The Sampling Problem for High Accuracy Climate Monitoring from Space
The proposed NASA CLARREO (Climate Absolute Radiance and Refractivity Observatory) mission would involve a set of orbiting observatories designed from start to finish for high absolute accuracy, traceable to international standards. They will observe spectrally resolved infrared and visible radiance, and radio-frequency refractivity by GPS occulatation. My contribution to this project involves studies of the sampling error characteristics of data from a range of candidate satellite orbital configurations. To achieve very high accuracies in climate means (e.g. less than 0.1 K in infrared brightness temperature), both random errors and sampling bias must be considered. This means large numbers of observations (by averaging over relatively large geographic regions and temporal ranges), and also careful attention to the interactions of satellite orbital frequency, ground track repeat cycles, and seasonal, semi-seasonal, diurnal and semi-diurnal variability.
This figure shows the variation of the correlation of grid point brightness temperature as a function of distance separating the points. If the correlation decays rapidly with distance, then increasing sampling frequency will effectively reduce sampling noise.
Kirk-Davidoff, D.B., R.M. Goody, and J.G. Anderson, 2005: Analysis of sampling errors for climate monitoring satellites. J. Climate. 18:810-822. PDF.
Anderson, J.G., J.A. Dykema, R.M. Goody, H. Hu, D.B. Kirk-Davidoff, 2004: Absolute Spectrally Resolved Radiance: A Benchmark for Climate Monitoring from Space. J.Q.R.S.T. 85:367-383. PDF.