Abstract:To address the challenge of graded straight-line wind warnings in fine short-term forecasting and nowcasting,this study utilizes polarimetric S-band Doppler weather radar data together with 1-h maximum wind observations to analyze 40 convective wind events triggered by isolated severe storms(reflectivity not lower than 60 dBZ)in the spring of 2024.The aim is to extract radar precursors and early warning indicators.These storms are categorized into two groups based on the maximum surface wind gust:the strong-wind group(Force 9-13)and the non-strong-wind group(not higher than Force 7).The results indicate that the radar signatures of strong-wind events resemble those of severe-wind-producing supercells,with the majority exhibiting persistent mesocyclones and other supercell characteristics.This indicates that the isolated storms producing strong straight-line winds are primarily supercells,with significantly higher reflectivity,vertically integrated liquid water content,mid-altitude radial convergence intensity and storm motion speed than those of the non-strong-wind group.Notably,the descent of reflectivity core is a common feature of storms and cannot distinguish the intensity of straight-line winds.About 40％of the severe wind events show a ZDR trough 42 min before the surface wind gusts,indicating that the strong downdrafts induced by the phase changes(e.g.,melting and evaporation)of hail or graupel particles represent one of the formation mechanisms for straight-line winds.A relatively continuous ZDR trough can serve as a precursor for strong straight-line winds.This study identifies the radar precursors and warning indicators,as well as their associated lead times,for isolated severe storms that produce severe straight-line winds in spring.These findings provide a scientific basis for the warning and objective algorithm design of severe straight-line winds.

Abstract:Sea fog is a phenomenon of water vapor condensation in the atmospheric boundary layer over oceanic or coastal regions.Due to its low visibility,it has a significant impact on maritime transportation,port operations and other activities.This article systematically reviews the research progress of the sea fog observations in the Yellow Sea,focusing on the analysis from two dimensions:fixed-point observation and large-scale observation.The study indicates that the Yellow Sea fog predominantly occurs in spring and summer(April-July),with its formation closely linked to low-level temperature inversions,high-humidity conditions and specific weather patterns;modern observation techniques such as millimeter-wave radar have markedly enhanced the detection accuracy of boundary layer structures,yet the systematic observations of microphysical and chemical characteristics remain inadequate.Satellite remote sensing technology enables large-scale sea fog monitoring through methods like the dual-channel difference approach and multi-band thresholding,while the integration of AI technology has further improved recognition accuracy.However,the spectral similarity between low clouds and sea fog remains a technical bottleneck.This paper also presents a dedicated observation experiment on the microphysical and chemical properties of the Yellow Sea fog,which preliminarily reveals the scavenging effect of sea fog on aerosols.Future research should strengthen three-dimensional collaborative observations,deepen studies on mechanisms of the interaction between microphysical processes and aerosols,and promote the in-depth integration of multi-source data with AI technology to enhance sea fog monitoring and forecasting capabilities.

Abstract:The atmospheric circulation during the autumn(from September to November)of 2025 was characterized by a single-pole type of polar vortex in the Northern Hemisphere and a 4-wave pattern in the middle and high latitudes.In Eurasia,the circulation pattern was flat,exhibiting a"two troughs and one ridge"pattern,and there were no significant ridges or troughs in the westerlies.A total of 13 typhoons formed in western North Pacific and the South China Sea,1.66 more than the multi-year(from 1949 to 2024)average.In addition,22 tropical cyclones were named in the world's other oceans.A total of 14 gale events of Beaufort wind force scale 8 or above occurred over China's offshore waters,including three events induced by typhoons,6 by the combined influence of typhoons and cold air,one by extratropical cyclones,three by the joint effects of cold air and cyclones,and one solely by cold air.There were 18 sea wave events with significant wave height exceeding 2.0 m,with large wave days accounting for about 74.7％of the total number of days during autumn.In autumn,the sea surface temperature(SST)in China's offshore waters was generally higher than the climatological normal.In September,the maximum positive SST anomaly occurred in the eastern Yellow Sea and the northeastern East China Sea,3-4 ℃above the climatological normal,whereas in October,the minimum SST anomaly occurred over the Bohai Sea and the Bohai Strait,less than 1 ℃ above the climatological normal.

Abstract:Based on hourly observations of marine meteorological elements from automatic weather stations and buoys,air quality monitoring data and ERA5 reanalysis data,combined with the results of the HYSPLIT trajectory model,this study analyzes the rapid formation mechanism of sea fog over the coastal waters south of the Shandong Peninsula after the influence of weak cold air.The results are as follows.(1)The sea fog event occurs during the transitional phase when the surface weak cold air is replaced by warm and moist air,and belongs to the isobaric-field advection fog type.The sea fog near the coast is also affected by radiative cooling,thus exhibiting the characteristics of advection-radiation fog.(2)The establishment of the temperature inversion layer is mainly caused by radiative cooling in the near-surface layer at night,supplemented by the warming effect of the warm advection at 975 hPa.(3)The synergistic effects of sea breeze,turbulent heat exchange and nocturnal radiative cooling promote the atmospheric cooling and moistening,providing the necessary humidity conditions for sea fog formation.Under high humidity conditions over the sea,the increased mass concentrations of aerosol particles lead to reduced visibility in offshore areas away from the coast,facilitating the development of light fog into dense fog.(4)In addition to its cooling and moistening effects,the weak cold air transports aerosol particles to the coastal waters south of the Shandong Peninsula.Meanwhile,it provides a favorable weak circulation background for the sea breeze circulation,and the sea-land breeze convergence line creates advantageous conditions for the accumulation of aerosol particles.

Abstract:Based on the real-time operation data of Central Meteorological Observatory,the best track data of China Meteorological Administration,Fengyun satellite data and conventional observing data,the characteristics of typhoon activities over western North Pacific and the South China Sea in 2025,as well as the tracks,intensities,wind and rainfall of the typhoons that had great influence on China are summarized and analyzed statistically.The analysis results are as follows.(1)A total of 27 typhoons were formed over western North Pacific and the South China Sea in 2025,1.9 more than the climate average.The averaged formation region was 3.2° further north and 5.3° further west.The averaged lifelong maximum intensity was 5.2 m·s-1 weaker.(2)The first typhoon Wutip was formed on 11 June,later than the historical average.Typhoon formation exhibited an uneven distribution,characterized by a scarcity in the early stage,a concentration in the latter stage,and active autumn typhoons.(3)A total of 10 typhoons made landfall along China's coasts,2.8 more than the climate average.The landfall locations were concentrated in the coastal areas of South China.In autumn,4 typhoons successively landed in Guangdong.The superimposed effects of strong winds and heavy rainfall caused severe disasters in the coastal areas of South China.

Abstract:This study conducts a comparative analysis between the forecast products of ECMWF(denoted as EC)and three initial field-driven forecast products,which are based on the ECMWF global model,CMA-GFS and NCEP-GFS of the Pangu-Weather Model(denoted as EC_PG,CMA_PG and NCEP_PG,collectively known as the three Pangu models).The forecast performance of the Pangu-Weather model is evaluated preliminarily against EC for surface and upper-air meteorological elements in Shandong from August to December 2024.The main results are as follows.(1)In the 2-m temperature forecast,EC_PG has the best root mean square error(RMSE)and accuracy(ACC)indexes within the 168-h forecast period.Compared with EC,the three Pangu models can effectively reduce the nighttime high forecast errors and improve the underestimation in the Shandong plains at 09:00 UTC.(2)In the 10-m wind forecast,EC_PG takes the lead in the wind speed and direction scores within the 168-h forecast period.Compared with EC,the three Pangu models can effectively reduce the nighttime high forecast errors of wind speed.The three Pangu models and EC show an overall trend of overestimation of wind speed at night and underestimation during the day.(3)In the forecast of upper-air(500 hPa,700 hPa and 850 hPa)elements,the three Pangu models outperform EC in the specific humidity forecast at each layer within the 72-h forecast period,and CMA_PG performs the best.Among the three Pangu models,EC_PG has the best performance in the temperature and wind speed forecast at each layer.Compared with EC,EC_PG has significantly improved the temperature forecast at each layer at Zhangqiu station,while its wind speed forecast at 850 hPa at Qingdao station is not as good as EC.Overall,among the three Pangu models evaluated,EC_PG has the optimal integrated forecast performance,and its forecast ability is significantly better than that of EC for key meteorological elements such as 2-m temperature,10-m wind speed and specific humidity at key layers(500 hPa,700 hPa and 850 hPa).This study provides initial ideas for systematic and comprehensive verification of artificial intelligence(AI)meteorological models in the future.

Abstract:Based on CMIP6 climate models and CN05.1 grid observation data,the simulation of the extreme temperature indices in Shandong by CMIP6 models is evaluated.Meanwhile,the changing trends of the future extreme temperature indices in Shandong under three shared socioeconomic pathways(SSPs)scenarios during different time periods in the future are predicted,and the spatiotemporal variation characteristics of the extreme temperature indices under different SSPs scenarios are explored in depth.The estimated results indicate that,compared with the base period from 1995 to 2014,the annual maximum value of daily maximum temperature(TXx)and annual minimum value of daily minimum temperature(TNn)in Shandong will show an upward trend in the future,and the warming of TNn will be more obvious than that of TXx,while both the number of frost days(FD)and icing days(ID)will show a decreasing trend.From the perspective of spatial distribution,in the future,both the highest TXx and the lowest TNn(the lowest TXx and the highest TNn)will appear in the northwestern region of Shandong(the southeastern region of Shandong and Shandong Peninsula),and the number of FD and ID will be the largest in the northern region of Shandong.

Abstract:Taking the hourly data of PM2.5 mass concentration monitored by the LGH-01E β-ray method atmospheric particulate matter monitor(hereinafter referred to as the atmospheric particulate matter monitor)in 2024 at Huanggang national basic meteorological station as the benchmark,combined with simultaneous meteorological data,this study systematically evaluates the accuracy and consistency of the observation data from the newly deployed DXC1 visual obstruction phenomenon observer(hereinafter referred to as the visual obstruction observer)at the same station.It also analyzes the impacts of climatic characteristics in different months and various meteorological factors on the differences between the observation data of the two devices.The results are as follows.(1)The monthly analysis reveals that the PM2.5 mass concentration from the visual obstruction observer and the atmospheric particulate matter monitor exhibits a consistent monthly variation characteristic of first decreasing and then increasing.Their difference is the smallest from May to August,and the maximum negative bias reaches-20.1 μg·m一3 from October to December.(2)In terms of meteorological factors,under high humidity conditions(relative humidity equal to or higher than 80％),the average error of PM2.5 mass concentration measured by the visual obstruction observer is reduced to±5 μg·m-3;under low temperature conditions(temperature equal to or lower than 4 ℃),the average error of concentration increases significantly,with a maximum of-17.6 μg·m-3 at-4 ℃;under calm winds or small wind speeds,the negative bias is large,and when the wind speed is equal to or higher than 1 m·s-1,the bias decreases rapidly;under high-pressure systems(pressure higher than 1 010 hPa),the maximum negative bias can reach-40.3μg·m-3.(3)The regression slope(0.86),intercept(7.8 μg·m-3)and absolute error(12.5 μg·m-3,when PM2.5 mass concentration equal to or lower than 100 μg·m-3)of PM2.5 mass concentration from the visual obstruction observer meet the requirements of the observer's performance indicators.When the mass concentration is higher than 100 μg·m-3,the relative error is 23.5％,which exceeds the requirements.(4)The annual average systematic error of PM2.5 mass concentration from the visual obstruction observer is-3.86 μg·m-3,which is slightly lower.In conclusion,the visual obstruction observer exhibits good data reliability,and the data quality is closely related to different weather conditions.

Abstract:The main characteristic of Typhoon Doksuri(2305)are summarized,and the difficulties in its forecast are also analyzed.The main conclusions are as follows.(1)Typhoon Doksuri is characterized by its strong landfall intensity,which,for the year 2023,is the strongest typhoon that makes landfall in China by October.Sustaining on land for a long time after landing,it breaks the historical records of wind and precipitation at multiple stations in places such as Fujian and Anhui,and brings historically extreme heavy rainfall to Huang-Huai region and North China.(2)After the genesis of Doksuri,as the circulations that affect the subtropical high are complicated,the numerical prediction of the intensity and location for the newborn tropical disturbance on the east of Doksuri has deviations,which is responsible for the track forecast errors.(3)The formation of double eyewall structure before Doksuri lands increases the difficulty of predicting the landfall intensity,while the favorable circulations and the application of multiple observations are supportive of the typhoon intensity prediction.(4)The sustainable water vapor transport from the southwest monsoon and Typhoon Khanun(2306),the terrain effect of Taihang Mountain,and the weak vertical wind shear along the typhoon track jointly help the tropical depression maintain for a long time after Doksuri makes landfall.

Abstract:Typhoon Doksuri(2305)is the second strongest typhoon landing in Fujian from 1949 to September 2023,causing extreme heavy precipitation in Fujian.In this paper,the main characteristics of the extreme precipitation in Fujian are analyzed using multi-source observation data such as dual-polarization radar and FY-4A satellite data.It is found that the two obvious precipitation stages are caused by typhoon eyewall/inner spiral rain band and outer spiral rain band,respectively.The meso-β scale convective cloud in the eyewall of Typhoon Doksuri is mainly characterized by large raindrops after landing.The convective cloud splits,goes into the inner spiral rain band,and organizes into a linear convective system,with large raindrops of higher number density causing extreme hourly rainfall.After Typhoon Doksuri moves out of Fujian,the mesoscale convective system along the outer spiral rain band continuously affects the coastal areas of Fujian through the train effect,causing extreme precipitation.The high-concentration of small raindrops is the main cloud microphysical feature.The spatial distribution of precipitation is closely related to the topography such as Jiufeng Mountain and Daiyun Mountain.The trumpet-shaped topography of sea-land interface contributes to the forming of the extreme precipitation center.

Abstract:Using the data such as the CM A(China Meteorological Administration)Tropical Cyclone Best Track Dataset,an analysis and review are conducted on the main characteristics of the typhoon activities in western North Pacific and the South China Sea in 2022,focusing on the tracks,intensities,and wind and rainfall impacts of the typhoons on China.The results are as follows.In 2022,the number of typhoons generated in western North Pacific and the South China Sea is consistent with the annual average,and the overall intensity of typhoons is relatively weak with significant northward shifts in their genesis regions.The number of landfalling typhoons is less,and their intensities upon landfall are comparatively weak.Three typhoons make landfall concentratedly in the western part of Guangdong,and the severe typhoon Muifa has become the first to make landfall in 4 different provinces since 1949.The multiple typhoon coexisting scenarios occur throughout the year with a total of 11 typhoon groups,which is a rare phenomenon.The typhoon-related disasters in 2022 exert relatively mild impacts,the summer of 2022 experiences less typhoons,while the autumn is characterized by intense typhoon activities.