. "Sea Surface Temperature." Issues in the Integration of Research and Operational Satellite Systems for Climate Research: Part I. Science and Design. Washington, DC: The National Academies Press, 2000.
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN
Summary and Findings
There are two substantive issues associated with the NPOESS environmental data record (EDR) requirements for sea surface temperature (SST) observation. First, the SST requirement has not been modified to be compatible with the results of the Climate Requirements Workshop Report (CRWP) (Jacobowitz et al., 1996). Second, calibration and validation are not a part of the NPOESS specification.
The CRWP developed a modified set of ocean observation requirements for SST. It noted that the accuracy objective can be relaxed from 0.1 K1 at pixel resolution to 25 km spatial scale and a one-week temporal scale. It also commented on resolution of diel2 effects and instrumental stability. The CRWP suggested that resolution of the diel cycle would require a constellation of four polar platforms, rather than the three specified by NPOESS, i.e., 3-hour temporal sampling. The CRWP recommended that satellite-based instruments have a demonstrable stability of 0.1 K.
1In space studies of weather and climate, it is customary to denote temperature in the Kelvin, or absolute, scale. For Celsius temperature readings, 0 °C = 273.16 K.
2Diel is defined as a variation over a 24-hour period.
Monitoring stability in the SST record during NPOESS missions and in the handoff periods between NPOESS and Earth Observing System (EOS) platforms requires extensive preflight characterization and post-launch validation, as outlined in the text of this chapter. The NPOESS EDRs neither specify such an activity nor suggest how sensor providers will demonstrate on-orbit stability that meets the requirements. On a more general level, there is no strategy either to integrate the lessons learned from EOS into NPOESS, or to provide inter- or intrasystem validation.
Interestingly enough, the increasing density of observations has shown that each approach provides a slightly different estimate of the SST because of the peculiarities of each sampling system. This understanding has motivated development of techniques for assimilation that attempt to compensate for such peculiarities and provide surface temperature fields with known characteristics.
Generally, SST analyses have been of two types: pattern discrimination and quantitative field estimates. It should be noted that satellite infrared (IR) observations of surface temperature were initiated to support meteorological applications, not to further oceanographic or climatic purposes; later such requirements started to drive accuracy, spectral placement of radiometer windows, and so on. Early satellite-based analyses could discern the edge of the Gulf Stream or the California Current because of the strong surface temperature gradient. However, the estimate of surface temperature might have been accurate only to 1.5 K or so. Eddies, boundary currents, and other mesoscale phenomena were readily identified, even though the accuracy of the estimated temperatures in and around the features was less than that obtained with in situ techniques. Moreover, the level of accuracy was not useful for following large-scale, low-frequency temperature change in the surface ocean, such as might be caused by the El Niño/Southern Oscillation (ENSO), the North Atlantic Oscillation, or other lower-frequency phenomena. During the last two decades, however, the accuracy of SST mapping from satellites has improved so that observations are routinely produced at rms (root mean square) accuracies of 0.6 K or better, thus permitting the observation and study of large-scale, low-frequency fluctuations in the ocean that might be associated with climatic variation or ecosystem change.