Four-Dimensional Variational Data Analysis of Water Vapor Raman Lidar Data and Their Impact on Mesoscale Forecasts

Abstract

Abstract The impact of water vapor observations on mesoscale initial fields provided by a triangle of Raman lidar systems covering an area of about 200 km × 200 km is investigated. A test case during the Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH-2005) was chosen. Evaluation of initial water vapor fields derived from ECMWF analysis revealed that in the model the highly variable vertical structure of water vapor profiles was not recovered and vertical gradients were smoothed out. Using a 3-h data assimilation window and a resolution of 10–30 min, continuous water vapor data from these observations were assimilated in the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) by means of a four-dimensional variational data analysis (4DVAR). A strong correction of the vertical structure and the absolute values of the initial water vapor field of the order of 1 g kg−1 was found. This occurred mainly upstream of the lidar systems within an area, which was comparable with the domain covered by the lidar systems. The correction of the water vapor field was validated using independent global positioning system (GPS) sensors. Much better agreement to GPS zenith wet delay was achieved with the initial water vapor field after 4DVAR. The impact region was transported with the mean wind and was still visible after 4 h of free forecast time.