Implementation of Globally Simulated Dust within a Physical Sea Surface Temperature Retrievals for Numerical Weather Prediction

Aerosols are not the only source of error in sea surface temperature (SST) retrievals; however, it is nontrivial problem that requires attention. Simulation and validation of aerosol in radiative transfer models (RTM) is considered extremely challenging, especially in the infrared (IR); this is because brightness temperatures (BTs) retrievals --which are converted into SSTs-- are highly influenced by changes in atmospheric composition. Tropospheric aerosols seem to have a persistent impact that may result in negative SST biases of 1K or more. Several questions arise around this topic, but most importantly: is it even possible to simulate aerosols using a RTM for a SST retrieval application? If so, what are the implications?

This works presents the results for the first study to ever attempt to analyze the full potential and limitations of incorporating aerosols within a truly physical SST retrieval for operational weather forecasting purposes. This is accomplished through the application of a satellite sea surface temperature (SST) physical retrieval for split-window and hyperspectral infrared (IR) sensors that allows a better representation of the atmospheric state under aerosol-laden conditions. The new algorithm includes 1) accurate specification of the emissivity that characterizes the surface leaving radiance and 2) transmittance and physical characterization of the atmosphere by using the Community Radiative Transfer Model (CRTM). This project includes application of the NEMS-Global Forecasting System Aerosol Component (NGAC) fields, which corresponds to the first global interactive atmosphere-aerosol forecast system ever implemented at NOAA's National Center for Environmental Prediction (NCEP). SST outputs are validated against a bulk and a parameterized SST derived from operational products and partly against observed measurements from the eastern Atlantic Ocean, which is dominated by Saharan dust throughout most of the year and that is also a genesis region for Atlantic tropical cyclones. These observations are obtained from the NOAA Aerosols and Ocean Science Expeditions (AEROSE). By studying potential approaches to correct aerosol-induced biases, the accuracy of remotely-sensed BTs/SSTs can be greatly improved.