Climate Scenario Development
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Point Downscaling of Surface Wind Speed for Forecast Applications
MARCH 2018 T A N G A N D B A S S I L L 659 Point Downscaling of Surface Wind Speed for Forecast Applications BRIAN H. TANG Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York NICK P. BASSILL New York State Mesonet, Albany, New York (Manuscript received 23 May 2017, in final form 26 December 2017) ABSTRACT A statistical downscaling algorithm is introduced to forecast surface wind speed at a location. The down- scaling algorithm consists of resolved and unresolved components to yield a time series of synthetic wind speeds at high time resolution. The resolved component is a bias-corrected numerical weather prediction model forecast of the 10-m wind speed at the location. The unresolved component is a simulated time series of the high-frequency component of the wind speed that is trained to match the variance and power spectral density of wind observations at the location. Because of the stochastic nature of the unresolved wind speed, the downscaling algorithm may be repeated to yield an ensemble of synthetic wind speeds. The ensemble may be used to generate probabilistic predictions of the sustained wind speed or wind gusts. Verification of the synthetic winds produced by the downscaling algorithm indicates that it can accurately predict various fea- tures of the observed wind, such as the probability distribution function of wind speeds, the power spectral density, daily maximum wind gust, and daily maximum sustained wind speed. Thus, the downscaling algo- rithm may be broadly applicable to any application that requires a computationally efficient, accurate way of generating probabilistic forecasts of wind speed at various time averages or forecast horizons. -
Climate Change and Human Health: Risks and Responses
Climate change and human health RISKS AND RESPONSES Editors A.J. McMichael The Australian National University, Canberra, Australia D.H. Campbell-Lendrum London School of Hygiene and Tropical Medicine, London, United Kingdom C.F. Corvalán World Health Organization, Geneva, Switzerland K.L. Ebi World Health Organization Regional Office for Europe, European Centre for Environment and Health, Rome, Italy A.K. Githeko Kenya Medical Research Institute, Kisumu, Kenya J.D. Scheraga US Environmental Protection Agency, Washington, DC, USA A. Woodward University of Otago, Wellington, New Zealand WORLD HEALTH ORGANIZATION GENEVA 2003 WHO Library Cataloguing-in-Publication Data Climate change and human health : risks and responses / editors : A. J. McMichael . [et al.] 1.Climate 2.Greenhouse effect 3.Natural disasters 4.Disease transmission 5.Ultraviolet rays—adverse effects 6.Risk assessment I.McMichael, Anthony J. ISBN 92 4 156248 X (NLM classification: WA 30) ©World Health Organization 2003 All rights reserved. Publications of the World Health Organization can be obtained from Marketing and Dis- semination, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland (tel: +41 22 791 2476; fax: +41 22 791 4857; email: [email protected]). Requests for permission to reproduce or translate WHO publications—whether for sale or for noncommercial distribution—should be addressed to Publications, at the above address (fax: +41 22 791 4806; email: [email protected]). 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 World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. -
Climate Scenarios Developed from Statistical Downscaling Methods. IPCC
Guidelines for Use of Climate Scenarios Developed from Statistical Downscaling Methods RL Wilby1,2, SP Charles3, E Zorita4, B Timbal5, P Whetton6, LO Mearns7 1Environment Agency of England and Wales, UK 2King’s College London, UK 3CSIRO Land and Water, Australia 4GKSS, Germany 5Bureau of Meteorology, Australia 6CSIRO Atmospheric Research, Australia 7National Center for Atmospheric Research, USA August 2004 Document history The Guidelines for Use of Climate Scenarios Developed from Statistical Downscaling Methods constitutes “Supporting material” of the Intergovernmental Panel on Climate Change (as defined in the Procedures for the Preparation, Review, Acceptance, Adoption, Approval, and Publication of IPCC Reports). The Guidelines were prepared for consideration by the IPCC at the request of its Task Group on Data and Scenario Support for Impacts and Climate Analysis (TGICA). This supporting material has not been subject to the formal intergovernmental IPCC review processes. The first draft of the Guidelines was produced by Rob Wilby (Environment Agency of England and Wales) in March 2003. Subsequently, Steven Charles, Penny Whetton, and Eduardo Zorito provided additional materials and feedback that were incorporated by June 2003. Revisions were made in the light of comments received from Elaine Barrow and John Mitchell in November 2003 – most notably the inclusion of a worked case study. Further comments were received from Penny Whetton and Steven Charles in February 2004. Bruce Hewitson, Jose Marengo, Linda Mearns, and Tim Carter reviewed the Guidelines on behalf of the Task Group on Data and Scenario Support for Impacts and Climate Analysis (TGICA), and the final version was published in August 2004. 2/27 Guidelines for Use of Climate Scenarios Developed from Statistical Downscaling Methods 1. -
Developing and Applying Scenarios
3 Developing and Applying Scenarios TIMOTHY R. CARTER (FINLAND) AND EMILIO L. LA ROVERE (BRAZIL) Lead Authors: R.N. Jones (Australia), R. Leemans (The Netherlands), L.O. Mearns (USA), N. Nakicenovic (Austria), A.B. Pittock (Australia), S.M. Semenov (Russian Federation), J. Skea (UK) Contributing Authors: S. Gromov (Russian Federation), A.J. Jordan (UK), S.R. Khan (Pakistan), A. Koukhta (Russian Federation), I. Lorenzoni (UK), M. Posch (The Netherlands), A.V. Tsyban (Russian Federation), A. Velichko (Russian Federation), N. Zeng (USA) Review Editors: Shreekant Gupta (India) and M. Hulme (UK) CONTENTS Executive Summary 14 7 3. 6 . Sea-Level Rise Scenarios 17 0 3. 6 . 1 . Pu r p o s e 17 0 3. 1 . Definitions and Role of Scenarios 14 9 3. 6 . 2 . Baseline Conditions 17 0 3. 1 . 1 . In t r o d u c t i o n 14 9 3. 6 . 3 . Global Average Sea-Level Rise 17 0 3. 1 . 2 . Function of Scenarios in 3. 6 . 4 . Regional Sea-Level Rise 17 0 Impact and Adaptation As s e s s m e n t 14 9 3. 6 . 5 . Scenarios that Incorporate Var i a b i l i t y 17 1 3. 1 . 3 . Approaches to Scenario Development 3. 6 . 6 . Application of Scenarios 17 1 and Ap p l i c a t i o n 15 0 3. 1 . 4 . What Changes are being Considered? 15 0 3. 7 . Re p r esenting Interactions in Scenarios and Ensuring Consistency 17 1 3. 2 . Socioeconomic Scenarios 15 1 3. -
Downscaling of General Circulation Models for Regionalisation of Water
Climate Change Causes and Hydrologic Predictive Capabilities V.V. Srinivas Associate Professor Department of Civil Engineering Indian Institute of Science, Bangalore [email protected] 1 2 Overview of Presentation Climate Change Causes Effects of Climate Change Hydrologic Predictive Capabilities to Assess Impacts of Climate Change on Future Water Resources . GCMs and Downscaling Methods . Typical case studies Gaps where more research needs to be focused 3 Weather & Climate Weather Definition: Condition of the atmosphere at a particular place and time Time scale: Hours-to-days Spatial scale: Local to regional Climate Definition: Average pattern of weather over a period of time Time scale: Decadal-to-centuries and beyond Spatial scale: Regional to global Climate Change Variation in global and regional climates 4 Climate Change – Causes Variation in the solar output/radiation Sun-spots (dark patches) (11-years cycle) (Source: PhysicalGeography.net) Cyclic variation in Earth's orbital characteristics and tilt - three Milankovitch cycles . Change in the orbit shape (circular↔elliptical) (100,000 years cycle) . Changes in orbital timing of perihelion and aphelion – (26,000 years cycle) . Changes in the tilt (obliquity) of the Earth's axis of rotation (41,000 year cycle; oscillates between 22.1 and 24.5 degrees) 5 Climate Change - Causes Volcanic eruptions Ejected SO2 gas reacts with water vapor in stratosphere to form a dense optically bright haze layer that reduces the atmospheric transmission of incoming solar radiation Figure : Ash column generated by the eruption of Mount Pinatubo. (Source: U.S. Geological Survey). 6 Climate Change - Causes Variation in Atmospheric GHG concentration Global warming due to absorption of longwave radiation emitted from the Earth's surface Sources of GHGs . -
Downscaling Climate Modelling for High-Resolution Climate Information and Impact Assessment
HANDBOOK N°6 Seminar held in Lecce, Italy 9 - 20 March 2015 Euro South Mediterranean Initiative: Climate Resilient Societies Supported by Low Carbon Economies Downscaling Climate Modelling for High-Resolution Climate Information and Impact Assessment Project implemented by Project funded by the AGRICONSULTING CONSORTIUM EuropeanA project Union funded by Agriconsulting Agrer CMCC CIHEAM-IAM Bari the European Union d’Appolonia Pescares Typsa Sviluppo Globale 1. INTRODUCTION 2. DOWNSCALING SCENARIOS 3. SEASONAL FORECASTS 4. CONCEPTS & EXAMPLES 5. CONCLUSIONS 6. WEB LINKS 7. REFERENCES DISCLAIMER The information and views set out in this document are those of the authors and do not necessarily reflect the offi- cial opinion of the European Union. Neither the European Union, its institutions and bodies, nor any person acting on their behalf, may be held responsible for the use which may be made of the information contained herein. The content of the report is based on presentations de- livered by speakers at the seminars and discussions trig- gered by participants. Editors: The ClimaSouth team with contributions by Neil Ward (lead author), E. Bucchignani, M. Montesarchio, A. Zollo, G. Rianna, N. Mancosu, V. Bacciu (CMCC experts), and M. Todorovic (IAM-Bari). Concept: G.H. Mattravers Messana Graphic template: Zoi Environment Network Graphic design & layout: Raffaella Gemma Agriconsulting Consortium project directors: Ottavio Novelli / Barbara Giannuzzi Savelli ClimaSouth Team Leader: Bernardo Sala Project funded by the EuropeanA project Union funded by the European Union Acronyms | Disclaimer | CS website 2 1. INTRODUCTION 2. DOWNSCALING SCENARIOS 3. SEASONAL FORECASTS 4. CONCEPTS & EXAMPLES 5. CONCLUSIONS 6. WEB LINKS 7. REFERENCES FOREWORD The Mediterranean region has been identified as a cli- ernment, the private sector and civil society. -
A Review of Climate Change Scenarios and Preliminary Rainfall Trend Analysis in the Oum Er Rbia Basin, Morocco
WORKING PAPER 110 A Review of Climate Drought Series: Paper 8 Change Scenarios and Preliminary Rainfall Trend Analysis in the Oum Er Rbia Basin, Morocco Anne Chaponniere and Vladimir Smakhtin Postal Address P O Box 2075 Colombo Sri Lanka Location 127, Sunil Mawatha Pelawatta Battaramulla Sri Lanka Telephone +94-11 2787404 Fax +94-11 2786854 E-mail [email protected] Website http://www.iwmi.org SM International International Water Management IWMI isaFuture Harvest Center Water Management Institute supportedby the CGIAR ISBN: 92-9090-635-9 Institute ISBN: 978-92-9090-635-9 Working Paper 110 Drought Series: Paper 8 A Review of Climate Change Scenarios and Preliminary Rainfall Trend Analysis in the Oum Er Rbia Basin, Morocco Anne Chaponniere and Vladimir Smakhtin International Water Management Institute IWMI receives its principal funding from 58 governments, private foundations and international and regional organizations known as the Consultative Group on International Agricultural Research (CGIAR). Support is also given by the Governments of Ghana, Pakistan, South Africa, Sri Lanka and Thailand. The authors: Anne Chaponniere is a Post Doctoral Fellow in Hydrology and Water Resources at IWMI Sub-regional office for West Africa (Accra, Ghana). Vladimir Smakhtin is a Principal Hydrologist at IWMI Headquarters in Colombo, Sri Lanka. Acknowledgments: The study was supported from IWMI core funds. The paper was reviewed by Dr Hugh Turral (IWMI, Colombo). Chaponniere, A.; Smakhtin, V. 2006. A review of climate change scenarios and preliminary rainfall trend analysis in the Oum er Rbia Basin, Morocco. Working Paper 110 (Drought Series: Paper 8) Colombo, Sri Lanka: International Water Management Institute (IWMI). -
Challenges in the Paleoclimatic Evolution of the Arctic and Subarctic Pacific Since the Last Glacial Period—The Sino–German
challenges Concept Paper Challenges in the Paleoclimatic Evolution of the Arctic and Subarctic Pacific since the Last Glacial Period—The Sino–German Pacific–Arctic Experiment (SiGePAX) Gerrit Lohmann 1,2,3,* , Lester Lembke-Jene 1 , Ralf Tiedemann 1,3,4, Xun Gong 1 , Patrick Scholz 1 , Jianjun Zou 5,6 and Xuefa Shi 5,6 1 Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung Bremerhaven, 27570 Bremerhaven, Germany; [email protected] (L.L.-J.); [email protected] (R.T.); [email protected] (X.G.); [email protected] (P.S.) 2 Department of Environmental Physics, University of Bremen, 28359 Bremen, Germany 3 MARUM Center for Marine Environmental Sciences, University of Bremen, 28359 Bremen, Germany 4 Department of Geosciences, University of Bremen, 28359 Bremen, Germany 5 First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; zoujianjun@fio.org.cn (J.Z.); xfshi@fio.org.cn (X.S.) 6 Pilot National Laboratory for Marine Science and Technology, Qingdao 266061, China * Correspondence: [email protected] Received: 24 December 2018; Accepted: 15 January 2019; Published: 24 January 2019 Abstract: Arctic and subarctic regions are sensitive to climate change and, reversely, provide dramatic feedbacks to the global climate. With a focus on discovering paleoclimate and paleoceanographic evolution in the Arctic and Northwest Pacific Oceans during the last 20,000 years, we proposed this German–Sino cooperation program according to the announcement “Federal Ministry of Education and Research (BMBF) of the Federal Republic of Germany for a German–Sino cooperation program in the marine and polar research”. Our proposed program integrates the advantages of the Arctic and Subarctic marine sediment studies in AWI (Alfred Wegener Institute) and FIO (First Institute of Oceanography). -
Cccma CMIP6 Model Updates
CCCma CMIP6 Model Updates CanESM2! CanESM5! CMIP5 CMIP6 AGCM4.0! AGCM5! CTEM NEW COUPLER CTEM5 CMOC LIM2 CanOE OGCM4.0! Model Improvements NEMO3.4! Atmosphere Ocean − model levels increased from 35 to 49 − new ocean model based on NEMO3.4 (ORCA1) st nd − aerosol updates (1 and 2 indirect effects) − LIM2 sea-ice component − improved treatment of volcanic aerosol − new in-house coupler developed − improved aerosol radiative effects for black and organic carbon Ocean Biogeochemistry − subgrid scale lakes added (FLAKE) − new parameterization, the Canadian Ocean Ecosystem model, CanOE Land Surface − double the number of biogeochemical tracers − land-surface scheme updated CLASS2.7→CLASS3.6 − increase number of classes of phytoplankton, − improved treatment of snow and snow albedo zooplankton and detritus from one to two − land biogeochemistry → wetlands added with − prognostic iron cycle methane emissions CanESM Functionality − new mineral dust parameterization − new “relaxed CO2” option for specified CO2 concentration simulations Other issues: 1. We are currently in the process of migrating to a new supercomputing system – being installed now and should be running on it over the next few months. 2. Global climate model development is integrated with development of operational seasonal prediction system, decadal prediction system, and regional climate downscaling system. 3. We are also increasingly involved in aspects of ‘climate services’ – providing multi-model climate scenario information to impact and adaptation users, decision-makers, -
A Performance Evaluation of Dynamical Downscaling of Precipitation Over Northern California
sustainability Article A Performance Evaluation of Dynamical Downscaling of Precipitation over Northern California Suhyung Jang 1,*, M. Levent Kavvas 2, Kei Ishida 3, Toan Trinh 2, Noriaki Ohara 4, Shuichi Kure 5, Z. Q. Chen 6, Michael L. Anderson 7, G. Matanga 8 and Kara J. Carr 2 1 Water Resources Research Center, K-Water Institute, Daejeon 34045, Korea 2 Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA; [email protected] (M.L.K.); [email protected] (T.T.); [email protected] (K.J.C.) 3 Department of Civil and Environmental Engineering, Kumamoto University, Kumamoto 860-8555, Japan; [email protected] 4 Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY 82071, USA; [email protected] 5 Department of Environmental Engineering, Toyama Prefectural University, Toyama 939-0398, Japan; [email protected] 6 California Department of Water Resources, Sacramento, CA 95814, USA; [email protected] 7 California Department of Water Resources, Sacramento, CA 95821, USA; [email protected] 8 US Bureau of Reclamation, Sacramento, CA 95825, USA; [email protected] * Correspondence: [email protected]; Tel.: +82-42-870-7413 Received: 29 June 2017; Accepted: 9 August 2017; Published: 17 August 2017 Abstract: It is important to assess the reliability of high-resolution climate variables used as input to hydrologic models. High-resolution climate data is often obtained through the downscaling of Global Climate Models and/or historical reanalysis, depending on the application. In this study, the performance of dynamically downscaled precipitation from the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) reanalysis data (NCEP/NCAR reanalysis I) was evaluated at point scale, watershed scale, and regional scale against corresponding in situ rain gauges and gridded observations, with a focus on Northern California. -
Statistical Downscaling
Statistical downscaling of the Community Climate System Model (CCSM) monthly temperature and precipitation projections White Paper by Tim Hoar and Doug Nychka (IMAGe/NCAR) April 2008 Statistical Downscaling The outputs from the Community Climate System Model (CCSM) may be relatively coarse for applications on regional and local scales. This results from an attempt to balance the computational cost of producing many long simulations and the cost of running at higher resolutions. W hile useful for their intended purpose, it is also desirable to use this information at a local scale. The spatial resolution of climate change datasets generated from the CCSM runs is approximately 1.4 x 1.4 degrees (Figure 1). Figure 1: Centroids of CCSM grid cells at approximately 1.4 degree spatial resolution Downscaling is the general name for a procedure to take information known at large scales to make predictions at local scales. Statistical downscaling is a two-step process consisting of i) the development of statistical relationships between local climate variables (e.g., surface air temperature and precipitation) and large-scale predictors (e.g., pressure fields), and ii) the application of such relationships to the output of Global Climate Model (GCM) experiments to simulate local climate characteristics in the future. Statistical downscaling may be used in climate impacts assessment at regional and local scales and when suitable observed data are available to derive the statistical relationships. A variety of statistical downscaling methods have been developed, ranging from seasonal and monthly to daily and hourly climate and weather simulations on a local scale. The majority of methods have been developed for the US, European and Japanese locations, where long-term observed data are available for model calibration and verification. -
Climate Change Scenario Report
2020 CLIMATE CHANGE SCENARIO REPORT WWW.SUSTAINABILITY.FORD.COM FORD’S CLIMATE CHANGE PRODUCTS, OPERATIONS: CLIMATE SCENARIO SERVICES AND FORD FACILITIES PUBLIC 2 Climate Change Scenario Report 2020 STRATEGY PLANNING TRUST EXPERIENCES AND SUPPLIERS POLICY CONCLUSION ABOUT THIS REPORT In conjunction with our annual sustainability report, this Climate Change CONTENTS Scenario Report is intended to provide stakeholders with our perspective 3 Ford’s Climate Strategy on the risks and opportunities around climate change and our transition to a low-carbon economy. It addresses details of Ford’s vision of the low-carbon 5 Climate Change Scenario Planning future, as well as strategies that will be important in managing climate risk. 11 Business Strategy for a Changing World This is Ford’s second climate change scenario report. In this report we use 12 Trust the scenarios previously developed, while further discussing how we use scenario analysis and its relation to our carbon reduction goals. Based on 13 Products, Services and Experiences stakeholder feedback, we have included physical risk analysis, additional 16 Operations: Ford Facilities detail on our electrification plan, and policy engagement. and Suppliers 19 Public Policy This report is intended to supplement our first report, as well as our Sustainability Report, and does not attempt to cover the same ground. 20 Conclusion A summary of the scenarios is in this report for the reader’s convenience. An explanation of how they were developed, and additional strategies Ford is using to address climate change can be found in our first report. SUSTAINABLE DEVELOPMENT GOALS Through our climate change scenario planning we are contributing to SDG 6 Clean water and sanitation, SDG 7 Affordable and clean energy, SDG 9 Industry, innovation and infrastructure and SDG 13 Climate action.