Climate Change Scenarios PRECIS
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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 Models and Their Evaluation
8 Climate Models and Their Evaluation Coordinating Lead Authors: David A. Randall (USA), Richard A. Wood (UK) Lead Authors: Sandrine Bony (France), Robert Colman (Australia), Thierry Fichefet (Belgium), John Fyfe (Canada), Vladimir Kattsov (Russian Federation), Andrew Pitman (Australia), Jagadish Shukla (USA), Jayaraman Srinivasan (India), Ronald J. Stouffer (USA), Akimasa Sumi (Japan), Karl E. Taylor (USA) Contributing Authors: K. AchutaRao (USA), R. Allan (UK), A. Berger (Belgium), H. Blatter (Switzerland), C. Bonfi ls (USA, France), A. Boone (France, USA), C. Bretherton (USA), A. Broccoli (USA), V. Brovkin (Germany, Russian Federation), W. Cai (Australia), M. Claussen (Germany), P. Dirmeyer (USA), C. Doutriaux (USA, France), H. Drange (Norway), J.-L. Dufresne (France), S. Emori (Japan), P. Forster (UK), A. Frei (USA), A. Ganopolski (Germany), P. Gent (USA), P. Gleckler (USA), H. Goosse (Belgium), R. Graham (UK), J.M. Gregory (UK), R. Gudgel (USA), A. Hall (USA), S. Hallegatte (USA, France), H. Hasumi (Japan), A. Henderson-Sellers (Switzerland), H. Hendon (Australia), K. Hodges (UK), M. Holland (USA), A.A.M. Holtslag (Netherlands), E. Hunke (USA), P. Huybrechts (Belgium), W. Ingram (UK), F. Joos (Switzerland), B. Kirtman (USA), S. Klein (USA), R. Koster (USA), P. Kushner (Canada), J. Lanzante (USA), M. Latif (Germany), N.-C. Lau (USA), M. Meinshausen (Germany), A. Monahan (Canada), J.M. Murphy (UK), T. Osborn (UK), T. Pavlova (Russian Federationi), V. Petoukhov (Germany), T. Phillips (USA), S. Power (Australia), S. Rahmstorf (Germany), S.C.B. Raper (UK), H. Renssen (Netherlands), D. Rind (USA), M. Roberts (UK), A. Rosati (USA), C. Schär (Switzerland), A. Schmittner (USA, Germany), J. Scinocca (Canada), D. Seidov (USA), A.G. -
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. -
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). -
Chapter 3. Modelling the Climate System
Introduction to climate dynamics and climate modelling - http://www.climate.be/textbook Chapter 3. Modelling the climate system 3.1 Introduction 3.1.1 What is a climate model ? In general terms, a climate model could be defined as a mathematical representation of the climate system based on physical, biological and chemical principles (Fig. 3.1). The equations derived from these laws are so complex that they must be solved numerically. As a consequence, climate models provide a solution which is discrete in space and time, meaning that the results obtained represent averages over regions, whose size depends on model resolution, and for specific times. For instance, some models provide only globally or zonally averaged values while others have a numerical grid whose spatial resolution could be less than 100 km. The time step could be between minutes and several years, depending on the process studied. Even for models with the highest resolution, the numerical grid is still much too coarse to represent small scale processes such as turbulence in the atmospheric and oceanic boundary layers, the interactions of the circulation with small scale topography features, thunderstorms, cloud micro-physics processes, etc. Furthermore, many processes are still not sufficiently well-known to include their detailed behaviour in models. As a consequence, parameterisations have to be designed, based on empirical evidence and/or on theoretical arguments, to account for the large-scale influence of these processes not included explicitly. Because these parameterisations reproduce only the first order effects and are usually not valid for all possible conditions, they are often a large source of considerable uncertainty in models. -
Chapter 1 Ozone and Climate
1 Ozone and Climate: A Review of Interconnections Coordinating Lead Authors John Pyle (UK), Theodore Shepherd (Canada) Lead Authors Gregory Bodeker (New Zealand), Pablo Canziani (Argentina), Martin Dameris (Germany), Piers Forster (UK), Aleksandr Gruzdev (Russia), Rolf Müller (Germany), Nzioka John Muthama (Kenya), Giovanni Pitari (Italy), William Randel (USA) Contributing Authors Vitali Fioletov (Canada), Jens-Uwe Grooß (Germany), Stephen Montzka (USA), Paul Newman (USA), Larry Thomason (USA), Guus Velders (The Netherlands) Review Editors Mack McFarland (USA) IPCC Boek (dik).indb 83 15-08-2005 10:52:13 84 IPCC/TEAP Special Report: Safeguarding the Ozone Layer and the Global Climate System Contents EXECUTIVE SUMMARY 85 1.4 Past and future stratospheric ozone changes (attribution and prediction) 110 1.1 Introduction 87 1.4.1 Current understanding of past ozone 1.1.1 Purpose and scope of this chapter 87 changes 110 1.1.2 Ozone in the atmosphere and its role in 1.4.2 The Montreal Protocol, future ozone climate 87 changes and their links to climate 117 1.1.3 Chapter outline 93 1.5 Climate change from ODSs, their substitutes 1.2 Observed changes in the stratosphere 93 and ozone depletion 120 1.2.1 Observed changes in stratospheric ozone 93 1.5.1 Radiative forcing and climate sensitivity 120 1.2.2 Observed changes in ODSs 96 1.5.2 Direct radiative forcing of ODSs and their 1.2.3 Observed changes in stratospheric aerosols, substitutes 121 water vapour, methane and nitrous oxide 96 1.5.3 Indirect radiative forcing of ODSs 123 1.2.4 Observed temperature -
Installing and Using the Hadley Centre Regional Climate Modelling System, PRECIS
Installing and using the Hadley Centre regional climate modelling system, PRECIS Version 1.9.4 www.metoffice.gov.uk/precis Simon Wilson, David Hassell, David Hein, Chloe Eagle, Simon Tucker, Richard Jones and Ruth Taylor April 12, 2012 Contents 1 Introduction 11 1.1 Background .............................. 11 1.2 Objectivesandstructureofthemanual . 12 2 Hardware, operating system and software environment 13 2.1 Recommended Hardware Configurations . 13 2.2 Multi-processorsystems . 14 2.3 InstallationofLinux ......................... 15 2.4 Compilers ............................... 16 2.5 System setup before installing PRECIS . 17 3 PRECIS software and installation 19 3.1 Introduction.............................. 19 3.2 Disklayout .............................. 20 3.3 Main steps in installation process . 21 3.4 Installation of PRECIS software and data . 21 3.5 InstallationofMetOfficedata . 25 3.5.1 Boundary data supplied on hard drive . 25 3.6 Installation verification . 27 3.7 InstallationofCDAT ......................... 28 4 Experimental design and setup 30 4.1 Experimentaldesign ......................... 30 4.1.1 Regional climate model . 30 2 4.1.2 Choice of driving model and forcing scenario . 30 4.1.3 Simulationlength. 36 4.1.4 Initial condition ensembles . 37 4.1.5 Choice of land surface scheme . 38 4.1.6 Outputdata.......................... 38 4.1.7 Spinup............................. 38 4.1.8 Choice of region . 39 4.1.9 Land-seamask ........................ 39 4.1.10 Altitude ............................ 40 4.1.11 Altitude of inland waters . 41 4.1.12 Soil and land cover . 41 4.1.13 RCM calendar and clock . 42 4.1.14 RCM Resolution . 42 4.1.15 Outputformat ........................ 43 4.1.16 Checklist............................ 43 5 Configuring an experiment with PRECIS 45 5.1 Introduction............................. -
Tracking Climate Models
TRACKING CLIMATE MODELS CLAIRE MONTELEONI*, GAVIN SCHMIDT**, AND SHAILESH SAROHA*** Abstract. Climate models are complex mathematical models designed by meteorologists, geo- physicists, and climate scientists to simulate and predict climate. Given temperature predictions from the top 20 climate models worldwide, and over 100 years of historical temperature data, we track the changing sequence of which model currently predicts best. We use an algorithm due to Monteleoni and Jaakkola that models the sequence of observations using a hierarchical learner, based on a set of generalized Hidden Markov Models (HMM), where the identity of the current best climate model is the hidden variable. The transition probabilities between climate models are learned online, simultaneous to tracking the temperature predictions. On historical data, our online learning algorithm's average prediction loss nearly matches that of the best performing climate model in hindsight. Moreover its performance surpasses that of the average model predic- tion, which was the current state-of-the-art in climate science, the median prediction, and least squares linear regression. We also experimented on climate model predictions through the year 2098. Simulating labels with the predictions of any one climate model, we found significantly im- proved performance using our online learning algorithm with respect to the other climate models, and techniques. 1. Introduction The threat of climate change is one of the greatest challenges currently facing society. With the increased threats of global warming, and the increasing severity of storms and natural disasters, improving our understanding of the climate system has become an international priority. This system is characterized by complex and structured phenomena that are imperfectly observed and even more imperfectly simulated. -
Assimila Blank
NERC NERC Strategy for Earth System Modelling: Technical Support Audit Report Version 1.1 December 2009 Contact Details Dr Zofia Stott Assimila Ltd 1 Earley Gate The University of Reading Reading, RG6 6AT Tel: +44 (0)118 966 0554 Mobile: +44 (0)7932 565822 email: [email protected] NERC STRATEGY FOR ESM – AUDIT REPORT VERSION1.1, DECEMBER 2009 Contents 1. BACKGROUND ....................................................................................................................... 4 1.1 Introduction .............................................................................................................. 4 1.2 Context .................................................................................................................... 4 1.3 Scope of the ESM audit ............................................................................................ 4 1.4 Methodology ............................................................................................................ 5 2. Scene setting ........................................................................................................................... 7 2.1 NERC Strategy......................................................................................................... 7 2.2 Definition of Earth system modelling ........................................................................ 8 2.3 Broad categories of activities supported by NERC ................................................. 10 2.4 Structure of the report ........................................................................................... -
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. -
Insights Into Paleoclimate Modeling
Insights into paleoclimate modeling EMMA J. STONE1, P. BAKKER2, S. CHARBIT3, S.P. RITZ4 AND V. VARMA5 1School of Geographical Sciences, University of Bristol, UK; [email protected] 2Earth & Climate Cluster, Department of Earth Sciences, Vrije Universiteit Amsterdam, The Netherlands; 3Laboratoire des Sciences du Climat et de l'Environnement, CEA Saclay, Gif-sur-Yvette, France; 4Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Switzerland; 5Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Germany We describe climate modeling in a paleoclimatic context by highlighting the types of models used, the logistics involved and the issues that inherently arise from simulating the climate system on long timescales. n contrast to "data paleoclimatologists" requires performing simulations on the al. 2011). Although computing advance- Past 4Future: Behind the Scenes 4Future: Past Iwho encounter experimental chal- order of thousands to tens of thousands ments have allowed transient climate lenges, and challenges linked to archive of model years and due to computa- experiments to be realized on long tim- sampling and working in remote and/or tional time this is not easily achievable escales, performing snapshot simulations difficult environments (e.g. Gersonde and with a GCM. Therefore, compromises are with EMICs or GCMs is still frequent and Seidenkrantz; Steffensen; Verheyden and required in terms of model resolution, useful (see Lunt et al. 2012). Genty, this issue) we give a perspective complexity, number of Earth system com- on the challenges encountered by the ponents and the timescale of the simula- Climate modeling by Past4Future "computer modeling paleoclimatologist". -
Climate Risk Management Xxx (2016) Xxx–Xxx
Climate Risk Management xxx (2016) xxx–xxx Contents lists available at ScienceDirect Climate Risk Management journal homepage: www.elsevier.com/locate/crm Regional climate change trends and uncertainty analysis using extreme indices: A case study of Hamilton, Canada ⇑ Tara Razavi a,c, , Harris Switzman b,1, Altaf Arain c, Paulin Coulibaly a,c a McMaster University, Department of Civil Engineering, 1280 Main Street West, Hamilton, Ontario L8S 4L7, Canada b Ontario Climate Consortium/Toronto and Region Conservation, Toronto, Ontario, Canada c McMaster University, School of Geography and Earth Sciences, 1280 Main Street West, Hamilton, Ontario L8S 4L7, Canada article info abstract Article history: This study aims to provide a deeper understanding of the level of uncertainty associated Received 17 December 2015 with the development of extreme weather frequency and intensity indices at the local Revised 13 June 2016 scale. Several different global climate models, downscaling methods, and emission scenar- Accepted 14 June 2016 ios were used to develop extreme temperature and precipitation indices at the local scale Available online xxxx in the Hamilton region, Ontario, Canada. Uncertainty associated with historical and future trends in extreme indices and future climate projections were also analyzed using daily Keywords: precipitation and temperature time series and their extreme indices, calculated from grid- Climate change ded daily observed climate data along with and projections from dynamically downscaled Uncertainty Trend datasets of