A Simulation Study on the Clouds Microphysical Processes of Heavy Precipitation in Hebei Area Caused by"Lekima"

During the period of the super typhoon"Lekima"(No.1909)landed on the coast of North China,a high-resolution numerical simulation study was carried out with the WRF model on the clouds microphysical process of heavy precipitation.The results showed that(1)the water vapor convergence tended to develop and strengthen on the way forward of typhoon center,and the evolution of water vapor convergence zone was closely related to the development of typhoon asymmetric structure,and had a good corresponding relationship with the falling zone of the rainstorm.(2)The eastern coast of Hebei was located in the big-value area of water vapor transport belt in the northwest quadrant of the typhoon.Below 850 hPa,northeast wind appeared,and warm humid water vapor was transported from marine area to terrestrial by typhoon.Affected by upper-level westerly trough,westerly wind was dominated above 700 hPa,and water vapor convergence was transported from low level to upper level,and several rainstorm center appeared.(3)In the spiral rain bands of typhoon,the big-value center of graupel particles cooperated with the warm cloud enriched with water content,and the ground would produce a center of heavy precipitation,and the precipitation center of pure warm cloud appeared in 117.5°E.This phenomenon rarely occurred during continental cloud precipitation.Therefore,the contribution of warm cloud precipitation mechanism to the typhoon spiral rain belt should be emphasized.

Quantitative Precipitation Estimation Using X-band Phased Array Weather Radar

This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Area from 20:00 on August 21 to 07:00 on August 22,2022.The analysis applied the Z-R relationship method for radar-based precipitation estimation and evaluated the QPE algorithm s performance using scatter density plots and binary classification scores.The results indicated that the QPE algorithm accurately estimates light to moderate rainfall but significantly underestimates heavy rainfall.The study identified disparities in the predictive accuracy of the QPE algorithm across various precipitation intensity ranges,offering essential insights for the further refinement of QPE techniques.

Machine Learning-Based Temperature and Wind Forecasts in the Zhangjiakou Competition Zone during the Beijing 2022 Winter Olympic Games

Weather forecasting for the Zhangjiakou competition zone of the Beijing 2022 Winter Olympic Games is a challenging task due to its complex terrain.Numerical weather prediction models generally perform poorly for cold air pools and winds over complex terrains,due to their low spatiotemporal resolution and limitations in the description of dynamics,thermodynamics,and microphysics in mountainous areas.This study proposes an ensemble-learning model,named ENSL,for surface temperature and wind forecasts at the venues of the Zhangjiakou competition zone,by integrating five individual models—linear regression,random forest,gradient boosting decision tree,support vector machine,and artificial neural network(ANN),with a ridge regression as meta model.The ENSL employs predictors from the high-resolution ECMWF model forecast(ECMWF-HRES) data and topography data,and targets from automatic weather station observations.Four categories of predictors(synoptic-pattern related fields,surface element fields,terrain,and temporal features) are fed into ENSL.The results demonstrate that ENSL achieves better performance and generalization than individual models.The root-mean-square error(RMSE) for the temperature and wind speed predictions is reduced by 48.2% and 28.5%,respectively,relative to ECMWF-HRES.For the gust speed,the performance of ENSL is consistent with ANN(best individual model) in the whole dataset,whereas ENSL outperforms on extreme gust samples(42.7% compared with 38.7% obtained by ECMWF-HRES in terms of RMSE reduction).Sensitivity analysis of predictors in the four categories shows that ENSL fits their feature importance rankings and physical explanations effectively.

Aircraft Observation Analysis on Stratiform Cloud Structure near a Low Trough - Inverted Trough

An aircraft precipitation operation and detecting was implemented by Hebei Weather Modification Office over Shijiazhuang City during18:18-19:37 on April 2,2014. The detecting area was near 500 hP a of high-altitude trough and surface inverted trough. Slight shower had appeared in Tianjin( rear of inverted trough) and Shanxi Province( near the inverted trough) at 20:00,while there was not precipitation in Hebei Province which was near the inverted trough. Analysis showed that the water vapor supply was not enough below 550 hP a in south-central Hebei Province,and cloud system development condition was poor. The cold cloud developed better,but there was not warm cloud,causing no precipitation on the ground.