5 – End-century RCP 8.5 – stress – End-century RCP 4.5 – Vulnerability Potential impact Vulnerability Potential impact

279 287 291 297

14 FIGURE 211: FIGURE 218: FIGURE 225: FIGURE 232: Health conditions due to heat Employment rate for the Employment rate for the People Sector – Vulnerability – stress – End-century RCP 8.5 – agricultural sector – agricultural sector – End-century RCP 8.5 Potential impact Adaptive capacity Mid-century RCP 8.5 – Vulnerability

297 303 309 314

FIGURE 212: FIGURE 219: FIGURE 226: Health conditions due to heat Employment rate for the Employment rate for the stress – Mid-century RCP 4.5 – agricultural sector – agricultural sector – Vulnerability Reference period – End-century RCP 4.5 – Vulnerability Vulnerability CHAPTER 14

299 304 309

FIGURE 213: FIGURE 220: FIGURE 227: FIGURE 233: Health conditions due to heat Employment rate for the Employment rate for the Water sector – Vulnerability stress – Mid-century RCP 8.5 – agricultural sector – agricultural sector – hotspots – End-century RCP 8.5 Vulnerability Mid-century RCP 4.5 – End-century RCP 8.5 – Potential impact Vulnerability

299 305 310 320

FIGURE 214: FIGURE 221: FIGURE 228: FIGURE 234: Health conditions due to heat Employment rate for the People sector – Vulnerability – Biodiversity and ecosystems stress – End-century RCP 4.5 – agricultural sector – Reference period sector – Vulnerability hotspots – Vulnerability Mid-century RCP 8.5 – End-century RCP 8.5 Potential impact

300 306 311 320

FIGURE 215: FIGURE 222: FIGURE 229: FIGURE 235: Health conditions due to heat Employment rate for the People Sector – Vulnerability – Agriculture sector – Vulnerability stress – End-century RCP 8.5 – agricultural sector – Mid-century RCP 4.5 hotspots – End-century RCP 8.5 Vulnerability End-century RCP 4.5 – Potential impact

300 306 312 321

FIGURE 216: FIGURE 223: FIGURE 230: FIGURE 236: Impact chain and weights Employment rate for the People Sector – Vulnerability – Infrastructure and human for employment rate for the agricultural sector – Mid-century RCP 8.5 settlements sector – Vulnerability agricultural sector End-century RCP 8.5 – hotspots – End-century RCP 8.5 Potential impact

301 307 313 321

FIGURE 217: FIGURE 224: FIGURE 231: FIGURE 237: Employment rate for the Employment rate for the People Sector – Vulnerability – People sector – Vulnerability agricultural sector – agricultural sector – End-century RCP 4.5 hotspots – End-century RCP 8.5 Reference period – Mid-century RCP 4.5 – Potential impact Vulnerability

302 308 313 322

15 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

TABLES

TABLE 1: TABLE 8: TABLE 15: TABLE 22: Essential climate variables Extreme events indices studied Mean ensemble 100-year flood Percentage of study area by values (m3/s) for different vulnerability classification for emission scenarios and time area covered by forests periods for the Nahr el Kabir River basin 43 78 158 224

TABLE 2: TABLE 9: TABLE 16: TABLE 23: Climate Indices (developed by Comparison of temperature Extreme event indices values for Percentage of study area by the WMO Expert Team on Climate and SU40 indicator results for different emission scenarios and vulnerability classification for Change Detection and Indices) the RICCAR reference period time periods for the Wadi Diqah area covered by wetlands (1986–2005) and observed River basin station data (1980–2008)

44 79 161 233

TABLE 3: TABLE 10: TABLE 17: TABLE 24: Summary of losses and damage Comparison of precipitation Mean ensemble 100-year flood Percentage of study area by for selected Arab States for the results between RICCAR RCMs values (m3/s) for different vulnerability classification for specified data periods (1986–2005) and station data emission scenarios and time biodiversity and ecosystems (1980-2008) periods for the Wadi Diqah River sector basin

54 79 162 237

TABLE 4: TABLE 11: TABLE 18: TABLE 25: RCM simulations conducted over List of sub-domains considered Extreme event indices values for Percentage of study area by the CORDEX-MENA Domain by for analysis different emission scenarios and vulnerability classification for the Rossby Centre at SMHI under time periods for the Medjerda water availability for crops RICCAR River basin

72 81 165 251

TABLE 5: TABLE 12: TABLE 19: TABLE 26: Hydrological models applied Description of simulations Projected percentage of time with Water demand for selected crops under RICCAR moderate, severe and extreme in the Arab region drought conditions until the end of the century for the six-month SPI value and the 12-month SPI value in the Medjerda River basin

74 102 166 252

TABLE 6: TABLE 13: TABLE 20: TABLE 27: Description of the RCA4 Indicators presented Mean ensemble 100-year flood Virtual water content of selected ensembles values (m3/s) for different livestock in the Arab region emission scenarios and time periods for the Medjerda River basin

76 154 167 256

TABLE 7: TABLE 14: TABLE 21: TABLE 28: RCM and RHM output variables Extreme event indices values for Percentage of study area by Percentage of study area by different emission scenarios and vulnerability classification for vulnerability classification for time periods for Nahr el Kabir water availability water availability for livestock River basin

77 157 211 262

16 TABLE 29: TABLE 32: TABLE 35: TABLE 38: Percentage of ruminant Percentage of study area by Percentage of study area by Summary of vulnerability population by vulnerability vulnerability classification for vulnerability classification assessment results classification for each projected water available for drinking for employment rate for the scenario agricultural sector

262 289 307 318

TABLE 30: TABLE 33: TABLE 36: Percentage of study area by Percentage of study area by Averages for selected sensitivity vulnerability classification for the vulnerability classification for indicators for employment rate for agriculture sector health due to heat stress the agricultural sector

266 298 308

TABLE 31: TABLE 34: TABLE 37: Percentage of study area by Average climate parameters by Percentage of study area by vulnerability classification for vulnerability classification vulnerability classification for inland flooding area people sector

278 298 312

BOXES

BOX 1: BOX 4: BOX 7: Sand and dust storms in the Arab ALADIN-Climate projections for Implications of climate change for region the Arab region the Iraqi Marshlands

38 102 239

BOX 2: BOX 5: BOX 8: Siwa Oasis in Egypt Using RICCAR outputs to inform Country-level application of further basin research the integrated vulnerability assessment

51 146 322

BOX 3: BOX 6: Comparing RICCAR reference Recent disease outbreaks due to period data with observed data in climate conditions: yellow fever the Arabian Peninsula and other diseases

79 189

FOREWORD

This Arab Climate Change Assessment Report (ACCAR) regional-specific indicators related to geography, climate, is the outcome of work conducted within the framework water and vulnerability, based on scientific methods. of the Regional Initiative for the Assessment of Climate These findings are also the outcome of the partnership Change Impacts on Water Resources and Socio-Economic forged with the Adaptation to Climate Change in the Water Vulnerability in the Arab Region (RICCAR), which was Sector in the MENA Region (ACCWaM) project, which launched jointly by the League of Arab States and United contributed significantly to the development of the integrated Nations organizations as a response to the first Arab vulnerability assessment applied in this report. Declaration on Climate Change issued in December 2007. Both the preparation and the findings of this report have The report is the first regional assessment to informed policy dialogue on climate change at the Arab comprehensively assess the impact of climate change on regional level. It has enhanced the capacity of governments, water resources in the Arab region as a single geospatial unit experts and civil society to draw upon climate science by generating ensembles of regional climate and hydrological to inform decision-making by regularly informing, and modelling projections until the year 2100. It is also the first to engaging with, them throughout the preparatory process conduct an integrated assessment of these climate change via intergovernmental sessions, expert groups, consultative impacts as they effect the socioeconomic and environmental forums, workshops, working groups, task forces and high- vulnerability of Arab States. Previous analyses of climate level events. This has included deliberations that have taken change across the Arab region had been drawn from global place under the auspices of the Arab Ministerial Water assessments that segment Arab States between the Asian Council, the Arab Permanent Committee for Meteorology and African continents or various sub-domains; stand-alone and the Arab Group of climate change negotiators that modelling outputs; or country-level studies that aimed for reports to the Council of Arab Ministers Responsible for the a regionally representative picture, despite differences in Environment. assumptions, scenarios and methodologies. The Implementing Partners and Donors of the Regional The findings presented in this report fill this gap and are Initiative for the Assessment of Climate Change Impacts based on a common and uniform methodological framework on Water Resources and Socio-Economic Vulnerability in applied across the Arab region, which thus allows for the Arab Region are thus pleased to present to you – our regional dialogue and exchange among Arab stakeholder stakeholders and colleagues – this Arab Climate Change groups, whether they are situated on the Atlantic Ocean Assessment Report, 10 years after the first Arab Declaration or the Sea of Oman. This framework was developed under on Climate Change was issued. It is hoped that this report RICCAR through a collaborative partnership involving the will continue to inform regional dialogue, priority-setting League of Arab States, United Nations organizations and and positioning on climate change in the Arab region as specialized agencies. It was realized by engaging scientists envisioned under this collaborative regional effort. and stakeholders in an integrated assessment that considers

19 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

CONTRIBUTORS AND ACKNOWLEDGEMENTS

RICCAR IMPLEMENTING PARTNERS Grigory Nikulin1 The following experts from the RICCAR implementing partners Elin Sjökvist2 contributed to the inception or preparation of this report. Names are listed in alphabetical order. United Nations Educational, Scientific and Cultural Organisation (UNESCO) – Cairo Office United Nations Economic and Social Commission for Western Asia (ESCWA): Coordinator Bisher Imam Abdelaziz Zaki Carol Chouchani Cherfane1 Joelle Comair1 United Nations Environment Programme (UN Environment) – Ziad Khayat West Asia Office Roula Majdalani Diane Klaimi Tarek Sadek United Nations University Institute for Water, Environment and Marlene Tomaszkiewicz1 Health (UNU-INWEH) Souraya Zein Vladimir Smakhtin League of Arab States United Nations Office for Disaster Risk Reduction (UNISDR) Djamal Djaballah Ahsraf Nour Shalaby Sahar Safaie Shahira Wahbi Ragy Saro Arab Center for the Studies of Arid Zones and Dry Lands World Meteorological Organization (WMO) (ACSAD) Omar Baddour Hiam Alachkar1 Rupa Kumar Kolli Ihab Jnad1 Deutsche Gesellschaft für Internationale Zusammenarbeit(GIZ), GmbH DONORS The preparation of this report was made possible by the Matthias Bartels1 contribution of the RICCAR implementing partners and the Abdullah Droubi financial support provided by the: Hammou Laamrani2 Gerhard Lichtenthäler2 Government of Sweden - Swedish International Development Cooperation Agency (Sida) Food and Agriculture Organization of the United Nations (FAO) Government of the Federal Republic of Germany - German Mohamed AbdelMonem Federal Ministry for Economic Cooperation and Development Safinaz Ahmed (BMZ) through the Adaptation to Climate Change in the Water Giuseppina Cinardi2 Sector in the MENA Region (ACCWaM) programme led by GIZ. Aziz Elbehri1 Alessandra Falcucci2 Gianluca Franceschini AbdelHamied Hamid2 CONTRIBUTING EXPERTS, REVIEWERS AND VULNERABILITY Fawzi Karajeh2 ASSESSMENT TASK FORCE MEMBERS Michela Marinelli Anne Mottet2 Chadi Abdallah, Lebanese National Council for Scientific Pasquale Steduto2 Research, Lebanon Wafa Aboulhosn, Statistics Division, ESCWA Swedish Meteorological and Hydrological Institute (SMHI) Yaser Abunnasr, American University of Beirut, Lebanon 1 Ghasem Alavi Mansour Almazroui, King Abdulaziz University, Kingdom of Saudi 1 Nina Bosshard Arabia Thomas Bosshard1 Joel Dahné1 Said Al Sarmi, Gulf Cooperation Council, Kingdom of Saudi 2 Cristina Alionte Eklund Arabia Bode Gbobaniyi2 Rouba Arja, Social Development Division, ESCWA Phil Graham1 Ayah Badran, American University of Beirut, Lebanon Elenor Marmefelt Adriana Bruggeman, The Cyprus Institute, Cyprus

20 Fatima Driouech, Direction de la Météorologie Nationale, Fouad Abousamra, United Nations Environment Programme, Morocco2 Bahrain Khalid El Rhaz, Direction de la Météorologie Nationale, Morocco Mohamed Abdrabo, University of Alexandria, Egypt Wadid Erian, Cairo University, Egypt Nohal Al Homsi, World Health Organization, Lebanon Panos Hadjinicolaou, The Cyprus Institute, Cyprus Sabah Aljenaid, Arab Gulf University, Bahrain Omar Abdulaziz Hallaj, American University of Beirut, Lebanon Matthias Bartels, Adaptation to Climate Change in the Water Khadija Kabidi, Ministère Délégué Chargé de l’Eau, Morocco Sector in the MENA Region (ACCWaM), Deutsche Gesellschaft für Ismail Lubbad, Statistics Division, ESCWA Internationale Zusammenarbeit, GmbH, Egypt Bothayna Rashed, Sustainable Development Policies Division, Monia Braham, Ministry of Environment, Tunisia ESCWA Carol Chouchani Cherfane, United Nations Economic and Social Fahad Saeed, Climate Service Center, Germany Commission for Western Asia Ahmed Hameed Shihab, Ministry of Water Resources, Iraq Ali Eddenjal, National Meteorological Center Advisory Body, Libya Georgiy Stenchikov, King Abdullah University of Science and Nadim Farajalla, American University of Beirut, Lebanon Technology, Saudi Arabia Ihab Jnad, Arab Centre for the Studies of Arid Zones and Dry Rashyd Zaaboul, International Center for Biosaline Agriculture, Lands, Syrian Arab Republic United Arab Emirates Rachael McDonnell, International Center for Biosaline Agriculture, Rami Zaatari, Statistics Division, ESCWA United Arab Emirates George Zittis, The Cyprus Institute, Cyprus Ashraf Nour Shalaby, League of Arab States, Egypt Abdelaziz Zaki, United Nations Educational, Scientific and NATIONAL HYDROLOGICAL FOCAL POINTS Cultural Organization, Egypt Listed by country Technical advisors

Ismail Elmi Habane, Ministry of Agriculture, Water, Livestock, Alexander Carius, adelphi Consult GmbH, Germany Fisheries, Djibouti Kerstin Fritzsche, adelphi Consult GmbH, Germany Ahmed Shihab, Ministry of Water Resources, Iraq Stefan Schneiderbauer, Institute for Applied Remote Sensing, Suhair Zeki, Ministry of Water Resources, Iraq European Academy of Bozen/Bolzano, Italy Saleh Al Ouran, Ministry of Water and Irrigation, Jordan Kathrin Renner, Institute for Applied Remote Sensing, European Mohamed Abdellahi Ali, Ministry of Water and Sanitation, Academy of Bozen/Bolzano, Italy Mauritania Ali Ben Mohsen Ben Jawad, Ministry of Regional Municipalities SPECIAL THANKS and Water Resources, Oman to the following colleagues who contributed to the inception or Salam Abouhantash, Palestinian Water Authority, advancement of the report: State of Palestine Saad Abdullah Al Hitmi, Ministry of Environment, Qatar Fouad Abousamra, Luna Abu-Swaireh, Katrin Aidnell, Mahmood Al-Sibai, Sarah Dickin2, Dony El Costa, Fatma El Mallah, Yaser Bin Misfir El Asmari, Ministry of Water and Electricity, Anders Jägerskog, Khaled Mawed, Nanor Momjian, Saudi Arabia George Nasr, Atsuko Okuda, Jose Antonio Pedrosa Garcia, Dieter Ammar Abbker Abdalla, Ministry of Water Resources and Prinz, Jannis Rustige, Wael Seif, John Sloan, Adeel Zafar Electricity, Sudan Widad Mutwakil Saadalla, Ministry of Water Resources and Electricity, Sudan ESCWA EDITORIAL, DESIGN AND PRINTING TEAM Abdulkhaleq Alwan, Ministry of Water and Environment, Yemen Emile Aoun Marilynn Dagher VULNERABILITY ASSESSMENT WORKING GROUP MEMBERS Ghazal Lababidi El Hadi Radwan Tarek Abdel Aziz, Ministry of Water Resources and Irrigation, Judith Torres Egypt 1 Lead author Deeb Abdelghafour, Palestinian Water Authority, 2 Contributing author State of Palestine

21 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

ACRONYMS AND ABBREVIATIONS CRU University of East Anglia Climatic Research Unit

abs.diff absolute difference CWD maximum length of wet spell

ACCAR Arab Climate Change Assessment Report DARE data rescue

ACCWaM Adaptation to Climate Change in the Water days/yr days per year Sector in the MENA Region DBS distribution-based scaling ACSAD Arab Center for the Studies of Arid Zones and DMN-MOR Direction de la Météorologie Nationale- Dry Lands Morocco ACL anthroponotic cutaneous leishmaniasis DRR disaster risk reduction AEZ agro-ecological zones DTR diurnal temperature range ALADIN Aire Limitée Adaptation dynamique EBM ecosystem-based management Développement InterNational EC-EARTH ECMWF-based Earth-system model AMWC Arab Ministerial Water Council ECMWF European Centre for Medium Range Forecasts APCM Arab Permanent Committee for Meteorology EGM expert group meetings Apr-Sept April–September EH Ethiopian Highlands ArabCOF Arab Climate Outlook Forum ERA-Interim ECMWF Re-Analysis Interim AR4/AR5 Fourth/Fifth Assessment Report (IPCC) ERAINT ERA Interim-driven ARPEGE Action de Recherche Petite Echelle Grande Echelle ESCWA United Nations Economic and Social Commission for Western Asia ARST active red sea trough ESM Earth System Model BCIP Bias Correction Intercomparison Project ET evapotranspiration BMZ German Federal Ministry for Economic Cooperation and Development ETCCDI Expert Team on Climate Change Detection and Indices CAMRE Council of Arab Ministers Responsible for the Environment EU Upper Euphrates

CDD maximum length of dry spell ESDB European Soil Database

CH4 methane FAO Food and Agriculture Organization of the United Nations CL cutaneous leishmaniasis FAR First Assessment Report (IPCC) CMIP Coupled Model Intercomparison Project GAP Southeastern Anatolia Project CNRM-CM5 Centre National de Recherches Météorologiques- Climate Model 5 GCM global climate model or general circulation model CO2 carbon dioxide GCOS Global Climate Observing System COP Conference of Parties GDP gross domestic product CORDEX Coordinated Regional Climate Downscaling Experiment GFDL-ESM2M Geophysical Fluid Dynamics Laboratory-Earth System Model 2 CPET Collaborative Programme on the Euphrates and Tigris GHG greenhouse gas

22 GIAHS Globally Important Agricultural Heritage m metres Systems m asl/ m bsl metres above sea level/ metres below sea GIS Geographic Information Systems level

GIZ Deutsche Gesellschaft für Internationale MD Mediterranean Coast Zusammenarbeit GmbH MENA Middle East North Africa GLWD Global Lakes and Wetlands Database MH Moroccan Highlands GLC global land cover MIRCA monthly irrigated and rainfed crop areas GMIA Global Map of Irrigation Areas mm millimetres GPC Global Precipitation Climatology Project mm/day millimetres per day GPCC Global Precipitation Climatology Centre mm/mon millimetres per month GRACE Gravity Recovery and Climate Experiment mm/yr millimetres per year GRanD Global Reservoir and Dam Database MNA22 25-km resolution (MENA domain GRDC Global Runoff Data Centre 0.22 degrees)

GSFC DAAC Goddard Space Flight Center Distributed MNA44 50-km resolution (MENA domain Active Archive Center 0.44 degrees) ha hectares MPI-ESM-LR Max Planck Institute for Meteorology-Earth system model hPa hectopascals MR Medjerda River HWSD Harmonized World Soil Database MSLP mean sea level pressure HIRAM High Resolution Atmospheric Model MW megawatt HIRLAM High Resolution Limited Area Model m3/s cubic metre per second HEC-HMS Hydrologic Engineering Center Hydrological Modelling System (hydrological model) m3/t cubic metre per tonne

HydroSHEDS Hydrological data and maps from Shuttle m3/yr cubic metre per year elevation derivatives at multiple scales (WWF) NAO North Atlantic oscillation HYPE Hydrological Predictions for the Environment (hydrological model) NASA National Aeronautics and Space Administration (USA) IM integrated mapping no. number IPCC Intergovernmental Panel on Climate Change NOAA National Oceanic and Atmospheric ITCZ intertropical convergence zone Administration (USA)

IWRM Integrated Water Resources Management NTD neglected tropical disease

JCDMS Jordanian Climate Data System NWP numerical weather prediction

JMD Jordanian Meteorological Department N2O nitrous oxide JR Jordan River Oct-Mar October–March km kilometres ODA official development assistance km2 square kilometres PMD Palestinian Meteorological Department km3 cubic kilometres ppm parts per million

23 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

RCA3 Rossby Centre Regional Atmospheric Model 3 UNISDR United Nations Office for Disaster Risk Reduction RCA4 Rossby Centre Regional Atmospheric Model 4 UN Environment United Nations Environment Programme RCM regional climate model UDEL University of Delaware Air Temperature and RCP representative concentration pathway Precipitation

REMO Regional Model, Max Planck Institute, UNESCO United Nations Educational, Scientific and Hamburg, Germany Cultural Organization

RHM regional hydrological model USGS United States Geological Survey

RICCAR Regional Initiative for the Assessment of UNU-INWEH United Nations University Institute for Water Climate Change Impacts on Water Resources Environment and Health and Socio-Economic Vulnerability in the Arab Region US$ United States dollar

R10 annual number of days with precipitation VA vulnerability assessment greater than 10 mm VA-WG Vulnerability Assessment Working Group R20 annual number of days with precipitation greater than 20 mm VIC Variable Infiltration Capacity (hydrological model) RVF rift valley fever WADI water associated disease index SDII simple daily intensity index WAM West African monsoon SDS sand and dust storms WATCH Integrated Project Water and Global Change Sida Swedish International Development Cooperation Agency WCRP World Climate Research Programme

SMHI Swedish Meteorological and Hydrological WFDEI WATCH Forcing Data methodology applied to Institute ERA-Interim

SPI standardized precipitation index WHIST World Hydrological Input Set-up

SR Senegal River Headwaters WMO World Meteorological Organization

SRTM Shuttle Radar Topography Mission WSDI warm spell duration index

SU number of summer days WWF World Wildlife Fund

2 SU35 number of hot days W/m watts per square metre

SU40 number of very hot days ZCL zoonotic cutaneous leishmaniasis

Td dew-point temperature yr year

ton/ha tonnes per hectare ºC degree Celsius

TR tropical nights % per cent

TRMM Tropical Rainfall Measurement Mission

TU Upper Tigris

UAE United Arab Emirates

UDEL University of Delaware Air Temperature and Precipitation data

UNFCCC United Nations Framework Convention on Climate Change

ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

26 OVERVIEW

ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

BACKGROUND

REGIONAL INITIATIVE FOR THE ASSESSMENT OF CLIMATE CHANGE IMPACTS ON WATER RESOURCES AND SOCIO-ECONOMIC VULNERABILITY IN THE ARAB REGION

The Arab region with its unique and complex geopolitical at 1.1 °C above pre-industrial levels.2 The Fifth Assessment and socioeconomic setting is facing major challenges Report of the Intergovernmental Panel on Climate Change affecting the ability of Arab States1 to ensure the sustainable (IPCC)3 projects the global mean surface temperature by management of water resources and the delivery of water the end of the 21st century likely to increase as low as services for all. Freshwater scarcity, population growth, 1.1 °C under a moderate scenario or up to 4.8 °C under urbanization, conflict and changing migration patterns have a high-end scenario relative to the 1986–2005 reference increased pressures on human settlements and ecosystems period. and are impacting the health and welfare of women and men, children and the elderly, including vulnerable groups. In tandem, the IPCC report is virtually certain that there This is despite regional, national and local efforts to achieve will be more frequent hot temperature extremes over most the United Nations Sustainable Development Goals in an land areas as global mean surface temperature increases. integrated and inclusive manner. The report further elaborates on the breadth and intensity of socioeconomic and environmental risks attributable to Climate change and climate variability are imposing climate change as the temperature increases above the additional pressures, with adverse impacts being felt largely 1.5 °C and 2 °C thresholds relative to pre-industrial levels. on the quantity and quality of freshwater resources and the ability of the region to ensure food security, satisfy energy While these international assessments provide important demand, sustain rural livelihoods, protect human health and insights into global processes and threats to global systems, preserve ecosystems. A higher frequency and intensity of it is crucial to understand what this means for the Arab floods, droughts and extreme weather events has also been region that is already hot, arid and water scarce. To do so experienced in many Arab States. means assessing these global temperature changes through a regional lens that characterizes regional specificities, These disasters have affected the built environment, conditions and constraints. Such efforts must be firmly fragile land resources and natural ecosystems, which have grounded in science that can inform policy through dialogue aggravated the situation of already vulnerable communities, between Arab States and among various stakeholder groups. and resulted in significant economic losses, social dislocation, environmental degradation and displacement in To better bridge the science–policy interface, such several parts of the region. assessments should take into consideration the impact of climate change on water resources and what this means Studies since the early 20th century have concluded that for the vulnerability of peoples and ecosystems throughout the climate is changing. Historical climate records show an the region. Combining impact assessment projections with increase in the global mean temperature over the last 165 vulnerability assessment also furthers efforts to identify years, with the year 2016 reported to be the hottest year on regional vulnerability hotspots and priorities for coordinated record by the World Meteorological Organization (WMO), action on climate change adaptation in the Arab region. which places the average temperature of the Earth today

29 OVERVIEW

1 MANDATES AND PARTNERSHIPS

The Council of Arab Ministers Responsible for the Environment (CAMRE) adopted the first Arab Ministerial Declaration on Climate Change in December 2007 during its 19th session convened at the League of Arab States secretariat in Cairo, Egypt. The declaration is considered the starting point of Arab collective action on climate change, and serves as the basis for subsequent Arab action and positioning thereon. The declaration asserts that the Arab region will be among the regions most vulnerable to the potential impacts of climate change and that these

impacts might have negative repercussions on Arab regional Sirs Al-Muqassar Reserve, State of Palestine, 2017. Source: Alaa Kanaan. development. The extent of these potential impacts and effects were not well understood at that time, however, as the it also mandated the establishment of the Arab Ministerial only references available were the global assessment reports Water Council as a new intergovernmental mechanism issued by IPCC and a limited number of country-level reports. to be responsible for addressing water challenges facing No comprehensive picture of climate change impacts the Arab region. The Kuwait Summit further assigned this across the Arab region was available, and thus no strategy new ministerial council the responsibility to follow up on for addressing them. The Arab declaration recognized the implementation of the five IWRM projects submitted this challenge and demonstrated an appreciable and early by ACSAD. In tandem, work on the preparation of the Arab understanding of the importance that climate change Framework Action Plan on Climate Change (2010–2020) assessment plays in informing climate action. It does so by was initiated under CAMRE in 2009 to formulate a collective calling for adaptation measures to be fully consistent with programme of work on climate change adaptation, mitigation socioeconomic development, sustainable economic growth and cross-cutting issues across a range of socioeconomic and poverty eradication goals, which should be based on “the and environmental sectors. development and dissemination of methodologies and tools that assess the impacts of climate change and their extent.” Inter-agency collaboration was then formalized at the United The declaration concludes with the call to: Nations–League of Arab States 9th Sectoral Meeting (Cairo, June 2009), which focused on climate change. It concluded “Establish studies and research centres for climate change with the agreement that the United Nations and League of in the regions of developing countries, including the Arab Arab States and their respective specialized organizations region. These centres should be concerned with examining would collaborate on the preparation of a joint assessment impacts and challenges facing the citizens and peoples of the of vulnerabilities and impacts of climate change on land and developing countries as a result of climatic change.” water resources management. The Expert Group Meeting towards Assessing the Vulnerability of Water Resources to In response to this mandate, the 25th Ministerial Session Climate Change in the Arab Region (Beirut, October 2009) of the United Nations Economic and Social Commission was then hosted by ESCWA, the League of Arab States and for Western Asia (ESCWA) adopted Resolution 281 (XXV) UN Environment with the financial support of the Islamic in May 2008 in Sana’a, Yemen. The resolution requests Educational, Scientific and Cultural Organization and the ESCWA to prepare an assessment of the vulnerability of involved Arab member States and sister United Nations and economic and social development to climate change, with League of Arab States organisations. A joint concept note particular emphasis on freshwater resources.4 ESCWA was formulated outlining four pillars of work, which was subsequently consulted with the League of Arab States, the presented by ACSAD to the Arab Ministerial Water Council United Nations Environment Programme (UN Environment) (AMWC) in July 2010 and endorsed. Further discussion and regional partners to pursue this work. The Arab Center of the four pillars was then undertaken during the United for the Studies of Arid Zones and Dry Lands (ACSAD) of the Nations–League of Arab States Expert Group Meeting on League of Arab States subsequently submitted a project the Development of a Vulnerability Assessment for the brief to the Arab Economic and Social Development Summit Arab Region to Assess Climate Change Impacts on the proposing to conduct an assessment of climate change Water Resources Sector (Beirut, November 2010) hosted impacts on available water resources in the Arab region as by ESCWA and then welcomed by the inter-agency Regional one of five projects proposed to advance integrated water Coordination Mechanism based on the report submitted by resources management (IWRM) for sustainable development UN Environment as chair of the Thematic Working Group in the region. The Arab Summit endorsed the five projects on Climate Change (Beirut, November 2010). The resulting at its ministerial session in January 2009 in Kuwait, where concept note for the Regional Initiative for the Assessment of

30 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

the Impact of Climate Change on Water Resources and Socio- Permanent Committee for Meteorology (APCM) and CAMRE. Economic Vulnerability in the Arab Region was finalized The ACSAD Board of Directors comprised of Arab ministers by ESCWA in December 2010. The Regional Coordination of agriculture and the ESCWA Committee on Water Resources Mechanism Thematic Working Group on Climate Change have also continued to mandate the work being conducted mandated ESCWA to lead the coordination of the regional under RICCAR. The regional initiative is also referenced in the initiative, which is now referred to as the Regional Initiative Arab Strategy for Water Security in the Arab Region to Meet for the Assessment of Climate Change Impacts on Water the Challenges and Future Needs for Sustainable Development Resources and Socio-Economic Vulnerability in the Arab 2010–2030 and its Action Plan, the Arab Framework Action Region (RICCAR). Plan on Climate Change, and the Arab Strategy for Disaster Risk Reduction 2020 and its Implementation Plan. RICCAR is implemented through an inter-agency collaborative partnership involving 11 partner organizations, namely ACSAD, ESCWA, the Food and Agriculture Organization 2 OBJECTIVES of the United Nations (FAO), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, the League RICCAR aims to assess the impacts of climate change on of Arab States Secretariat, the Swedish Meteorological freshwater resources in the Arab region and to examine and Hydrological Institute (SMHI), the United Nations the implications of these impacts for socioeconomic and Educational, Scientific and Cultural Organization (UNESCO) environmental vulnerability based on regional specificities. Cairo Office, UN Environment, the United Nations Office It does so through the application of scientific methods and for Disaster Risk Reduction (UNISDR), the United Nations consultative processes that are firmly grounded in enhancing University Institute for Water, Environment and Health (UNU- access to knowledge, building capacity and strengthening INWEH) and the WMO. institutions for climate change assessment in the Arab region. In so doing, RICCAR provides a common platform Three climate research centres were consulted under the for assessing, addressing and identifying regional climate regional climate modelling component of the initiative, change challenges, which, in turn, inform dialogue, priority namely the Center of Excellence for Climate Change setting, policy formulation and responses to climate change Research at King Abdulaziz University (Saudi Arabia), King at the Arab regional level. Abdullah University of Science and Technology (Saudi Arabia) and the Climate Service Center (Germany). The Cyprus Institute (Cyprus) and the International Center for Biosaline 3 IMPLEMENTATION FRAMEWORK Agriculture (United Arab Emirates) were also consulted during the technical review of the RICCAR Arab Domain, The regional initiative is structured along four pillars of work which was subsequently adopted as the Middle East North (see Figure 1): Africa (MENA) Domain by the Coordinated Regional Climate Modelling Experiment (CORDEX) of the World Climate Pillar 1: Baseline review of water and climate information Research Programme (WCRP).5 and the development of a regional knowledge hub to provide a common knowledge base; Funding for the initiative has been provided by the in-kind contributions of the implementing partners as well as Pillar 2: Preparation of an integrated assessment that by the generous support of the Government of Sweden combines regional climate modelling, regional through the Swedish International Development Cooperation hydrological modelling and vulnerability assessment Agency (Sida) since 2010. The Government of the Federal tools at the Arab regional level; Government of Germany, through the German Federal Ministry for Economic Cooperation and Development (BMZ), Pillar 3: Institutional strengthening and capacity-building launched the Adaptation to Climate Change in the Water of water and meteorological organizations, as Sector in the MENA Region (ACCWaM) programme in 2011, well as related ministries and expert stakeholders, which is led by GIZ. GIZ subsequently joined RICCAR as in the area of data management, seasonal an implementing partner and has actively supported the forecasting, regional climate modelling, hydrological initiative ever since. FAO formally joined the initiative in 2013 modelling and vulnerability assessment; and has been contributing to RICCAR through its Near East and North Africa Water Scarcity Initiative. Pillar 4: Awareness-raising activities and dissemination of information tools to facilitate access to key Commitment and support for the initiative have been further message, methodologies and information to articulated by Arab States through follow-up resolutions targeted stakeholders. adopted by the Arab Ministerial Water Council (AMWC), Arab

31 OVERVIEW

The culmination of work to date on the second pillar is As preparation of the regional assessment outputs advanced, represented by the issuance of this report. However, peer reviews were organized to ensure the validity of the the preparation of this report is the product of efforts applied methodology and findings. conducted under all four pillars of work, under which regular consultations and exchanges with Arab States, international These efforts also resulted in the efforts to establish an Arab experts, regional organizations and local stakeholders were Climate Outlook Forum (ArabCOF) and a regional knowledge pursued. hub, which will continue to support and deliver on RICCAR’s four pillars of work. As shown in Figure 2, this process included the nomination of national hydrological focal points and the formation of FIGURE 1: RICCAR implementation framework regionally representative working groups and task forces, including the Vulnerability Assessment Working Group, Regional Knowledge Hub Working Group, Task Force on REGIONAL KNOWLEDGE HUB Sensitivity and the Task Force on Adaptive Capacity. The Task Force on Regional Climate Modelling was established early on in the initiative and contributed to the vetting and establishment of the Arab Domain, which was subsequently INTEGRATED ASSESSMENT adopted by WCRP-CORDEX as the CORDEX-MENA Domain. Consultation with international climate scientists interested Climate Change Climate Change in regional climate modelling in the Domain followed. Vulnerability Impact Assessment Assessment Annual expert group meetings were also conducted during the development and vetting of the integrated assessment methodology and preliminary findings, while capacity- building workshops provided training on climate data rescue, extreme climate indices, regional climate modelling, CAPACITY BUILDING & hydrological modelling and vulnerability assessment INSTITUTIONAL STRENGHTHENING integrated mapping tools. Regional stakeholders were also invited to complete a survey to help finalize the set of indicators and indicator weights assigned to inform the AWARENESS RAISING & INFORMATION DISSEMINATION integrated vulnerability assessment.

FIGURE 2: RICCAR-related consultative mechanisms informing integrated assessment

INTEGRATED ASSESSMENT Annual Expert Group Meetings (2009, 2010, 2011, 2012, 2013, 2014)

IMPACT ASSESSMENT Technical Training Workshops (2011, 2012, 2013, 2014, 2015)

Regional Climate Modelling Vulnerability Assessment Working Group (2013 to 2015) Regional Knowledge Hub Working Group (2013 to 2014)

Regional Hydrological Modelling National Hydrological Focal Points (2013, 2014, 2015)

Vulnerability Assessment Sensitivity Task Force (2014) Vulnerability Assessment Adaptive Capacity Task Force (2014)

RCM Ensemble Task Force (2011) VULNERABILITY CORDEX Working Group (2014) ASSESSMENT Expert Peer Review Meetings (April and December 2016)

32 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

OVERVIEW

This Arab Climate Change Assessment Report (ACCAR) to address the root causes of vulnerability and adapt to presents a comprehensive picture of the impact that climate climate change. A series of selected essential climate change is expected to have on freshwater resources in the variables, extreme climate indices and socioeconomic and Arab region and how this will affect the vulnerability of environmental parameters are used for presenting and water resources, agriculture, natural ecosystems, human illustrating the outcomes of the integrated assessment. settlements and people until the end of the century. Three time periods were selected for presenting results, namely the reference period (1986–2005), mid-century The results are based on the outcome of a region-specific (2046–2065) and end-century (2081–2100) periods. integrated assessment that generates regional climate The analysis is elaborated based on two representative modelling and hydrological modelling projections for concentration pathways, which generally describe a moderate the Arab region and for selected sub-domains, including emissions scenario (RCP 4.5) and a high emissions scenario the region’s major shared surface water basins. These (RCP 8.5). These time periods and scenarios were selected outputs are then used to inform an integrated vulnerability to facilitate comparability with other climate modelling assessment that considers how exposure to climate change experiments being conducted at global, regional and national over time will affect the vulnerability of five key sectors levels. Regional climate modelling and hydrological modelling and nine sub-sectors in the Arab region, in the absence of outputs presented in this report were generated based on a adaptation or any mitigating measures. 50 km2 grid, while other scales of analysis were applied when conducting some of the impact assessment case studies Impact assessment studies focusing on extreme climate and during the preparation of the integrated vulnerability events, the agricultural sector and human health provide assessment. additional insights on how climate change is projected to impact Arab States. In so doing, the report identifies It is expected that this scientific report will help to inform vulnerability hotspots and vulnerable sectors across the decision-makers, advisors, researchers and stakeholders Arab region and illustrates how the relative resilience of about climate change impacts as they affect the Arab region, Arab communities and strategic sectors will be affected with a view to informing policy dialogue, priority-setting, and unless collective, coherent and coordinated action is taken action across the Arab region.

1 INTEGRATED ASSESSMENT FIGURE 3: RICCAR integrated assessment methodology METHODOLOGY IMPACT VULNERABILITY This report presents the outcomes of the RICCAR integrated ASSESSMENT ASSESSMENT assessment methodology that was developed based on the interest to combine impact assessment and vulnerability assessment approaches into a cohesive framework for assessing the impact of climate change on water resources Representative GCM RCM RHM VA IM and socioeconomic vulnerability at the Arab regional level. Concentration Pathway (RCP) The methodology is grounded on the use of regional climate THE ARAB REGION modelling, hydrological modelling, vulnerability assessment and integrated mapping tools. Five stages of analysis were agreed upon (see Figure 3):

Step 1. Select representative concentration pathways Step 2. Generate ensembles of regional climate modelling (RCPs) to adopt and review available global (RCM) projections over an Arab Domain. This climate models (GCMs). In order to be coherent involved defining the Arab Domain and generating with other work being pursued under CORDEX, it dynamically downscaled RCM projections and was determined that RICCAR would purse regional ensembles for specific climate scenarios and climate modelling for RCP 4.5 (moderate scenario) resolutions, for general climate variables as well and RCP 8.5 (high-end scenario). as for region-specific extreme climate indices.

33 OVERVIEW

Step 3. Interface regional hydrological models (RHM) with The introduction provides background on the regional RCM outputs to analyse climate change impacts initiative, an overview of the report and a review of baseline on water resources. This involved bias-correcting information and sources of data used to prepare the the RCM results to serve as inputs for the generation integrated assessment. All the integrated assessment of RHM ensembles using two hydrological models, outputs and case studies presented are original work with specific focus on the region’s shared river generated within the framework of the regional initiative basins and specific sub-domains. and build upon the dynamically downscaled regional climate modelling outputs presented in Part I. Step 4. Conduct a vulnerability assessment (VA) based on the impact assessment findings across the Arab Part I (Impact Assessment, Chapters 1–7) reviews regional region in targeted sectors and sub-sectors climate modelling and hydrological modelling projections identified through a consultative process, and generated for the Arab Domain and selected subdomains, based on the classification and weighting of region and how these results were generated. Results and findings specific geospatial indicators that characterize of concern to some of the major shared surface-water sector exposure, sensitivity and adaptive capacity basins in the Arab region are presented in Chapter 4. Impact with respect to climate change. assessment case studies of extreme events and sector- based case studies based on RCM and RHM outputs are Step 5. Complete the integrated mapping (IM) of the presented in Chapters 5, 6 and 7. assessment for facilitating regional policy analysis and dialogue by presenting vulnerability hotspots Part II (integrated vulnerability assessment, Chapters 8–14) and climate change trends and challenges across the reviews VA methodology and main components of the Arab region. assessment (Chapter 8), followed by the results for each of the five sectors and nine subsectors studied (Chapters 9–13), This methodological framework is elaborated in a series followed by a brief summary of the findings (Chaper 14). of publications focusing on various components of the integrated assessment.6 The development and application The conclusion presents key findings and explores how this of this methodological framework were pursued through assessment report can inform regional policymaking and iterative consultations with Arab States and international future work. experts, the designation of national hydrological focal points and regional consultations organized through expert groups, The main report is complemented by a technical annex workshops, working groups and task forces, as was shown in that presents more than 400 maps and figures that provide Figure 2. further information on the indicators and outputs generated during the regional application of the integrated assessment. The aim of this integrated assessment methodology is to provide a regional, science-based assessment of climate The report is part of a RICCAR publication series, which change impacts and vulnerability based on uniform and elaborates and complements the methodologies presented harmonized datasets and assumptions, which can inform in this report. The publication series is comprised of: further climate change research and foster dialogue across Arab States about priority issues, challenges and Technical notes – these serve as stand-alone explanatory opportunities for collective action. The application of this notes and elaborate in greater detail the applied methodology also provides a regional baseline, regional methodologies and information sources used. datasets and assessment outputs that can, in turn, be used to inform and prepare smaller-scale assessments at the Technical reports – these serve as stand-alone publications sub-regional, national and local levels. and present detailed case studies or provide additional analysis that build upon the RICCAR modelling outputs, several of which are summarized in the main report.

2 STRUCTURE OF THE REPORT Training materials – these can be used to inform training on methodologies and climate change assessment and This Arab Climate Change Assessment Report is structured adaptation in the Arab region, based on work being conducted into four sections and divided among 14 chapters. It opens under RICCAR and RICCAR-related projects and initiatives. with an introduction followed by two parts that echo the main components of the integrated assessment methodology, Datasets and files used to produce the modelling outputs and namely impact assessment (Part I) and vulnerability integrated mapping assessment results are made available assessment (Part II), which are followed by a conclusion. online or upon request through the regional knowledge hub.

34 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

BASELINE INFORMATION AND DATASETS

Data availability and data quality are crucial for the conduct Such a limitation may not be the case when integrated of any assessment. The availability of observed climate and vulnerability assessment using the same methodology is water station data across the Arab region is very limited and applied at the country or local level. the distribution of quality-controlled, long-term observational sites within the Arab region is uneven. In areas where station The following sections review the main climate features data are recorded, access to datasets may not be publicly and trends that characterize climate in the Arab region, available or not available in digitized form to allow for use in followed by a description of the meteorological data, water- computer-based modelling applications. resources-related data, topography and other terrestrial data, in addition to the socioeconomic related datasets RICCAR efforts were thus focused on using national data used to inform the climate, hydrological and vulnerability from regional or global data sources whenever possible to assessments presented in this report. This section also ensure the use of harmonized and quality-controlled datasets offers information on related work conducted under RICCAR that are comparable across Arab States. This limited the to support Arab States in the area of climate data rescue ability of the initiative to adopt indicators and use data that (DARE) and the development of disaster-loss databases, were well-elaborated in some Arab States, but not in others. highlighting their usefulness for climate change analysis.

1 CLIMATE CHARACTERISTICS OF THE ARAB REGION 1.1 Climate zones and features

Most of the Arab region is characterized by a predominantly arid to semi-arid climate (annual rainfall distribution shown in Figure 4). The Sahara Desert constitutes most of the surface area of North Africa, covering Mauritania, southern Morocco, and extending further east into vast are of Libya, Egypt and as far as Atbara in Sudan. This desert exhibits one of the harshest climates in the world, with an annual rainfall of less than 25 mm and temperatures rising over 50 °C in the hottest months to below freezing in the winter. Liwa Desert, Abu Dhabi, 2012. Source: Khajag Nazarian. Located just at the south of the Sahara Desert, the Sahel has a tropical, hot steppe climate and represents an ecoclimatic with cooler temperatures and much higher precipitation zone of transition between the Sahara to the north and the (up to 1,500 mm/yr). These areas, which extend to Sudanian Savanna. This zone includes southern Mauritania, the northern stretches of Libya and Egypt, exhibit a the extreme south of Algeria, as well as central and Mediterranean climate as in the western areas of Jordan, southern Sudan. Constant heat and little variations in Lebanon, State of Palestine and Syrian Arab Republic with temperatures characterize this area, with an average mean warm, dry summers and rainy, cool winters. In the highlands temperature never lower than 18 °C. The dry season in the of Lebanon, northern Syrian Arab Republic and north- Sahel lasts for 8 to 10 months with irregular rainfall during eastern Iraq, temperatures are, on average, below 10 °C in the short rainy period, and receives 100–600 mm of rain winter (January), and receive more than 1,000 mm/yr of annually, depending on the different sub-zones (around precipitation on average, with snowfall covering mountainous 100–200 mm in Khartoum and 200–600 mm in Kiffa, south areas above 1,500 m. South of the high elevations, the cold Mauritania). semi-arid steppe climate with cold winters occurs along a narrow stretch of Morocco, Algeria and Tunisia, as well as in Although mostly arid or semi-arid, the Arab region also Jordan, Syrian Arab Republic and Iraq in the Mashreq region. encompasses temperate zones in the northern and Further inland, it transforms into an arid desert climate as higher elevations of the Maghreb and Mashreq. The Atlas it reaches the Sahara Desert in North Africa and the vast Mountains, located in the northern parts of Morocco, Desert in Syrian Arab Republic covering more than half of the Algeria and Tunisia, constitute relief from the dry desert country and extending through inland Iraq and Jordan.

35 OVERVIEW

FIGURE 4: Mean annual precipitation distribution across the Arab region (1986-2005)

Average annual precipitation (mm) Low: 0 mm 100 200 300

400 500 600 High: > 650 mm

A limited portion of the Arab region exhibits an equatorial upon moving from the North African coast towards the climate characterized by high year-round temperatures Sahara inland, and then decreases gradually with increase and heavy precipitation most of the year, such as southern in rainfall and relative humidity as it reaches southern Somalia and some parts of southern Sudan. The southern Sudan with evaporation rates in the order of 1,500 mm/yr. Somalia area, for example, receives 300–500 mm of rainfall In the Arabian Peninsula, the total annual evaporation rate annually; minimum temperatures are around 30 °C all year ranges from 2,500 mm in the coastal areas to more than long and can be as high as 41 °C in March – the hottest 4,500 mm inland. Similar to evaporation, observations month of the year. of evapotranspiration (ET) rates vary both spatially and temporally. The largest annual ET values are found in Most of the Arabian Peninsula is characterized by a hot south-western Algeria, southern Egypt, Djibouti, southern desert climate with less than 100 mm/yr of rainfall. Average Iraq, south-eastern Saudi Arabia, north-eastern Yemen, and temperatures range from 40 °C to 50 °C in summer and western Oman with more than 2,200 mm/yr. Overall, the 5 °C –15 °C in winter, with very high daily fluctuations. summer rate in the Arabian Peninsula is three times the Exceptions to these conditions occur in coastal zones potential evapotranspiration rate in wintertime.8 of eastern Oman, south-western Saudi Arabia (Hijaz) and Yemen, where rainfall is higher, due to the seasonal monsoon winds and northward expansion of the Intertropical 1.2 Atmospheric patterns affecting Convergence Zone (ITCZ). For instance, precipitation levels climate variability can attain 1,500 mm/yr on the south-western mountain slopes of Yemen.7 The state of the North Atlantic Oscillation (NAO) – the principal feature affecting climate variability in the northern While annual rainfall varies between 0 mm and 650 mm on hemisphere – largely governs annual variations of rainfall average for the region as whole (rainfall can exceed 900 in the Maghreb, most of the Mashreq and the northern part mm in some areas), average evaporation rates often exceed of the Arabian Peninsula. It consists of opposing variations 2,000 mm/yr. Evaporation observations along the southern between areas of low pressure centred near Iceland and and eastern shores of the Mediterranean indicate rates high pressure zones in the south of the Azores in the Atlantic in the order of 1,000 mm/yr increasing to 2,000 mm/yr or Ocean. The interaction of these two poles modifies the more while moving further inland. The same trend is found circulation of the westerly winds across the Atlantic into

36 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

Europe and the Mediterranean, with important effects on also recently been experiencing devastating floods and flash the winter season at mid-high latitudes. When the pressure floods. They occur after intense and short-duration rainstorm difference is high (positive NAO phase), the westerly winds events, causing severe damage to infrastructure and often are stronger and track more to the north, leading to higher- leading to human losses. Major floods have been striking than-normal temperatures and precipitation levels across Saudi Arabia recurrently since 2009, the most recent of which northern Europe in winter, but causing drier conditions in the – in February 2017 – caused the loss of several human lives. Mediterranean. In the opposite phase, the westerlies and the Other countries, such as Oman, experienced similar events storms they bring track farther south, leading to cold winters with heavy flooding in early 2017, which led to four deaths and in Europe, but more storms in the Mediterranean and more destroyed hundreds of settlements.14 rain in North Africa.9 Precipitation variability in the Arabian Peninsula is affected by the Indian seasonal monsoon winds The Active Red Sea Trough (ARST) is an occasional weather that bring moist airmasses from the Indian Ocean, causing phenomenon associated with extreme precipitation, flash rainfall in the coastal zones of eastern Oman, Saudi Arabia floods, and severe societal impacts in the Middle East, as (Hijaz region) and Yemen. Most of the precipitation occurs was the case with a major flood in Jeddah, Saudi Arabia, on in May and continues until August in the uplands, but often 25 November 2009. ARST results from the interaction of a appears as early as March. In this area, rain falls mainly as persistent stationary wave in the tropical easterlies with a heavy showers followed by flash floods. Occasionally, these superimposed amplifying Rossby wave, resulting in northward countries also experience serious consequences of tropical propagating moist airmasses over the Red Sea.15 cyclones. The Indian monsoon system is largely controlled by the position of the ITCZ, a zone of low pressure at the Heavy flood conditions also often follow tropical cyclones Equator, where the north-east and southeast trade winds events, which are widespread in the vicinity of the Indian converge to form a band of increased convection, cloudiness, Ocean and Arabian Sea, and can have long-lasting impacts and precipitation, that moves seasonally south and north on coastal settlements and natural systems. Examples of the Equator.10 The ITCZ also affects the West African include tropical cyclone Gonu, the strongest tropical cyclone Monsoon (WAM), which is the circulation pattern affecting on record in the Arabian Sea, which struck Oman in June most of the rainfall in the Sahel. It consists of a low-level 2007, leaving 49 dead and costing about US$ 4 billion moisture flow originating in the equatorial and southern in widespread damage.16 More recently, tropical cyclone tropical Atlantic Basin. When the ITCZ seasonally shifts Chapala hit coastal Yemen in November 2015 and was the northwards, reaching West Africa in mid-June, it interacts first hurricane-strength storm known to make landfall in with the WAM which converges on to the continent bringing Yemen, leaving hundreds of dwellings submerged by water.17 rains to the Sahel from July to September.11 The impacts of extreme events such as storm surges in the region also add to the vulnerability of coastal zones, which house highly populated cities as well as major centres of 1.3 Extreme events and climate related hazards economic development. They expose potentially vulnerable locations to sea-level rise, particularly in low-elevation areas. In recent years, extreme temperatures and precipitation An example is the Nile Delta which has been extensively events in the region have recurrently led to a variety of documented and studied as it is an area of high risk in weather- and climate-related hazards, such as heatwaves, the case of sea-level rise, with locations susceptible to droughts, floods, cyclones and sand- and dust storms (SDS). inundation encompassing major urban neighbourhoods, These natural events have become more frequent and more agricultural areas and coastal wetlands.18 Other major natural severe, with substantial and widespread consequences on hazards in the region are sand- and duststorms. They result social and economic conditions in many areas. Drought is from high winds associated with extreme heat, and have the most prevalent climate hazard; its impacts on livelihoods led, in many Arab States, to serious adverse impacts on are severe and cause the highest human losses. Its effects human health and agricultural productivity, as well as traffic include decreased water supplies, as well as loss of harvest accidents and airline delays (see Box 1). All these extreme and livestock, which, in turn, threaten food security and events, when associated with unstable conditions, such as often cause widespread malnutrition. One example is the the development of informal, unsafe settlements or limited devastating droughts in Syrian Arab Republic of 1998– access to transport, health, education and other basic 2000 and 2007–2010, which were the most severe in some services, become disasters rather than just hazards, given 1,100 years, causing considerable economic losses and the extensive devastation they can inflict, and require risk the displacement of more than one million people.12 This is reduction on a large-scale. In light of the increased frequency the case currently in the Greater Horn of Africa, where the and intensity of these disaster events, an urgent need for prolonged drought has led to successive failed harvests and disaster prevention and management has been identified in widespread livestock deaths in some areas.13 Though usually the region and is currently being developed through disaster associated with drought and desertification, the region has loss databases, detailed in the section on disaster loss.

37 OVERVIEW

BOX 1: Sand and dust storms in the Arab region

Sand and dust storms (SDS) are common examples of Jordan.23 The storm was unprecedented in recent Lebanese extreme weather conditions in the Arab region. These history, leading to five deaths and 750 cases of asphyxiation events can last from a few hours up to several days and or shortness of breath.24 create long-lasting environmental impacts in the source areas (loss of surface sediments, disturbed consolidation While the natural geological topographical and climatic of topsoil) but, most importantly, affect the receiving areas features constitute key factors in determining the incidence with severe adverse impacts. Common effects include severe of SDS, human interference with natural land features is air pollution and reduced visibility leading to increased an additional significant contributing factor in generating traffic and aircraft accidents. In addition, severe impacts on them. This includes practices such as overgrazing and human health are systematically reported, such as increased overworking of farm areas, poor water use, and land clearing. occurrence of respiratory diseases. These events also affect This combination of driving factors is further compounded by livelihoods and the economy as they exacerbate, in a cyclic increasing climate variability in many already fragile regions, way, the loss of land productivity, ecosystem integrity and with decreased rainfall, extended drought periods, higher biodiversity, leading to population displacement and loss temperatures and increased frequency of high-velocity wind of critical habitats and wetlands in the Mesopotamia area.19 events, all of which exacerbate the conditions that spawn It is estimated that about US$ 13 billion of gross domestic SDS.25 In line with IPCC AR5 findings, RICCAR results project product are lost every year to duststorms in the Middle East warming in the region, as well as an intensification of extreme and North Africa. events, which implies that the region will be potentially challenged by droughts and water scarcity, compounded by The North African region is the largest global source of SDS heightened SDS events, in the future. (with the Sahara Desert as the most significant source of dust) followed by the West Asia region.20 In the latter region, For these reasons and because of the continuum and the major dust sources extend in a continuous band from the interconnectivity of ecosystems and landscapes across northern part of the Tigris-Euphrates basin to the coast of the region, a coordinated and integrated approach among Oman.21 Accordingly, SDS are persistent issues of concern, affected countries is essential to effectively tackle this particularly in Iraq and the southern Arabian Peninsula, and challenge. Several steps have been taken in this regard at are most prevalent during the spring and summer months the regional level, such as the Ankara Ministerial Declaration owing to the strong winds characterizing the winter–spring on the issue of SDS, signed in 2010 by countries of West seasonal transition. Examples include a duststorm hitting Asia, including Iraq and the Syrian Arab Republic, along the Arabian Peninsula in late February 2015, when the with a follow-up action plan. At the national level, the low-pressure system triggered strong north-westerly winds Iraqi Government has made efforts to develop a national carrying dust from as far as northern Saudi Arabia, Iraq and programme to combat SDS, in collaboration with UN Kuwait to the shores of the Persian Gulf and the Arabian Environment and FAO. Sea.22 The Mashreq region also recently widely witnessed such phenomena, with a massive duststorm in September More recently, international resolutions have also been 2015, which lasted for several days, striking the Syrian Arab adopted concerning this issue. Building upon the United Republic and Iraq and spreading through Lebanon, Egypt and Nations Environment Assembly Resolution 1/7 on promoting air quality26 and the United Nations General Assembly resolution 70/195 on combating sand and dust storms,27 Syria the United Nations Environment Assembly adopted a Euphrates resolution on SDS (UNEP/EA.2/Res21)28 in 2016 to promote a Source point – coordinated approach to globally combating SDS and support Member States in addressing the challenges through policy measures and actions. UN Environment is also playing an important role in raising awareness and elevating SDS as a

Iraq regional and global emerging environmental issue as part of its programme of work, in particular at the West Asia office, which covers an area deeply affected by this phenomenon.29 Dust Storm in Syria and Iraq, 2011. Source: NASA, LANCE/EOSDIS MODIS Rapid Response Team.

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FIGURE 5: Observed globally averaged combined land- and 2 CLIMATE DIAGNOSTICS ocean-surface temperature anomaly until 2012 (relative to 1986–2005) Summary for Policymakers (a) Globally averaged combined land and ocean surface temperature anomaly 2.1 Global observed climate trends 0.40.4

0.20.2 Summary for Policymakers

Observations of changes in the climate system are based (a) Globally00 averaged combined land and ocean surface temperature anomaly 0.4 on records from direct physical and biogeochemical −0.2-0.2

(°C) 0.2 measurements, ground stations, satellites and many other (°C) −0.4-0.4 Summary for Policymakers 0 types of observing systems that monitor the Earth’s weather (a) −0.6-0.6Globally averaged combined land and ocean surface temperature anomaly −0.20.4 and climate. Records of data from hundreds to millions of −0.8-0.8 SPM (°C) −0.40.2 years are studied through paleoclimate reconstructions, −1-1 1850 1900 1950 2000 −0.60 Year while actual global-scale observations began in the mid- Year −0.8 SPM 19th century. Together, they provide a comprehensive view (b)Source:−0.2 IPCC, 2014 Globally averaged sea level change of the variability and long-term changes in the atmosphere, (°C) −0.40.1−1 FIGURE 1850 6: Global mean 1900sea-level change 1950until 2010 2000 30 −0.6 Year the ocean, the cryosphere and the land surface. According 0.05 (relative to 1986–2005) (b) Globally averaged sea level change to the IPCC, scientific evidence for warming of the climate −0.80 SPM 0.10.1 −1 system is undeniable. Each of the last three decades has −0.05 1850 1900 1950 2000 been successively warmer at the Earth’s surface than any (m) 0.050.05 Year −0.1 preceding decade since 1850 (Figure 5).31 The globally (b) 00 Globally averaged sea level change −0.150.1

(°C) −0.05-0.05 averaged combined land and ocean surface temperature data (m) 0.05−0.2 as calculated by a linear trend show an increase of about −0.1-0.1 1850 1900 1950 2000 0 Year 0.85 °C from 1880 to 2012 (based on multiple independently −0.15-0.15 (c) Globally averaged greenhouse gas concentrations produced datasets), and about 0.72 °C from 1951 to 2012 −0.05 (m) −0.2-0.2400 1850 1900 1950 2000 (based on three independently-produced data sets). −0.1 1850 1900 Year 1950 2000 380 Year (c)−0.15 Globally averaged greenhouse gas concentrations Source:360 IPCC, 2014 Recent observations and analysis by the US National 400 1800 −0.2 330

FIGURE (ppm) 340 7: Globally averaged observed greenhouse gas Aeronautics and Space Administration (NASA) and National 2 1850 1900 1950 2000 1600 380 Year 320 CO 320 concentrations until 2011 1400 310

Oceanic and Atmospheric Administration (NOAA) have (ppb)

1200 O (ppb)

1800 2 shown that, since instrumental record-keeping began in 400300 CH 290330 N

(ppm) 340 1000 2 1600 280320 1880, surface temperatures of the Earth were the warmest 380 380280 800(ppb) CO 270 14004 310

320 O (ppb) (ppb) 1850 1900 1950 2000 2 4 N in the year 2016, making it the third year in a row to set CH 300

360 Year 1200 O (ppb) 2 32 300 CH 290 18001800 N a new record for global average surface temperatures. Global anthropogenic CO emissions 1000 330Cumulative330 CO (ppm) 2 280 2 (ppm) 340 (d)2 2 16001600 320 Phenomena such as El Niño or La Niña, which warm or cool 280 Quantitative information of CH4 and N2O emission time series from 1850 to 1970 is limited 800 emissions320270 CO 310 CO 40 320 1850 1900 1950 2000 14001400 310 Year (ppb) the upper tropical Pacific Ocean and cause corresponding 35 Fossil fuels, cement and ﬂaring 20003004 300 12001200 O (ppb)

290 2 300 Forestry and other land use CH Cumulative290 CO variations in global wind and weather patterns, may Global anthropogenic CO emissions N 2 (d) 30 2 10001000 280 Quantitative information of CH4 and N2O emission time series from 1850 to 1970 is limited emissions280 800800 1500270

25 ) contribute to short-term variations in global average /yr) 28040 270 2 2 1850 1900 1950 2000 3520 1850 Fossil fuels, cement 1900and ﬂaring 1950 2000 2000 temperature. A warming El Niño event occurred for most YearYear 1000 Forestry and other land use (GtCO (GtCO 3015 of 2015 and the first four months of 2016, and its direct Source: IPCC, 2014 Global anthropogenic CO2 emissions Cumulative CO2 (d) 10 Quantitative information of CH and N O emission time series from 1850 to 1970 is limited 1500

25 4 2 ) /yr) 500 emissions 2 warming impact in the tropical Pacific is believed to have 2 40 205 period35 1901–2010.Fossil fuels, cement Moreover, and ﬂaring it has been shown that northern 20001000 led to an increased annual global temperature anomaly for 0 0 (GtCO (GtCO 15 Forestry and other land use 2016 by 0.12 °C. The oceans have absorbed a considerable hemisphere30 1850 spring snow1900 cover has continued1950 to decrease2000 in 1750 1750 10 Year 500 – – 34 1500

25 ) /yr) 1970 2011 2 part of this increased heat, and accounted for more than 90% extent2 5 over the past five decades. 20 Figure SPM.1 | The complex relationship between the observations (panels a, b, c, yellow background) and0 the emissions (panel d, of the energy accumulated in the climate system between 0 1000 (GtCO light blue (GtCO background)15 1850 is addressed in Section1900 1.2 and Topic 1. Observations1950 and other indicators2000 of a changing global1750 climate1750 system. Observa- 1971 and 2010 (only about 1% stored in the atmosphere) with The increasing amount of greenhouseYear gases (GHGs) in the – – tions: (a) Annually10 and globally averaged combined land and ocean surface temperature anomalies relative to the average500 over1970 the period2011 1986 to 2005. Colours indicate different data sets. (b) Annually and globally averaged sea level change relative to the average over the period 1986 to 2005 in the a virtually certain warming of the upper ocean (0–700 m) atmosphere5 plays a major part in these warming trends Figurelongest-running SPM.1 |dataset. The complex Colours indicaterelationship different between data sets. the All observations datasets are aligned (panels to a,have b, thec, yellow same value background) in 1993, the and first the year emissions of satellite (panel altimetry d, 33 0 during this period. The current warming trend indicates thatlightdata (red).blueby Wherebackground) radiatively0 assessed, is uncertaintiesaddressed perturbing in are Section indicated the 1.2 Earth’sby and coloured Topic energy shading.1. Observations (c) balance. Atmospheric and other concentrationsindicators of a changingof the greenhouse global climate gases system. carbon Observa dioxide- 1850 1900 1950 2000 1750 1750 a key change is occurring in the balance of energy fluxes, tions:(CO2, green),(a)Anthropogenic Annually methane and (CHglobally4, orange) averaged GHG and nitrouscombined emissions oxide land (N and2O,Year red)have ocean determined surface increased temperature from ice coresince anomalies data (dots)the relative and from to the direct average atmospheric over –the measurementsperiod– 1986 to (lines). 2005. Indicators: (d) Global anthropogenic CO emissions from forestry and other land use as well as from burning of fossil fuel, cement1970 production2011 and flaring. Colours indicatepre-industrial different data sets.era, (b) driven 2Annually byand globallypopulation averaged seagrowth level change and relative economic to the average over the period 1986 to 2005 in the with the energy influx outweighing the outflow. This is also longest-runningCumulative emissions dataset. of COColours2 from indicate these sources different and data their sets. uncertainties All datasets are are shown aligned as to bars have and the whiskers, same value respectively, in 1993, onthe the first right year hand of satelliteside. The altimetry global Figure SPM.1 | The complex relationship between the observations (panels a, b, c, yellow background) and the emissions (panel d, reflected in other observed processes which are also shiftingdataeffects (red). ofdevelopments the Where accumulation assessed, of uncertainties CH 4(Figure and N2O are emissions 7). indicated Historical are byshown coloured in panel emissions shading. c. Greenhouse (c) Atmospheric have gas emission driven concentrations data from 1970of the to greenhouse 2010 are shown gases in carbon Figure dioxideSPM.2. light(CO{Figures, bluegreen), 1.1, background) 1.3,methane 1.5} (CH is, orange)addressed and innitrous Section oxide 1.2 (N andO, red) Topic determined 1. Observations from ice andcore other data indicators(dots) and of from a changing direct atmospheric global climate measurements system. Observa (lines).- to reflect the climate system’s transition towards a warmer tions:2 (a) atmosphericAnnually and globally4 concentrations averaged combined land andof2 oceancarbon surface dioxide, temperature methaneanomalies relative to the average over the period 1986 to 2005. Indicators: (d) Global anthropogenic CO2 emissions from forestry and other land use as well as from burning of fossil fuel, cement production and flaring. ColoursCumulative indicate emissions different of COdata from sets. these (b) Annually sources andand theirglobally uncertainties averaged aresea shownlevel change as bars relative and whiskers, to the averagerespectively, over onthe the period right 1986hand toside. 2005 The inglobal the 3 state. For example, over the last two decades, the Greenlandlongest-running and nitrousdataset. Colours 2oxide indicate to different levels data that sets. areAll datasets unparallelled are aligned to have in atthe sameleast value in 1993, the first year of satellite altimetry effects of the accumulation of CH4 and N2O emissions are shown in panel c. Greenhouse gas emission data from 1970 to 2010 are shown in Figure SPM.2. and Antarctic continental ice sheets have been losing mass data{Figures (red). 1.1,the Where 1.3, last 1.5}assessed, 800,000 uncertainties years, are indicated leading by coloured to an shading.uptake (c) Atmosphericof energy concentrations by of the greenhouse gases carbon dioxide and glaciers continued to shrink almost worldwide and (CO2, green),the methane climate (CH4, orange)system. and nitrous Concentrations oxide (N2O, red) determined of carbon from ice coredioxide data (dots) (CO and from), direct atmospheric measurements (lines). Indicators: (d) Global anthropogenic CO2 emissions from forestry and other land use as well as from burning2 of fossil fuel, cement production and flaring. 3 Cumulative emissions of CO from these sources and their uncertainties are shown as bars and whiskers, respectively, on the right hand side. The global contributed to sea-level rise throughout the 20th century, methane (CH2 4) and nitrous oxide (N2O) have all shown major effects of the accumulation of CH4 and N2O emissions are shown in panel c. Greenhouse gas emission data35 from 1970 to 2010 are shown in Figure SPM.2. with a global mean sea-level rise of 0.19 m recorded over the{Figures 1.1,increases 1.3, 1.5} since 1750 (40%, 150% and 20%, respectively).

39 3 OVERVIEW

Calotropis procera indicating desertification, North Kordofan, Sudan, 2004. Source: Stefan Schneiderbauer.

Moreover, satellite data have confirmed that the annual tropics, demonstrates the importance of also conducting

CO2 level has now exceeded 400 parts per million (ppm) as smaller-scale geographic assessments that can provide a global average, compared to around 280 ppm measured in more regional-specific insights. ice cores during the pre-industrial revolution period.36

As for the observed precipitation trends, the IPCC AR5 2.2 Regional climate observations reports that precipitation has likely increased since 1901 when considering the average over the mid-latitude land Relatively little is known about the evolution of climate areas of the northern hemisphere. However, IPCC expresses over the Arab region in recent decades compared to other low confidence in findings related to area-averaged, long- parts of the World. One of the first regional studies on term trends in other latitudinal zones due to poor data climate trends focusing on extreme indices was conducted quality, data incompleteness or disagreement among by Zhang et al. (2005) and examined trends in extreme available estimates.37 This is evidenced by observed temperature and precipitation for the period 1950−2003 precipitation trends along Mediterranean coastlines that based on national data from 52 stations in 15 countries in have witnessed a decline in precipitation. The IPCC AR5 the eastern part of the Arab region.40 Results have shown also assessed the literature on global and regional changes statistically significant warming trends in the region based in climate extremes, indicating a very likely global trend on temperature indices indicating a significant increase in towards fewer cold days and nights and more warm days and the frequency of warm days, in particular towards the 1990s, nights. It also expressed consensus that heavy precipitation as well as a significant but gradual reduction in the number events have likely increased in more regions than decreased. of cold days starting in the 1970s. On the other hand, trends Decadal variability dominated longer-term trends in drought in precipitation were characterized by strong interannual extremes, although regional trends were witnessed, including variability without any significant trend. More recently and increasing dryness or drought in East Asia, the Mediterranean to date, the most comprehensive study of extreme climate and West Africa and decreasing drought in central North trends across the whole Arab region is the one conducted by America and north-western Australia.38 Other studies have Donat et al. (2014), which was the outcome of a workshop indicated that both observations and models show generally organized by ESCWA in 2012.41 Daily observational data increasing trends in extreme precipitation since 1901, with obtained from more than 100 weather stations spanning the largest changes in the deep tropics. On a global scale, the Arab region42 since the middle of the 20th century were AR5 reports that the observational annual-maximum daily collected and data from 61 stations were ultimately analysed precipitation increased by an average of 5.73 mm/day over after assessment of quality and homogeneity. Their results the period 1901–2010, or 8.53% in relative terms.39 This gave evidence of consistent and significant warming trends increase was evidently not uniform across the globe. The across the region with clear increased frequencies of warm broadness of these statements to ensure representation of days and warm nights, higher extreme temperature values, global trends in high and low altitudes, from the poles to the fewer cold days and nights and shorter cold spells since

40 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

the early 1970s. On the other hand, analyses of changes in In terms of temperature, trends have showed an extensive precipitation extremes were less significant and spatially increase in summer temperature in all Syrian Arab Republic inconsistent, whereby results of area-average, long- stations with prominent increases in coastal and western term trends since 1960 showed a tendency towards drier regions. The analysis of extreme events and indices for the conditions, but with little change since the 1970s. Results, period 1965–2006 showed significant increasing trends for however, indicated that the western part of the region several parameters, such as annual maximum and minimum (Algeria, Morocco, Mauritania) had exhibited a consistent daily temperatures, the number of tropical nights and the tendency towards wetter conditions during the past 30 years, number of summer days. On the other hand, the number unlike the eastern part (Egypt, Djibouti, Arabian Peninsula) of cool nights and days and diurnal temperatures revealed which showed some consistent drying trends. significant decreasing trends.46 In Iraq, temporal and spatial changes in precipitation and temperatures were assessed for Other studies encompassing the Arab region were the period 1980–2011, based on 28 station data distributed conducted, using globally available datasets such as throughout the country. Increasing trends in minimum and Tanarhte et al. (2012), which compared different gridded maximum temperatures were observed, as well as decreasing datasets of temperature and precipitation across several precipitation trends (ranging from 1.3 to 6.2 mm/yr). Results subregions over the Mediterranean and the Middle East also showed no differences in the geographic location for the period 1961–2000.43 Similar trends of increasing throughout Iraq, implying that climatic impacts are spatially temperatures and downward trends of precipitation were uniform in this area.47 found for most subregions in all datasets, however with different magnitudes and levels of significance. For instance, Several studies have examined trends of area-specific an overall positive temperature trend of 0.2 °C to 0.4 °C climate and extremes in the North Africa region. One of per decade was found in Saudi Arabia and the Arabian Gulf them assessed trends based on daily precipitation data and was particularly significant during the summer months. from 22 stations in Algeria, Morocco and Tunisia for the Similar trends were also found for the northern parts of common period 1970–2002. Results have indicated strong Morocco, Algeria, Tunisia, Libya and Egypt, starting in the mid trends towards a decrease in precipitation totals and in the 1970s. For precipitation, though showing mostly downward duration of precipitation episodes (length of wet spells), trends, the study indicated variable and sometimes coupled to increases in the ratio of dry days and the duration contradicting results among datasets with overall non- of dry spells. These results were particularly pronounced significant trends, which is in line with the findings mentioned for Morocco and western Algeria. The study also pointed to previously. Characteristics of heatwaves in the Middle East a greater significance and spatial consistency for indices region (excluding North Africa) were also investigated, based representing dry periods than heavy precipitation indices, on data from a global dataset covering the period 1973–2010. indicating that droughts periods are simultaneously The analysis of long-term temperature data suggested an impacting large areas.48 Another study focused on the increased frequency of heat extremes since the 1970s, with Greater Horn of Africa and analysed daily observed increasing trends in the number of heatwaves found at all station data for maximum and minimum temperatures and stations, although no significant change in their duration and precipitation for the period 1971–2009. It showed increased maximum temperature were detected, implying no change in frequencies of warm days and warm nights coupled to their intensity.44 decreased frequencies of cold days and cold nights. It was also observed that extreme indices, such as the length of Most of the studies investigating the evolution of climate in the maximum number of consecutive dry days (CDD) and the Arab region have focused on analysing trends in specific the length of the maximum number of consecutive wet days subregions or individual countries. (CWD) significantly decreased in Eritrea and Djibouti. This is likely to be associated with the sharp decline in total In the Mashreq, most studies using station data are annual precipitation in these areas observed around 2000– conducted at the country level. For instance, a recent 2010.49 Other work on climate trends in North Africa was analysis of 44 years of daily measurements from 58 stations conducted using globally available datasets. For instance, in the western, populated and agricultural areas of Jordan analysis of time evolution of air temperature and heatwaves over the period 1970–2013 showed a significant decrease in occurrences over this area for the period 1979–2011 have rainfall at a rate of 1.8 mm/yr.45 In the Syrian Arab Republic, shown a significant warming (1 °C–3 °C) appearing by the analysis of the 52-year record (1955–2006) from 30 selected mid-1960s over the Sahara and Sahel. This was associated synoptic stations for temperature and precipitation have with clear, higher frequencies of warm temperatures and revealed an overall decrease in precipitation in northern lower frequencies of cold temperatures, as well as longer and north eastern zones of the country, while autumn duration and more frequent occurrences of heatwaves (mean precipitation significantly increased at the stations lying frequency multiplied by 2 or 3 after 1997). The latter occurred mostly in the northern zone of central Syrian Arab Republic. mostly during the March–May dry season and tended to be

41 OVERVIEW

preceded by an abnormal warm episode starting over Libya and propagating eastward.50 Another study over sub-Saharan Africa (5°S–25°N) examined a combination of downscaled global datasets and station data covering the period 1979–2005. Results have shown a statistically significant increase in the annual number of warm days and nights and a corresponding decrease in cold days and nights. Moreover, increases in total annual precipitation were observed mainly in the western part of North Africa, accompanied by a significant decrease in the annual number of CDD in these regions51, which supports the findings of Donat et al. (2014). Regional warming trends have also been reported in country- level studies of North Africa, such as at stations in Libya52, Kawkaban, Yemen, 2013. Source : Wikimedia Commons/ Rod Waddington. Sudan53 Tunisia54 and Morocco. For instance, a study was conducted in the latter country on 20 selected stations for trends in terms of magnitude and significance over the the period 1970–2012, mostly located in the northern part northern Arabian Peninsula for day-time extremes, while, for of Morocco and covering the most important agricultural night-time extremes, the trends were higher and significant zones and also the rainiest regions that are contributing for the southern region especially during recent decades. most of the country’s water resources. As seen in previously Analysis of precipitation indices showed less robust results mentioned results, trend analysis indicated more statistically with no significant trends except for the annual number of significant trends for temperature than for precipitations days with precipitation greater than 10 mm (R10), which indices. In this study, all temperature-based indices showed showed a significant decrease during 1986–2008. Moreover, increasing trends for the number of warm days and nights the analysis of changes in the dew point temperature (Td) and a decrease for the number of cold days and nights over and mean sea-level pressure (MSLP) indicated a potential for the past four decades. On the other hand, precipitation significant dynamical control of climate change in this region. indices showed a tendency towards wetter conditions for a Another station-based study for the north-eastern Arabian few locations in the far north of Morocco, compared to the Peninsula/Gulf area and the period 1973–2012 has also drier conditions in the south.55 indicated an upward temperature trend of 0.8 °C on average, accompanied by a decrease in barometric pressure (1 hPa), Climate trends have also been assessed in the eastern reduction in humidity (6%), and decrease in visibility (9%).59 area of the Arab region, such as the Arabian Peninsula. These results generally support findings from country-level Analysis of quality controlled records of temperature analyses, such as reported statistically significant decreasing and precipitation data from a total of 44 stations56 was rainfall trend in Saudi Arabia of as much as 47.8 mm per conducted by AlSarmi and Washington (2011) for the period decade for the recent past (1994–2009), as well as significant 1980–2008 and has shown a significant warming trend. increasing rates of temperature which were faster in the Results indicated that annual minimum and maximum dry season of June–September (0.72 °C per decade) than temperatures have increased by 0.55 °C and 0.32 °C per the wet season of November–April (0.51 °C per decade).60 decade, respectively and over all the Arabian Peninsula, Another study over Kuwait for 1958–2000, based on summer which led to significant decrease in the Diurnal Temperature extreme temperatures, has indicated that the most significant Range (DTR). It was also shown that warming rates were observed heatwave events occurred in the last decade of the higher in the non-monsoonal region located north of 20° N 20th century.61 and that the highest significant warming was experienced in spring (March–April) and summer (May–September) As can be seen from these observations, the region has seasons. On the other hand, declining precipitation trends been subject to evident warming trends since the middle were observed but were insignificant and the interannual of the 20th century. Although the studies conducted give temperature and precipitation variability indicated a marked a reasonable idea of the status of the past climate and its negative association after 1998.57 A subsequent study trends to this date, it is important to note that most of the on climate extremes based on daily datasets indicated a available station data in the region are limited in coverage, general decreasing trend of cold temperature extremes and consistency and accessibility, which hampers accurate increasing trends of warm temperature extremes during the knowledge of climate trends over the whole Arab region. The period of analysis.58 In particular, a remarkable and highly availability of quality meteorological observation datasets significant increase in very warm nights has occurred in the and the access to long-term measurements is thus paramount last two decades with a rate of increase in frequency of 3.6% in this context and would allow a more thorough and detailed per decade over the period 1986–2008. On the other hand, analysis of the evolution of the climate with consideration of spatial patterns have shown, in general, higher temperature wider spatial coverage and longer time spans.

42 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

3 CLIMATE INDICES AND DATA make a global and multi-model comparison possible. ETCCDI SOURCES suggests 27 indices (Table 2) related to either temperature or precipitation, which are commonly calculated based on daily observed precipitation data and daily minimum and 3.1 Essential climate variables maximum temperatures.64

For purposes of consistently reporting climatological A set of extreme event indices that are most representative information, the climate is described by a set of 50 essential and of concern for the region were selected for study in this climate variables developed under the Global Climate report (see Chapter 1). Analysis of additional indices from Observing System (GCOS),62 which are listed in Table 1. IPCC the ETCCDI list can be generated from the RICCAR regional has adopted this set of variables as a basis for understanding climate modelling data that will be available on a regional past, current and possible future climate variability and knowledge hub to inform further research. change.63 The interest of Arab meteorologists in improving regional 3.2 Extreme event Indices analysis of extreme climate indices was evident at the RICCAR regional workshop on Climate Change Prediction/ Extreme weather events have a severe impact on many key Projection and Extreme Events Indices in the Arab Region, aspects of our lives, such as health, agriculture, economy and organized by WMO and ESCWA, in cooperation with the infrastructure and it is thus necessary to predict the patterns National Meteorological Service of Morocco (Casablanca, of future extreme events with a view to building the resilience March 2012). The workshop initiated intensive data- of Arab States. In this regard, observations provide a key collection and compilation activities using daily information foundation to understanding their long-term changes and the from a large number of weather stations in the region. The underpinning of climate model evaluation and projections. results allowed for the identification of annual maximum Indices for climate extremes were developed by the WMO daily precipitation trends and provided new information Expert Team on Climate Change Detection and Indices on extreme events over the Arab region using historical (ETCCDI) with the aim of providing an easily understandable observations, which are now documented in a peer-reviewed and manageable set of indices for impact studies and to journal article.65

TABLE 1: Essential climate variables

Surface Upper air Composition

- Air temperature - Temperature - Carbon dioxide - Air pressure - Water vapour - Methane ATMOSPHERIC - Precipitation - Wind speed and direction - Other long-lived greenhouse gases - Radiation budget - Cloud properties - Ozone and aerosols supported by - Water vapour - Earth radiation budget their precursors - Near-surface wind speed and direction

Surface Subsurface

- Sea-surface temperature - Temperature - Sea-surface salinity - Salinity - Sea level - Current - Sea state - Nutrients OCEANIC - Sea Ice - CO2 partial pressure - Surface current - Ocean acidity

- CO2 partial pressure - Oxygen - Ocean colour - Tracers - Ocean acidity - Phytoplankton

- River discharge - Permafrost - Leaf Area Index (LAI) - Water use - Albedo - Above-ground biomass - Groundwater - Land cover (including vegetation type) - Soil carbon TERRESTRIAL - Lakes - Fraction of absorbed - Soil Moisture - Snow cover photosynthetically active radiation - Fire disturbance - Glaciers and ice caps (FAPAR) - Ice sheets

Source: GCOS, 2010 43 OVERVIEW

TABLE 2: Climate Indices (developed by the WMO Expert Team on Climate Change Detection and Indices)

Index Description Definition Unit

Temperature indices TXn* Min Tmax Coldest daily maximum temperature °C

TNn* Min Tmin Coldest daily minimum temperature °C

TXx* Max Tmax Warmest daily maximum temperature °C

TNx* Max Tmin Warmest daily minimum temperature °C

DTR* Diurnal temperature range Mean difference between daily maximum and daily minimum temperature °C Annual number of days between the first occurrence of 6 consecutive days with GSL Growing season length days Tmean >5 °C and first occurrence of consecutive6 days with Tmean <5 °C. Annual number of days with at least 6 consecutive days when CSDI Cold spell duration index days Tmin <10th per centile Annual number of days with at least 6 consecutive days when WSDI Warm spell duration index days Tmax>90th per centile TX10p* Cool days Share of days when Tmax <10th per centile % of days

TN10p* Cool nights Share of days when Tmin <10th per centile % of days

TX90p* Warm days Share of days when Tmax >90th per centile % of days

TN90p* Warm nights Share of days when Tmin >90th per centile % of days

FD Frost days Annual number of days when Tmin <0 °C days

ID Icing days Annual number of days when Tmax <0 °C days

SU Summer days Annual number of days when Tmax >25 °C days

TR Tropical nights Annual number of days when Tmin >20 °C days

Precipitation indices Rx1day* Max 1-day precipitation Maximum 1-day precipitation total mm

Rx5day* Max 5-day precipitation Maximum 5-day precipitation total mm Annual total precipitation divided by the number of wet days SDII Simple daily intensity index mm/day (when precipitation ≥1.0 mm) Annual contribution from very wet R95p Annual sum of daily precipitation >95th per centile mm days Annual contribution from extremely R99p Annual sum of daily precipitation >99th per centile mm wet days PRCPTOT Annual contribution from wet days Annual sum of daily precipitation ≥1mm mm Maximum length of wet spell/ CWD Maximum annual number of consecutive days with daily precipitation ≥1.0 mm days consecutive wet days Maximum length of dry spell/ CDD Maximum annual number of consecutive days with daily precipitation <1.0 mm days consecutive dry days R10 mm Heavy precipitation days Annual number of days when precipitation ≥10mm days

R20 mm Very heavy precipitation days Annual number of days when precipitation ≥20mm days Precipitation above a user-defined Rnnmm Annual number of days when precipitation ≥nn mm (nn: user-defined threshold) days threshold

Note: All indices are calculated annually. * denotes indices which are also calculated monthly. Source: ETCCDI, 2009; Donat et al., 2014

44 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

3.3 Meteorological data sources

Climate datasets originate as measurements of sub-daily or daily weather variables collected over time and merged to create climate records. Point measurements taken in situ at observation stations are usually the most direct and therefore precise form of observation. For regional analysis, however, the point data may not be representative for larger regions, particularly where the terrain varies widely (e.g. mountains and coast) and the measurement itself can also be error- prone. As an example, measured precipitation observations can be lower than the actual amount due to losses from wind or evaporation. Such limitations should be kept in mind when using observed climate data. Also, observation data can be organized into gridded datasets, similar to how data are organized in climate model outputs. It is an interpolation of available observed station data from non-uniform point data to the selected grid. While an advantage of gridded data is that they can provide data at points where there are no observation stations, the quality of the gridded data is always a function of the amount of station data that they contain.

Due to the infrequency of reporting and quality assurance Snow cover over Lebanon, 2017. Source: Carol Chouchani Cherfane. issues, it can be difficult and time- consuming to work directly from station data. However, international research new methods for combining in situ observations with groups have created gridded observed datasets from such numerical methods and remote- sensing continue to station data that are suitable for climate-related studies and evolve. Even though measurements for a wide range of are freely available. These have gone through some type parameters exist, none of these datasets individually gives of quality control and further processing to improve their a perfect representation of the actual observations and usability. Generating re-analysis data is a specific application thus a combination of different datasets has been drawn that uses a numerical weather prediction (NWP) model to upon under RICCAR to make best use of their different incorporate all available meteorological observations (from characteristics. They include observed station data provided ground weather stations and satellites) into a common by meteorological services through ACSAD as well as the structure over an observed period of time, this process following datasets: is referred to as data assimilation.66 The outcome is data that are evenly spaced in the gridded structure of the NWP University of East Anglia Climatic Research Unit Time model, both horizontally and at various vertical levels in the Series (CRU v3.21) consists of datasets comprising atmosphere. Since, in these simulations, large amounts of month-by-month variations in climate, starting in 1901 surface and upper-air observations are assimilated, they on 0.5° resolution grids. Variables include cloud cover, provide a close representation of reality and are particularly diurnal temperature range, frost day frequency, potential useful for sites where there are no actual observations. evapotranspiration, precipitation, daily mean temperature, Reanalysis data are seen as an important component for monthly average daily maximum and minimum temperature, both testing and evaluating climate models and are also used vapour pressure and wet day frequency. Period of data used in combination with other observations to improve gridded for RICCAR was until 2012 according to data available at the observed datasets. As with all climate data, however, they time of study.67 have some limitations. An example is precipitation data from reanalyses, which have been shown to provide good Global Precipitation Climatology Project (GPCP v1.2) representation of the temporal precipitation distribution, but provides global monthly surface precipitation data at 60 can have large biases in precipitation magnitude, which can arcminute (1 degree) grid resolution from 1979 onwards.68 vary, depending on location. Reanalysed temperature data, on the contrary, generally show a better agreement with Global Precipitation Climatology Centre (GPCC v6): full data observations. reanalysis of monthly global land-surface precipitation based on the 67 200 stations worldwide. Data used at the time of Numerous historical meteorological datasets are available analysis covered the period 1901–2010 at a spatial resolution for the Arab region, with continuous developments, as of 0.5° x 0.5°.69

45 OVERVIEW

University of Delaware Air Temperature and Precipitation (UDEL v3.01) comprises a series of gridded temperature and precipitation datasets based on station records starting from 1900 (data used for this study covered the period 1900– 2010). It provides relatively detailed global land-surface climatology of the two most essential variables in a spatial resolution of 0.5° x 0.5°.70

Tropical Rainfall Measurement Mission Project (TRMM 3B42-v7), published by the Goddard Space Flight Center Distributed Active Archive Center (GSFC DAAC), provides daily precipitation data from 1997 onwards at a resolution of 0.25° x 0.25°.71 Amman, Jordan, 2017. Source: Carol Chouchani Cherfane. European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim Reanalysis is a global atmospheric reanalysis product that covers the period from 1979 onwards variability. The need for rescuing these climate assets and and is continuously updated in real time. It includes a ensuring high-quality, long-term climate time series to enable set of 3-hourly surface parameters, describing weather, a better understanding, detection and prediction of global as well as ocean-wave and land-surface conditions, and climate variability and change is therefore of paramount 6-hourly upper-air parameters covering the troposphere and importance. In this context, there has been rising awareness stratosphere. The spatial resolution is approximately 80 km among international bodies and the scientific community on (T255 spectral) on 60 vertical levels from the surface up to the key and urgent need to recover and transfer into digital 0.1 hPa.72 format historical weather observations held in perishable media in order to enable their treatment, which led to major WATCH forcing data methodology applied to ERA-Interim data rescue (DARE) initiatives. This concept refers to the (WFDEI) was used for setting up the hydrological models process of preserving all data at risk of being lost due to and for the bias correction of modelled precipitation. It is deterioration of the medium and digitizing current and past interpolated to a 0.5° x 0.5° grid and is a combination of data into computer-compatible form for easy access.76 These observations and reanalysis model data. As mentioned rescued data combined with already available data enable previously, the re-analysis uses NWP to incorporate all enhanced climate model evaluation and consequently better available weather observations into a common structure assessments of projections of the climate into the future that over an observed period of time.73 WFDEI covers the period can serve as input for policymakers to prepare appropriate 1979–2012 and is based on monthly observed values plans in view of climate change conditions. One of the from the CRU dataset that are distributed to daily values, important additional benefits is that longer climate records of according to the temporal distribution coming from the ERA- extended location coverage make possible a better analysis Interim reanalysis.74 of climate extremes.77

A number of DARE efforts are currently underway at the 3.3.1 Climate data rescue global, regional, and national levels, based on guiding principles developed by WMO, which includea number of Past records of the climate system represent key information DARE initiatives aimed at improving both the availability for undertaking thorough and reliable/comprehensive and accessibility to long-term and high-quality climate climate assessments. Despite the considerable amount records, as well as capacity-building through integrated of past climate data and recent efforts to improve data bilateral and multilateral DARE projects.78 An important availability and accessibility, records are still spatially and resource that has been recently developed is the I-DARE temporarily limited and are often not homogeneous in terms portal, which consists of a web-based database providing of quality standards. Moreover, it is estimated that most a single point of entry for information on the status of past climate records prior to the 1960s are not digitized and only and present DARE projects worldwide, on data that need to available in hard-copy or imaged form.75 Even raw digital be rescued and on the methods and technologies involved.79 climate data are frequently subject to a wide range of errors Moreover, as mentioned in the previous section, a set of which can be further introduced into the chain of processing climate-data standards and protocols has been developed and data transmission. This situation makes these records and implemented at the global level (e.g.temperature and unusable preventing undertaking reliable climate analysis precipitation extremes) in order to maximize the utility of and restricting the knowledge of past and future climate rescued data and newly produced datasets and overcome

46 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

issues related to data standards, digitization, exchange and include population growth, migration, changing consumption sharing at multi-spatial scales. patterns, regional conflicts and governance. The potential implications of climate change and future climate variability As part of RICCAR meetings, and further to recommendations are additional factors putting further pressure on its from participants for follow up actions on climate data availability, which varies in terms of occurrence and extent exchange between meteorological offices in the region across the region. and data rescue, ESCWA organized a Subregional Training Workshop on Climate Data Rescue and Digitization in 2013 Water resources availability is affected by the predominant under RICCAR. It aimed to provide training on theoretical and semi-arid to arid climate and the combination of high practical aspects of DARE and digitization of climate records, spatial and temporal rainfall variability. Only certain parts including discussion of methods of transferring source of the mountainous areas along the northern and southern medium, converting to digital records, required metadata, boundaries of the region exhibit prevailing wet conditions storage and back-up practices, quality-control of data and that enables the occurrence of surface water. Narrow coastal homogenization. It involved participants from meteorological plains in North Africa, the eastern Mediterranean, and the services in Jordan, State of Palestine, Saudi Arabia and south-western corner of the Arabian Peninsula receive Yemen and paved the way for collaboration opportunities considerable runoff from mountain ranges as opposed to the and for the initiation of new climate data rescue initiatives.80 interior deserts. In North Africa, the humid conditions in the One of the outcomes was the development of a climate data Atlas Mountains enable the occurrence of several coastal rescue implementation plan for the Jordanian Meteorological rivers in Morocco, Algeria and Tunisia such as the Sebou Department (JMD) and the Palestinian Meteorological River, the Chelif River and the Medjerda River respectively. Department (PMD). Paper records housed at JMD consisted primarily of notebooks containing daily and sub-hourly data, Surface water resources in the Mashreq are mainly derived as well as a large number of charts. from large, humid areas in the north of the Arab region that are characterized by higher and more consistent A joint ESCWA/WMO mission was thus conducted with JMD precipitation. The Taurus-Zagros Mountain range in the staff to train local staff on data rescue and digitization north captures significant precipitation from moist westerly of climate records; establish an inventory of climate data winds and constitutes the main headwaters of the Euphrates records in paper format to be recovered and digitized; and Tigris Rivers. Similarly, precipitation from the eastern ensure a safe and well organized archiving storage with Mediterranean mountain ranges feed the headwaters of the involvement of local authorities; and develop an the shared Jordan, Orontes and Nahr el Kabir Rivers, as implementation plan for the recovery and digitization of well as smaller Lebanese and Syrian Arab Republic rivers. all inventoried archives, including estimated time steps for South of the Arab region, runoff generated in the Ethiopian each element of the plan. As a result, the monthly registers and equatorial highlands constitute the headwaters of the and associated charts (temperature, humidity, rainfall, Nile River, which is shared by Egypt and Sudan as well as pressure, sunshine, and wind data) have been organized, nine other non-Arab riparian countries. As for the Arabian stored in labelled archival boxes, with each box catalogued Peninsula, its scant rainfall and very high evaporation rates electronically. Approximately 98% of the JMD paper notebook impede the occurrence of surface water and groundwater data have been inventoried, quality-controlled and keyed recharge and cannot sustain perennial river systems. The into the Jordanian Climate Data System (JCDMS). A mission irregular but intense rainfall that occurs in the mountainous between JMD and the PMD to rescue the Climate Data of areas along the Red Sea and Arabian Sea, however, West Bank Stations at JMD was also established and a joint accumulates in, and infiltrates along, the extensive wadi project to rescue climate data of 10 gauging stations from channels (intermittent streams), often constituting important the 1950s to the 1960s with the support of ESCWA and Sida localized sources of freshwater. is now completed.81 Groundwater resources constitute a major source of water supply in the region. Renewable groundwater resources are 3.4 Water resources in the Arab region limited and occur mainly in the form of shallow aquifers recharged from activities dependent on surface water, 3.4.1 Water availability especially during large floods. Most aquifer systems are found in large geological formations that can cover hundreds Water is a scarce and fragile resource in the Arab region, of kilometres with significant volumes of stored fossil with an uneven spatial and temporal distribution both at groundwater stemming mainly from past pluvial periods. regional level and within each country. Several factors have These non-renewable resources are found in particular in increased strains on this resource in terms of quantity and the Sahara and the Arabian Peninsula and span several Arab quality over recent decades. In a regional context, these States. Examples include the Nubian sandstone aquifer

47 OVERVIEW

(Egypt, Libya, Sudan and Chad), the north-western Sahara networks for both the impact and vulnerability assessments. aquifer (Algeria, Libya and Tunisia), the eastern Arabian It is derived from elevation data of the Shuttle Radar aquifer (Bahrain, Iraq, Jordan, Kuwait, Oman, Qatar, Saudi Topography Mission (SRTM) elevation data at 3 arcsecond Arabia, Syrian Arab Republic, United Arab Emirates (UAE) resolution (GL3S). The original SRTM data have been and Yemen) and the Disi aquifer (Saudi Arabia and Jordan). conditioned in terms of hydrology using a sequence of Smaller aquifer systems also exist, such as those in wadi automated procedures. Manual corrections were made where discharge areas, where several channels join and allow the necessary.82 Information on groundwater resources was used accumulation of thick alluvial deposits to form wadi aquifers. only for the vulnerability assessment, and was based on data They often constitute a major source of recharge to the deep included in the Map of Global Groundwater Vulnerability to underlying aquifers. In addition, coastal aquifers are common Floods and Droughts at the scale of 1: 25,000,000 published in the region especially around the Mediterranean, namely on in 2015.83 the northern coast of Egypt, the Lebanese coastline and the Gaza Strip, as well as several coastal cities along the eastern Gulf. 3.4.3 River discharge data

In line with natural spatial water availability, some countries River discharge observations are point measurements rely more on surface water resources (for example Egypt representing the integrated sum of all runoff occurring and Iraq), while others rely mainly on groundwater resources upstream of the measurement point. They provide an (for example Libya, Gulf countries), almost every Arab State important variable for analysing changing hydrological, depends for its water supply on rivers or aquifers that are climatological and development conditions in the upstream shared with neighbouring Arab or non-Arab countries. This basin. They also provide an important variable for calibrating high dependency underpins the necessity and importance and testing hydrological models. of transboundary cooperation for the efficient management of these resources and to ensure its sustainability, knowing Access to observed river discharge data is, however, limited that Arab States are among the most water-scarce countries in the Arab region. International sources from outside the in the world. In this regard, and based on mandates from the region proved to be the main supplier for river discharge Arab Ministerial Water Council, particular emphasis was given data, and it is of limited extent. Data from the Global Runoff to shared water resources in RICCAR by providing climate Data Centre (GRDC)84 was used but many discharge stations change projections and analysis for five selected shared had only short periods of record which ended in the early to surface water basins (See Chapter 4). mid-1980s. River discharge records were also obtained from various freely available reports and publications, such as a report published by the US Geological Survey (USGS) on the 3.4.2 Water basin delineations and drainage networks Tigris and Euphrates river basins.85 Some records were also obtained from national hydrological focal points designated The Hydrological data and maps from Shuttle elevation through the Arab Ministerial Water Council by Arab States. derivatives at multiple scales (HydroSHEDS) dataset was Longer records of observed river discharge would have used for topography, watershed delineation and drainage benefited the assessment.

Habbaniyah Lake, Anbar, Iraq, 2011. Source: Sadeq Oleiwi Sulaiman. 48 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

3.4.4 Lakes and reservoirs Western Asia is bounded by the Taurus-Zagros Mountain range in the north, which extends from southern Turkey Data sources on lakes and reservoirs used for the impact to the Iraq-Iran border. They extend for thousands of assessment are the following: kilometres and represent a barrier to the movement of cold airmasses from the north. Two other mountain Global Lakes and Wetlands Database (GLWD) is published chains run along the eastern Mediterranean shore: by the World Wildlife Fund (WWF) and the Centre for the Lebanon Western Mountain range with Qurnat as Environmental Systems Research, at the University of Kassel Sawda as its highest peak (3,090 m) and the Eastern in Germany based on the combination of best available Mountain Range (Anti-Lebanon) running parallel to it sources for lakes and wetlands on a global scale (1:1 to and stretching to the Golan Heights Plateau in the south, 1:3 million resolution), and the application of Geographic where Mount Hermon (2,814 m) on the Lebanese-Syrian Information Systems (GIS) functionality. It enabled the Arab Republic border is the highest peak. More than generation of a database focused on three coordinated half of the Syrian Arab Republic is covered by the Syrian levels: large lakes and reservoirs, smaller water bodies, and Desert (500,000 km2), which also extends into parts of wetlands.86 western Iraq, Jordan and Saudi Arabia.

Global Reservoir and Dam Database (GRanD) is based In the Arabian Peninsula, the Nafud Desert (65,000 km2) on the compilation of global available reservoir and dam spans north-western Saudi Arabia to the Dahna Desert. information with corrections and completion of missing It joins the Rub’ al Khali Desert, one of the world’s information from new sources or statistical approaches. largest sand deserts covering more than 650,000 km2 It initially included all reservoirs with a storage capacity in southern Saudi Arabia as well as parts of Oman, UAE of more than 0.1 km³, but many smaller reservoirs were and Yemen. The Arabian Peninsula also features several added depending on data availability.87 This dataset was mountain ranges, of which the Hijaz and Asir Mountains complemented with national data provided by ACSAD. along the length of the Red Sea coast reach elevations of 2,000 m. Further south, the Yemen Mountain range rises For the vulnerability assessment, data related to dams were up to 3,666 m along the southern stretch of the Red Sea based on the Aquastat 2015 database88 complemented with coast and then runs parallel to the Gulf of Aden as the data from national sources for selected countries (Oman, Hadhramaut Mountain range. The fertile Najd Plateau in Saudi Arabia, Iraq, Sudan and the Syrian Arab Republic).89 the centre of the Arabian Peninsula reaches elevations of up to 1,500 m as it slopes from west to east. Wadis and saltmarshes (sabkhas) are common features of the 4 TOPOGRAPHIC AND TERRESTRIAL peninsula. In the south-east, the Oman Mountain range FEATURES AND DATA SOURCES (Al-Hajar) borders the Gulf of Oman and eastern area of the UAE, peaking at more than 3,000 m at Jebel Shams. 4.1 Topographical features of the Arab region In addition to mountain ranges and highlands, the region also hosts areas well below sea level, of which the The Arab region extends over an area of some lowest exposed point on Earth at the Dead Sea 14,000,000 km2 including about 30,000 km of coastline, (422 m bsl) and other areas of depression such as and exhibits widely contrasting topography and distinctive Djibouti’s Lake Assal at 155 m bsl. landforms. It is characterized by large mountainous zones and vast deserts that cover most of the area, in which several oases create microclimates where limited agriculture can 4.1.1 Wadis be practiced. The Sahara Desert in North Africa spans elevations that range from 30 m below sea level to peaks Intermittent streams or wadis are one of the most that exceed 3,000 m in the Ahaggar Mountains in southern common and important landscape elements of the Algeria and the Tibesti Mountains in southern Libya. The region, in particular in the Arabian Peninsula, draining Atlas Mountains along the northern coast provide a shield wide catchment areas and ranging from ten to hundreds from the desert, stretching from south-western Morocco of kilometres in length. For example, Wadi al Batin is (peaking at 4,167 m) to the eastern edge of Tunisia. Further a shared wadi with a length of 970 km crossing Iraq, east, the Sinai Peninsula is largely desert with mountainous Kuwait and extending south-westwards into Saudi topography and covers a surface area of 13,000 km2. The Arabia, where it is referred to as Wadi ar Rimah. Wadis Karkaar Mountains in Somalia along the Gulf of Aden, provide have played an important role in both the ancient topographic relief to a landscape dominated by plateaus, and recent history of tribes zand settlements of the plains and highlands in the Horn of Africa. Peninsula such as in Yemen, Saudi Arabia and Oman,

49 OVERVIEW

providing important supplies of water to populations for adversely impacted plant and vegetation cover, constituted domestic and irrigation purposes. These seasonal streams corrosion hazards and caused damage to construction are affected by the drainage system, the transport and sites. They are currently being increasingly considered as texture of sediments, the frequency of overflows and the important ecosystems, however, and hold considerable variability of rainfall. Upon the offset of heavy rains, the potential as sources of solar power generation, algae culture peak flood carried by a wadi can reach some thousands of and hydrocarbon energy.94 cubic metres per second (m3/s). Better management and control of wadi flows is a subject of growing interest in Arab States from a disaster risk perspective, as destructive wadi 4.1.3 Oases overflows are common and cause major damage to dwellings and agricultural areas). They are also, however, an important Oases are isolated areas of vegetation found in deserts and source of freshwater to exploit in view of the ever-increasing represent complex and fragile agro-ecosystems. They are demand on water.90 It is to be noted that there is sometimes generally located along non-perennial rivers (wadis), shallow confusion between the English and Arabic language use of water tables or deep artesian groundwater, creating enough the term “wadi”, which also means “valley” in Arabic. pressure for water to seep to the surface. Natural oases are sustained by occasional rainstorms feeding the underground. Management practices and agricultural techniques that have 4.1.2 Sabkhas been implemented for millennia in the oases of the world reflect the remarkable skills of local populations in using Sabkhas or saline flats are a distinctive geomorphologic their limited natural resources in a sustainable manner. feature of the Arab region. These are salt-crusted depressions with impermeable floors lying just above the Oasis ecosystems are unique in nature and were sustained water table, where salt brine has accumulated after being in the Arab region through a rigorous management of limited subject to periodic flooding and evaporation.91 Sabkhas are water, land and biological resources over the years in strong commonly found in the eastern Arabian Peninsula (UAE, alliance with date-palm tree plantations. Traditionally, Qatar, Oman), in parts of Iraq and the Syrian Arab Republic, communities have planted strong trees, such as palms, as well as along the shores of the Gulf of Suez and the Red around the perimeter of oases to minimize damage and Sea and the coastal lands of North Africa, where they are encroachment from desert sand. The region is home to major commonly referred to as “shotts”.92 Outstanding examples oases such as the Al-Hasa Oasis in Saudi Arabia, which is of sabkhas include the Umm es Samim Sabkha, one of the the largest in the world, having a surface area exceeding highest salt formations in the region (100 m high) located 10,000 ha and hosting some 3 million palm trees.95 The in the east of the Rub’ al-Khali Desert in Oman. The Shott Tafilalet Oasis in Morocco is also one of the largest in el Djerid in Tunisia is another example; it constitutes the the world. The sustainability of the latter oasis system is largest saltpan of the Sahara Desert with a surface area increasingly being threatened. A recent study indicated that of more than 5,000 km2, and is part of a series of seasonal the groundwater table depth has dropped 50% over the past saltpans in the country fed from groundwater in the Atlas 40 years, leading to a 50% decline in the number of date- Mountains, some of which extend into Algeria.93 Until palm trees.96 Other major oasis systems are found in Algeria, recently, sabkhas were considered as wastelands which Tunisia, Egypt, Libya and the UAE.

Shott el Djerid, Tunisia, 2012. Source: Dennis Jarvis-flickr.com 50 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

For many decades, oases in the region have played an in Tunisia (2011), the Al Ain and Liwa Historical Date Palm essential role in the development of local communities and in Oases in UAE (2015) and, most recently, the Siwa Oasis in maintaining ecological balance owing to established cultural Egypt, which was recognized in 2016 for the preservation of and indigenous knowledge. They represent vital sites for the environmental and heritage ecosystem in the cultivation trade and transportation routes in deserts and are important of dates (see Box 2).98 Main challenges to achieving biodiversity and ecosystem-rich areas97 but are increasingly sustainable adaptive management of oases in the Arab vulnerable to changing environments. As such, they have region include shortage of information and knowledge on received much attention in the past few years, with several the status and trends of oasis ecosystem behaviour among being designated as Globally Important Agricultural Heritage decision-makers, as well as the lack of public awareness as a Systems (GIAHS) by the Food and Agricultural Organization means to support the implementation of best agro-ecological of the United Nations (FAO). These are the Oases System and economic management practices. in the Atlas Mountains of Morocco (2011), the Gafsa Oases

BOX 2: Siwa Oasis in Egypt

Siwa Oasis is located in a depression in the northern area wells. Agriculture has been, and continues to be, the most of Egypt’s Western Desert, 80 km from the Egyptian-Libyan important economic activity in Siwa and is the main source of border and 300 km south of the Mediterranean port town livelihood of its population. There are currently some 280,000 of Marsa Matrouh. Much of the depression sits below sea date-palms with an annual yield of about 25,000 tonnes of level, reaching 133 m bsl at its deepest. The climate of Siwa dates, which represent an important local staple food in the exhibits extreme aridity from April to November and very low oasis and a pillar for local food security. Similarly, the oasis rainfall from December to March (10 mm/yr on average), and hosts a significant share of national olive production with a its population increased from about 8,000 in 1980 to 28,000 total annual yield of 27,500 tonnes of green olives. Livestock in 2016. is also an important component of the Siwaian cropping system with a total number of about 9,000 goats and sheep The eco-geographical isolation of Siwa from the Nile and more than a thousand cattle providing manure as a Valley and Egyptian Delta made its conditions favourable source of organic fertilizer for crops. for agricultural production that depends completely on groundwater resources for irrigation. The oasis is located In 2002, the Egyptian Government declared 7,800 km2 in above two reservoirs of groundwater. The upper reservoir and around Siwa Oasis a protected area in recognition of its exhibits high salinity (1,800–7,500 ppm) and the deep Nubian cultural, biological and environmental diversity. In October sandstone reservoir exhibits salinity of the drinking-water 2016, FAO awarded the dates production sector in the Siwa standard (170–325 ppm). Oasis the Globally Important Agricultural Heritage Systems (GIAHS) certificate, which assigns the oasis the status of About 97 km2 (10% of the total depression area) are currently an international agricultural heritage system that preserves cultivated, comprising mainly date- palm and olive orchards agro-biodivesity, traditional knowledge and livelihoods that are irrigated by several hundred groundwater-fed associated with the cultivation of dates.

Siwa Oasis, Egypt, 2016. Source: FAO.

51 OVERVIEW

4.2 Topographic and other terrestrial data sources 4.2.3 Land use

For climate modelling, different sources were used to obtain For the impact assessment, the Global Land Cover (GLC terrestrial data with a varying level of detail depending on the 2000) dataset was used by SMHI for climate modelling. different models applied (Chapter 1). The WHIST programme Produced by an international partnership of 30 research (World Hydrological Input data Set-up Tool)99 was used to groups coordinated by the European Commission’s Joint prepare the baseline information for the models applied by Research Centre, the dataset is at 1 km resolution and SMHI in this study. Its function was to develop information contains two levels of land-cover information – detailed, for the hydrological models (such as the delineation of regionally optimized land-cover legends for each continent sub-basins, production of river routeing and calculation of and a less thematically detailed global legend that the proportions of soil and land-use classes) based on the harmonizes regional legends into one consistent product.102 different source databases on topography, soil, land use and agriculture detailed in the sections below. For modelling using the HEC-HMS model and for the Vulnerability Assessment, land use data was based on the Global Land Cover-SHARE (GLC-SHARE). It was published by 4.2.1 Topography FAO in 2014 and provides a set of 11 major thematic land- cover layers resulting from a combination of best available, Topography data are based on the HydroSHEDS Database100, high-resolution national, regional and/or subnational land- which is also used for drainage networks and watershed cover databases. The database is produced with a resolution delineation. of 30 arcseconds. The major benefit of the GLC-SHARE product is its capacity to preserve available land-cover information at the country level obtained by spatial and 4.2.2 Soils multi-temporal source data.103

Soil data were based on the Harmonized World Soil Database (HWSD). Version 1.2 is a 30 arcsecond raster database with 4.2.4 Agriculture over 15,000 different soil mapping units that combine existing regional and national updates of soil information For the impact and vulnerability assessments, Version 5 of worldwide. It is based on four source -databases: the the Global Map of Irrigation Areas (GMIA), published by FAO European Soil Database (ESDB), the Soil Map of China in 2013 was used. It shows the area equipped for irrigation (1:1 000 000), various regional SOTER Databases (SOTWIS around the year 2005 as a percentage of the total area as Database) and the FAO–UNESCO Soil Map of the World.101 a raster with a resolution of 5 arcminutes. Additional map

Jebel Akhdar, Libya, 2009. Source: Ihab Jnad.

52 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

layers show the percentage of the area equipped for irrigation The urban extent grids distinguish urban and rural areas that was actually used for irrigation.104 In addition, the Global based on a combination of population counts (persons), Monthly Irrigated and Rainfed Crop Areas (MIRCA) dataset settlement points and the presence of night-time lights. was used for the modelling undertaken by SMHI. It provides both irrigated and rainfed crop areas of 26 crop classes Share of children and elderly of total population. Data for for each month of the year with a spatial resolution of 5 this indicator was based on data of the Population Division of arcminutes.105 UN-DESA for the year 2015.111

4.2.5 Forest cover 5.2 Economic datasets

For the vulnerability assessment, a map of global forest Economic resources datasets included estimates on indicators change published by the Department of Geographical such as the gross domestic product (GDP) per capita, based on Sciences at the University of Maryland, USA, was used. It has the latest available data (2007–2014) published by the World a spatial resolution of 1 arcsecond and maps global forest Bank.112 Additionally, the International Development Statistics loss and gain from 2000 to 2012 based on Earth observation (IDS) online database was used to provide information on the satellite data.106 Official Development Assistance Index for the Arab States. It is based on the latest available data (2007–2014) and covers bilateral aid, multilateral aid, private providers’ aid and other 5 SOCIO-ECONOMIC DATA SOURCES resource flows to developing countries.113

The main socioeconomic-related datasets used for the vulnerability assessment are listed below. Detailed 5.3 Technology-related datasets information on the applied data, including metadata on data sources, how the data were developed, their spatial The International Telecommunication Union (ITU) dataset resolution, statistical scale etc., is provided in the individual of 2013 was used to provide information on Information and indicator factsheet that will be made available via the Communication Technologies (ICT) expressed as the ICT regional knowledge hub. Development Index per country.114

5.1 Demographic datasets 5.4 Equity-related datasets

The main data sources used for population and Some indicators of equity include the female to male demographics-related estimates in the region are presented unemployment ratio with data based on estimates by the below. International Labour Organization (ILO) as the latest available data (2007–2014).115 Another example is the female to male Population density. Estimates were based on the LandScan literacy ratio across Arab States that was provided through Global Population Database, which comprises the estimations for the year 2015 from the UNESCO Institute for geographical distribution of population at 1 km resolution. It Statistics.116 represents census data from the period 2010–2014 and was adjusted to take refugees and internally displaced people inot account in 2015.107 6 DISASTER LOSS DATABASES

Migrant and refugee population. Data from the Population The development of national disaster databases represents Division of the United Nations Department of Economic and a low-cost, high-impact strategy to systematically account Social Affairs (UN-DESA) for the years 2010–2015 were used for disaster losses. It is the crucial first step to generate to provide migrant population estimates108, while refugee the necessary knowledge to inform efficient risk estimation, population estimates were based on the United Nations climate change adaptation and disaster risk reduction (DRR) High Commissioner for Refugees (UNHCR) data of 2015.109 processes. National disaster databases record a good Estimates were given as the number of migrants/refugees number of indicators of loss of both human and economic per 1,000 inhabitants. assets, such as fatalities, injuries and evacuation, as well as damage to infrastructure and livelihood assets, such as Urban extent. Version 1 of the Global Rural-Urban Mapping housing, agriculture, livestock, critical services and line Project, (GRUMPv1) was used for this indicator and consists utilities. This information is collected locally with a relatively of estimates of human population for the years 1990, 1995, high degree of detail, usually up to the municipality level or and 2000 at 30 arcsecond (1 km) grid resolution.110 even lower, depending on the size of the country. 53 OVERVIEW

In order to strengthen global accounting for disaster losses, UNISDR initiated the Global Disaster Loss Collection Initiative that is designed to assist in the establishment of national disaster-loss databases in all regions of the world following a methodology established under “Desinventar”.117 It is the only publicly available methodology and open- source tool for building disaster databases, and permits the homogeneous capture, analysis and graphic representation of information on disaster occurrence and loss. It has been under continuous development and improvement for almost two decades, when Latin American countries began to build systematic disaster inventory databases. Forest fire, Lebanon, 2010. Source: Carol Chouchani Cherfane.

The Sendai Framework for Disaster Risk Reduction, well-informed decisions and effective disaster risk reduction adopted by the international community in March 2015, interventions, and whose main findings are presented in the was developed to guide efforts on disaster risk reduction following section. in the period 2015–2030 and calls for countries to systematically account their disaster losses in order to measure and understand their risks in all its dimensions 6.1 Main findings from disaster loss databases of vulnerability, capacity, exposure of persons and assets, in selected Arab States hazard characteristics and the environment. Recognizing the importance of having sound disaster loss and damage Nationally reported disaster datasets were used and databases to use as information for efficient risk reduction customized to take into account only disasters triggered and development, Arab States have recently expressed by natural hazards (weather-related or of geological origin) interest in establishing such databases. RICCAR supported and therefore excludes the records that refer to man-made the population of disaster loss databases in six Arab States, hazards (such as oil spills, technological disasters, etc.).119 In namely Jordan, Lebanon, Morocco, the State of Palestine, addition, the records were evaluated against a set of quality Tunisia and Yemen, based on the methodology and tools criteria prior to analysis.120 In order to compare disaster developed by UNISDR. The outcome was a comprehensive losses and damage across all six countries with national analysis of weather-related and geological disasters together disaster-loss databases, the last available 30–40 years with their socioeconomic and environmental impacts over were considered for the regional analysis. The breakdown a 30-year period. The findings of this report are based on of loss and damage due to disasters during this period national disaggregated disaster-loss data customized for the is summarized in Table 3 for the period covered in each 2015 Global Assessment Report on Disaster Risk Reduction country. (GAR, 2015)118, and provides an overview of the national risk context of the selected countries, based on their nationally As seen in Figure 8, forest fires were the highest in frequency accounted disaster loss and focusing attention on frequency, for the combined designated countries, followed by drought. mortality and economic loss indicators. The result is a In terms of combined economic losses by hazard type, historical review of disaster trends that provides the basis for results show that floods accounted for the highest share

TABLE 3: Summary of losses and damage for selected Arab States for the specified data periods

Country Data period Number of events Number of deaths Houses destroyed Houses damaged Damage to crops (ha)

Jordan 1982-2012 593 145 83 594 840

Lebanon 1980-2013 2,527 156 181 1,366 17,700

Morocco 1990-2013 713 2,165 5,109 21,915 281,807

State of 1980-2013 388 45 65 798 0 Palestine

Tunisia 1982-2013 1,918 330 17,821 24,728 837,288

Yemen 1971-2013 1,637 4,126 22,392 37,311 20,234

Source: based on Data provided by UNISDR, 2017a, based on Desinventar Consolidated Database, 2015 54 ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

(Figure 9), which was also often the case at the individual incontestable imperatives to invest in disaster risk reduction country level. In Yemen, for example, the vast majority of and climate change adaptation: for example, losses of economic losses (87%) were caused by floods and flash almost US$ 20 million per year in climate- related disasters floods. The highest human losses, by far, were reported in Morocco is a fact that can be used to justify projects using in Yemen and Morocco (even when comparing similar cost–benefit analyses. In Lebanon, where there is a much time periods) and the highest combined economic losses lower level of losses per year, database records show that culminated in Yemen with around US$ 3 billion, followed 40% of all costs are associated with forest fires, probably by Tunisia (about US$ 685 million) and Morocco (about making it a priority for climate change adaptation/disaster US$ 530 million) as shown in Figure 10. risk reduction plans. In Tunisia, almost 50% of all mortality due to floods is concentrated in the province of Sfax, while When examining the distribution of losses caused by climate- 70% of reported economic loss is concentrated in the related and geological hazards through the database, data province of Tozeur: regions that could obtain priority when records clearly show the prevalence, with the exception of designing actions to reduce flood risk. Yemen, of climate- related hazards as the source of most of the damage. In addition, climate-related hazards have very Data available through these disaster loss databases also defined increasing trends in the region. Frequency, mortality helped ACSAD generate updated flood risk maps for the and economic losses are on the rise, especially regarding Arab region, which were used to inform the vulnerability small- and medium-scale events (extensive events).121 assessment and particularly the sub-sector assessment related to inland flooding.

6.2 Using historical disaster data for climate FIGURE 9: Combined economic losses by hazard type in US$ change analysis Drought $110,489,628 (3%) Disaster-loss databases can play an important role in climate Snowstorm Earthquake $81,125,497 (2%) change analysis by helping in the identification of “hotspot” $155,975,021 (4%) Other areas, where impacts are higher or more recurrent than Forest fire $65,524,390 (1%) normal, helping prioritizing actions based on evidence and $244,142,211 (6%) by providing strong justification for investments in climate change adaptation and disaster risk reduction. A better understanding of patterns and trends and quantitative measures of risk can contribute to improving the process of planning by making it more transparent and comprehensive and can provide the quantitative measures needed to identify and advocate for solutions with the highest possible levels Flood of efficiency and/or effectiveness. In the case of the Arab $3,381,452,422 (84%) States considered, the elevated average annual losses are

FIGURE 8: Hazard frequency by type (for the six countries combined) FIGURE 10: Combined economic losses by country in US$

Jordan Frost - 125 (2%) $29,537,755 Lebanon Earthquake - 174 ( 2%) Erosion - 102 (1%) State of Palestine $48,871,381 Rain - 209 (3%) Other - 114 (1%) $11,559,086 Morocco Fire - 229 (3%) Forest Fire - 2,173 (28%) $530,370,196 Landslide - 289 (4%) Tunisia $684,634,428 Flood - 903 (12%)

Flash flood - 1,057 (13%) Drought - 1,228 (16%)

All storms* - 1,173 (15%) Yemen $3,023,206,166

* The “All storms” hazard includes, in order of descending frequency: Note: Figures 8,9 and 10 are based on Data provided by UNISDR, 2017a, based snowstorms, electric storms, storms, hailstorms, windstorms and sandstorms. on Desinventar Consolidated Database, 2015 55

OVERVIEW

ENDNOTES 33. IPCC, 2014 34. IPCC, 2014 1. There are 22 Arab States, namely Algeria, Bahrain, 35. IPCC, 2014 Comoros, Djibouti, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Mauritania, Morocco, Oman, State of Palestine, 36. NASA, 2017b Qatar, Saudi Arabia, Somalia, Sudan, Syrian Arab Republic, 37. IPCC, 2013 Tunisia, United Arab Emirates and Yemen. 38. IPCC, 2013 2. WMO, 2017 39. Asadieh and Krakauer, 2015 3. IPCC, 2014 40. Study by Zhang et al., 2005 covering the Mashreq and 4. ESCWA, 2008 Arabian Peninsula. 5. WCRP is co-sponsored by WMO, the International 41. The Regional Workshop on Climate Change Prediction/ Council for Science (ICSU) and the Intergovernmental Projection and Extreme Events Indices in the Arab Region, Oceanographic Commission of UNESCO. 13–16 March 2012, Casablanca, Morocco (ESCWA, 2012) 6. ESCWA, 2011; ACSAD et al., 2017; SMHI, 2017; 42. Data stations comprised the following countries: Algeria, ESCWA et al., 2017 Bahrain, Djibouti, Egypt, Jordan, Kuwait, Libya, Mauritania, 7. Shahin, 2007; WWF, 2011; UNEP, 2013 Morocco, Saudi Arabia, Sudan, Syrian Arab Republic, Tunisia and United Arab Emirates. 8. Based on Shahin, 2007; Odhiambo, 2016; Terink et al., 2013 43. Tanarhte et al., 2012 9. Brandimarte et al., 2011; Hurrell et al., 2013 44. Tanarhte et al., 2015 10. Krishnamurti et al., 2013 45. Rahman et al., 2015 11. Cornforth, 2012 ; Roehrig et al., 2013 46. MSEA and UNDP, 2010 12. Kelley et al., 2015; Flohr et al., 2017 47. Agha and Şarlak, 2016 13. UNISDR, 2017c 48. Tramblay et al., 2013 14. Khan, 2013; Express News, 2017; The National, 2017 49. Omondi et al., 2014 15. Vries et al., 2013 50. Fontaine et al., 2013 16. Fritz et al., 2010 51. Chaney et al., 2014 17. AccessScience, 2015; WHO, 2015 52. El-Fadli, 2012 18. Hereher, 2010; Hasan et al., 2015; Shaltout et al., 2015 53. Elagib, 2010 19. De Longueville et al., 2010; Almazroui, 2013; 54. Dahech and Beltrando, 2012 Giannadaki et al., 2014 55. Filahi et al., 2016 20. UNEP et al., 2016 56. Bahrain (1 station), Kuwait (1 station), Oman (24 stations), 21. WMO and UNEP, 2013 Qatar (1 station), Saudi Arabia (11 stations), United Arab Emirates (4 stations) and Yemen (2 stations). 22. NASA, 2015 57. AlSarmi and Washington, 2011 23. UNISDR, 2015b; Jasim, 2016 58. AlSarmi and Washington, 2014 24. The Daily Star Lebanon, 2015 59. Senafi and Anis, 2015 25. UNEP et al., 2016 60. Almazroui et al., 2012a; Almazroui et al., 2012b 26. UNEA, 2014 61. Nasrallah et al., 2004 27. Resolution A/RES/70/195 of 2015 (UNGA, 2015) 62. GCOS was founded in 1992 by WMO, the 28. UNEA, 2016 Intergovernmental Oceanographic Commission of 29. WMO and UNEP, 2013 UNESCO, UN Environment and the International Council for Science. 30. Stocker et al., 2013 63. Bojinski et al., 2014; GCOS, 2010 31. IPCC, 2014 64. The full list of extreme events indices can be found at 32. NASA, 2017a ETCCDI, 2009

ARAB CLIMATE CHANGE ASSESSMENT REPORT - MAIN REPORT

65. Donat et al., 2014. The full reference is Donat, M. G., 94. Gulf News Environment, 2015; The Gulf Today, 2015 Peterson, T. C., Brunet, M., King, A. D., et al. 2014. Changes 95. Aldakheel, 2011 in Extreme Temperature and Precipitation in the Arab Region: Long-term Trends and Variability Related to ENSO 96. Khoumsi et al., 2014; Euronews, 2016 and NAO. International Journal of Climatology, 34(3): 97. Hassan, 2003; Battesti, 2005; Mekki et al., 2013 p. 581-592. 98. FAO, 2017; Egyptian Desert Research Center, 2016; 66. Uppala et al., 2005 FAO, 2016 67. CRU, 2013 99. SMHI, 2014 68. Adler et al., 2003 100. Lehner et al., 2008 69. Schneider et al., 2011 101. Fischer et al., 2008; Batjes, 2012 70. NCAR, 2014 102. Arino et al., 2008; JRC, 2000 71. TRMM, 2015 103. Latham et al., 2014 72. Dee et al., 2011 104. FAO, 2013 ; Siebert et al., 2005 73. Uppala et al., 2005 105. Portmann et al., 2010 74. Weedon et al., 2014 106. Hansen et al., 2013 75. Brunet et al., 2014 107. University of Tennessee Battelle, 2015 76. WMO, 2016 108. UN-DESA, 2016a 77. McGregor, 2015 109. UNHCR, 2016 78. WMO, 2015 110. CIESIN, 2014 79. WMO and GFCS, 2016b. The portal is maintained by 111. UN-DESA, 2016b WMO with the assistance of the Royal Netherlands Meteorological Institute and the WMO Commission of 112. The World Bank, 2015 Climatology Expert Team on Data Rescue. 113. OECD, 2015 80. ESCWA, 2013 114. ITU, 2016 81. ESCWA, 2014; WMO and GFCS, 2016a 115. ILO, 2015 82. Lehner et al., 2008 116. UNESCO Institute for Statistics, 2015 83. BGR and UNESCO, 2015b. Data on groundwater resources 117. DesInventar, 2016. DesInventar is an open-source data tool basins in this map is based on the Groundwater Resources which helps to compile a detailed disaster loss and damage Map of the World 1:25 000 000 published by BGR/UNESCO inventory. It offers several functions for the analysis of in 2008 and complemented by additional types of aquifers information gathered based on assessments following pre- which were added in 2015 (BGR and UNESCO, 2015a). defined but adaptable indicators through a very simple and 84. GRDC, 2012 user-friendly interface. 85. USGS, 2012 118. UNISDR, 2015a 86. Lehner and Döll, 2004; WWF and CESR, 2004 119. GAR can be accessed at: www.desinventar.net 87. GWSP, 2015; Lehner et al., 2011 120. More information on the methodology and subsequent datasets is available in the technical report Disaster Loss Data 88. FAO, 2015 and Linkage to Climate Change Impacts for the Arab Region 89. Information from the Aquastat database was from the (2017), which was prepared by the UNISDR Regional Office for year 2010 data and that from national sources from 2013 Arab States as part of RICCAR publication series (UNISDR, 2017). data. Refer to the factsheet “Areas served by Dams” for 121. Extensive disaster risk events refer to low-severity, high- detailed information on the datasets used for the frequency disasters, while intensive events have a high level of vulnerability assessment. intensity with mid to low frequencies. 90. Based on Edgell, 2006; Şen, 2008; Shahin, 2007 91. West, 2013 92. Al-Farraj, 2005; Ghazanfar, 2006; Ashour, 2013; El-Omla and Aboulela, 2012 93. IUCN, 2015 57

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