Christa D. Peters-Lidard

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Spatially distributed soil moisture profiles are required for watershed applications such as drought and flood prediction, crop irrigation scheduling, pest management, and determining mobility with lightweight vehicles. Satellite-based soil moisture can be obtained from passive microwave, active microwave, and optical sensors, although the coarse spatial(More)
Knowledge of land surface water, energy, and carbon conditions are of critical importance due to their impact on many real world applications such as agricultural production, water resource management, and flood, weather, and climate prediction. Land Information System (LIS) is a software framework that integrates the use of satellite and ground-based(More)
NEXRAD precipitation estimates are used for hydrological, meteorological, and climatological studies at a wide range of spatial and temporal scales. The utility of radar-based precipitation estimates in such applications hinges on an understanding of the sources and magnitude of estimation error. This study examines precipitation estimation in the complex(More)
The Land Information System software (LIS;, 2006) has been developed to support high-performance land surface modeling and data assimilation. LIS integrates parallel and distributed computing technologies with modern land surface modeling capabilities , and establishes a framework for easy interchange of subcomponents, such as land(More)
One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid-and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite(More)
A GIS framework, the Army Remote Moisture System (ARMS), has been developed to link the Land Information System (LIS), a high performance land surface modeling and data assimilation system, with remotely sensed measurements of soil moisture to provide a high resolution estimation of soil moisture in the near surface. ARMS uses available soil (soil texture,(More)
[1] The key question that is asked in this study is ''how are the three independent bias components of satellite rainfall estimation, comprising hit bias, missed, and false precipitation, physically related to the estimation uncertainty of soil moisture and runoff for a physically based hydrologic model?'' The study also investigated the performance of(More)