![]() ![]() Assimilating the ground-based microwave radiometer data into WRF had a positive impact on the prediction of temperature and humidity analyses, whereas the impact on precipitation accumulation forecasts was more obvious. For example, Vandenberghe and Ware (2002) assimilated the temperature and humidity profile data of the single station ground-based microwave radiometer into MM5, effectively improved the prediction of winter fog. However, the assimilation of the microwave radiometers into numerical weather prediction systems has been limited to a few sporadic attempts. The ground-based microwave radiometer observations have been playing an increasingly important role in numerical weather prediction systems. Among multiple cycle experiments, the onset of 0600 UTC cycle closest to the beginning of rainfall performed best by assimilating the ground-based microwave radiometer profiles. The assimilation of the ground-based microwave radiometer profiles improved the skills of the quantitative precipitation forecast to a certain extent. Thus, assimilating MWRPS improved the skills of the precipitation forecast in both the distribution and the intensity of rainfall precipitation, capable of predicting the process of belt-shaped radar echo splitting and the precipitation bifurcation in the urban area of Beijing. The results show that in comparison with the Control test, the MWRPS test made reasonable adjustments for the thermal conditions in time, better reproducing the weak heat island phenomenon in the observation prior to the rainfall. The Control experiment only assimilated conventional observations and radar data, while the microwave radiometers profilers (MWRPS) experiment assimilated conventional observations, the ground-based microwave radiometer profiles and radar data into the RMAPS-ST model. For this purpose, two experiments were set. The precipitation bifurcation prediction that occurred in Beijing on was selected as a case to evaluate the impact of their assimilation. In this study, the temperature and relative humidity profiles retrieved from five ground-based microwave radiometers in Beijing were assimilated into the rapid-refresh multi-scale analysis and prediction system-short term (RMAPS-ST).
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