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Retrieval of sea surface temperature from space based on modeling of infrared radiative transfer: capabilities and limitations

Merchant, C. J. ORCID: https://orcid.org/0000-0003-4687-9850 and Le Borgne, P. (2004) Retrieval of sea surface temperature from space based on modeling of infrared radiative transfer: capabilities and limitations. Journal of Atmospheric and Oceanic Technology, 21 (11). pp. 1734-1746. ISSN 1520-0426

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To link to this item DOI: 10.1175/JTECH1667.1

Abstract/Summary

The retrieval (estimation) of sea surface temperatures (SSTs) from space-based infrared observations is increasingly performed using retrieval coefficients derived from radiative transfer simulations of top-of-atmosphere brightness temperatures (BTs). Typically, an estimate of SST is formed from a weighted combination of BTs at a few wavelengths, plus an offset. This paper addresses two questions about the radiative transfer modeling approach to deriving these weighting and offset coefficients. How precisely specified do the coefficients need to be in order to obtain the required SST accuracy (e.g., scatter <0.3 K in week-average SST, bias <0.1 K)? And how precisely is it actually possible to specify them using current forward models? The conclusions are that weighting coefficients can be obtained with adequate precision, while the offset coefficient will often require an empirical adjustment of the order of a few tenths of a kelvin against validation data. Thus, a rational approach to defining retrieval coefficients is one of radiative transfer modeling followed by offset adjustment. The need for this approach is illustrated from experience in defining SST retrieval schemes for operational meteorological satellites. A strategy is described for obtaining the required offset adjustment, and the paper highlights some of the subtler aspects involved with reference to the example of SST retrievals from the imager on the geostationary satellite GOES-8.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:33778
Publisher:American Meteorological Society

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