In this study, three typical and most extreme precipitation events in the history of North China are analyzed and compared in terms of accumulated precipitation and synoptical circulation using surface station observations of China and the ERA5 dataset. The three events happened in August 1963 (“63.8” event, hereafter), August 1975 (“75.8” event), and July 2021 (“21.7” event), respectively, mainly in Hebei and Henan Provinces of North China. The results show that the maximum daily and 4-day accumulated precipitation of all three events exceeded 500 mm and 800 mm, with many stations’ daily precipitation ranking Top 1. The “63.8” event persisted for the longest time, affected the largest area, and rained the most in 7 days (over 1000 mm). The “75.8” event was characterized by the most extreme daily precipitation and a concentrated area. All three events characterize a normal northward subtropical high that was located in North China and Northeast China. At 500 hPa, the area from South China to the South China Sea was dominated by a uniform pressure field. In the upper levels, there were troughs and divergence anomalies in all three events. In the low levels, there were anomalous low-level jets and the associated water vapor flux anomalies, which were located at different levels and came from different directions. Stable synoptical circulation and persistent jet and water vapor flux anomalies are the key factors in these extreme events.

In order to meet the high demand for advanced weather forecasts in the 2022 Olympic and Paralympic Winter Games, hourly wind observation data of some venues in Zhangjiakou City  is analyzed. Based on the specific gust characteristics in these venues, deviation of numerical weather prediction model is initially calculated to demonstrate the systematic bias of instantaneous wind speed forecasts derived from ECMWF. Additionally, a statistical down scaling method is further used by establishing the relationship between model forecasts and observation. Then independent samples are imported to the established equations to generate revised outputs. Tests show that the established equations have a better effect on forecasting the instantaneous wind speed than original model outputs and the corrected outputs have significantly better accuracy in predicting the instantaneous wind speed in the studied area.

The ECMWF (European Centre for Medium-Range Weather Forecasts) precipitation type forecast products—PTYPE are verified using the weather observations of more than 2000 stations in China of the past three winter half years (October to next March). The products include the deterministic forecast from High-resolution model (HRE) and the probability forecast from ensemble prediction system (EPS). Based on the verification results, optimal probability thresholds approaches under criteria of TS maximization (TSmax), frequency match (Bias1) and HSS maximization (HSSmax) are used to improve the deterministic precipitation type forecast skill. The researched precipitation types include rain, sleet, snow and freezing rain.The verification results show that the proportion correct of deterministic forecast of ECMWF high-resolution model is mostly larger than 90% and the TSs of rain and snow are high, next is freezing rain, and the TS of sleet is small indicating that the forecast skill of sleet is limited. The rain and snow separating line of deterministic forecasts show errors of a little south in short-range and more and more significant north following elongating lead times in medium-range. The area of sleet forecasts is smaller than observations and the freezing rain is bigger for the high-resolution deterministic forecast. The ensemble prediction system offsets these errors partly by probability forecast. The probability forecast of rain from the ensemble prediction system is smaller than the observation frequency and the probability forecast of snow is larger in short-range and smaller in medium-range than the observation frequency. However, there are some forecast skills for all of these probability forecasts. There are advantages of ensemble prediction system compared to the high-resolution deterministic model. For rain and snow, for some special cost/loss ratio events the EPS is better than the HRD. For sleet and freezing rain, the EPS is better than the HRD significantly, especially for the freezing rain.The optimal thresholds of snow and freezing rain are largest which are about 50%~90%, decreasing with elongating lead times. The thresholds of rain are small which are about 10%~20%, increasing with elongating lead times. The thresholds of sleet are the smallest which are under 10%. The verifications show that the approach of optimal probability threshold based on EPS can improve the forecast skill of precipitation type. The proportion correct of HRD is about 92%. Bias1 and TSmax improve it and the improvement of HSSmax is the most significant which is about 94%. The HSS of HRD is about 0.77~0.65. Bias1 increases 0.02 and TSmax increases more. The improvement of HSSmax is the biggest which is about 0.81~0.68 and the increasing rate is around 4%. From the verifications of every kinds of precipitation types, it is demonstrated that the approach of optimal probability threshold improves the performance of rain and snow forecasts significantly compared to the HRD and decreases the forecast area and missing of freezing rain and sleet which are forecasted more areas and false alarms by the HRD.Key words: ECMWF; ensemble prediction system；precipitation type forecast; approach of optimal probability threshold; verification