Abstract:There are two types of sea fog affecting the Shandong Peninsula's southern shore,namely widespread sea fog and coastal sea fog.Although the coastal sea fog predominantly causes considerable interruptions to port operations and coastal activities,existing studies on this phenomenon remain limited and lack depth.This study aims to explore the spatio-temporal distribution patterns of the coastal sea fog events in the Shandong Peninsula's southern shore from 2008 to 2023,as well as the underlying causes,using data of coastal stations,reanalysis grid data and satellite observations.The major findings are as follows.(1)Based on the geographical spread of fog areas,we further divide the coastal sea fog into 5 types under 5 kinds of synoptic situations,and the monthly variations of each type's frequency are significantly different.(2)The spatio-temporal evolution of coastal sea fog displays significant diurnal variations.Rapidly changing synoptic systems have a substantial influence on the morphology of fog areas,while sea surface temperature and sea-air temperature difference play crucial roles in fog development under slowly changing synoptic situations.(3)Most coastal sea fog episodes are accompanied by sea-land breeze processes.There is an essential temporal correlation between the emergence of sea fog and the establishment of land breeze circulation,both of which demonstrate consistent intermonthly fluctuations.This study suggests that the sea-land breeze circulation may play an important role in the formation of coastal sea fog along the Shandong Peninsula's southern shore.To better understand this mechanism,additional research should be conducted utilizing high-resolution numerical models.

Abstract:The Northwest Pacific is one of the areas with the highest sea fog frequency globally and serves as a major shipping route.Currently,there are no dedicated sea fog prediction products for this region.Therefore,studying the characteristics and prediction of the sea fog in this area is crucial.Based on the data from International Comprehensive Ocean-Atmosphere Data Set(ICOADS)and ERA5 data from 2013 to 2023,this study analyzes the distribution characteristics of the sea fog over Northwest Pacific and develops a sea fog prediction model using the machine learning method.By calculating mutual information(MI)values,we identify 12 key factors closely related to the occurrence of sea fog,including sea surface temperature(SST),relative humidity,difference between SST and dew point temperature(tSST-td)and geographical coordinates.To address the class imbalance between fog and non-fog samples,we apply resampling techniques and assess the impacts of various sampling strategies on the model performance.The results indicate that adding geographical information as factors and applying oversampling significantly improve the model performance,and the eXtreme Gradient Boosting(XGBoost)model shows the highest threat score.The feature importance analysis indicates that the difference between SST and dew point temperature and relative humidity serve as the core factors in the sea fog prediction model.Among comparative models,the XGBoost model achieves the best overall performance,followed by the convolutional neural network(CNN)and support vector machine(SVM),and both CNN and SVM achieve a threat score above 0.3.Case studies further confirm that the XGBoost model shows the best results,demonstrating the highest agreement with the observed fog coverage.This study reveals the complexities of sea fog formation over Northwest Pacific and provides a scientific basis for sea fog prediction over open ocean areas.

Abstract:Based on observational data and multi-source reanalysis materials,this study explores the characteristics and possible influencing factors of the Siberia-Qinghai-Tibet Plateau dipole surface temperature anomaly pattern during the winter(December-February of the following year)from 1981 to 2023.The research shows the following results.(1)The Siberia-Qinghai-Tibet Plateau dipole surface temperature anomaly is observed over Asia in winter.The Siberia cold anomaly is primarily driven by cold advection resulting from weakened sub-polar westerlies under the influence of an anomalous low-pressure system over Lake Baikal.The Qinghai-Tibet Plateau warm anomaly stems from the increased short-wave radiation due to reduced cloud cover controlled by a persistent high-pressure anomaly,with additional amplification via ice/snow-albedo feedback.(2)In late autumn(October-November),the low sea ice concentration in the Barents-Kara Sea triggers an abnormal high-pressure system in the upper atmosphere by thermal action and maintains it until winter.Subsequently,the Rossby wave energy spreads to the south,which is conducive to the formation of a low-pressure anomaly over Lake Baikal.This is conducive to the occurrence of the Siberia cold anomaly and ultimately helps to form the positive phase of the Siberia-Qinghai-Tibet Plateau dipole temperature anomaly.However,the situation is the opposite when there is high sea ice concentration.(3)The positive(negative)winter precipitation anomaly over western Mediterranean Sea-northeastern Atlantic Ocean excites a negative(positive)upper-level wave source,which in turn triggers both sub-polar and sub-tropical wave trains.Contrasting pressure anomalies—low pressure(high pressure)near Lake Baikal and high pressure(low pressure)over the Qinghai-Tibet Plateau,promote the development of the positive(negative)phase of the Siberia-Qinghai-Tibet Plateau dipole temperature anomaly.This study clarifies the regulatory effects of the thermal-dynamic coupling between sea ice and the atmosphere and the remote propagation of wave energy on the Siberia-Qinghai-Tibet Plateau dipole temperature anomaly,providing a theoretical basis for predicting the interannual variations of winter temperatures in Siberia and Qinghai-Tibet Plateau.

Abstract:On 2 March 2025,an extreme rain-to-snow weather event occurred in Shandong,with daily precipitation at 53 meteorological stations exceeding the historical records in March.Based on data of vertical detection networks and meteorological stations as well as ERA5 data,this study analyzes the microphysical parameter characteristics of hydrometeor particles during the event's phase transition and summarizes the monitoring indicators using novel detection data.The results are as follows.(1)The synoptic system of the event is the Jianghuai cyclone.During the initial rainfall stage,the primary synoptic systems are upper-level trough,shear line and surface inverted trough.After it turns to easterly winds in the lower troposphere,the temperature decreases,the precipitation phase changes from rain to sleet or ice particles,and finally to pure snow.The circulation during the pure snow stage is a backflow pattern,with a cold pad in the lower troposphere and warm and humid air climbing along the cold pad in the middle and upper troposphere.When the cold pad thickens to nearly 5 km,the snowfall ends.(2)During the rainfall stage,a melting layer exists near 2 km altitude.Below this layer,the radial velocity is generally above 5 m·s-1.As the radial velocity gradually decreases,the phase transforms into sleet or ice particles.When the radial velocity drops below 2 m·s-1,the precipitation becomes pure snow.Notably,the melting layer abruptly decreases to the surface during the rain-to-snow transition,linked to the intensity of near-surface cold air intrusion,and it can be observed by dual-polarization radar,millimeter wave cloud measuring instrument and wind profile radar.Heavy snowfall stage normally corresponds to high ZH values and low ZDR values below 1 km.(3)When the precipitation phase is rain,ice particles or sleet,the joint distribution patterns of particle diameter and terminal fall velocity are similar,all approximating the empirical relationship of raindrops.After the precipitation transitions to pure snow,the particle size spectrum broadens,the particle diameter reaches its maximum,and the terminal fall velocities of most particles concentrate below 4 m·s-1.Precipitation intensity could be determined by particle concentration,spectral width and ZH.

Abstract:Typhoon Khanun(2306)undergoes two significant turning tracks in its mid-to-late life cycle,posing substantial challenges to operational forecasting.This study analyzes the causes of the two abrupt track changes and forecast deviations using the operational typhoon track data from National Meteorological Center,numerical models output and ERA5 reanalysis data.The results are as follows.During the first abrupt track change,the southwest monsoon to the south of Typhoon Khanun intensifies and shifts northward,while the western North Pacific subtropical high to its east strengthens and extends to the south of the typhoon.The combination of these factors creates a deep southwesterly steering environmental field,leading to the abrupt track change of Typhoon Khanun(stagnation near the sea followed by a westward turn).The second abrupt track change occurs due to the re-intensification and westward extension of the subtropical high to the east of Typhoon Khanun,causing it to first decelerate and then turn northward.Prior to the first abrupt track change,numerical models underestimate the intensity of the subtropical high core,leading to weaker pressure gradient and thus weaker monsoon channel winds to the south,and the rapid movement of Typhoon Khanun causes a detachment from the monsoon channel,resulting in the failure of the forecast for the first abrupt track change.During the second abrupt track change,the models overestimate the intensity of an upper tropospheric cold low to the northeast of Typhoon Khanun,suppressing the subtropical high's westward extension and inducing a failure of the forecast for the track change.The findings inspire a new approach for the subjective forecasting of typhoon tracks:by integrating the correction of typhoon's moving speed with changes in the steering flow,the typhoon's direction can be simultaneously adjusted and thus the track forecasts improve.

Abstract:To distinguish and precisely extract the information of different types of facility agriculture,this study takes the solar greenhouses and polyhouses in Weifang as the research objects using the Google Earth Engine(GEE)platform.By integrating Sentinel-1 radar data,Sentinel-2 optical data and SRTM DEM data,41 feature variables are extracted,including the features of spectrum,index,radar,texture and topography,and the optimal selection of features is conducted.By comparing 14 window scales with the cumulative difference method,the optimal texture features for Sentinel-2 imagery are identified.The experiments with 6 combinations of features are designed using the random forest classification algorithm to generate a distribution map of facility agriculture in Weifang with the resolution of 10 m in 2023,and the impacts of different combinations on the accuracy of extraction are explored.The results are outlined below.(1)The optimal window scale of the texture feature for extracting facility agriculture using Sentinel-2 is 27×27,and the best combination of texture features includes Mean,Entropy,Variance,Dissimilarity and Contrast.(2)Besides the features of spectrum and index,the features of texture,radar and topography are used to classify facility agriculture.The order of different features beneficial to extract facility agriculture from high to low is texture,topography and radar,and compared to the classification using only spectrum and index,the accuracy increases by 4.08％,1.40％and 0.80％,respectively.(3)The optimal selection of features yields the highest classification accuracy,with an overall accuracy of 91.03％and a Kappa coefficient of 0.86.The producer's accuracy and user's accuracy for polyhouses are 92.21％and 91.83％,respectively,while those for solar greenhouses are 88.54％and 89.47％,respectively.(4)The remote sensing extraction method for various facility agriculture types in Weifang using Sentinel imagery and SRTM DEM topography data offers decision-making support for disaster risk management of facility agriculture.

Abstract:Using the data of conventional observation,FY-2F satellite,S-band dual-polarization radar and ERA5 reanalysis,the circulation situations,environmental parameters,characteristics of dual-polarization parameters and triggering mechanisms of the extremely strong convection weather on 17 May 2020 in Shandong are analyzed.The results are shown below.(1)This extremely strong convective weather occurs under the background of the northeast cold vortex with the low-level jets and convective available potential energy significantly enhanced at night,the precipitable water and vertical wind shear both exceeding the threshold values in Shandong and suitable height of the 0 ℃ layer and melting level,all of which provide favorable environmental conditions for the extremely strong convection.Hails are located in the superimposed area of dryline,strong upward movement and water vapor convergence.(2)The supercell storm formed in Weifang led to the occurrence of the large hails in Changyi,Weifang and the exceptionally large hails in Pingdu,Qingdao.The rapid decrease in the vertically integrated liquid water content during the mature phase of the storm,as well as the descent of the storm top and the centroid of the storm cell,has indicative significance for the hail prediction.(3)The supercell storms that resulted in the different hail sizes between Changyi and Pingdu have distinct dual-polarization characteristics.Both have a large ZH corresponding to a small ZDR,Cc and KDP,as well as strong hail attenuation and beam non-uniform filling characteristics,ZDR arcs in the inflow region and near the mesocyclone,and higher ZDR columns in the updraft area.In comparison with the hails in Changyi,the hails in Pingdu have a larger ZH,but smaller minima of ZDR and Cc.(4)This strong convective weather process is primarily triggered by the dryline,with convective storms developing violently where the surface convergence line meets the dryline.

Abstract:In 2023,the average summer precipitation in Shandong was 414.4 mm,1.0％less than that in normal years.The precipitation processes were less,and the precipitation was mainly caused by Typhoon Doksuri.If the typhoon precipitation was removed,the summer precipitation in Shandong would be 15.9％less than that in normal years.Based on the daily precipitation observation data of 122 national meteorological stations in Shandong from 1961 to 2023 and ERA5 monthly reanalysis data,this study analyzes the characteristics of summer precipitation in Shandong in 2023 and explores the circulation patterns during the early-onset El Nino years.The results are as follows.In summer,the western section of the western Pacific subtropical high lies southward and the conditions for transfer of water vapor are poor,accompanied with positive geopotential height anomalies over Lake Baikal and weaker cold air affecting Shandong,which directly cause the less summer precipitation.The year 2023 featured an early-onset El Niño event.During such early-onset El Niño years,anomalously cold sea surface temperatures in the western Pacific trigger anomalous Walker circulation,consequently inducing a weakened and southward-displaced Hadley cell,while concurrently intensifying the Ferrel cell.Consequently,the western Pacific subtropical high shifts southward,and with subsiding airflow prevailing particularly over Shandong and insufficient moisture transport,the summer precipitation is suppressed.

Abstract:Short-term heavy precipitation is a leading disastrous weather occurring during the warm season in China.This study examines the meso-and small-scale characteristics of short-term heavy precipitation and the configuration of three-dimensional wind field in depth,using the heavy precipitation event of weak synoptic disturbance that occurred in Shanghai on 29 June 2022 as a case study.Utilizing observations of X-band phased array weather radar(XAWR),S-band dual-polarization Doppler weather radar,and surface and sounding data,the mechanisms behind this heavy rainfall and its developmental evolution are explored.The findings are as follows.(1)The event is a rainstorm that forms in the warm sector before the cold front,where the shallow cold air from the surface interacts with the warm and humid airflow,creating a mesoscale convergence line that triggers the convection.(2)During this heavy precipitation,the radar echoes experience three merging and intensifications.The first merging increases the echo intensity.In the second merging,multiple cells move towards southeast,and the diffusion of the sinking airflow from these cells in the lower layer intensifies the near-surface northerly airflow,continuously generating new cells at the southern edge of the thunderstorm.The multiple cells formed after the third merging move towards northeast,the outflow from the thunderstorm sustains the near-surface northerly airflow,and new cells are generated on the southern side of the echo.(3)The strengthening of southwesterly winds and the weakening of northerly airflow lead to a rapid decline in the radar echo intensity,signaling the end of this short-term heavy precipitation event.

Abstract:The honeysuckle yield data and meteorological data in Pingyi,Linyi from 1998 to 2024 are used to construct a model for precipitation suitability-yield reduction rate of honeysuckle with precipitation suitability as the meteorological index.Based on the goodness-of-fit test method,the probability and grade of yield reduction rate are determined,and then the pure premium rate for honeysuckle insurance is determined.The results are shown below.(1)Due to the interannual differences in meteorological conditions,the meteorological yield of honeysuckle in Pingyi fluctuates greatly from 2001 to 2024,and the annual yield reduction rate is 41.7％.(2)The best relationship between precipitation suitability and yield reduction rate of honeysuckle is reflected by a quadratic polynomial regression model.The smaller the precipitation suitability of honeysuckle,the greater the yield reduction rate of honeysuckle.When the precipitation suitability is 0,the yield reduction rate of honeysuckle reaches its maximum,namely 68.874％.(3)The pure premium rate for honeysuckle insurance in Pingyi is determined to be 4.01％by using the distribution model for yield reduction rate and the classical combustion analysis method,which could provide scientific basis for the design of agricultural insurance products.

Abstract:This study aims to study the applicability of cloud model forecasting products in artificial rain enhancement operations in complex terrain areas of Guizhou based on the quantitative forecasting products of CMA-CPEFS(China Meteorological Administration-Cloud and Precipitation Explicit Forecasting System)model developed by CMA Weather Modification Centre.The fusion diagnosis method using multi-source observation data of ground-based radar,geostationary satellite and sounding profile is adopted to test the model forecasting performance of 30 cases of aircraft-based rain enhancement in Guizhou from 2020 to 2021.The results are as follows.(1)The model accuracy of distinguishing cloud phase is 93％(28/30),and the matching degrees of the operation height layer and the catalyst type configuration are 93％(28/30)and 100％(30/30),respectively,confirming that the model's ability to characterize the cloud physical parameters meets the operational standard.(2)There is a systematic positive deviation in the height of 0 ℃layer,the mean bias error is+108 m,which passes the 95％confidence level test,and the confidence interval is(+108±97)m with p＜0.01.The mean absolute error is+205 m.The forecast accuracy of cloud system's horizontal moving direction is 80％,slightly higher than that of cloud system's horizontal moving speed(77％).(3)The threat score(TS)of the potential area for rain enhancement is 0.67,but there is a significant deviation in spatial expansion(the forecasting range is 18％±3％larger than that of the actual situation),which is significantly correlated(R2=0.82,p＜0.001)with the subjective analysis error and overestimation of cloud water content by the model(the deviation is+0.15 g·m-3).The results provide key physical constraints for the optimization of numerical models for weather modification in the karst landform areas of Guizhou.

Abstract:On 22 March 2023,a sandstorm weather occurred in Shandong with a wide range,high intensity and long duration,making it a rare event in recent years.It was included in the top 10 weather and climate events in Shandong in 2023.This study analyzes the characteristics of this sandstorm weather using the data of aerosol lidar,L-band boundary layer wind profiling radar,air quality data from China National Environmental Monitoring Center,routine ground and upper-air observations and ERA5 reanalysis data.The conclusions are as follows.(1)From January to March 2023,the temperature in sand source areas such as Mongolia and Northwest China was significantly higher than usual,and precipitation was scarce in desert regions,which formed the climatic background for the sandstorm in Shandong.The sandstorm occurs under the weather conditions of a strong Siberian high-pressure system and a Mongolian cyclone,with the pressure difference between the two systems exceeding 52 hPa during their strongest phase.(2)The Mongolian cyclone is the triggering mechanism for the sandstorm.From 20 to 21 March,a warm center developed at low levels in Northwest China and North China regions,with a temperature difference between 850 hPa and 500 hPa reaching 33-35 ℃.The atmospheric stratification develops unstably,the cyclone triggers thermal instability and strong winds,the disturbance loosens the surface,and the upward motion lifts the surface dust and sand/stones from sand source areas into the air.When the cold front of the cyclone passes through Shandong,the horizontal transport by the northeasterly winds behind the front and dynamic deposition directly contribute to the sandstorm.The increase in the wind speed and the sharp rise in the mass concentration of PM10 correspond well with the stronger positive pressure change in 3 h.(3)The wind speed affects the vertical diffusion of particulate matter.The aerosol lidar monitoring shows that the sand and dust transport height in Shandong is less than 2.5 km,but the high-concentration sand and dust particles are concentrated below 1 km,and as the sandstorm moves eastward and southward,the transport height gradually decreases.When the wind speed decreases,the sand and dust particles are dispersed into higher altitudes,increasing the impact height again.

Abstract:To assess the impact of the modification of underlying surface at the new airport site in Foshan on the local fog and low clouds that can cause low visibility,this study employs a combined approach of numerical simulation and observational data to analyze the evolution characteristics of visibility,low cloud cover and relative humidity before and after the modification.The results are shown below.(1)The low clouds and low visibility events at the preselected site predominantly occur from predawn to early morning with similar diurnal variation patterns,whose frequencies account for of 11.0％and 19.7％of the total number of days throughout the year,respectively.(2)The simulations demonstrate that the post-construction alterations in surface properties and terrain elevation induce localized warming and reduced relative humidity,and particularly at night,the relative humidity drops by over 10％.This effectively inhibits the fog formation and significantly improves the visibility,with the maximum improvement exceeding 10 km.Concurrently,the markedly elevated high-humidity layer suppresses the condensation into clouds,reducing the frequency of low clouds.This work quantitatively reveals the suppressive effect of the modification of underlying surface on low visibility,providing direct scientific support for flight safety threshold design,reference for meteorological risk prediction in terms of airport operations,and a climate impact assessment framework for siting comparable major infrastructure projects such as transportation hubs.

Abstract:Based on the needs for accurate analysis of the wind field data of the wind radar(WindRAD)onboard Fengyun-3E(FY-3E),this paper uses multi-source data from buoy stations,numerical prediction model and satellites to evaluate the quality of FY-3E WindRAD wind field products with all wind speeds in multiple dimensions.The additive,multiplicative and random errors of 4 independent observation sources are analyzed by using the triple collocation(TC)method.Taking the buoys as an unbiased observation source,it can be found from the error analysis of multi-source data that the negative deviation of the additive error of FY-3E WindRAD C-band wind speed is larger,the deviation of Ku-band and dual-band wind speed is similar,the multiplicative error of C-band is the smallest,and their random errors are similar.Among the independent sources,the root mean square errors(RMSEs)of the buoys are the smallest,the two satellite products are similar and larger than those of the buoys,and the RMSEs of the model are the largest.In summary,FY-3E WindRAD can provide high-precision wind field products,but the main problem is that the consistency of products in different datasets needs to be optimized.The research results of the accuracy of satellite products based on multi-source data in this paper can provide more comprehensive and reliable information for satellite product users,and provide a basis for objective calibration methods for predicting sea surface wind field by numerical models.

Abstract:An advection fog event occurred along the coast of Qingdao from 22 to 25 May 2024.This study analyzes the microphysical characteristics of the sea fog using the data of FM-120 fog monitors at two coastal observing sites(Baguan Hill and Xiaomai Island),observations of surface automatic meteorological stations and ERA5 reanalysis data.The results are as follows.(1)The fog event is characterized by stable synoptic situation,southeast warm and moist airflow and a strong inversion layer.(2)During the event,the average number concentration at Baguan Hill(Xiaomai Island)is 277.02 cm-3(77.58 cm-3)with an average liquid water content of 0.051 g·m-3(0.027 g·m-3),an average effective radius of 4.92 μm(7.39 μm)and an average radius of 2.65 μm(2.78 μm).(3)The microphysical characteristics from these two observing sites exhibit synchronous temporal evolution,and the fog droplet spectrum displays a distinct bimodal structure during the development and maturation of the fog,particularly evident in the large particle range above 15 μm.(4)The visibility parameterization scheme established based on both number concentration and liquid water content shows optimal predictive performance during the fog event.

Abstract:The characteristics of typhoon activities over western North Pacific and the South China Sea in 2024,as well as the tracks,intensities,wind and rainfall of the typhoons that had great influence on China were summarized and analyzed statistically.The data used included the real-time operation data of the Central Meteorological Observatory,the best track data of China Meteorological Administration,Fengyun satellite data and conventional observing data.The analysis results are as follows.(1)A total of 26 typhoons were formed over western North Pacific and the South China Sea in 2024,which was basically the same as that of the climate average.The formation regions were further north and west,the generation time was more concentrated,and the typhoons in autumn were more active.(2)A total of 8 typhoons landed in China's coastal areas,which was more than the climate average.The landfalling sites were concentrated in the coastal areas of East China and South China,and the number of typhoons landing on Taiwan and Shanghai was obviously higher than that in normal years.The average intensity of initial landings was stronger,and the total landing times were more than the average.Typhoon Yagi has been the strongest typhoon landing on China in autumn since meteorological records began.(3)There were 468 rivers in 25 provinces that had exceeded the warning level.Typhoon Gaemi caused a large-range and long-term heavy rainfall in Northeast China,North China,regions south of the Yangtze River and Southwest China.

Abstract:The characteristics of the atmospheric circulation in the Northern Hemisphere in winter 2024 (from December 2024 to February 2025)were as follows.The polar vortex was characterized by a dipole type,and the circulation in the middle and high latitudes had a three-wave distribution.There was a significantly positive anomaly in the high pressure ridge in Siberia,and the ridge was stronger than the annual average,which was conducive to the accumulation of cold air.The East Asian large trough had a weak negative anomaly,and the trough was stronger than the annual average,which helped to guide the cold air southward.One tropical cyclone was generated in western North Pacific and the South China Sea,and 15 tropical cyclones were generated in other oceans.There were 11 gale processes of Beaufort wind force scale 8 or above in the offshore waters of China,including 9 processes produced by cold air,one process by cold air and extratropical cyclones and one process by cold air and typhoon.The number of days with large waves above 2.0 m in the offshore waters of China was 54,accounting for about 60％of the total number of days in winter.There were 4 relatively obvious sea fog processes in the offshore waters of China.In winter 2024,China's offshore waters showed an obvious cooling trend,and the cooling range of the northern waters was significantly greater than that of the southern waters.The sea surface temperature(SST)of China's offshore waters in December 2024 was generally higher than that of the normal years,while the SST from January to February 2025 was generally lower than usual.

Abstract:Using the air-sea coupled model simulations from CMIP6 and PMIP4,this study extracts the intrinsic modes of mid-Holocene ENSO(El Niño-Southern Oscillation)in the perspective of the ENSO recharge-discharge oscillator via the linear inverse model method,thereby elucidating the dynamic mechanisms for the ENSO amplitude reduction during this period.The research reveals that the reduced ENSO amplitude in the mid-Holocene results from a decreased growth rate of the intrinsic ENSO mode,which is linked to weakened thermocline feedback and zonal advection feedback.The results are as follows.(1)The weakened thermocline feedback is primarily driven by a significant reduction in the response strength of the zonal slope of the thermocline to the wind stress over the equatorial central Pacific during autumn and winter of the mid-Holocene.(2)Simultaneously,the weakened zonal advection feedback is attributed to a notable decline in the response strength of anomalous zonal currents in the equatorial eastern Pacific to the wind stress over the equatorial central Pacific during summer-winter.The weakening of these two critical positive feedbacks reduces the development rate of the initial ENSO sea surface temperature anomalies emerged in summer,ultimately reducing the ENSO amplitude in winter.(3)In contrast,the enhanced ENSO amplitude in some models is associated with the significantly strengthened thermocline feedback,although the zonal advective feedback is weakened as well but to a smaller extent,compared to the enhancement of thermocline feedback.

Abstract:Based on the WRF-CMAQ(Weather Research and Forecasting-Community Multiscale Air Quality)model,the evolution characteristics of sulfate aerosol in China in the middle of the 21st century(2056-2060)are studied.The results are listed as follows.(1)Under the past scenario(2015-2019),the mass concentration of sulfate aerosol in China exhibits substantial spatio-temporal variations.The typical feature is that the areas of high mass concentration are located in the northern part of China,such as North China,with the highest mass concentration in winter and generally lower mass concentration in summer.(2)The simulation of future scenario selects both the quasi-carbon neutrality scenario Shared Socioeconomic Pathways(SSP)126 and SSP585 with continuous increase of greenhouse gases and slightly reduction in air pollutants.Under the SSP 126 scenario,compared with the historical scenario,the average mass concentration of sulfate aerosol in 4 seasons in China decreases by 3.1,2.7,3.5 and 4.1 μg·m-3,respectively;under the SSP585 scenario,it decreases by 1.8,1.5,2.0 and 2.2 μg·m-3,respectively.Both scenarios see the largest decrease in winter.(3)The effects of anthropogenic emissions and climate change on sulfate aerosol are isolated.Due to the reduction in anthropogenic emission sources,the mass concentration of sulfate aerosol decreases by 3.5 and 2.1 μg·m-3 under the SSP126 and SSP585 scenarios,respectively.To investigate the impact of climate change only,two numerical simulation experiments are set up,in which the climate changes but the emissions maintain at the historical level.The average mass concentration of sulfate aerosol in China under the SSP585 scenario with greater change of climate shows a larger degree of increase(+0.4 μg·m-3)compared to that under SSP 126(+0.2 μg·m-3)with smaller change of climate.The research shows that the impact of anthropogenic emission reduction on the mass concentration of sulfate aerosol in China is greater than that of climate change,and especially over the areas with severe pollution in winter(e.g.,Beijing-Tianjin-Hebei),the decrease is more than 14 μg·m-3.Nevertheless,the effect of climate change remains to be nonnegligible.

Abstract:In order to analyze the evolution of microbursts in Shanghai under weak synoptic forcing and reveal the common characteristics of dual-polarization radar,this paper analyzes the evolutionary characteristics of 6 microburst storm cells in two local severe convection events in Shanghai under weak synoptic-scale background on 6 and 12 August 2022,using S-band dual-polarization Doppler weather radar data,conventional observations and other relevant datasets.The results are as follows.(1)Thermodynamic environments and triggering conditions.Both events are under the control of the subtropical high and characterized by high instability and weak vertical wind shear,with boundary layer convergence lines(e.g.,sea breeze fronts,horizontal convective rolls,thunderstorm outflow and their interactions)as the primary triggering mechanisms for thunderstorms.Pulse storms merge and strengthen,or develop rapidly under the collision of early thunderstorm outflows,resulting in short-term heavy precipitation and microburst.(2)Dominant physical mechanisms of microbursts.During the two events,the average wind speed in the entrainment layer is relatively low,leading to a weak momentum downward transport mechanism;the primary physcial mechanism for microburst formation is the phase-change cooling(evaporation,melting,etc.)of hydrometeor particles and precipitation drag.(3)Dual-polarization radar precursors.The KDP core near the melting layer(wet bulb temperature zero)and 1 km below it can directly indicate the melting and descent of ice-phase particles within the melting layer,generating negative buoyancy.The increase in the peak KDP core can foreshadow an impending downdraft burst within the next 12-6 min.(4)Other dual-polarization radar precursors.The descending of ZH core and KDP core,which both indicate the fall of ice-phase precipitation particles,the weakening and descending of ZDR column near the melting layer,which reflects strong updrafts,and the ZDR trough observed during the process with large hailstones etc.,can all be used as precursors of microbursts.