CrIS Cloud clearing using VIIRS and application to Hurricane forecast

Retrieval of atmosphere temperature and moisture profiles from combined radiance measurements of the Atmospheric InfraRed Sounder (AIRS) and the Moderate resolution Imaging Spectroradiometer (MODIS) onboard the NASA Aqua satellite is investigated. Hyperspectral resolution IR sounder onboard the low Earth orbit (LEO) satellites, such as AIRS, IASI and CrIS are capable of obtaining atmospheric temperature and moisture profiles with high spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers observations of the terrestrial, atmospheric, and ocean phenomenology with high spatial resolutions. The collocated operational MODIS cloud mask product and the clear-sky InfraRed (IR) radiance measurements are used to characterize the AIRS sub-pixel cloud fraction and improve the atmospheric sounding and the surface parameters at the AIRS single field-of-view (SFOV) resolution. Based on regression retrieval and physical retrieval algorithm, methods are developed to combine the hyperspectral resolution IR radiances and MODIS data, which aids in deriving more accurate atmospheric thermodynamic state over land and ocean. Previous researches have shown the benefits of combining AIRS and MODIS referring cloud parameters (Li et al., 2004, 2005), atmospheric profiles (Liu et al., 2008) and dust properties (Yao et al., 2015). To improve the retrieval accuracy of atmospheric profiles by synergy retrieval in certain areas such as Tibetan Plateau remains to be explored. Evaluation of the synergistic retrieval method is performed by comparing combined retrieval profiles with collocated analysis/reanalysis data and stand-alone retrievals from either AIRS or MODIS systems. Evaluation of benefits/limitations of retrieval performances is performed by applying synergistic retrieval method to different layers or regions. To find out the potential application of synergy information on weather forecasts, further investigation plans on assimilation of combined retrieval to regional numerical weather prediction (NWP) model and evaluation of the added impact for improving the forecasts of hurricane track or intensity by case study.