Sea surface temperature estimation from the Geostationary Operational Environmental Satellite 12 (GOES-12)

Merchant, C. J. ORCID: https://orcid.org/0000-0003-4687-9850, Harris, A. R., Maturi, E., Embury, O. ORCID: https://orcid.org/0000-0002-1661-7828, MacCallum, S. N., Mittaz, J. and Old, C. P. (2009) Sea surface temperature estimation from the Geostationary Operational Environmental Satellite 12 (GOES-12). Journal of Atmospheric and Oceanic Technology, 26 (3). pp. 570-581. ISSN 1520-0426 doi: 10.1175/2008JTECHO596.1

Abstract/Summary

This paper describes the techniques used to obtain sea surface temperature (SST) retrievals from the Geostationary Operational Environmental Satellite 12 (GOES-12) at the National Oceanic and Atmospheric Administration’s Office of Satellite Data Processing and Distribution. Previous SST retrieval techniques relying on channels at 11 and 12 μm are not applicable because GOES-12 lacks the latter channel. Cloud detection is performed using a Bayesian method exploiting fast-forward modeling of prior clear-sky radiances using numerical weather predictions. The basic retrieval algorithm used at nighttime is based on a linear combination of brightness temperatures at 3.9 and 11 μm. In comparison with traditional split window SSTs (using 11- and 12-μm channels), simulations show that this combination has maximum scatter when observing drier colder scenes, with a comparable overall performance. For daytime retrieval, the same algorithm is applied after estimating and removing the contribution to brightness temperature in the 3.9-μm channel from solar irradiance. The correction is based on radiative transfer simulations and comprises a parameterization for atmospheric scattering and a calculation of ocean surface reflected radiance. Potential use of the 13-μm channel for SST is shown in a simulation study: in conjunction with the 3.9-μm channel, it can reduce the retrieval error by 30%. Some validation results are shown while a companion paper by Maturi et al. shows a detailed analysis of the validation results for the operational algorithms described in this present article.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/33725
Item Type	Article
Refereed	Yes
Divisions	No Reading authors. Back catalogue items Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Uncontrolled Keywords	Sea surface temperature; Satellite observations; Instrumentation/sensors
Publisher	American Meteorological Society
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