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Uncertainty and hotspots in 21st century projections of agricultural drought from CMIP5 models

机译:CMIP5模型对21世纪农业干旱的不确定性和热点预测

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摘要

Future climate changes could alter hydrometeorological patterns and change the nature of droughts at global to regional scales. However, there are considerable uncertainties in future drought projections. Here, we focus on agricultural drought by analyzing surface soil moisture outputs from CMIP5 multi-model ensembles (MMEs) under RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios. First, the annual mean soil moisture by the end of the 21st century shows statistically significant large-scale drying and limited areas of wetting for all scenarios, with stronger drying as the strength of radiative forcing increases. Second, the MME mean spatial extent of severe drought is projected to increase for all regions and all future RCP scenarios, and most notably in Central America (CAM), Europe and Mediterranean (EUM), Tropical South America (TSA), and South Africa (SAF). Third, the model uncertainty presents the largest source of uncertainty (over 80%) across the entire 21st century among the three sources of uncertainty: internal variability, model uncertainty, and scenario uncertainty. Finally, we find that the spatial pattern and magnitude of annual and seasonal signal to noise (S/N) in soil moisture anomalies do not change significantly by lead time, indicating that the spreads of uncertainties become larger as the signals become stronger.
机译:未来的气候变化可能会改变水文气象模式,并在全球到区域范围内改变干旱的性质。但是,未来的干旱预测存在很大的不确定性。在这里,我们通过分析RCP2.6,RCP4.5,RCP6.0和RCP8.5方案下CMIP5多模型合奏(MME)的地表土壤水分输出,重点关注农业干旱。首先,到21世纪末,年平均土壤湿度在所有情况下均显示出统计学意义上的大规模干燥和有限的润湿区域,随着辐射强迫强度的增加,干燥强度也随之增加。其次,MME预计所有地区和所有未来RCP情景的严重干旱的平均空间范围都会增加,最显着的是中美洲(CAM),欧洲和地中海(EUM),南美热带地区(TSA)和南非(SAF)。第三,模型不确定性是整个21世纪不确定性的三大来源中最大的不确定性来源(超过80%):内部可变性,模型不确定性和场景不确定性。最后,我们发现土壤水分异常中年度和季节性信噪比(S / N)的空间格局和强度在提前期之前并没有显着变化,这表明不确定性的扩散随着信号的增强而变大。

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