HR: 09:15h
AN: OS31A-06    [Abstracts]
TI: Establishing a Climate Data Record for MODIS Sea Surface Temperatures - error characteristics and traceability to temperature standards
AU: * Minnett, P J
EM: pminnett@rsmas.miami.edu
AF: University of Miami, Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric Science University of Miami 4600 Rickenbacker Causeway, Miami, FL 33149, United States
AU: Evans, R H
EM: revans@rsmas.miami.edu
AF: University of Miami, Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric Science University of Miami 4600 Rickenbacker Causeway, Miami, FL 33149, United States
AB: The establishment of Climate Data Records from satellite sensors requires extensive characterization of the uncertainties in the retrieved geophysical variables, ideally by comparison with measurements using independent sensors of known accuracy and traceability to a National Standard. To achieve an adequate description of the error characteristics the validation data sets should encompass the full climatological range of not only the retrieved variables, but also those that introduce uncertainties. Thus, for example, the validation of sea surface temperatures (SSTs) should cover not only the full range of SSTs, but also span the range of atmospheric water vapor distribution. This presentation describes the approach of validating the skin SSTs from MODISs (MODerate-resolution Imaging Spectroradiometers) on Terra and Aqua using shipboard M-AERIs (Marine-Atmospheric Emitted Radiance Interferometers) and drifting buoys. An additional approach of using microwave SST retrievals from AMSR-E (Advanced Microwave Scanning radiometer for the Earth Observing System) as a "transfer standard" is being explored. The uncertainty characteristics in the satellite retrievals that are considered acceptable depends on the intended applications, and while for many purposes knowledge of the globally averaged errors is sufficient, but for others it is necessary to specify the uncertainties in regionally or temporally constrained conditions. Here we discuss an approach of stratifying the error statistics in a multi- dimensional space, an error hypercube, that allows rapid and easy predictions of the expected retrieval errors on a pixel-by-pixel basis. This has been implemented in the Global Data Assimilation Experiment (GODAE) High Resolution Sea Surface Temperature Pilot Project (GHRSST-PP), and is argued should be adopted for the forthcoming NPP and NPOESS missions to extend the SST CDRs into the next decade.
DE: 4294 Instruments and techniques
DE: 6959 Radio oceanography (1222)
DE: 6969 Remote sensing
SC: Ocean Sciences [OS]
MN: 2007 Joint Assembly