SNPP ATMS Striping Mitigation and Its Impacts on Numerical Weather Prediction

Observations from satellite microwave radiometers contain random noise and sometimes also coherent noise. For the Advanced Microwave Sounding Technology (ATMS) on board Suomi NPP satellite, the coherent noise at 50-60 GHz (V-band) is noticeable as a striping pattern in the global differences of brightness temperatures between observations (O) and simulations (B) and is also shown as 1/F noise spectrum of calibration counts. This striping noise in ATMS data is of a serious concern for many applications and can degrade the data impacts on NWP forecast skill if not identified and eliminated. In this study, we present a new technique for reducing the striping noise contained in ATMS, Microwave Humidity Sounder (MHS), the Advanced Microwave Sounding Unit–B (AMSU-B) and the Global Precipitation Measurement Microwave Imager (GMI) data. Note that the striping noise is visually discernible in global O-B fields in ATMS V-band channels, but hidden in WG and K/Ka band channels due to much larger dynamic variability compared with that of V-band channels. To reduce the ATMS striping noise, four sets of along-track optimal filters are developed for the scene counts, cold counts, warm counts and brightness temperatures for the de-striping purpose of the 22 ATMS channels. While the striping noise spectra in the brightness temperatures are contributed from those in the earth scene count and calibration counts, the de-striping to calibration counts is in general not sufficient for removing the striping noise in brightness temperatures. The de-striping impacts on NWP will be demonstrated by comparing data assimilation and forecast results with and without applying the proposed optimal de-striping filters.