MWR and WindSat inter-satellite radiometric calibration plan

Abstract

In late 2010, the Aquarius/SAC-D joint international science mission, between the National Aeronautics and Space Administration (NASA) and the Argentine Space Agency (CONAE), will be launched on a polar-orbiting satellite. This mission of discovery will provide measurements of the global sea surface salinity, which contributes to understanding climatic changes in the global water cycle and how these variations influence the general ocean circulation [1]. The Microwave Radiometer (MWR) [2], a three channel Dicke radiometer operating at 23.8 GHz H-Pol and 36.5 GHz V-& H-Pol provided by CONAE, will complement Aquarius (NASA's L-band radiometer/scatterometer) by providing simultaneous spatially collocated environmental measurements such as water vapor, cloud liquid water, surface wind speed, rain rate and sea ice concentration. This paper presents a short description of the MWR system design with emphasis on the internal radiometric calibration approach and the plan for on-orbit radiometric calibration. A major part of the MWR on-orbit calibration plan involves the inter-satellite radiometric cross-calibration using the Naval Research Laboratory's multi-frequency polarimetric microwave radiometer, WindSat, on board the Coriolis satellite. Because Coriolis and Aquarius/SAC-D are both polar orbiting satellites with similar altitudes, inclinations, and ascending/descending nodes, these two satellites have high percentage overlapping swaths giving spatial/temporal collocations within a ±45 min window. Also, WindSat is an accepted well-calibrated radiometer, and MWR channels are a subset of WindSat, with only minor differences (incidence angles and frequencies), which simplifies the inter-comparison. Details of the inter-comparison are presented using orbital simulation for swath overlap, and a discussion of the radiative transfer modeling brightness temperature (T b ) normalization procedure to account for expected incidence angle and frequency differences is also discussed. Two examples are provided from our previous experience with WindSat and Tropical Rainfall Measurement Mission Microwave Imager (TMI).