Four-Dimensional Variational Assimilation of Total Column Water Vapor in Rainy Areas

Abstract

This paper studies the impact of assimilating rain-derived information in the European Centre for Medium-Range Weather Forecasts (ECMWF) four-dimensional variational (4DVAR) system. The approach is based on a one-dimensional variational (1DVAR) method. First, model temperature and humidity profiles are adjusted by assimilating observed surface rain rates in 1DVAR. Second, 1DVAR total column water vapor (TCWV) estimates are assimilated in 4DVAR. Observations used are Tropical Rainfall Measuring Mission (TRMM) surface rain-rate estimates from the TRMM Microwave Imager. Two assimilation experiments making use of 1DVAR TCWV were run for a 15-day period. The ?Rain-1? experiment only assimilates 1DVAR retrievals where the observed rain rate is nonzero while the ?Rain-2? experiment assimilates all 1DVAR TCWV estimates. The period selected includes Hurricane Bonnie, which was well sampled by TRMM (late August 1998). Results show a positive impact on the humidity analysis of assimilating 1DVAR TCWV in 4DVAR. The model rain rates at the analysis time are closer to the TRMM observations showing a posteriori the consistency of the two-step approach chosen to assimilate rain-rate information in 4DVAR. The modification of the humidity analysis induces changes in the wind and pressure analysis. In particular the analysis of the track of Hurricane Bonnie is noticeably improved for the early stage of the storm development for both the Rain-1 and Rain-2 experiments. When Bonnie is in a mature stage the influence of the 1DVAR TCWV assimilation is to intensify the hurricane. Comparison with Clouds and the Earth's Radiant Energy System (CERES) measurements also show a neutral impact on the radiative fluxes at the top-of-the atmosphere when using 1DVAR TCWV estimates. The impact on the forecasts is a slight reduction of the model precipitation spindown over tropical oceans. Objective scores for the Tropics are improved, particularly for wind and for upper-tropospheric temperature. Analysis and forecast results are generally better for the Rain-2 experiment compared to Rain-1, implying that the 1DVAR TCWV estimates retrieved where no rain is observed provide useful information to 4DVAR.