An intercomparison study under the auspices of NASA's Precipitation Measurement Missions (PMM) Science Team was organized to assess the current status of established and emerging emissivity data sets and techniques. Currently, the PMM Land Surface Characterization Working Group (LSWG) is comparing seven algorithms that use different techniques to estimate emissivity (e.g., by direct observational, by using a land surface model, and by physical retrieval). These algorithms are compared during a three year period (July 2004 to June 2007), initially at three different sites (continental US (central, and southern) and in southern Canada). Amongst the data set being compared are estimates coming from passive microwave radiometer (e.g. SSMI/I, SSMI/S, AMSR-E, TMI, AMSU/MHS, WindSat), or in combination with ancillary data (e.g. land surface model data, ISSCP cloud mask, satellite-based precipitation data).
The comparison study tries to explore similarities and differences between the different techniques. These techniques are being compared by time series, monthly means, and percent of difference between them during periods of land surface change, such as snow cover, vegetation, presence of clouds, and precipitation. The results to date demonstrate that emissivity is affected by these conditions, more or less depending on the target site, but some of the discrepancies between these techniques are still unknown, and are under current evaluation.