Microwave Radiometer Calibration on Decadal Time Scales Using On-Earth Brightness Temperature References: Application to the TOPEX Microwave Radiometer

A method is described to calibrate a satellite microwave radiometer operating near 18-37 GHz on decadal time scales for the purposes of climate studies. The method uses stable on-earth brightness temperature references over the full dynamic range of on-earth brightness temperatures to stabilize the radiometer calibration and is applied to the Ocean Topography Experiment (TOPEX) Microwave Radiometer (TMR). These references are a vicarious cold reference, which is a statistical lower bound on ocean surface brightness temperature, and heavily vegetated, pseudoblackbody regions in the Amazon rain forest. The sensitivity of the on-earth references to climate variability is assessed. No significant climate sensitivity is found in the cold reference, as it is not sensitive to a climate minimum (e. g., coldest sea surface temperature or driest atmosphere) but arises because of a minimum in the sea surface radio brightness that occurs in the middle of the climatic distribution of sea surface temperatures (SSTs). The hot reference is observed to have a small climate dependency, which is most evident during the 1997/98 El Nino event. A time-dependent model for the hot reference region is constructed using meteorological fields from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis product. This model is shown to accurately account for the small climate variations in this reference. In addition to the long-term stabilization of the brightness temperatures, an improvement to the TMR antenna pattern correction is described that removes residual geographically correlated errors, in particular errors correlated with distance to land or sea ice. The recalibrated TMR climate data record is cross-validated with the climate data record produced from the Special Sensor Microwave Imager (SSM/I). It is shown that the intersensor drift is small, providing realistic error bars for the climate trends generated from the instrument pair, as well as validating both the methodology described in this paper and the SSM/I climate data record.