Data Assimilation of GPS Precipitable Water Vapor into the JMA Mesoscale Numerical Weather Prediction Model and its Impact on Rainfall Forecasts

Abstract

Precipitable water vapor (PWV), which was obtained from the nation wide GPS (Global Positioning System) network over Japan, operated by the Geographical Survey Institute (GSI), was assimilated into the meso data assimilation (DA) system of the Japan Meteorological Agency (JMA). Two different methods were examined; one is an optimum interpolation (OI) method, and the other is a 4-dimensional variational (4D-Var) method. Using the analysis data derived from both systems, a number of forecast experiments for rainfall events in Baiu and summer seasons were carried out using the JMA meso scale numerical weather prediction model (MSM). Remarkable improvements in rainfall forecast were seen in several cases, both for the OI and 4D-Var experiments. A statistical score of the 4D-Var experiments, however, showed that the impact of GPS PWV was almost neutral for rainfall forecast, and no substantial improvements were obtained. One of the reasons might be that GPS sites used for the experiments were too few, and sparsely distributed compared to the rainfall systems. Another reason specific for the 4D-Var is that, although the 4D-Var improved PWV analyses, it sometimes modified vertical profiles of water vapor significantly, which brought about different static stability from the first guess of the model (MSM) or from the observations. These results suggested the importance of correct assimilation of vertical profiles of water vapor.