Soil moisture plays a key role in regulating water and energy cycle in the Tibetan Plateau, which further impacts regional climate. However, the quality of existing soil moisture products over the central to west TP (CWTP) remains unclear due to the lack of in-situ observations. Using rain gauge data from a recently established rainfall network in the CWTP region and by checking the hydrological consistency between surface soil moisture and precipitation, this study performed a first evaluation of several satellite soil moisture products, including those from the Soil Moisture Active Passive (SMAP), the European Space Agency Climate Change Initiative (ESA CCI), and the artificial neural network reproduced AMSR-E/2 retrievals (NNsm) in this area. Results show that: (1) both descending and ascending orbits of the SMAP product generally outperform ESA CCI and NNsm, with more robust hydrological consistency across all rain gauge stations; (2) ESA CCI is subjected to low availability of effective retrievals in this area, with the combined one performs slightly more robust than the active and passive channels; and (3) NNsm possesses the most effective soil moisture retrievals owing to less revisit time of AMSR2, but its hydrological consistency is the lowest as compared to the other two products. Further analysis suggests that large topography and dense vegetation can potentially impact the retrieval accuracy of surface soil moisture and thus hydrological consistency. Besides, relatively large amounts of rainfall is likely to impose more positive increments in surface soil moisture, whereas extremely heavy rainfall may further degrade hydrological consistency. These findings are complementary to existing soil moisture evaluations in the eastern TP, and are expected to contribute to improving soil moisture retrieval algorithms and understanding land–atmosphere interactions over the entire plateau.

中文翻译：

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使用雨量计观测对青藏高原中西部卫星土壤水分产品进行首次评估


土壤水分在青藏高原的水和能量循环调节中起着关键作用，这进一步影响了区域气候。然而，由于缺乏原位观测，中西部 TP （CWTP） 现有土壤水分产品的质量仍不清楚。使用来自 CWTP 地区最近建立的降雨网络的雨量计数据，并通过检查表层土壤水分和降水之间的水文一致性，本研究对几种卫星土壤水分产品进行了首次评估，包括来自土壤水分主动被动 （SMAP）、欧洲航天局气候变化倡议 （ESA CCI） 的产品， 人工神经网络在该区域再现了 AMSR-E/2 检索 （NNSM）。结果表明：（1） SMAP 产品的下降和上升轨道通常优于 ESA CCI 和 NNsm，在所有雨量计站中具有更强大的水文一致性;（2） ESA CCI 在该区域的有效检索可用性较低，组合后的性能比主动和被动信道略强;（3） 由于 AMSR2 的重访时间较短，NNsm 具有最有效的土壤水分反演能力，但与其他两种产品相比，其水文一致性最低。进一步的分析表明，大型地形和茂密的植被可能会影响表层土壤水分的反演精度，从而影响水文的一致性。此外，相对大量的降雨可能会使表层土壤水分增加更多正增量，而极强降雨可能会进一步降低水文的一致性。 这些发现与青藏高原东部现有的土壤水分评估相辅相成，有望有助于改进土壤水分反演算法和了解整个高原的陆地-大气相互作用。