Tohru Kuroda

A Cloud-Resolving 4DVAR Assimilation Experiment for a Local Heavy Rainfall Event in the Tokyo Metropolitan Area

AbstractA cloud-resolving nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) was modified to directly assimilate radar reflectivity and applied to a data assimilation experiment using actual observations of a heavy rainfall event. Modifications included development of an adjoint model of the warm rain process, extension of control variables, and development of an observation operator for radar reflectivity.The responses of the modified NHM-4DVAR were confirmed by single-observation assimilation experiments for an isolated deep convection, using pseudo-observations of rainwater at the initial and end times of the data assimilation window. The results showed that the intensity of convection could be adjusted by assimilating appropriate observations of rainwater near the convection and that undesirable convection could be suppressed by assimilating small or no reflectivity.An assimilation experiment using actual observations of a local heavy rainfall in the Tokyo, Japan, metropo...

Forecasting a Large Number of Tropical Cyclone Intensities around Japan Using a High-Resolution Atmosphere-Ocean Coupled Model

AbstractThis work quantifies the benefits of using a high-resolution atmosphere–ocean coupled model in tropical cyclone (TC) intensity forecasts in the vicinity of Japan. To do so, a large number of high-resolution calculations were performed by running the Japan Meteorological Agency (JMA) nonhydrostatic atmospheric mesoscale model (AMSM) and atmosphere–ocean coupled mesoscale model (CMSM). A total of 281 3-day forecasts were compiled for 34 TCs from April 2009 to September 2012 for each model. The performance of these models is compared with the JMA global atmospheric spectral model (GSM) that is used for the operational TC intensity guidance. The TC intensities are better predicted by CMSM than the other models. The improvement rates in CMSM relative to GSM and AMSM generally increase with increasing forecast time (FT). CMSM is better than GSM and AMSM by 27.4% and 21.3% at FT = 48 h in terms of minimum sea level pressure, respectively. Regarding the maximum wind speed, CMSM is better than GSM and AMSM...

Development of a cloud-resolving 4DVAR data assimilation system based on the JMA nonhydrostatic model

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.