Verification of the SMAP Level-4 Soil Moisture Analysis Using Rainfall Observations in Australia

R. Reichle, Qing Liu, G. Lannoy, W. Crow, L. Jones, J. Kimball, R. Koster
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Abstract

Global, 3-hourly, 9-km resolution soil moisture estimates are available with a mean latency of ~2.5 days from the NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product. These estimates are based on the assimilation of SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. Routine monitoring of the L4_SM system’s assimilation diagnostics revealed occasionally large observation-minus-forecast Tb differences across eastern central Australia that resulted in large analysis increments (or adjustments) of the model forecast soil moisture. Because this region lacks in situ soil moisture measurements, we developed an alternative approach to assess the veracity of the soil moisture analysis increments in the L4_SM system. Using regional gauge-based precipitation data, we demonstrate that the L4_SM soil moisture increments are correlated with errors in the L4_SM precipitation forcing, suggesting that the SMAP Tb observations contribute valuable information to the L4_SM soil moisture estimates.
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基于澳大利亚降雨观测的SMAP 4级土壤湿度分析的验证
NASA土壤湿度主被动(SMAP)任务4级土壤湿度(L4_SM)产品提供了3小时、9公里分辨率的全球土壤湿度估计,平均延迟约2.5天。这些估算是基于SMAP辐射计亮度温度(Tb)观测数据同化到NASA集水区地表模型中,使用空间分布的集合卡尔曼滤波。L4_SM系统同化诊断的常规监测显示,在澳大利亚中东部地区,偶尔会出现观测减去预测的Tb差异,这导致模型预测土壤湿度的分析大幅增加(或调整)。由于该地区缺乏原位土壤湿度测量,我们开发了一种替代方法来评估L4_SM系统中土壤湿度分析增量的准确性。利用基于区域测量的降水数据,我们证明了L4_SM土壤水分增量与L4_SM降水强迫误差相关,表明SMAP Tb观测值为L4_SM土壤水分估算提供了有价值的信息。
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