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Passive microwave remote sensing of surface soil moisture: Methods, results, and applications

Posted on:2006-12-08Degree:Ph.DType:Dissertation
University:Princeton UniversityCandidate:Gao, HuilinFull Text:PDF
GTID:1453390008470381Subject:Hydrology
Abstract/Summary:
This study investigates passive microwave remote sensing of surface soil moisture from three aspects: methods, results, and applications. A land surface microwave emission model (LSMEM) has been implemented to retrieve soil moistures from various remote sensing data. Chapter 2 introduces the physics and parameterization of the LSMEM algorithm. Based on this framework, soil moisture is estimated from L band synthetic radiometry during the Southern Great Plains 1999 experiment. Results show a RMS of 1.8-2.8% volumetric soil moisture. To conduct operational retrievals from spaceborne radiometry, LSMEM is further parameterized at large scales in Chapter 3. A five-year (1998-2002) surface soil moisture product is derived across the southern United States from TRMM/TMI X band horizontally polarized brightness temperatures. Because of the limited information content on soil moisture in the observed brightness temperatures over regions characterized by heavy vegetation, active precipitation, snow, and frozen ground, quality control flags for the retrieved soil moisture are provided. The product is validated by Oklahoma Mesonet field measurements and its spatial patterns also demonstrate consistencies with precipitation fields. This is the first time that a fully validated approach and product is implemented and the product is to be made available through the NASA Goddard Space Flight Center Distributed Active Archive Center (NASA/GSFC DAAC). Chapter 4 explores the application potential of assimilating spaceborne remote sensing soil moisture product into land surface models through the development of "observational operators." Besides the TMI product, soil moisture from AMSR-E using the operational NASA retrieval algorithm is involved. The focus is to use Copula, a probabilistic approach, to generate observation operators so that the systematic bias between remotely sensed and modeled soil moisture can be reduced and the error structure can be provided for generation of assimilation ensembles. Observation operators are derived from different remote sensing products for two land surface models: Variable Infiltration Capacity (VIC) and ECMWF reanalysis (ERA40).
Keywords/Search Tags:Remote sensing, Soil moisture, Surface, Microwave, Results, Product
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