J7.4
An Inter-calibrated Passive Microwave Brightness Temperature Data Record and Ocean Products

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Tuesday, 6 January 2015: 11:45 AM
230 (Phoenix Convention Center - West and North Buildings)
Kyle A. Hilburn, Remote Sensing Systems, Santa Rosa, CA; and F. J. Wentz

Inter-calibration of passive microwave sensors has been the subject of on-going activity at Remote Sensing Systems (RSS) since 1974. RSS has produced a brightness temperature TB data record that spans the last 28 years (1987-2014) from inter-calibrated passive microwave sensors on 14 satellites: AMSR-E, AMSR2, GMI, SSMI F08-F15, SSMIS F16-F18, TMI, and WindSat. Accompanying the TB record are a suite of ocean products derived from the TBs that provide a 28-year record of wind speed, water vapor, cloud liquid, and rain rate; and 18 years (1997-2014) of sea surface temperatures, corresponding to the period for which 6 and/or 10 GHz measurements are available. Crucial to the inter-calibration and ocean product retrieval are a highly accurate radiative transfer model RTM. The RSS RTM has been continually refined for over 30 years and is arguably the most accurate model in the 1-100 GHz spectrum. The current generation of TB and ocean products, produced using the latest version of the RTM, is called Version-7. The accuracy of the Version-7 inter-calibration is estimated to be 0.1 K, based on inter-satellite comparisons and validation of the ocean products against in situ measurements.

The data record produced by RSS has had a significant scientific impact. Over just the last 14 years (2000-2013) RSS data have been used in 743 peer-reviewed journal articles. This is an average of 4.5 peer-reviewed papers published every month made possible with RSS data. Some of the most important scientific contributions made by RSS data have been to the study of the climate. The AR5 Report “Climate Change 2013: The Physical Science Basis” by the Intergovernmental Panel on Climate Change (IPCC), the internationally accepted authority on climate change, references 20 peer-reviewed journal papers from RSS scientists. The report makes direct use of RSS water vapor data, RSS atmospheric temperatures from MSU/AMSU, and 9 other datasets that are derived from RSS data. The RSS TB data record is used to produce the NSIDC Sea Ice, NASA Sea Ice, and NASA GPCP Rain Rate datasets. The RSS ocean products are used to produce the NCDC ERSST, CCMP Winds, NOAA Sea Winds, WHOI OA Flux, OSU Wind Stress, and UWISC Cloud Water datasets. The large number of scientific articles and significant impact on the IPCC report demonstrate the success of RSS inter-calibration methodology.