Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation
► We examine the impacts of climate change on soybean and spring wheat using a crop model. ► Climate model uncertainty is represented by 14 different climate models. ► Impact varies by crop, location, climate model and with adaptation. Crop production is inherently sensitive to fluctuations in weath...
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Veröffentlicht in: | Agricultural and forest meteorology 2013-03, Vol.170, p.183-194 |
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description | ► We examine the impacts of climate change on soybean and spring wheat using a crop model. ► Climate model uncertainty is represented by 14 different climate models. ► Impact varies by crop, location, climate model and with adaptation.
Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs.
Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation. |
doi_str_mv | 10.1016/j.agrformet.2012.07.006 |
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Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs.
Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.</description><identifier>ISSN: 0168-1923</identifier><identifier>EISSN: 1873-2240</identifier><identifier>DOI: 10.1016/j.agrformet.2012.07.006</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Adaptation ; Assessments ; Climate ; Climate change ; Climate models ; Computer simulation ; Crop modelling ; Crop yield ; Crops ; Triticum aestivum ; Uncertainty</subject><ispartof>Agricultural and forest meteorology, 2013-03, Vol.170, p.183-194</ispartof><rights>2012 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c447t-c207d235c7303a934afbf79357cb337805dfdfde10a9bf21048111da1d592b113</citedby><cites>FETCH-LOGICAL-c447t-c207d235c7303a934afbf79357cb337805dfdfde10a9bf21048111da1d592b113</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.agrformet.2012.07.006$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Osborne, Tom</creatorcontrib><creatorcontrib>Rose, Gillian</creatorcontrib><creatorcontrib>Wheeler, Tim</creatorcontrib><title>Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation</title><title>Agricultural and forest meteorology</title><description>► We examine the impacts of climate change on soybean and spring wheat using a crop model. ► Climate model uncertainty is represented by 14 different climate models. ► Impact varies by crop, location, climate model and with adaptation.
Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs.
Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.</description><subject>Adaptation</subject><subject>Assessments</subject><subject>Climate</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Computer simulation</subject><subject>Crop modelling</subject><subject>Crop yield</subject><subject>Crops</subject><subject>Triticum aestivum</subject><subject>Uncertainty</subject><issn>0168-1923</issn><issn>1873-2240</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkUtLxDAUhYMoOD5-g1m6ac2jnbRLEV8guFG34Ta5HTO0TU1SQfDHGx1xK4GbzXfOfRxCzjgrOePri20Jm9D7MGIqBeOiZKpkbL1HVrxRshCiYvtklcmm4K2Qh-Qoxi3LoFLtiny-QHCQnJ-om2h6RboZfAdDEQ0MSN04g0mR-p6awY2QkJpXmDZIs8AEP9M5eLuY5N5d-qB2QZr8Hzp6iwNdJoMhgZsyAJOlYGFOPy1PyEEPQ8TT3_-YPN9cP13dFQ-Pt_dXlw-FqSqVCiOYskLWRkkmoZUV9F2vWlkr00mpGlbbPj_kDNquF5xVDefcArd1KzrO5TE53_nmYd8WjEmPLhocBpjQL1FzpZgUTZ3r_6jMpnIt6oyqHZrvEGPAXs8h7x0-NGf6Oxq91X_R6O9oNFM6R5OVlzsl5qXfHQYdjcN8JusCmqStd_96fAHmUZ2q</recordid><startdate>20130301</startdate><enddate>20130301</enddate><creator>Osborne, Tom</creator><creator>Rose, Gillian</creator><creator>Wheeler, Tim</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TG</scope><scope>7U6</scope><scope>7UA</scope><scope>C1K</scope><scope>KL.</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20130301</creationdate><title>Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation</title><author>Osborne, Tom ; Rose, Gillian ; Wheeler, Tim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c447t-c207d235c7303a934afbf79357cb337805dfdfde10a9bf21048111da1d592b113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adaptation</topic><topic>Assessments</topic><topic>Climate</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Computer simulation</topic><topic>Crop modelling</topic><topic>Crop yield</topic><topic>Crops</topic><topic>Triticum aestivum</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Osborne, Tom</creatorcontrib><creatorcontrib>Rose, Gillian</creatorcontrib><creatorcontrib>Wheeler, Tim</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Agricultural and forest meteorology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Osborne, Tom</au><au>Rose, Gillian</au><au>Wheeler, Tim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation</atitle><jtitle>Agricultural and forest meteorology</jtitle><date>2013-03-01</date><risdate>2013</risdate><volume>170</volume><spage>183</spage><epage>194</epage><pages>183-194</pages><issn>0168-1923</issn><eissn>1873-2240</eissn><abstract>► We examine the impacts of climate change on soybean and spring wheat using a crop model. ► Climate model uncertainty is represented by 14 different climate models. ► Impact varies by crop, location, climate model and with adaptation.
Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs.
Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.agrformet.2012.07.006</doi><tpages>12</tpages></addata></record> |
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subjects | Adaptation Assessments Climate Climate change Climate models Computer simulation Crop modelling Crop yield Crops Triticum aestivum Uncertainty |
title | Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation |
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