A daily blended analysis for sea surface temperature
Richard W. Reynolds, NOAA/NESDIS/NCDC, Asheville, NC; and K. S. Casey, T. M. Smith, and D. B. Chelton
A weekly optimum interpolation (OI) sea surface temperature (SST) analysis has been produced at the National Oceanic and Atmospheric Administration since 1993. The analysis is produced on a one degree spatial grid from November 1981 to present and uses bias corrected Advanced Very High Resolution Radiometer (AVHRR) infrared satellite retrievals and in situ SST observations from ships and buoys. The analysis has been widely used for weather and climate monitoring and forecasting.
A higher resolution version of the OI analysis has been produced daily on a 0.25-degree spatial grid for 2002-2003. The analysis uses in situ data and three different types of satellite data: Pathfinder AVHRR, operational Navy AVHRR and Advanced Microwave Scanning Radiometer (AMSR) satellite data. The results show that the gradient features in the analysis have been systematically improved, even in regions with sparse AVHRR data due to cloud cover. This implies that many SST features evolve slowly in time. However, because of the near-all-weather measurement capability of AMSR, the gradients are sharpest when AMSR data are used. The daily OI analysis includes a weekly correction of satellite biases. Thus, the new analysis is useful for climate studies, as well as for users requiring higher resolution. Intercomparisons of the different analyses and the input satellite data are presented. A final version is also presented using AVHRR, AMSR and microwave data from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). Because the microwave and infrared retrieval methods are different, the bias errors from the two different sources are independent. Thus a combination of these two types of satellite data reduces any residual bias that is not corrected by the in situ data.
Extended Abstract (260K)
Session 8, Operational Products
Thursday, 2 February 2006, 8:30 AM-9:45 AM, A305
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