Minimizing CLARREO sampling errors through orbit selection

The CLARREO mission aims to provide spectrally resolved radiance observations that are accurate to 0.1 K in brightness temperature at spatial and temporal scales most important to climate change detection and attribution. We explore the impact of imperfect sampling by a suite of up to three nadir-sampling satellites on the accuracy with which mean radiance can be determined for 15 degree square grid boxes and monthly, seasonal and annual mean brightness temperature, and brightness temperature diurnal range. Using both high temporal resolution geostationary satellite data, and modeled radiances from General Circulation Models, we show that in addition to random weather noise and diurnal sampling bias, the correlation between spatial, diurnal and seasonal sampling bias within grid squares can become important, depending on orbit height and inclination. In addition, we use high resolution geostationary satellite radiance data to define the role of footprint size and temporal sampling frequency in producing accurate climate statistics.