Spatial and temporal trends in land surface moisture and temperature observable using data from the Nimbus-7 microwave radiometer

Nimbus-7 SMMR brightness temperatures have been reprocessed in a form that simplifies the data handling associated with estimation and analysis of global land parameter fields. Spatial and temporal analyses of the brightness temperatures indicate their sensitivities to land surface and atmospheric conditions, and show trends linked to changing surface moisture, temperature, and vegetation patterns. An estimation algorithm is used, calibrated to sites in arid regions and forests, to obtain preliminary estimates of the land parameters for a given geographic region focusing on semiarid areas were the potential for observing moisture variability using the SMMR channels is greatest, the estimates are compared with model output data. Results of the study are helpful in evaluating the potential of future L-band spaceborne radiometer measurements, which would have greatly increased capability for surface moisture estimation if available