Abstract

Hyperspectral infrared radiance measurements from satellite sensors contain valuable information on atmospheric temperature and humidity profiles and greenhouse gases, and therefore are directly assimilated into numerical weather prediction (NWP) models as inputs for weather forecasting. However, data assimilations in current operational NWP models still mainly rely on cloud-free observations due to the challenge of simulating cloud-contaminated radiances when using hyperspectral radiances. The limited spatial coverage of the 3×3 field of views (FOVs) in one field of regard (FOR) (i.e., spatial gap among FOVs) as well as relatively large footprint size (14 km) in current Cross-track Infrared Sounder (CrIS) instruments limits the amount of clear-sky observations. This study explores the potential impacts of future CrIS FOV configuration (including FOV size and spatial coverage) on the amount of clear-sky observations by simulation experiments. The radiance measurements and cloud mask products (VCM) from the Visible Infrared Imager Radiometer Suite (VIIRS) are used to simulate CrIS clear-sky observation under different FOV configurations. The results indicate that, given the same FOV coverage (e.g., 3×3), the percentage of clear-sky FOVs and the percentage of clear-sky FORs (that contain at least one clear-sky FOV) both increase as the FOV size decreases. In particular, if the CrIS FOV size were reduced from 14 km to 7 km, the percentage of clear-sky FOVs increases from 9.02% to 13.51% and the percentage of clear-sky FORs increases from 18.24% to 27.51%. Given the same FOV size but with increasing FOV coverage in each FOR, the clear-sky FOV observations increases proportionally with the increasing sampling FOVs. Both reducing FOV size and increasing FOV coverage can result in more clear-sky FORs, which benefit data utilization of NWP data assimilation.

© 2016 Optical Society of America

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