Abstract:Based on the S-band dual-polarization Doppler weather radar data in Jinan,sounding data and surface meteorological observations,the dual-polarization characteristics of the evolution of two severe storms,namely the squall line on 30 June and the supercell on 9 July 2021,are analyzed.The results are outlined below.(1)The two severe storms both occur in the synoptic situation of cold vortex,and their trigger mechanisms and morphological structures are different.The supercell storm is triggered by the gust front on 9 July,while the strong squall line is triggered by the weak cold front on 30 June.(2)The continuous stimulating,merging and developing of new convective cells result in the two severe storms lasting for a long time.(3)The stimulation of new cells in the intersection area of the gust front and the right side of supercell causes the storm to propagate rightward,so the right side of the supercell storm is the key area.The continuous stimulation of convective cells ahead of the east side of the strong squall line guides the storm to rapidly propagate,move forward,and evolve into bow echoes,so the key area is the front of the squall line's left side.(4)At the initial moment of the new cells(30-44 dBZ),the differential reflectivity(ZDR)columns can reach the height of-10℃,containing a few medium sized raindrops.With the rapid development of new cells,ZDR columns can extend to the height of-20 ℃ or even higher,containing a small amount of large liquid raindrops or small melted ice particles.(5)The main characteristic of the cell merging is the merging of ZDR columns,that is,the merging of the updraft zones.After merging,the width or height of ZDR columns and the values of ZDR and KDP increase,and the size and concentration of liquid particles in the strong updraft zone grow larger obviously.There are extra-large raindrops with the diameter exceeding 5 mm or melted ice particles equivalent to extra-large raindrops inside ZDR columns.

Abstract:Based on conventional meteorological observations,retrieval data of microwave radiometer,L-band radiosonde observations in Rongcheng,ERA5 data and NOAA(National Oceanic and Atmospheric Administration)data,three typical non-precipitation sea fog cases occurring over the northern Yellow Sea from May to July 2024 are analyzed.Correlation analysis is conducted on data from microwave radiometer and L-band radiosonde,and the average correlation coefficients of temperature and relative humidity below 2 km are 0.83 and 0.64,which belong to significant correlation.On this basis,the characteristics of temperature and humidity structures and the differences in formation mechanisms of sea fog under different synoptic systems in different seasons are investigated.The results are as follows.(1)When sea fog occurs behind cold high in spring,the low-level southerly winds transport warm and humid airflow,the cold air mass behind the cold high and the nocturnal radiation cooling produce cooling effect of the surface,so the formation of heavy fog has humidification and cooling effect.The temperature and humidity elements exhibit distinct characteristics of day and night changes,with a high air-sea temperature difference in the afternoon and a decrease in relative humidity.The liquid water is concentrated at the height of 0.1-0.2 km with a maximum of 0.57 g·m-3,which is in line with the formation time of high humidity layer.The increase in the surface temperature destroys the temperature inversion layer,which is the main reason for the dissipation of heavy fog.(2)The weak cold front type of heavy fog in early summer occurs in the northwesterly flow behind the trough with poor water vapor conditions.The microwave radiometer detects a thinner high humidity layer than the advection cooling fog,and there is a dry layer in the humid layer.The cooling effect is obvious near the surface layer,and a strong temperature difference(5.3 ℃)in the inversion layer forms between the surface and the height of 300 m.The temperature rises in the afternoon and the heavy fog dissipates.(3)The prevailing advection cooling fog in summer is closely related to the stable subtropical high.The low-level easterly winds continue to transport water vapor,and heavy fog can last for several days.During the heavy fog,the day and night changes of temperature and humidity are not dramatic,with a maximum temperature difference of only 3.81 ℃ in the inversion layer.The liquid water content is abundant,and the large values last for a long time with a maximum exceeding 1.0 g·m-3,which is mainly due to the humidification effect.When the previous stable synoptic situation changes,the stable layer is destroyed and the heavy fog dissipates.

Abstract:Taking the heavy precipitation caused by the long-duration Typhoon Khanun(2306)affecting Liaoning and its surrounding regions as an example,this study uses the TS(threat score)verification method and various spatial verification methods to examine and analyze the deviation characteristics of the 24-h,48-h and 72-h daily precipitation forecasts from the CMA_MESO,CMA_GFS and EC_IFS models in three aspects:intensity,distribution pattern and location.(1)The TS verification method shows that within the 24-h forecast period,the forecast scores of the CMA_MESO,CMA_GFS and EC_IFS models for precipitation magnitudes below heavy rain are 0.64,0.66 and 0.69,respectively.As the precipitation threshold increases,the TS decreases to around 0.40.Among them,EC_IFS achieves the best TS,while CMA_MESO has the highest false alarm rate.(2)The SAL(structure,amplitude and location)spatial verification method indicates that the overall precipitation location forecasts of the three numerical models are basically consistent,but the precipitation intensity forecasts are all weaker.The forecasted precipitaion area structure from EC_IFS is the most similar to the actual situation,however,its predicted range for precipitation of rainstorm and above magnitudes is larger.(3)The comprehensive similarity score of MODE(method for object based diagnostic evaluation)indicates that CMA_GFS is unstable in forecasting the precipitation associated with this typhoon;CMA_MESO shows stable performance,but its forecasting effect for rainstorms is not ideal;EC_IFS has the highest similarity score for 24-h forecast and demonstrates the best reliability in forecasting the precipitation of this typhoon.Compared with the traditional TS,the spatial verification method can more accurately identify the models' structural deviations in terms of rainstorm magnitude and quantify the positional offset of rainbands.In practical operational work,different verification methods should be selected according to different needs.At the same time,different verification methods can also be combined to analyze the performance of numerical models from different perspectives,which is helpful to improve the model applicability for precipitation forecasts of similar typhoons.

Abstract:As a sensitive area to global climate change,the Qinghai-Tibet Plateau plays an important role in the climate system through the changes in glaciers and lakes.Based on the remote sensing imagery data from 2000 to 2023 and selected typical glaciers and lakes on the Qinghai-Tibet Plateau,the normalized difference snow index(NDSI)and Glacier-Unet method are used to extract the area of glaciers,and the area of lakes is extracted by combining the normalized difference water index(NDWI)and sentinel dual-polarized water index(SDWI).Meanwhile,by using the annual average temperature and annual precipitation data from neighboring weather stations,the principal component analysis is utilized to quantitatively reveal that rising temperatures directly drive glacier retreat by enhancing ablation,while the increased precipitation dominates lake expansion by enhancing lake inflow.The results are shown below.(1)The area of 7 typical glaciers decreases by 20.75 km2 cumulatively,and the retreat rate is decreasing from low latitude to high latitude.Temperature is the main driver of glacier retreat,and there are differences in the timing and magnitude of the response of different glaciers to the rising temperatures,but they all reflect the general trend of enhanced ablation and weakened accumulation in the context of long-term warming.(2)Ten typical lakes show an expansion trend,with the total area increasing by 757.55 km2,and the expansion is mainly concentrated in the endorheic lakes in the central-southern area.There are differences in the timing and magnitude of the response of different lakes to the changes in precipitation,but all of them reflect the general trend of expansion due to enhanced recharge and relatively insufficient evaporation and outflow in the context of long-term increase in precipitation.

Abstract:This paper reviews sea fog researches conducted over the past two decades on the climatology(e.g.spatial-temporal distribution and causes of global sea fog frequency),synoptic meteorology and relevant perspectives.Sea fog climatology examines the global(including both polar regions)distributions of sea fog frequency,seasonal variations and classifications.Researches on the synoptic meteorology and relevant perspectives of sea fog encompass the influence of various factors on the formation and evolution of sea fog,including gravity wave disturbances,land-sea thermal contrasts,sea surface temperature fronts,precipitation/clouds,radiation,turbulence,advection and air-sea interactions,and examine the formation mechanisms of sea fog and sea fog-low cloud systems under the impact of intense weather systems,such as typhoons and explosive cyclones.This section is primarily based on researches regarding sea fog over China's coastal waters,and also includes related representative studies in areas such as the North Pacific,the North Atlantic and the coastal waters of California,USA,helping readers gain a more comprehensive understanding of the latest developments in sea fog research.Through this synthesis,we aim to deepen the understanding of the complex physical processes governing the formation and dissipation of sea fog.Finally,the review summarizes key insights gained from the mentioned studies,highlights unresolved questions and uncertainties,and provides prospects for future research.

Abstract:This paper conducts an accuracy evaluation and improvement study on the synthetic aperture radar(SAR)sea surface wind speed products from the Sentinel-1C satellite under IW mode.Using the buoy observation data from the National Data Buoy Center(NDBC)as the ground truth,the accuracy of the official Sentinel-1C SAR Level-2 OCN wind speed products from April to June 2025 is evaluated.It is found that the root mean square error(RMSE)is 1.31 m·s-1,which meets the requirements of routine applications,but there is still room for improvement.To enhance the product accuracy,three improvement schemes are designed to systematically explore the influence of background wind field types,the adaptability of the geophysical model function and the correction of deviations in the normalized radar cross section(NRCS).The results are shown below.(1)Replacing the ECMWF(European Centre for Medium-Range Weather Forecasts)background wind field with higher-resolution CMEMS(Copernicus Marine Environment Monitoring Service)data can reduce the RMSE to 1.28 m·s-1.The retrieval effect of CMOD5.n model performs better than that of C-SARMOD2 due to its adaptation to conventional wind conditions and medium incidence angles.The NRCS re-calibration model constructed based on CMEMS and CMOD5.n can effectively correct the incidence angle-related residuals of the original NRCS.(2)The optimal improvement scheme significantly improves the product accuracy:the deviation drops to-0.35 m·s-1,the RMSE reduces to 1.21 m·s-1,and the correlation coefficient increases to 0.88.The research results can provide technical support for the operational improvement of SAR sea surface wind speed products from the Sentinel-1C satellite and offer reference for the accuracy improvement of similar C-band SAR wind speed products.

Abstract:To improve the consensus forecast of tropical cyclone(TC)tracks over western North Pacific,this study constructs 6 consensus schemes by combining three artificial intelligence(AI)weather prediction models(Pangu,FuXi and FengWu)with numerical weather prediction(NWP)models(including deterministic and ensemble forecasts)using three consensus methods:simple multi-model average(AVG),selective ensemble average(SEAV)and selective ensemble change-weighted average(SECW).These schemes are evaluated for their 120-h TC track forecasts from 2023 to 2024.The results are as follows.(1)Individual AI models exhibit clear advantages over NWP in TC track forecast(most notably at longer lead times).Compared to the ECMWF ensemble mean,FengWu shows comprehensive superiority,while the other two AI models perform worse at 24 h and 48 h,but better at 72-120 h.Against pure NWP consensus forecasts,FengWu has slightly higher errors at 24-72 h,but significant advantages at 96 h and 120 h.(2)The integrated schemes combining AI and NWP leverage the strengths of both approaches,substantially outperforming the ECMWF-EPS ensemble mean.They generally surpass both individual AI models and pure NWP consensus forecasts,and exceed pure AI consensus forecasts within 72 h.At 96 h and 120 h,however,the pure AI consensus forecasts show the most significant advantages.(3)Compared to the operational consensus forecasts from the Shanghai Typhoon Institute,the three proposed integrated schemes—incorporating additional ensemble and AI model members—significantly reduce track errors and enhance forecast stability,with the AI+NWP_SECW scheme performing the best.This study demonstrates that AI models have promising application potential in TC track consensus forecast.

Abstract:Using the meteorological observations from coastal observing stations in Guangxi from 1 January 2016 to 31 December 2021 and 0.25°×0.25° ERA5 data with a 3-h interval,this study calculates and analyzes the required physical quantity values based on the physical processes of sea fog formation and dissipation as well as forecasters' experience.A total of 68 physical quantities that may affect sea fog are preliminarily selected as initial forecasting factors,and an objective forecasting model for the sea fog in the Beibu Gulf is established using the ingredient-based method,decision tree method and index method.Verification is conducted using the threat score(TS)for the forecasts of the sea fog processes from January to April 2023.The results are as follows.(1)The three objective forecasting products perform well in predicting the sea fog in the Beibu Gulf,but the performance in the Beihai sea area is inferior to that in other sea areas.(2)Based on the TS of the 24-h forecasts using the three methods,the forecasting performance of the ingredient-based method is significantly better than that of the decision tree method and the index method.(3)Based on the TS of the 48-h and 72-h forecasts using the three methods,the decision tree method outperforms the ingredient-based method and the index method significantly.(4)A comparative analysis of the TS of the ECMWF(European Centre for Medium-Range Weather Forecasts)model products reveals that the average TS(only around 0.30)of the ECMWF model products for the coastal sea fog in the Beibu Gulf is lower than the TSs of the three objective methods,and notably lower than the average TS(0.40)of the ingredient-based method and the decision tree method.Nevertheless,from the perspective of the forecasting results across different sea areas,the ECMWF model products exhibit significantly better performance(with the TS of 0.46)in the Fangchenggang sea area compared to the ingredient-based method(with the TS of 0.38)and the index method(with the TS of 0.36).

Abstract:Using the relevant data of 17 typhoon cases in Binzhou from 1978 to 2019,this study establishes an Arc GIS-based disaster risk assessment model to assess the risk of typhoon disasters,in order to provide scientific basis for the layout of regional industries and meteorological disaster prevention and mitigation.The results are as follows.(1)The typhoons affecting Binzhou typically occur from July to September,and the impact duration is 1-6 d,whose interannual variation shows an increasing trend.A total of 34 typhoon disasters are recorded in all counties(county-level cities or districts),with 19 in medium-high disaster grades,accounting for 58.82％.(2)The typhoon disaster risk index is larger in the southeast and lower in the northwest.Among them,the disaster risk index of the maximum wind speed(MW)shows a spatial distribution of larger values in the north and lower values in the south;both the disaster risk index of the maximum daily rainfall for the process(MP)and the disaster risk index of the amount of precipitation(AP)distribute in a stepped pattern,characterized by larger values in the east and lower values in the west.(3)The analysis on the risk zonation of typhoon disasters for different disaster-bearing bodies in Binzhou indicates that the comprehensive risk in the southeast is higher than that in the north,and higher-high risks are relatively concentrated,which is consistent with the distribution of the typhoon disaster risk index.

Abstract:Based on the surface meteorological data of Langfang National Meteorological Observing Station and the particulate matter mass concentration and AQI(air quality index)data of Langfang Municipal Bureau of Ecology and Environment,the characteristics of the air pollution in Langfang from 1 December 2020 to 30 November 2023 are analyzed.The results are outlined below.(1)Of the sand and dust weather in Langfang,72.7％(8/11)can cause a significant increase by over 80 in AQI,and 88.9％of the severe pollution days occur under the influence of sand and dust weather,mostly in spring.(2)The sand and dust processes on 15 March 2021 and 10-13 April 2023 belong to the upstream transmission type with strong intensity and long duration.The mass concentrations of PM2.5 and PM10 generally show a trend of rising and falling together,and the occurrence of sand and dust lags behind the occurrence of strong winds.(3)The sand and dust process on 4 March 2022 belongs to the locally generated type,characterized by weak intensity,small impact range and short duration.At the same time,the change in the concentration of PM10 lags behind that of PM2.5,and the mass concentration of PM2.5 drops sharply when the concentration of PM10 suddenly rises.The sharp increase in the mass concentration of PM10 almost occurs synchronously with strong winds.(4)The analysis on the three typical sand and dust weather processes shows that the ratio between PM2.5 and PM10 corresponds well with the generation and dissipation of sand and dust.(5)A higher wind speed is beneficial for the formation of sand and dust weather,while when the wind speed is excessively high,it will hinder the settling of sand and dust particles.The pollutants brought in by the northerly and southwesterly winds have a greater impact on the air pollution in Langfang.

Abstract:Studying the impact of temperature on evaporation observations at automatic meteorological stations is of great significance for climate change research and the assessment of meteorological drought disasters.The diurnal variation characteristics are analyzed using the hourly evaporation and temperature data from Anqing national basic meteorological station(hereinafter referred to as Anqing station)from April to November 2017.The results are as follows.(1)The diurnal variation patterns of hourly evaporation and temperature are similar,both exhibiting one valley and one peak,with the peak hourly evaporation occurring 3 h later than that of the temperature.(2)Through the experimental research on the water temperature in evaporation measurements at Anqing station,it is found that after sunrise,the water temperature in the E601B evaporation pan rises,leading to an increase in volume.Combined with the influence of the operational software's automatic evaporation algorithm,it results in smaller measured hourly evaporation values in the morning but larger values from afternoon to evening on clear days.The analysis on the observation data from two typical warming days shows that the daily evaporation measurements are 7％-26％smaller,while the measurements from two systematic cooling processes are 15％-19％larger.(3)The complete correlation analysis of the hourly evaporation and related meteorological factors at Anqing and Taihu national basic meteorological stations in the southwest of Anhui Province indicates that the thermal factors are the primary drivers for the variations of hourly evaporation.The shallow ground temperatures at 10-20 cm have the most significant impact on hourly evaporation,with the ground temperature at 15 cm showing the strongest correlation with hourly evaporation.

Abstract:East Asia is one of the regions with the most potential for development and cooperation,and it is of scientific and social significance to study the impact of the El Niño-Southern Oscillation(ENSO),an interannual climate anomaly signal affecting stratospheric ozone,on the stratospheric ozone in East Asia.Based on the HadISST and ERA5 data from 1979 to 2021,the linkage between ENSO and the stratospheric ozone in East Asia and its impact mechanism are analyzed.The research findings are as follows.(1)ENSO mainly affects the ozone content and distribution in the lower stratosphere of East Asia,showing a significant positive correlation with the ozone content in the lower stratosphere in the ranges of 25°-30° N and 70°-120°E,with differences in the effects on positive and negative phases.(2)ENSO influences the stratospheric atmosphere of East Asia through the anomalies of Rossby wave activities.The ENSO-induced anomalies of Rossby wave activities are dominated by the lower stratospheric influence,with positive phases accompanying Rossby wave's upload at low latitudes and affecting East Asia through the northwestward wave flux anomalies from the tropical eastern-central Pacific to East Asia.The wave activities cause the atmosphere in East Asia to undergo meridional shifts and vertical motions,leading to the anomalous ozone content and distribution in this region.(3)In addition,it is found that there is an interdecadal variation in the relationship between ENSO and the stratospheric ozone in East Asia from 1979 to 2021,which is attributed to the change in the spatial correlation pattern between ozone and sea surface temperature in the two periods.

Abstract:Using the data of intensive automatic meteorological observing stations,lightning location system,Doppler weather radar and wind profile radar,as well as ERA5 data,the severe convection weather event in dry conditions that occurred in the central part of Shandong Province on 7 June 2023 is analyzed with a focus on the role of complex underlying surfaces.The results are shown below.(1)Due to the consideration of the relative humidity in the lower troposphere which is less than 40％,the larger convective inhibition and the weaker low-level system,the forecasters do not place enough attention on the environmental conditions,which are similar to the typical dry downburst in this area,and the role of complex underlying surfaces(the Yellow River surface,the big city and Mount Tai).Therefore,there is misjudgment in the prediction of the convection weather.(2)The convection cells first appear in the area of higher dew point temperature near the Yellow River west of Jinan City,and then move eastward into the city,where they are triggered by the dew point front and the ground mesoscale convergence line.The energy accumulated by the urban heat island effect is released,causing the convection cells to develop,intensify and eventually form a northwest-southeast echo band.(3)A gust front appears ahead of the echo band(i.e.,on the east side),and the convection cells triggered by the interaction of the gust front and the ground convergence line are continuously merged into the echo band,maintaining and strengthening the intensity of the echo band.After reaching the foot of Mount Tai,the echo band climbs up under topographic uplift effect,and the elevation enhances the echo intensity.As the ground convergence line disappears,the echo band weakens after crossing the mountain range,and the severe convection weather ends.(4)There are two local flow fields near Mount Tai,namely a zonal flow field on the west side of the mountain that rises near the mountain but sinks farther west,and a meridional flow field on the north side of the mountain that rises farther north but sinks near the mountain.The existence of these two flow fields,together with the triggering of the ground mesoscale system,makes the convection cells first develop and strengthen on the northwest side of the mountain.The south side of the mountain is not conducive to the development of convective clouds,resulting in the weakening of echoes after reaching the south side of the mountain.

Abstract:In order to quickly and accurately extract the lodging area of winter wheat,two lodging processes in Dezhou are taken as research cases.The data of GF-6 satellite and synthetic aperture radar aboard Sentinel-1 satellite are used to accurately extract the lodging area of the winter wheat according to different spectral characteristics of lodging wheat and normal wheat.The results are as follows.(1)The spectral analysis of normal wheat and lodging wheat shows that the reflectance of the green light band in the GF-6 image and the backscattering intensity in the VH(vertical-horizontal)image are significantly higher in the latter than in the former.(2)The lodging area of winter wheat extracted from these two features is generally larger than the measured area.When the lodging is serious,the relative error percentage ranges from 3.1％to 4.6％.Compared with the serious lodging,the relative error of extraction is larger in mild lodging.(3)The extraction result based on GF-6 satellite is more accurate when lodging and waterlogging are present at the same time.The research results provide reference for further improving the precision of extracting lodging area of winter wheat,and provide data support for timely prevention of and remedy for winter wheat lodging.

Abstract:Using the ground observation data of Xuwen National Meteorological Observing Station from 1990 to 2023 and the NCEP/NCAR reanalysis data,the characteristics of climate change,meteorological elements and common synoptic situations of the occurrence of dense fog in the Qiongzhou Strait are statistically analyzed.The results are shown below.(1)The annual average number of foggy days in the Qiongzhou Strait is 16.6 d,and the interannual change of foggy days presents a decreasing trend.Winter is the season with the highest frequency of dense fog in the Qiongzhou Strait,accounting for 51.8％of the annual total number of dense fog days,while summer sees the lowest frequency,making up only 7.8％.February is the month with the most dense fog days in the Qiongzhou Strait with an average of 4.2 d,accounting for 25.3％of the annual total number of dense fog days,while July has the least average number of dense fog days(only 0.3 d).The dense fog in the Qiongzhou Strait mainly occurs from 04:00 to 08:00,accounting for 42.7％of the whole day;the peak appears at 06:00,and the valley at 13:00.(2)The ideal meteorological conditions for the formation of dense fog in the Qiongzhou Strait are as follows:the easterly wind(ENE-ESE)prevails on the surface with the wind speed concentrated in the range of[1.0,5.0)m·s-1,the temperature is in the range of[16,22)℃,the depression of the dew point(t-td)does not exceed 2.0 ℃,the pressure is in the range of[1 005.0,1 017.5]hPa at the station,and the relative humidity is higher than 90％.(3)The circulation patterns of the fog in the Qiongzhou Strait can be divided into 5 types:the front low pressure,the high pressure entering the sea,the stationary front,the front of cold front and the equal pressure field,which account for 10.8％,13.5％,21.6％,24.3％and 29.8％,respectively.Among them,the front low pressure type and the high pressure entering the sea type mainly produce advection fog,the stationary front type often produces mixing fog,the front of cold front type produces frontal fog and the equal pressure field type mainly produces radiation fog.The 5 types of weather patterns and the fog types they generate provide reference for practical operations.

Abstract:To date,there are 8 satellites worldwide carrying various types of microwave scatterometers,providing indispensable support for the remote sensing of global sea surface winds.Quantitative and comprehensive evaluation of the error characteristics of those microwave scatterometer-derived sea surface winds is a prerequisite for the optimal application of multi-scatterometer wind data.This study conducts quality assessments on the sea surface wind data for 5 Chinese operational scatterometers and two Advanced Scatterometers(ASCAT)from the European Organization for the Exploitation of Meteorological Satellites(EUMETSAT),using both buoy wind and European Centre for Medium Range Weather Forecasts(ECMWF)data in 2022.The analytical techniques include pairwise comparison,Kolmogorov spectral analysis and triple collocation analysis.The results of spectral analysis are as follows.(1)All spaceborne scatterometers are able to depict more spatial variability compared to the ECMWF data,indicating that satellite scatterometers outperform ECMWF in resolving mesoscale(below 100 km)dynamic characteristics over sea surface.(2)The triple collocation analysis method not only enables quantitative evaluation of the inherent errors in each data source within the triple collocated datasets,but also facilitates cross-comparison of error characteristics among different scatterometers' wind products.(3)Overall,the inherent random errors of scatterometer wind u and v components range between 0.5 and 1.3 m·s-1.The results provide crucial references for the error covariance settings in applications utilizing multi-scatterometer sea surface wind data.

Abstract:Based on the data such as sea surface wind from Cross-Calibrated Multi-Platform(CCMP)version 3.1 provided by NASA,combined with the methods such as Mann-Kendall trend test,the anomalous variation characteristics of the strong breeze frequency over the Yellow Sea and Bohai Sea in winter are analyzed,and the possible influencing factors on the interdecadal time scale are explored.The results are outlined below.(1)From 1993 to 2008,the strong breeze frequency over the Bohai Sea,Bohai Strait and northwestern Yellow Sea shows an overall upward trend.However,the variation has decelerated since 2009.(2)After removing the long-term trend on the interdecadal scale,the North Atlantic sea surface temperature anomaly(SSTA)in November shows a tripolar mode from 1996 to 2020.When the SSTA shows a"+,-,+"phase,a negative phase of the North Atlantic Oscillation(NAO)appears at 850 hPa above the sea surface in winter.Meanwhile,a Rossby wave train propagates downstream from the area of negative phase of NAO to the Yellow Sea,Bohai Sea and Sea of Japan at 250 hPa,which is conducive to the accumulation of cold air in the key area and the outbreak of cold waves.In winter,there is a negative anomaly of meridional temperature gradient at 850 hPa over the Yellow Sea and Bohai Sea,contributing to the downward transfer of high-altitude momentum and the outbreak of cold waves and strong breeze.(3)When it retains the long-term trend of the data,the sea ice concentration anomaly(SICA)in the northern Barents Sea and Kara Sea in November from 1993 to 2008 shows a significant downward trend,which is negatively correlated with the Arctic oscillation in winter.The Rossby wave train at 250 hPa spreads from the Arctic to the Yellow Sea,Bohai Sea and Sea of Japan,while the Ural blocking at 500 hPa intensifies,and an abnormally low pressure occurs over Lake Baikal,which is conducive to the transport and accumulation of cold air from the Arctic to the key area of the cold wave,and the occurrence of a negative anomaly of meridional temperature gradient at 850 hPa over the Yellow Sea and Bohai Sea.The SICA in the Arctic in November has not changed significantly since 2009,the corresponding Ural blocking high pressure is abnormally weak,and an abnormally high pressure appears over Lake Baikal in winter,which is not in favor of the transport and accumulation of cold air in the key area,as well as the outbreak of strong breeze over the Yellow Sea and Bohai Sea in winter.

Abstract:Based on the daily gridded precipitation dataset(CN05.1),NCEP/NCAR reanalysis data and HadISST monthly data,the linear regression and wavelet analysis,as well as the linear baroclinic model(LBM),are employed to examine the spatial-temporal variability of the summer precipitation in North China from 1961 to 2020 and its relationship with Asian-Pacific Oscillation(APO).The results are as follows.(1)The summer precipitation in North China exhibits a spatial pattern of higher values in the southeast and lower values in the northwest,and there is notable interannual variability.(2)The APO modulates the summer precipitation in North China by altering the East Asian atmospheric circulation.More specifically,the intensified APO correlates with a stronger South Asia high,a stronger and northward western Pacific subtropical high and an enhancement of low pressure across the Asian continent,thereby intensifying the East Asian and South Asian summer monsoons.This leads to the enhanced transfer of water vapor towards North China,fostering convergence and ultimately higher summer precipitation in North China,and vice versa.(3)The APO also modifies the sea surface temperature(SST)gradient between the eastern and western Pacific regions via wind fields,inducing an ENSO(El Niño-Southern Oscillation)-like SST anomaly in the Pacific Ocean,which,in turn,impacts the Walker circulation and indirectly modulates the summer precipitation in North China.(4)The numerical simulations employing the LBM further validate that the anomalous heat sources over the Qinghai-Tibet Plateau elicit a response in the upper tropospheric geopotential height,which fosters APO development and consequently a stronger South Asia high.Simultaneously,the middle and lower troposphere exhibits an anomalous cyclonic circulation,which bolsters the East Asian and South Asian summer monsoons,thereby enhancing the transfer of water vapor towards North China and the summer precipitation there.

Abstract:To address the problems of fuzzy distortion in long-term echoes and low accuracy in predicting strong echoes in existing radar echo extrapolation models,this paper designs a radar echo extrapolation method based on self-attention and dense convolution improved convolutional long short-term memory(ConvLSTM)network by using the composite reflectivity mosaic image of Doppler radar data in Anhui from May to September 2016.Based on ConvLSTM,the model incorporates self-attention mechanism into each cell and Encoder-Decoder to enhance the ability of extracting features with long-term spatial dependence.Meanwhile,the model uses dense convolution instead of common convolution to improve the feature reuse ability.The experiment uses the past 1-h radar echo image to predict the future 2-h radar echo image,and compares the resluts with the ConvLSTM before the improvement,proving that the proposed model can improve the accuracy of radar echo extrapolation.

Abstract:Based on the observation data of daily maximum/minimum temperature and daily relative humidity from 116 national meteorological stations in Shandong between June and August from 1961 to 2022,the spatiotemporal distributions and variations of three types of heat waves,including daytime type,nighttime type and compound type,are analyzed using the total number,average duration,average intensity and average relative humidity indices.The results are as follows.(1)The spatial distributions of the three types are significantly different,because the daytime type is more in the west and less in the east of Shandong,the nighttime type is more in the south and less in the north of Shandong,and the compound type is more in the south of Shandong and less in Shandong Peninsula.The average duration of the three types is less than 4.5 d in most areas of Shandong.The average intensity of the compound type is higher than 8.0 ℃ in the west and middle of Shandong.The average relative humidity of the nighttime type is obviously larger than that of the daytime and nighttime types,with the average relative humidity commonly over 76％.(2)The three types of heat waves mainly occur in July.In June,it is mainly the daytime type and its duration is the longest,accompanied with the lowest relative humidity.Both in July and August,the average duration of the compound type is the longest.The average relative humidity is the highest in August for all the three types,and the average relative humidity of the nighttime type is the highest among three months.(3)The average relative humidity of the daytime type in Shandong shows a significantly decreasing trend,while the total number,average duration and average intensity of the nighttime and compound types display a significantly increasing trend.(4)The number of stations with the daytime type presents an insignificantly decreasing trend,but the number of stations with the nighttime and compound types reveals a significantly increasing trend.Around the mid-1990s,the nighttime and compound types obviously increased.