Proceedings Article | 30 April 2003
Don Cline, Kelly Elder, Bert Davis, Janet Hardy, Glen Liston, David Imel, Simon Yueh, Albin Gasiewski, Gary Koh, Richard Armstrong, Mark Parsons
KEYWORDS: Soil science, Data modeling, Sensors, Remote sensing, Clouds, Data archive systems, Microwave radiation, Microwave remote sensing, Atmospheric modeling, Snow cover
NASA's Earth Science Enterprise has identified the need for improved measurement of snow properties and frozen soils via a space-flight mission within the next decade. Microwave sensors appear ideal to measure these properties. Measurements of the Earth's surface in the microwave spectral regions can be largely insensitive to weather conditions and solar illumination, which is especially important during cold seasons. Both active and passive microwave sensors have demonstrated sensitivity to snow properties and the freeze/thaw status of soils. Microwave signal response is influenced by snow depth, density, wetness, crystal size and shape, ice crusts and layer structure, surface roughness, vegetation characteristics, soil moisture, and soil freeze/thaw status. These characteristics make microwave remote sensing attractive for providing spatially distributed information to improve and update land surface models for cold regions, either through assimilation of state-variable information estimated from microwave remote sensing observations using inversion algorithms, or through direct assimilation of microwave remote sensing data themselves. At the same time, the sensitivity of microwave signal response to several snow, soil, and vegetation characteristics also complicates the interpretation and analysis of these data. To better understand microwave remote sensing for measurement of snow and frozen soil properties, NASA is conducting the Cold Land Processes Field Experiment (CLPX). The CLPX is a large field experiment being conducted primarily over a two-year period (2002 and 2003) in Colorado, U.S.A. The purpose of the CLPX is to develop the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Of particular importance is the development of a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. Objectives of the CLPX include evaluation and improvement of algorithms for retrieving snow and frozen soil information from active and passive microwave sensors, evaluating the effects of sensor spatial resolution on retrieval skill, coupling forward microwave radiative transfer schemes to distributed snow/soil models to improve assimilation of microwave remote sensing data, and to develop sensor specifications for a new space-flight mission to measure cold land processes. This paper discusses the data sets collected during the CLPX-2002 to support these objectives.
