Hyperspectral IR two-layer cloud fast forward model - LY2G

A fast and accurate hyperspectral infrared clear/cloudy radiative transfer model is developed to simulate the Top-Of-Atmosphere (TOA) radiances and brightness temperatures over a broad spectral band (~3-100µm). The principal use of this effort is to generate TOA brightness temperature, radiances, and surface to space transmittance over large spatial domains for realistic surface states and atmospheric conditions to assist in retrieval algorithm development for next-generation hyperspectral IR sensors.

Cloud is a critical factor in radiative transfer model. Most of the models deal with one layer cloud only. Observations both from space and in situ indicate that multiple layer clouds occur more than 50% time globaly, most of them are two layer clouds. A two-layer cloud model in the framework of the GIFTS fast model (LY2G) has been implemented and an ecosystem surface emissivity model (MODIS band resolution) has been included. An automatic selection of cloud layer type, top height, optical depth (OD), effective diameter (De) from mesoscale model outputs, and/or from the atmosphere profiles with a two-layer cloud formation model has been developed and incorporated into LY2G. Overall, this model (LY2G) runs less than 1s per GIFTS spectrum (3000+ channels), and yields more accurate results in comparison to one layer cloud model in reference to a complete and sophisticated radiative model, i.e. LBLDIS.

For the purpose of comparison and validation, a range of simulations were performed for generating LY2G and LBLRTM/DISORT simulated brightness temperatures for GIFTS channels and equivalent cloudy profiles. Results show that adopting two-layer cloud model at least doubles accuracy of simulations in comparison to one layer-cloud model, which will eventually increase retrieval algorithm accuracy. A netCDF interface option was added to make easier the visualization of inputs/outputs with Unidata's IDV.