Enhancing Assimilation of Satellite Microwave Observations

Microwave satellite observations are crucial for the forecasts provided by the Numerical Weather Prediction (NWP) models, providing essential data on atmospheric conditions.These observations are particularly valuable for predicting tropical cyclones, offering detailed insights into storm structure and intensity. The Community Radiative Transfer Model (CRTM), developed by NOAA JCSDA, is extensively used to assimilate these microwave observations and retrieve geophysical parameters. However, CRTM’s current lookup tables for hydrometeor optical properties assume spherical shapes for frozen particles, which does not fully capture the diverse shapes of real cloud particles.

This presentation examines how microwave satellite observations enhance NWP forecasts and details the improvement of forward radiative transfer models through the integration of a Discrete Dipole Approximation (DDA) cloud scattering database into CRTM. The DDA technique offers a more accurate simulation of non-spherical hydrometeors' optical properties, particularly in the microwave spectrum. By incorporating this advanced DDA database, which includes water content-dependent particle size distributions and single scattering properties, we significantly enhance the model’s capability to simulate all-sky microwave observations accurately. We also explore the impact of these observations on NWP model forecasts, with a specific focus on tropical cyclone predictions. Evaluation with collocated datasets of short-term forecasts and satellite microwave data shows that the new DDA lookup tables substantially reduce discrepancies between simulated and observed values compared to traditional models, demonstrating their effectiveness in improving forecast accuracy.