The Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration differences relative to GMI are generally within 2–3 K for channels below 92 GHz, although AMSR2 exhibits larger differences that vary with scene temperature. SSMIS calibration differences also vary with scene temperature but to a lesser degree. For SSMIS channels above 150 GHz, the differences are generally within ~2 K with the exception of SSMIS on board DMSP F19, which ranges from 7 to 11 K colder than GMI depending on frequency. The calibrations of the cross-track radiometers agree very well with GMI with values mostly within 0.5 K for the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) and the Microwave Humidity Sounder (MHS) sensors, and within 1 K for the Advanced Technology Microwave Sounder (ATMS).

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A technique for comparing spaceborne microwave radiometer brightness temperatures (Tb) is described in the context of the upcoming National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission. The GPM mission strategy is to measure precipitation globally with high temporal resolution by using a constellation of satellite radiometers logically united by the GPM core satellite, which will be in a non-sun-synchronous medium inclination orbit. The usefulness of the combined product depends on the consistency of precipitation retrievals from the various microwave radiometers. The Tb calibration requirement to achieve such consistency demands first that Tb's from the individual radiometers be free of instrument and measurement artifacts and, second, that these self-consistent Tb's will be translated to a common standard (GPM core) for the unification of the precipitation retrieval. The intersatellite radiometric calibration technique described herein serves both the purposes by comparing individual radiometer observations to radiative transfer model (RTM) simulations (for "self-consistency" check) and by using a double-difference technique (to establish a linear calibration transfer function from one radiometer to another). This double-difference technique subtracts the RTMsimulated difference from the observed difference between a pair of radiometer Tb's. To establish a linear inter-radiometer calibration transfer function, comparisons at both the cold (ocean) and the warm (land) end of the Tb's are necessary so that, using these two points, slope and offset coefficients are determined. To this end, a simplified calibration transfer technique at the warm end (over the Amazon and Congo rain forest) is introduced. Finally, an error model is described that provides an estimate of the uncertainty of the radiometric bias estimate between comparison radiometer channels.

This dissertation provides a robust radiometric calibration for the TRMM Microwave Imager to correct systematic brightness temperature errors, which vary dynamically with orbit position (time) and day of the year. The presence of a time-varying bias in TMI is confirmed by inter-calibration with WindSat and SSMI. This time varying bias is manifested as a time of day dependent variation of the relative biases between TMI and both WindSat and SSMI. In this dissertation, we provide convincing evidence that this time-varying Tb bias in TMI is caused by variations in the physical temperature of the emissive TMI reflector antenna. This dissertation provides an empirical correction that largely corrects this timevarying bias. The TMI bias is estimated by comparing the 10.7 GHz V-polarization channel observations with RTM Tb predictions, and the Tb correction is applied as a function of orbit time for every day of the one year period. Furthermore, this dissertation provides a qualitative physical basis for the estimated Tb bias patterns and provides conclusive evidence that the empirical correction applied to TMI Tb measurements (both ocean and land) largely corrects the time-varying TMI calibration. This is accomplished by demonstrating that the local time-of-day dependence (in the uncorrected TMI Tb values) is removed in the corrected TMI Tb's.iii Dedicated to the fond hope that the expression "Main Street" will forever be banned from political discourse in the United States. iv

The National Aeronautics and Space Administration (NASA) has always included data reprocessing as a major component of every science mission. A final reprocessing is typically a part of mission closeout (known as phase F). The Tropical Rainfall Measuring Mission (TRMM) is currently in phase F, and NASA is preparing for the last reprocessing of all the TRMM precipitation data as part of the closeout. This reprocessing includes improvements in calibration of both the TRMM Microwave Imager (TMI) and the TRMM Precipitation Radar (PR). An initial step in the version 8 reprocessing is the improvement of geolocation. The PR calibration is being updated by the Japan Aerospace Exploration Agency (JAXA) using data collected as part of the calibration of the Dual-Frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) Core Observatory. JAXA undertook a major effort to ensure TRMM PR and GPM Ku-band calibration is consistent. A major component of the TRMM version 8 reprocessing is to create consistent retrievals with the GPM version 05 (V05) retrievals. To this end, the TRMM version 8 reprocessing uses retrieval algorithms based on the GPM V05 algorithms. This approach ensures consistent retrievals from December 1997 (the beginning of TRMM) through the current ongoing GPM retrievals. An outcome of this reprocessing is the incorporation of TRMM data products into the GPM data suite. Incorporation also means that GPM file naming conventions and reprocessed TRMM data carry the V05 data product version. This paper describes the TRMM version 8 reprocessing, focusing on the improvements in TMI level 1 products.