Assimilating Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Observations and the Relative Value of Other Observation Types

摘要

The Weather Research and Forecasting model is applied here to domains centered over southern California in early 2012 to investigate how to best assimilate single-level, above-surface observations (e.g., aircraft-based observations) as well as the relative value of various observation types. Various configurations of observation nudging are applied to a single case day to assimilate aircraft-based observations on a 3-km horizontal grid-spacing domain nested in a 9-km domain in order to determine the best nudging configuration. These results are then used to configure model experiments on 5 case days that investigate the value of the aircraft data, a local rawinsonde, and more dense surface observations. These experiments indicate substantial day- to-day variability in the forecast improvements due to inclusion of observations. Overall, the inclusion of aircraft data improves temperature and water-vapor predictions, but degrades short-term (1-6 hours h) wind forecasts. The use of local rawinsonde data improves short-term temperature and wind forecasts, but degrades water-vapor forecasts. Ingesting denser surface observations improves surface forecasts of temperature, moisture, and wind, but above the surface the results may be degraded. Further experimentation is necessary to refine the results found in this study.