The vertical distributions of the water vapor mixing ratio (w) were measured by Raman lidar at the Meteorological Research Institute, Japan, in 2000 to 2004. The measured values were compared with those obtained with radiosondes, hygrometers on the meteorological observation tower, and Global Positional System (GPS) antennas. The values of w obtained with the lidar agreed within 9% with those obtained with the Meisei RS2-91 radiosonde for w > 0.5 g/kg-1. However, they were systematically higher than those obtained with the Vaisala RS80-A radiosonde for that region. The vertical variations of w obtained with the lidar were similar to those obtained with the Meisei RS-01G and Meteolabor Snow White radiosondes for w > 0.3 g/kg-1. The temporal variations of w obtained with the lidar were similar to those obtained with the hygrometers at heights between 50 and 213 m on the tower, although the absolute values differed systematically due to the incomplete overlap of the laser beam and the receiver's field of view at the lower heights. The precipitable water vapor content obtained with the lidar generally agreed with those obtained with GPS, except for the period when the large spatial inhomogeneity of w was present.
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.
A profile of temperature and relative humidity retrieved from Mt. Fuji observed GPS “Downward Looking (DL)” data was assimilated into mesoscale weather prediction model by using four-dimensional variational data assimilation (4D-var) procedure for typhoon case of September 9, 2001. The DL observation offered the profile of the atmosphere over the ocean where typhoon approached. Because the retrieved case was few, the observation error was expediently decided as 1 centigrade for temperature and 4 percent for relative humidity without a statistical investigation. The assimilation results show a small but positive impact for precipitation forecast. But the position of the typhoon center in the initial field slightly shifted to the opposite direction from the best track analysis by the Japan Meteorological Agency (JMA). To decide observation error of DL retrieved refractive index profile, error estimation using a three-dimensional (3D) ray-tracing model which uses mesoscale weather model outputs was executed. The 3D ray-tracing model simulated propagation of GPS signal in the model atmosphere every one-second. Then, Doppler shift, bending angle, partial bending angle (PBA), and finally refractive index profile were retrieved. It was proven that PBAs are able to reproduce from Doppler shift in high accuracy. Error of retrieved refractive index showed high correlation with horizontal variation of refractive index. The results suggest that we should assimilate bending angle or excess phase delay rather than profile of retrieved refractive index, temperature and humidity.
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