资源环境科技发展态势分析平台

Forecasts from NOAA’s Global Forecast System (GFS) and the High-Resolution Rapid Refresh (HRRR) weather models are matched to surface observations for the winter season of November 2019 to March 2020 at 210 airports across the United States. The 2-m temperature errors, conditioned on observed weather conditions such as cloud cover amount and wind speed, are used to determine the nature of systematic model biases. We observe a strong diurnal cycle in 2-m temperature errors in the GFS in conditions with 50% and 25% sky cover, with a C warm bias at night and a C cold bias during the day. The HRRR, which uses a different set of physical parameterizations, does not have a clear diurnal cycle in errors under the same conditions. These results highlight the utility of weather-conditional comparisons across the diurnal cycle to diagnose sources of model weaknesses and to target model improvements.