Evaluation of synthetic satellite images computed from radiative transfer models over a region of South America using WRF and GOES-13/16 observations

Abstract

Synthetic infrared GOES-13 observations are generated from a high-resolution (4 km) Weather Research and Forecasting (WRF) model run over Argentina for a meteorological event of deep moist convection using two different radiative transfer models. The fast operational Community Radiative Transfer Model (CRTM) and the physics-based research model Atmospheric Radiative Transfer Simulator (ARTS) are compared with the available observations. CRTM shows good results at a low computational cost, and is a good candidate for operational use in the region. CRTM and ARTS synthetic satellite images show differences due to the treatment of the bulk scattering properties of the frozen hydrometeor species, especially around the cloud shield. With this WRF+CRTM configuration, a long-term evaluation is conducted over 12 hr forecasts from one month of data in a region of the South American autumn with four different initializations at 0000, 0600, 1200 and 1800 UTC, as operational at the National Meteorological Service of Argentina. The simulated and observed GOES-16 Advanced Baseline Imager (ABI) brightness temperatures (BTs) in the 6.9 (Formula presented.) m channel show good agreement with an averaged bias of (Formula presented.) K (RMSE 21.7 K), whereas the performances in the IR window channels show slightly larger averaged BT differences of 3.5 K (RMSE 15.2 K). BT differences between the 6.9 and 10.3 (Formula presented.) m channels indicate that the WRF+CRTM simulations underestimate low to mid-level clouds and to a lesser extent high-level clouds. In the BT (10.3 (Formula presented.) m) range between approximately 215 and 230 K, there is an overestimation of clouds with BT differences above 0 K between 6.9 and 10.3 (Formula presented.) m. This could be due to the misrepresentation of upper-level clouds.