A cloud resolving 4-dimensional variational data assimilation system (4DVAR) based on the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) is under development. One of the targets of this system is the analysis of mesoscale convective systems. Features of background error statistics for the model with a horizontal resolution of 2km (hereinafter abbreviated as 2km model) are much different from those with a 5km resolution (5km model). Thus, forecast error estimated by the scale-down method from that forecast error obtained from the 5km model was not applicable. To develop the cloud resolving system, background error statistics for the system with 2km horizontal intervals were calculated and a suitable set of control variables was designed. Using the new background error statistics and the new control variable set, a preliminary data assimilation experiment of the Global Positioning System (GPS)-derived precipitable water vapor (PWV) and radial wind observed by Doppler radars (RW) was performed. By assimilating GPS-PWV and RW, the convergence of horizontal wind was strengthened, and observed features of horizontal winds and PWV were reproduced in the analyzed field.
This study conducted data assimilation experiments using the operational mesoscale four-dimensional variational data assimilation (4D-Var DA) system for Mesoscale Model (MSM) and three-dimensional variational data assimilation (3D-Var DA) system for Non-hydrostatic Model (NHM) of the Japan Meteorological Agency (JMA). Experiments investigated the impacts of GPS-derived water vapor and Doppler radar-derived radial wind (RW) on precipitation prediction for a heavy rain event on 21 July 1999. Mesoscale model (MSM) is a hydrostatic model with the horizontal grid interval of 10 km. If the only conventional meteorological data was assimilated into MSM, precipitation regions were generated over a mountainous area far from Tokyo. If GPS-derived water vapor data, RW data, and conventional data were all simultaneously assimilated, the precipitation position was modeled correctly, and precipitation onset occurred as observed. However, the intensity of the precipitation was much weaker than observed one. The fields obtained by MSM-4DVar DA system were used as the initial condition of NHM, which was expected to improve intensity of precipitation. However, the convections over the southern Kanto were not reproduced. To strengthen updraft, RW data was further assimilated by NHM-3DVar DA system. The convective cells were also considered by saturating water vapor at intense updraft grids within the precipitation region. Evolution of the precipitation system was considered by introducing rain water, snow estimated from observed reflectivity fields, and relative humidity (RH) at the grids of downdraft within the precipitation region. From this modified condition, intense convective system was well reproduced by NHM.
Conference Committee Involvement (3)
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions III
14 October 2010 | Incheon, Korea, Republic of
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions II
19 November 2008 | Noumea, New Caledonia
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions