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首页> 外文期刊>Atmospheric and Climate Sciences >Climate Change Impact on Wheat Production in the Southern Great Plains of the US Using Downscaled Climate Data
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Climate Change Impact on Wheat Production in the Southern Great Plains of the US Using Downscaled Climate Data

机译：使用缩减的气候数据，气候变化对美国南部大平原小麦生产的影响

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Gradually developing climatic and weather anomalies due to increasing concentration of atmospheric greenhouse gases can pose threat to farmers and resource managers. There is a growing need to quantify the effects of rising temperature and changing climates on crop yield and assess impact at a finer scale so that specific adaptation strategies pertinent to that location can be developed. Our work aims to quantify and evaluate the influence of future climate anomalies on winter wheat (Triticum aestivum L.) yield under the Representative Concentration Pathways 6.0 and 8.5 using downscaled climate projections from different General Circulation Models (GCMs) and their ensemble. Marksim downscaled daily data of maximum (TMax) and minimum (TMin) air temperature, rainfall, and solar radiation (SRAD) from different Coupled Model Intercomparison Project GCMs (CMIP5 GCMs) were used to simulate the wheat yield in water and nitrogen limiting and non-limiting conditions for the future period of 2040-2060. The potential impact of climate changes on winter wheat production across Oklahoma was investigated. Climate change predictions by the downscaled GCMs suggested increase in air temperature and decrease in total annual rainfall. This will be really critical in a rainfed and semi-arid agro-ecological region of Oklahoma. Predicted average wheat yield during 2040-2060 increased under projected climate change, compared with the baseline years 1980-2014. Our results indicate that downscaled GCMs can be applied for climate projection scenarios for future regional crop yield assessment.
机译：由于大气中温室气体浓度的增加而逐渐形成的气候和天气异常可能对农民和资源管理者构成威胁。越来越需要量化温度升高和气候变化对作物产量的影响，并在更精细的规模上评估影响，以便可以制定与该地点有关的具体适应战略。我们的工作旨在使用不同的一般循环模式（GCM）的缩小气候预估，量化和评估未来气候异常对典型浓度途径6.0和8.5下冬小麦（ Triticum aestivum L.）产量的影响。和他们的合奏。来自不同耦合模型比较项目GCM（CMIP5 GCM）的Marksim缩减的最高（TMax）和最低（TMin）气温，降雨量和太阳辐射（SRAD）每日数据用于模拟水和氮限制下和非氮限制下的小麦产量-未来2040-2060年的限制条件。调查了气候变化对俄克拉荷马州冬小麦产量的潜在影响。降级的GCM对气候变化的预测表明，气温升高，年降水量减少。在俄克拉荷马州一个雨养半干旱的农业生态地区，这将是至关重要的。与1980-2014年的基准年相比，在预测的气候变化的影响下，2040-2060年小麦的预测平均单产增加。我们的结果表明，缩小的GCM可以用于未来区域作物产量评估的气候预测方案。

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