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Abstract
We present a new method to determine the near surface air temperature (Ta ) from satellite observations. The satellite observed parameters of total precipitable water (W), atmospheric boundary layer (∼500 m) water vapour (Wb ), and sea surface temperature (SST) are used to derive Ta . A genetic algorithm (GA) is used to find the optimum relation between the input (W, Wb , SST) and output (Ta) parameters. The input data consist of 6 years (1988–1993) of instantaneous as well as monthly averages of W, Wb from the Special Sensor Microwave Imager (SSM/I), and SST data from the Advanced Very High Resolution Radiometer (AVHRR). Ta observations based on Comprehensive Ocean Atmospheric Data Set (COADS) are used to develop and evaluate the new methodology. The global mean root mean square (rms) error for instantaneous Ta estimates is 1.4°C and for monthly averages it decreases to 0.74°C. Slightly higher discrepancies between Ta derived from the new method and in situ data are found over the western boundary currents (such as the Kuroshio and Gulf Stream) during wintertime. These regions are characterized by continental cold air outbreak and seasonal current systems, particularly during wintertime. During these conditions weak coupling between SST and Ta may be one of the reasons for large error over these regions. Our method improves upon the air temperature estimates of earlier studies.
Acknowledgment
The authors would like to acknowledge the Physical Oceanography Data Archival Centre (PO.DAAC) at the Jet Propulsion Laboratory (JPL), the SMD active archive at http://ingrid.ldeo.columbia.edu, the SSM/I ocean products at ftp.ssmi.com, and COADS data at ftp.cdc.noaa.gov.