to the real-time weather forecasting mission, but that are significant for long-term climate monitoring. For example, adjustments were developed for errors introduced from orbital drift, calibration shifts, and unanticipated biases, all of which generally fall below 0.1 C in magnitude. Since knowledge of changes in global temperature needs to be precise to a few hundredths of a degree per decade, such errors are important to detect and resolve.
Producing a data set with precision of this level on a continuing basis might best be called operational research. Unfortunately, there has not been a source of funding for this type of project because it requires constant human attentiveness and intervention rather than a set period of performance.
Because of the highly specialized expertise required for the construction of these data sets, few scientists undertake such endeavors, and such efforts are generally outside the tasks mandated for NOAA employees. NOAA has deemed a few of these data construction activities as vital for its climate monitoring function and so has initiated small contracts with groups such as the University of Alabama, Huntsville, which then provide monthly updates of these products, usually by the tenth day after each month’s end. As additional spurious effects are discovered and minimized, these data sets are updated, metadata files describing the issue are created, and if appropriate, the results are published in the peer-reviewed literature.
This case study presents a scenario in which NOAA’s mission to provide climate-quality data records for national and international assessments is met through the expertise of university scientists at relatively low cost.