Abstract
A new satellite sea surface temperature (SST) algorithm is developed that uses nearly coincident measurements from the microwave special sensor microwave imager (SSM/I) to correct for atmospheric moisture attenuation of the infrared signal from the advanced very high resolution radiometer (AVHRR). This new SST algorithm is applied to AVHRR imagery from the South Pacific and Norwegian seas, which are then compared with simultaneous in situ (ship based) measurements of both skin and bulk SST. In addition, an SST algorithm using a quadratic product of the difference between the two AVHRR thermal infrared channels is compared with the in situ measurements. While the quadratic formulation provides a considerable improvement over the older cross product (CPSST) and multichannel (MCSST) algorithms, the SSM/I corrected SST (called the water vapor or WVSST) shows overall smaller errors when compared to both the skin and bulk in situ SST observations. Applied to individual AVHRR images, the WVSST reveals an SST difference pattern (CPSST‐WVSST) similar in shape to the water vapor structure while the CPSST‐quadratic SST difference appears unrelated in pattern to the nearly coincident water vapor pattern. An application of the WVSST to week‐long composites of global area coverage (GAC) AVHRR data demonstrates again the manner in which the WVSST corrects the AVHRR for atmospheric moisture attenuation. By comparison the quadratic SST method underestimates the SST corrections in the lower latitudes and overestimates the SST in the higher latitudes. Correlations between the AVHRR thermal channel differences and the SSM/I water vapor demonstrate the inability of the channel difference to represent water vapor in the midlatitude and high latitudes during summer. Compared against drifting buoy data the WVSST and the quadratic SST both exhibit the same general behavior with relatively small differences with the buoy temperatures.
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