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数值模拟气候情景下未来30年内蒙古三种主要粮食作物生长季气温和降水量变化 被引量:3

Variations of Temperature and Precipitation during Growing-Season of Three Major Crops in Inner Mongolia under Numerical Simulation Scenarios in the Coming 30 Years
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摘要 利用PRECIS区域气候模式在SRES(A1B、A2和B2)大气主要温室气体排放情景下的降尺度数据集和中国国家气候中心CMIP5数值气候模式模拟结果,确定两种不同模式格点在内蒙古10个产粮盟(市)农区的位置和分布,并计算各盟(市)小麦、玉米和马铃薯生长季80a(1961-2040)数值模拟的月气温和降水量。通过与各盟(市)过去50a(1961-2010)气温和降水量观测数据比较,确定了数值模拟的偏差,并利用模拟值与观测值之差对未来30a(2011-2040)的模拟数据进行偏差订正处理,订正后的模拟结果显示,与过去50a均值相比,内蒙古3种主要粮食作物生长季降水量在未来30a无明显变化趋势,气温呈普遍增加趋势,不同作物生长季气温增幅不一致。研究结果可为预估未来30a内蒙古主要产粮地区的气候条件和未来粮食产量变化趋势提供参考。 In order to predict the climate condition of major cultivating areas in Inner Mongolia in the coming 30 years, the PRECIS (green-house emission scenario A1 B, A2 and B2) developed in Hadley Center in UK, and the CMIP5 multi-model dataset provided by China National Climate Center were employed to simulate the temperature and precipitation for 80 years (1961 -2040 ). The simulated crop-growing-season precipitation and accumulated temperature were calculated by using the simulated monthly precipitation and temperature after the longitude-latitude grid points that belong to cultivating areas of 10 leagues or cities in Inner Mongolia. In addition, simulating deviations for the leagues or cities were confirmed by comparing the simulated outputs with the observed records last 50 years (1961-2010). Then, deviations of the simulated precipitation and temperature of the coming 30 years (2011-2040 ) have been corrected by using the difference between observations and simulations. The corrected simulating results indicated that variation of the growing-season precipitation did not display significant trends for those three crops in the coming 30 years, whereas the accumulated temperatures for difference crops could present dissimilar increasing tendency.
出处 《中国农业气象》 CSCD 北大核心 2013年第5期501-511,共11页 Chinese Journal of Agrometeorology
基金 内蒙古自然科学基金重点项目(2010Zd17) 国家自然科学基金项目(40965007)
关键词 内蒙古农区 气候模拟 偏差订正 生长季温湿条件 气候预估 Inner Mongolia cultivating areas Climate simulation Deviation correcting Temperature and precipitationcondition of growing season Climate prediction
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