Land Surface Emissivity Impact on Advanced Infrared Soundings

Numerous global infrared land surface emissivity datasets have been available for sounding retrievals, radiance assimilation, and climate studies. To investigate the effects of different land surface emissivity datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational retrieval algorithm. The physical iterative retrievals using constant emissivity, the emissivity dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset (BLF) from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. It is found that the emissivity spectrums from the IASI and the BLF perform significantly better than the constant emissivity. It is also shown that the initial emissivity dependence of the temperature retrieval is relatively weak when the emissivity is simultaneously updated, but the emissivity dependence of the moisture retrieval is relatively strong. In addition, the comparisons reveal that the emissivity from the IASI has a more positive impact on the retrieval than the BLF, especially for moisture profile retrievals. Finally, emissivity angle dependence is also investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over ocean reveals weak angle dependence, which is consistent with that from the ocean emissivity model. This demonstrates the reliability of the algorithm for emissivity retrieval from hyperspectral IR radiance measurements.