A brief outline of the basic concepts of cloud filtering and atmospheric attenuation corrections used in the Multi‐channel Sea Surface Temperature (MCSST) method is given. The operational MCSST procedures and products are described in detail. The comparative performance of AVHRR‐based MCSST'S is discussed via the use of the results of the JPL Satellite‐Derived Sea Surface Temperature workshops. For the four data periods there is surprisingly good correspondence in the sign and location of the major monthly mean SST anomaly features derived from MCSST's and those from a screened set of ship‐based SST's. With the partial exception of the one data period severely affected in some areas by volcanic aerosol from El Chichon eruptions, global statistical measures of the MCSST anomalies relative to the the ship data are as follows: biases, 0.3–0.4°C (MCSST lower than ship); standard deviations, 0.5–0.6°C; and cross‐correlations, +0.3 to +0.7. A refined technique in use with NOAA 9 data in 1985 has yielded consistent biases and rms differences near −0.1°C and 0.5°C, respectively.
Abstract. Since 1990, the NOAA National Environmental Satellite Data and Information Service (NESDIS) has provided satellite-derived sea surface temperature (SST) measurements based on nonlinear SST algorithms, using advanced very high resolution radiometer (AVHRR) multiple-infrared window channel data. This paper develops linear and nonlinear SST algorithms from the radiative transfer equation. It is shown that the nonlinear algorithms are more accurate than linear algorithms but that the functional dependence of the nonlinearity is data dependent. This theoretical discussion (sections 2-4) is followed with a discussion in section 5 of the accuracy over a 9-year period of the satellite-derived SST measurements provided by NOAA NESDIS when compared with coincident drifting buoys. Between 1989 and 1998 the global scatter of the daytime satellite SST against drifting buoy measurements has decreased from -0.8 ø to 0.5øC, while the nighttime scatter has remained fairly constant at 0.5øC. An exception to these accuracy measurements occurred after the eruption of Mount Pinatubo in June 1991.
Abstract. The data received from the thermal infrared channel 4 (--•10.3-11.3 tzm) and channel 5 (--•11.5-12.5 tzm) of the advanced very high resolution radiometer (AVHRR) flown on the National Oceanic and Atmospheric Administration (NOAA) Polar-Orbiting Operational Environmental Satellites provide only a linear estimate of the actual radiance. We describe here a simple procedure, which incorporates data from prelaunch calibration tests, to correct the linear estimates for the nonlinear response of the channels 4 and 5 Mercury-Cadmium-Telluride (Hg-Cd-Te) sensors. The procedure applies a "nonzero radiance of space" concept to specify the form of the linear radiance estimate. This linear radiance is nearly independent of the operating temperature of the AVHRR and is the sole input to the correction algorithm. Additionally, it is demonstrated with NOAA 14 data that this calibration procedure resolves discrepancies found in the prelaunch data which can affect the calibration accuracy of channel 3 (--•3.55-3.95 tzm), which possesses a linear response, as well as channels 4 and 5. When applied to independent sets of prelaunch calibration data, this procedure reproduces the laboratory-measured temperature data to within an accuracy of 0.1ø-0.2øK. Comparison with nonlinearity corrections based on different procedures points to the superior applicability of the present results over the entire range of Earth-scene temperatures measured by the AVHRR in orbit. This accuracy is particularly important when these three infrared channels are used in multichannel algorithms to generate environmental parameters such as sea surface temperature. The algorithm coefficients and values of the nonzero radiance of space required to calculate the nonlinearity radiance corrections are given for the AVHRRs on NOAA 7, 9, 10, 11, 12, and 14 spacecraft. ]. We present here the derivation of a simple analytic formula that accurately reproduces the nonlinearities noticed in the prelaunch calibration of the thermal infrared channels in the laboratory. We demonstrate how this formula can be used to correct for sensor nonlinearities when the instrument is in orbit, assuming that the prelaunch sensor behavior is faithfully reproduced in the postlaunch environment. We shall also examine the implications for in-space data calibration resulting from laboratory-measured inconsistencies between the responses of the instrument when it views the Earth target and space target simulators, with special reference to the AVHRR 3323
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