多波長マイクロ波放射計データの直接的データ同化とTOGA COARE領域でのメソ数値予報モデルへのインパクトについて

Abstract

Direct assimilation using 1-dimensional variational method in the vertical (1D-VAR) was developed to incorporate vertically polarized brightness temperatures (TB's), and rain flag data (index of existence of precipitation) from the special sensor microwave imager (SSM/I), into a mesoscale numerical weather prediction (NWP) model. We used a radiative transfer model (RTM) developed by Liu (1998) to calculate TB's from NWP model variables. Observational residuals of TB's are assumed to be nonlinear functions of precipitation rates in rainy areas, and of other thermodynamic variables in rain-free areas. Quasiequilibrium assumptions on humidity and convective instability in model precipitation areas are used to assimilate TB's in rainy areas and rain flag data, which are functions of precipitation. TB's in rain-free areas are assimilated into total water content (cloud water content + humidity). Smith's method (1990) is used to calculate cloud water content and humidity from total water content. To simplify 1D-VAR, the following approximations are introduced: 1) In the tropics, variations in temperature are much smaller than variations in humidity. 2) Variations in divergence dominates the rainy areas, compared to vorticity and mass variables. Based on the above approximation, we assumed that the background error covariance of relative vorticity and the unbalanced component of mass variables is negligible, so we divided 1D-VAR into that for total water content and that for divergence. Newtonian iteration is used to solve these 1D-VAR problems. To study the assimilated variables, assimilation was applied to cases during 19-20 Dec. 1992 over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) domain. Results indicate: 1) Precipitable water content (PWC) obtained by assimilation agreed well with PWC calculated from radiosonde data and PWC retrieved from TB's using Shibata's algorithm (1994). 2) Consistency between humidity and cloud water content profiles was attained by Smith's method (1990), although no significant improvement was seen in humidity profile accuracy by assimilation. 3) Assimilation of rain flag and TB's in rainy areas successfully produced model precipitation areas agreeing with radar observation data by Short et al. (1997). To test the impact of assimilation on NWP forecasts, experiments were conducted assimilating TB data for 19 Dec. 1992. Results indicate: 1) Assimilation modified large-scale model humidity distribution, improving large-scale humidity and precipitation forecasts for 48 hours. 2) Assimilation of rain flag and TB's in rainy areas reduced spin-up error of precipitation and positional error of mesoscale precipitation patterns. 3) The boundary between subtropical northeasterly, and equatorial weak wind areas, shifted with the change in model precipitation areas by assimilation.