A Numerical Study on Forecasting the Henan Extraordinarily Heavy Rainfall Event in August 1975

This study is essentially an experiment on the control experiment in the August 1975 catastrophe which was the heaviest rainfall in China's Mainland with a maximum 24-h rainfall of 1060.3 mm, and it significantly demonstrates that the limited area model can still skillfully give reasonable results even only the conventional data are available. For such a heavy rainfall event, a grid length of 90 km is too large while 45 km seems acceptable. Under these two grid sizes, the cumulus parameterization scheme is evidently superior to the explicit scheme since it restricts instabilities such as CISK to limited extent. The high resolution scheme for the boundary treatment does not improve forecasts significantly.The experiments also revealed some interesting phenomena such as the forecast rainfall being too small while affecting synoptic system so deep as compared with observations. Another example is the severe deformation of synoptic systems both in initial conditions and forecast fields in the presence of complicated topography. Besides, the fixed boundary condition utilized in the experiments along with current domain coverage set some limitations to the model performances.

Experiments with the Improved Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation over South China

In recent work,three physical factors of the Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation(DSAEF_LTP model)have been introduced,namely,tropical cyclone(TC)track,TC landfall season,and TC intensity.In the present study,we set out to test the forecasting performance of the improved model with new similarity regions and ensemble forecast schemes added.Four experiments associated with the prediction of accumulated precipitation were conducted based on 47 landfalling TCs that occurred over South China during 2004-2018.The first experiment was designed as the DSAEF_LTP model with TC track,TC landfall season,and intensity(DSAEF_LTP-1).The other three experiments were based on the first experiment,but with new ensemble forecast schemes added(DSAEF_LTP-2),new similarity regions added(DSAEF_LTP-3),and both added(DSAEF_LTP-4),respectively.Results showed that,after new similarity regions added into the model(DSAEF_LTP-3),the forecasting performance of the DSAEF_LTP model for heavy rainfall(accumulated precipitation≥250 mm and≥100 mm)improved,and the sum of the threat score(TS250+TS100)increased by 4.44%.Although the forecasting performance of DSAEF_LTP-2 was the same as that of DSAEF_LTP-1,the forecasting performance was significantly improved and better than that of DSAEF_LTP-3 when the new ensemble schemes and similarity regions were added simultaneously(DSAEF_LTP-4),with the TS increasing by 25.36%.Moreover,the forecasting performance of the four experiments was compared with four operational numerical weather prediction models,and the comparison indicated that the DSAEF_LTP model showed advantages in predicting heavy rainfall.Finally,some issues associated with the experimental results and future improvements of the DSAEF_LTP model were discussed.

Analysis of a Heavy Rainfall Event over Beijing During 21-22 July2012 Based on High Resolution Model Analyses and Forecasts

The heaviest rainfall over 61 yr hit Beijing during 21-22 July 2012.Characterized by great rainfall amount and intensity,wide range,and high impact,this record-breaking heavy rainfall caused dozens of deaths and extensive damage.Despite favorable synoptic conditions,operational forecasts underestimated the precipitation amount and were late at predicting the rainfall start time.To gain a better understanding of the performance of mesoscale models,verification of high-resolution forecasts and analyses from the WRFbased BJ-RUCv2.0 model with a horizontal grid spacing of 3 km is carried out.The results show that water vapor is very rich and a quasi-linear precipitation system produces a rather concentrated rain area.Moreover,model forecasts are first verified statistically using equitable threat score and BIAS score.The BJ-RUCv2.0forecasts under-predict the rainfall with southwestward displacement error and time delay of the extreme precipitation.Further quantitative analysis based on the contiguous rain area method indicates that major errors for total precipitation（〉 5 mm h^（-1）） are due to inaccurate precipitation location and pattern,while forecast errors for heavy rainfall（〉 20 mm h^（-1）） mainly come from precipitation intensity.Finally,the possible causes for the poor model performance are discussed through diagnosing large-scale circulation and physical parameters（water vapor flux and instability conditions） of the BJ-RUCv2.0 model output.

Super-Parameterization in GRAPES: The Construction of SP-GRAPES and Associated Preliminary Results

Super-parameterization（SP） aims to explicitly represent deep convection within a coarse resolution global model by embedding a cloud resolving model（CRM） in each column of the mother model. For the first time, we implemented the SP in a mesoscale regional weather model, the Global/Regional Assimilation and Pr Ediction System（GRAPES）. The constructed SP-GRAPES uses a two-dimensional（2D） CRM in each grid column. A control and two SP simulations are conducted for the Beijing ＂7.21＂ heavy rainfall event to evaluate improvements in GRAPES using SP. The SP-run-I is a basic SP run delivering microphysics feedback only, whereas the SP-run-II delivers both microphysical and cloud fraction feedbacks. A comparison of the runs indicates that the SP-run-I has a slightly positive impact on the precipitation forecast than the control run. However, the inclusion of cloud fraction feedback leads to an evident overall improvement, particularly in terms of cloud fraction and 24-h cumulative precipitation. Although this is only a preliminary study using SP-GRAPES, we believe that it will provide considerable guidance for follow-up studies using SP in China.