An Improved Parameterization for Retrieving Clear-Sky Downward Longwave Radiation from Satellite Thermal Infrared Data

Abstract

Surface downward longwave radiation (DLR) is a crucial component in Earth’s surface energy balance. Yu et al. (2013) developed a parameterization for retrieving clear-sky DLR at high spatial resolution by combined use of satellite thermal infrared (TIR) data and column integrated water vapor (IWV). We extended the Yu2013 parameterization to Moderate Resolution Imaging Spectroradiometer (MODIS) data based on atmospheric radiative simulation, and we modified the parameterization to decrease the systematic negative biases at large IWVs. The new parameterization improved DLR accuracy by 1.9 to 3.1 W/m2 for IWV ≥3 cm compared to the Yu2013 algorithm. We also compared the new parameterization with four algorithms, including two based on Top-of-Atmosphere (TOA) radiance and two using near-surface meteorological parameters and water vapor. The algorithms were first evaluated using simulated data and then applied to MODIS data and validated using surface measurements at 14 stations around the globe. The results suggest that the new parameterization outperforms the TOA-radiance based algorithms in the regions where ground temperature is substantially different (enough that the difference between them is as large as 20 K) from skin air temperature. The parameterization also works well at high elevations where atmospheric parameter-based algorithms often have large biases. Furthermore, comparing different sources of atmospheric input data, we found that using the parameters interpolated from atmospheric reanalysis data improved the DLR estimation by 7.8 W/m2 for the new parameterization and 19.1 W/m2 for other algorithms at high-altitude sites, as compared to MODIS atmospheric products.

Keywords

• parameterization
• brightness temperature
• water vapor content
• ground-air temperature difference
• MODIS
• downward longwave radiation