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首页> 外文期刊>Journal of hydrometeorology >A Comparison of GLDAS Soil Moisture Anomalies against Standardized Precipitation Index and Multisatellite Estimations over South America
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A Comparison of GLDAS Soil Moisture Anomalies against Standardized Precipitation Index and Multisatellite Estimations over South America

机译:南美洲GLDAS土壤湿度异常与标准降水指数和多卫星估算的比较

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This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the need for assessing the reliability of GLDAS variables to be used in the characterization of soil state and its variability at the regional scale. The focus is on the southeastern part of South America (SESA), which is part of the La Plata basin, one of the largest basins of the world, where agriculture is the main source of income. The results show that GLDAS data capture soil moisture anomalies and their variability, taking into account regional and seasonal dependencies and showing correspondence with other proxies used to characterize soil states. Over large portions of the domain, and particularly over SESA, the correlation with the SPI is very high, with the second version of GLDAS, version 2 (GLDAS-2 v2), exhibiting the highest values regardless of the season. Similar results were obtained by comparing the surface soil moisture anomalies from the GLDAS land surface model (LSM) against the satellite estimations for a shorter period of time. This work documents that the precipitation dataset used to force each LSM and the choice of the LSM are of major relevance for representing soil conditions in an adequate manner. The results are considered to support the use of GLDAS as an indicator of soil moisture states and for developing new soil moisture-monitoring indices that can be applied, for example, in the context of agricultural production management.
机译:这项研究旨在比较来自不同版本的全球土地数据同化系统(GLDAS),标准降水指数(SPI)和南美南部新的多卫星表面土壤水分产物的模拟土壤水分异常。主要动机是需要评估GLADS变量的可靠性,以用于表征土壤状态及其在区域范围内的变异性。重点放在南美的东南部(SESA),它是拉普拉塔盆地的一部分,拉普拉塔盆地是世界上最大的盆地之一,农业是主要的收入来源。结果表明,GLDAS数据考虑了区域和季节依赖性并显示了与用于表征土壤状态的其他代理的对应关系,从而捕获了土壤水分异常及其变异性。在该域的大部分区域(尤其是SESA区域),与SPI的相关性非常高,第二版本的GLDAS版本2(GLDAS-2 v2)呈现最高值,与季节无关。通过比较来自GLDAS陆地表面模型(LSM)的地表土壤湿度异常与卫星估计的较短时间,可以得到类似的结果。这项工作证明,用于强迫每个LSM的降水数据集和LSM的选择对于以适当的方式表示土壤状况具有重大意义。研究结果被认为可支持将GLDAS用作土壤水分状态的指标,并支持开发可在例如农业生产管理中应用的新的土壤水分监测指标。

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