Brian Hornbuckle, Iowa State University, 3007 Agronomy Hall, Ames, IA 50011-1010, Martha C. Anderson, USDA ARS Hydrology and Remote Sensing Laboratory, Bg. 007, Rm. 104, BARC-West, Beltsville, MD 20705-2350, and Anthony W. England, University of Michigan, 1221 Beal Avenue
1221 Beal Avenue
1221 Beal Avenue
, Ann Arbor, MI 48109-2102.
Liquid water has distinct electrical properties at microwave frequencies. Consequently, microwave remote sensing is sensitive to both soil water content and to water contained within the vegetation canopy. Two future satellite missions, the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission in 2007 and NASA's Hydrospheric State (Hydros) mission in 2010, will each carry microwave remote sensing instruments at the optimal frequency for land surface hydrology. The primary focus of SMOS and Hydros is to measure soil moisture, the water content of the first few centimeters of the soil. What is not known is whether canopy water in the form of dew will also have a remote sensing signal. Both SMOS and Hydros will pass over points on Earth at 6 AM local solar time, when dew could be present.
We present time--series observations of microwave brightness, soil moisture, soil and canopy temperatures, precipitation, wind speed and direction, air temperature, relative humidity, and radiative fluxes measured at the plot-scale in a field of corn. Using the recorded data in conjunction with models of radiative transfer and land surface processes, we infer the sensitivity of land surface microwave brightness to dew. Two consecutive nights are analyzed during which the amount of dew present on the canopy varied. We use three methods to determine the effect of dew. First, we compare observations of the microwave brightness to predictions made by a model. Second, we evaluate the canopy energy balance and predict the relative amount of dew deposited to the canopy and compare observations of brightness in this context. Finally, we estimate dew deposition for each night with the Atmosphere-Land-Exchange (ALEX) model and infer a dew sensitivity.
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