Daily High-Resolution-Blended Analyses for Sea Surface Temperature

Journal of Climate - Tập 20 Số 22 - Trang 5473-5496 - 2007
Richard W. Reynolds1, Thomas M. Smith2, Chun‐Ying Liu1, Dudley B. Chelton3, Kenneth S. Casey4, Michael G. Schlax3
1noaa/national Climatic data Center, asheville, north Carolina
2NOAA/NESDIS, CICS/ESSIC, University of Maryland, College Park, College Park, Maryland
3College of Oceanic and Atmospheric Sciences, and Cooperative Institute for Oceanographic Satellite Studies, Oregon State University, Corvallis, Oregon
4NOAA/National Oceanographic Data Center, Silver Spring, Maryland

Tóm tắt

Abstract Two new high-resolution sea surface temperature (SST) analysis products have been developed using optimum interpolation (OI). The analyses have a spatial grid resolution of 0.25° and a temporal resolution of 1 day. One product uses the Advanced Very High Resolution Radiometer (AVHRR) infrared satellite SST data. The other uses AVHRR and Advanced Microwave Scanning Radiometer (AMSR) on the NASA Earth Observing System satellite SST data. Both products also use in situ data from ships and buoys and include a large-scale adjustment of satellite biases with respect to the in situ data. Because of AMSR’s near-all-weather coverage, there is an increase in OI signal variance when AMSR is added to AVHRR. Thus, two products are needed to avoid an analysis variance jump when AMSR became available in June 2002. For both products, the results show improved spatial and temporal resolution compared to previous weekly 1° OI analyses. The AVHRR-only product uses Pathfinder AVHRR data (currently available from January 1985 to December 2005) and operational AVHRR data for 2006 onward. Pathfinder AVHRR was chosen over operational AVHRR, when available, because Pathfinder agrees better with the in situ data. The AMSR–AVHRR product begins with the start of AMSR data in June 2002. In this product, the primary AVHRR contribution is in regions near land where AMSR is not available. However, in cloud-free regions, use of both infrared and microwave instruments can reduce systematic biases because their error characteristics are independent.

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Journal of Climate

Tập 20 Số 22

5473-5496

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