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This study evaluated the simulation performance of mesoscale convective system (MCS)-induced precipitation, focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula. The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP) analysis data, as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model. Particularly, temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data. Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis, which exhibited a cold and dry bias in the lower levels below 850 hPa. The model, in terms of the precipitation simulations, particularly for high-intensity precipitation over the Yellow Sea, demonstrated higher accuracy when applying ECMWF analysis data as the initial condition. This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features (i.e., warm and humid lower-level atmosphere) over the Yellow Sea. In conclusion, this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data. Furthermore, it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future. [ABSTRACT FROM AUTHOR]

Focusing on the role of initial condition uncertainty, we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone (TC) Rammasun (1409), which is the strongest TC to have made landfall in China during the past 50 years. Forecast results indicate that initial condition uncertainty leads to TC forecast uncertainty, particularly for TC intensity. This uncertainty increases with forecast time, with a more rapid and significant increase after 24 h. The predicted TC develops slowly before 24 h, and at this stage the TC in the member forecasting the strongest final TC is not the strongest among all members. However, after 24 h, the TC in this member strengthens much more than that the TC in other members. The variations in convective instability, precipitation, surface upward heat flux, and surface upward water vapor flux show similar characteristics to the variation in TC intensity, and there is a strong correlation between TC intensity and both the surface upward heat flux and the surface upward water vapor flux. The initial condition differences that result in the maximum intensity difference are smaller than the errors in the analysis system. Differences in initial humidity, and to a lesser extent initial temperature differences, at the surface and at lower heights are the key factors leading to differences in the forecasted TC intensity. These differences in initial humidity and temperature relate to both the overall values and distribution of these parameters. [ABSTRACT FROM AUTHOR]

Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associated cloud simulation on temporal and spatial scales becomes an important issue. We report a cloudresolving modeling analysis on this issue by comparing the control experiment with experiments perturbed by initial temperature, water vapor, and cloud conditions. The simulation is considered to be accurate only if the root-mean-squared difference between the perturbation experiments and the control experiment is smaller than the standard deviation. The analysis may suggest that accurate precipitation and cloud simulations cannot be obtained on both fine temporal and spatial scales simultaneously, which limits quantitative precipitation forecasting. The accurate simulation of water vapor convergence could lead to accurate precipitation and cloud simulations on daily time scales, but it may not be beneficial to precipitation and cloud simulations on hourly time scales due to the dominance of cloud processes. [ABSTRACT FROM AUTHOR]

Impacts of initial conditions on cloud-resolving model simulations are investigated using a series of sensitivity experiments. Five experiments with perturbed initial temperature, moisture, and cloud conditions are conducted and compared to the control experiment. The model is forced by the large-scale vertical velocity and zonal wind observed and derived from NCEP/Global Data Assimilation System (GDAS). The results indicate that model predictions of rainfall are much more sensitive to the initial conditions than those of temperature and moisture. Further analyses of the surface rainfall equation and the moisture and cloud hydrometeor budgets reveal that the calculations of vapor condensation and deposition rates in the model account for the large sensitivities in rainfall simulations. [ABSTRACT FROM AUTHOR]