Passive microwave remote sensing of soil moisture has been performed extensively for more than three decades. When compared with optical/infrared sensors, microwave radiometers offer the direct sensing of surface soil moisture through the large contrast of dielectric constant between soil and water at microwave frequencies. Spaceborne microwave radiometers that have 6 to 37 GHz channels and significant soil moisture sensitivity include the Scanning Multichannel Microwave Radiometer (SMMR) launched in 1978, the TRMM Microwave Imager (TMI) in 1997, the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) in 2002, and the WindSat radiometer in 2003.

In this paper, we will present a global soil moisture data set derived from the 10, 18, and 37 GHz WindSat data using a physically-based multi-channel maximum-likelihood land algorithm. The 6 GHz data were excluded for the mitigation of the RFI problems over the United States where most of the in situ validation data are available. The solution is found by iteratively minimizing the distance between radiative transfer simulations and measurements in the brightness temperature measurement spaces. The surface parameters considered by the algorithm include soil moisture, vegetation water content, land surface temperature, surface types, precipitation and snow cover.

Heat waves are the most lethal type of weather phenomenon. In the United States heat waves kill more people than any other natural disaster. The 2003 European Heat Wave killed at least 35,000 people in Europe, (14,802 in France alone), led to forest fires, crop shortfalls and large scale power outages. Although atmospheric circulation patterns have been inevitably linked to heat waves, the land-atmosphere interaction also contributes significantly to the strength and spatial and temporal extent of the heat waves. The depletion of soil moisture reduces latent cooling and amplifies the temperature extremes and the number of hot days, which is a critical measure for the impact on ecosystem and public health/mortality. Climate model simulations suggest that low soil moisture played a major role in the deadly 2003 heat wave. WindSat data corroborates such a theory. The vegetation water content was above the average between March and June, which helped to deplete the soil moisture. The soil moisture was below average after April. When the heat wave hits around mid-August, WindSat measurements indicate low soil moisture and vegetation water content. Without sufficient latent cooling, the heat wave became deadly.

We will present a description of the WindSat land products. Furthermore, we will describe in detail the correlations of WindSat data and European heat wave of 2003.