资源环境科技发展态势分析平台

Observations from the Global Precipitation Measurement (GPM) core satellite were used along with precipitation forecasts from the High Resolution Rapid Refresh (HRRR) model to assess and interpret differences between observed and modeled storms. Using a feature-based approach, precipitating objects were identified in both the National Centers for Environmental Prediction Stage IV multisensor precipitation product and HRRR forecast at lead times of 1, 2, and 3h at valid times corresponding to GPM overpasses. Precipitating objects were selected for further study if (a) the observed feature occurred entirely within the swath of the GPM Microwave Imager (GMI) and (b) the HRRR model predicted it at all three forecast lead times. Output from the HRRR model was used to simulate microwave brightness temperatures (Tbs), which were compared to those observed by the GMI. Simulated Tbs were found to have biases at both the warm and cold ends of the distribution, corresponding to the stratiform/anvil and convective areas of the storms, respectively. Several experiments altered both the simulation microphysics and hydrometeor classification in order to evaluate potential shortcomings in the model's representation of precipitating clouds. In general, inconsistencies between observed and simulated brightness temperatures were most improved when transferring snow water content to supercooled liquid hydrometeor classes.