Challinor, AJ orcid.org/0000-0002-8551-6617, Müller, C, Asseng, S et al. (7 more authors) (2018) Improving the use of crop models for risk assessment and climate change adaptation. Agricultural Systems, 159. pp. 296-306. ISSN 0308-521X
Abstract
Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/). |
Keywords: | Crop model; Risk assessment; Climate change impacts; Adaptation; Climate models; Uncertainty |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Funding Information: | Funder Grant number EU - European Union 308291 EU - European Union 308378 BBSRC BB/K010476/1 EU - European Union 308291 BBSRC BB/N004914/1 CGIAR Secretariat CRP-166-11 |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Jul 2017 10:04 |
Last Modified: | 21 Mar 2018 11:39 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.agsy.2017.07.010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:119377 |