P1.2
Prospects for high-latitude precipitation estimation with A-Train satellites
Eric J. Nelkin, NASA/GSFC and SSAI, Greenbelt, MD; and G. J. Huffman, R. F. Adler, and D. T. Bolvin
The widely-used Tropical Rainfall Measuring Mission (TRMM) 3B42 product has provided three-hourly estimates of precipitation in the range 50°N-50°S throughout the TRMM era (1998-present). In preparation for the follow-on Global Precipitation Mission (GPM), development work is underway to produce truly global estimates. This presentation will examine a methodology for retrieving precipitation in higher latitudes, particularly poleward of 50 degrees.
Another well-known project, the Global Precipitation Climatology Project (GPCP), has produced global estimates from 1979-present. Although it incorporates gauge data where available, coverage is sparse in high latitudes. Because current passive microwave retrievals are unable to distinguish between actual liquid/frozen precipitation and cold underlying surface, GPCP retrievals in these areas rely on estimates from the TIROS Operational Vertical Sounder (TOVS) for January 1979-April 2005, and the Atmospheric Infrared Sounder (AIRS) thereafter. However, both TOVS and AIRS estimates have been found to underestimate the true precipitation amount, while overestimating precipitation frequency.
The technique presented here takes advantage of the unique arrangement of satellites that form the “A-Train”. The Aqua satellite carries both the AIRS and the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). Meanwhile, CloudSat, with its Profiling Radar (CPR), trails Aqua in its orbit by roughly one minute, although it views only on a nadir track. This conjunction allows for numerous opportunities to compare precipitation retrievals from these three instruments. A robust database of matchups has been assembled for the period August 2006-July 2007.
Over ocean, the AIRS estimates are calibrated via a histogram-matching scheme to CPR values. Over land, a similar scheme is applied to adjust AIRS values to AMSR-E estimates. In both cases, attempts are made to scale up to the AIRS footprint size, which is larger than the other two. The resulting blend of adjusted AIRS estimates is evaluated initially on the twelve-month calibration period. After development on the dependent data set, the resulting relationships are then applied to independent data. This technique should be of benefit to both GPM and GPCP.
Poster Session 1, New and Future Sensor Applications and Systems
Tuesday, 13 January 2009, 9:45 AM-11:00 AM, Hall 5
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