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Evaluating Satellite-Based Diurnal Cycles of Precipitation in the African Tropics

机译:评估非洲热带地区基于卫星的降水昼夜周期

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Precipitation plays a major role in the energy and water cycles of the earth. Because of its variable nature, consistent observations of global precipitation are challenging. Satellite-based precipitation datasets present an alternative to in situ-based datasets in areas sparsely covered by ground stations. These datasets are a unique tool for model evaluations, but the value of satellite-based precipitation datasets depends on their application and scale. Numerous validation studies considered monthly or daily time scales, while less attention is given to subdaily scales. In this study subdaily satellite-based rainfall data are analyzed in West Africa, a region with strong diurnal variability. Several satellite-based precipitation datasets are validated, including Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), TRMM 3G68 products, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) morphing technique (CMORPH) data. As a reference, highly resolved in situ data from the African Monsoon Multidisciplinary Analysis-Couplage de l'Atmosphere Tropical et du Cycle Hydrologique (AMMA-CATCH) are used. As a result, overall the satellite products capture the diurnal cycles of precipitation and its variability as observed on the ground reasonably well. CMORPH and TMPA data show overall good results. For locally induced convective rainfall in the evening most satellite data show slight delays in peak precipitation of up to 2 h.
机译:降水在地球的能量和水循环中起着重要作用。由于其可变的性质,对全球降水的一致观测极具挑战性。基于卫星的降水数据集提供了地面站稀疏覆盖区域中基于现场数据集的替代方法。这些数据集是用于模型评估的独特工具,但是基于卫星的降水数据集的价值取决于其应用和规模。许多验证研究考虑了月度或每日时间尺度,而对次日尺度的关注则较少。在这项研究中,分析了西非(一个昼夜变化很大的地区)的次日卫星降水数据。验证了几个基于卫星的降水数据集,包括热带降雨测量任务(TRMM)多卫星降水分析(TMPA),TRMM 3G68产品,使用人工神经网络(PERSIANN)的遥感信息中的降水估计以及气候预测中心(CPC)的变体技术(CMORPH)数据。作为参考,使用了来自非洲季风多学科分析-热带大气与循环水文法(AMMA-CATCH)的高度解析的原位数据。结果,总体而言,卫星产品能够很好地捕获地面上观测到的降水的昼夜周期及其变化。 CMORPH和TMPA数据显示总体良好结果。对于傍晚的局部诱发对流降雨,大多数卫星数据都显示最高2小时的峰值降水略有延迟。

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