Assimilation of horizontal line-of-sight winds with a mesoscale EnKF data assimilation system

This paper compares the horizontal line-of-sight (HLOS) wind observations with a single wind component and full wind information in a limited-area domain over Europe and the North Atlantic. The motivation for the study is the forthcoming Aeolus mission of the European Space Agency which will provide vertical profiles of HLOS winds. A new observing system simulation experiment framework was developed using the Data Assimilation Research Testbed (DART) ensemble adjustment Kalman filter (EAKF) data assimilation with the Weather Research and Forecasting (WRF) model at a horizontal resolution of 15 km. The 50-member EAKF/WRF is nested in the operational 50-member ensemble prediction system of ECMWF (ENS) using model-level data available twice per day. The ensemble spread at lateral boundaries provided by ENS, especially in the North Atlantic, is shown to be sufficient to carry out experiments without covariance inflation. Results show that the information content of HLOS winds is on average divided linearly between the zonal and meridional wind components depending on the observation azimuth. In areas of significant covariances such as fronts in the Atlantic, multivariate covariance information provides significant useful analysis increments from the HLOS wind observations, especially if observations are aligned along the front. The application of the spatially and temporally adaptive prior inflation improved all scores compared with the case without inflation.