Assimilation of GNSS and Synoptic Data in a Convection Permitting Limited Area Model: Improvement of Simulated Tropospheric Water Vapor Content

The assimilation of observations in limited area models (LAMs) allows to find the best possible estimate a region’s meteorological state. Water vapor is crucial constituent terms cloud and precipitation formation. Its highly variable nature space time often insufficiently represented models. This study investigates improvement simulated water content within Weather Research Forecasting model (WRF) every season by assimilating temperature, relative humidity, surface pressure obtained from climate stations, as well geodetically derived Zenith Total Delay (ZTD) precipitable (PWV) data global navigation satellite system (GNSS) ground stations. In four case studies we analyze results high-resolution convection-resolving WRF simulations (2.1 km) between 2016 2018 each for 650 × 670 km domain tri-border-area Germany, France Switzerland. impact 3D VAR different variables combinations thereof, background error option, temporal spatial resolution evaluated. Both column values profiles radiosondes are addressed. Best outcome was achieved when ZTD synoptic at an hourly thinning distance 10 km. It concluded that careful selection options can additionally improve simulation season. Clear effects on budgets also be seen.