全球变暖背景下内蒙古地区沙尘暴频次变化的预估

构建一个基于BP神经网络的统计模型, 利用CMIP5模式中历史情景和未来情景的预估数据, 重建1860—2100年内蒙古地区春季沙尘暴频次(分辨率达到日尺度)序列。在此基础上, 研究内蒙古地区沙尘暴未来长期变化特征。结果表明, 在未来情景RCP2.6 和RCP8.5中, 与历史时期(1860—2005年)相比, 内蒙古地区沙尘暴频次持续减少; 影响范围较大的沙尘暴事件占比也持续减少; 在增温更多的RCP8.5情景中, 沙尘暴的减少更加显著; 春季沙尘暴的季节性锁相特征(4月沙尘暴频次达到峰值)不随全球变暖而变化。

Prediction of Dust Storm Frequency Variation in Inner Mongolia Region under Global Warming Scenarios

The authors reconstruct a new dust storm series on daily basis for Inner Mongolia Region covering the period 1860?2100, by applying a newly developed artificial neural network model onto CMIP5 results from historical and RCP runs. The authors investigate the new series and suggest that the number of China’s dust storms keeps decreasing in both RCP 2.6 and 8.5 scenarios; the proportion of dust storms with large impact area also decrease; the decreasing is more evident in the warmer RCP8.5 scenario than that in RCP2.6; the phase-lock features, i.e. maximum occurrence frequency of dust storms in April every year, remain unchanged in both global warming scenarios.