Based on the lightning observation data from the Fengyun-4A(FY-4A)Lightning Mapping Imager(FY-4A/LMI)and the Lightning Imaging Sensor(LIS)on the International Space Station(ISS),we extract the“event”type data as the...Based on the lightning observation data from the Fengyun-4A(FY-4A)Lightning Mapping Imager(FY-4A/LMI)and the Lightning Imaging Sensor(LIS)on the International Space Station(ISS),we extract the“event”type data as the lightning detection results.These observations are then compared with the cloud-to-ground(CG)lightning observation data from the China Meteorological Administration.This study focuses on the characteristics of lightning activity in Southeast China,primarily in Jiangxi Province and its adjacent areas,from April to September,2017–2022.In addition,with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis data,we further delved into the potential factors influencing the distribution and variations in lightning activity and their primary related factors.Our findings indicate that the lightning frequency and density of the FY-4A/LMI,ISS-LIS and CG data are higher in southern and central Jiangxi,central Fujian Province,and western and central Guangdong Province,while they tend to be lower in eastern Hunan Province.In general,the high-value areas of lightning density for the FY-4A/LMI are located in inland mountainous areas.The lower the latitude is,the higher the CG lightning density is.High-value areas of the CG lightning density are more likely to be located in eastern Fujian and southeastern Zhejiang Province.However,the high-value areas of lightning density for the ISS-LIS are more dispersed,with a scattered distribution in inland mountainous areas and along the coast of eastern Fujian.Thus,the mountainous terrain is closely related to the high-value areas of the lightning density.The locations of the high-value areas of the lightning density for the FY-4A/LMI correspond well with those for the CG observations,and the seasonal variations are also consistent.In contrast,the distribution of the high-value areas of the lightning density for the ISS-LIS is more dispersed.The positions of the peak frequency of the FY-4A/LMI lightning and CG lightning contrast with local altitudes,primarily located at lower altitudes or near mountainsides.K-index and convective available potential energy(CAPE)can better reflect the local boundary layer conditions,where the lightning density is higher and lightning seasonal variations are apparent.There are strong correlations in the annual variations between the dew-point temperature(Td)and CG lightning frequency,and the monthly variations of the dew-point temperature and CAPE are also strongly correlated with monthly variations of CG lightning,while they are weakly correlated with the lightning frequency for the FY-4A/LMI and ISS-LIS.This result reflects that the CAPE shows a remarkable effect on the CG lightning frequency during seasonal transitions.展开更多
The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameteri...The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.展开更多
The quantitative precipitation forecast(QPF)performance by numerical weather prediction(NWP)methods depends fundamentally on the adopted physical parameterization schemes(PS).However,due to the complexity of the physi...The quantitative precipitation forecast(QPF)performance by numerical weather prediction(NWP)methods depends fundamentally on the adopted physical parameterization schemes(PS).However,due to the complexity of the physical mechanisms of precipitation processes,the uncertainties of PSs result in a lower QPF performance than their prediction of the basic meteorological variables such as air temperature,wind,geopotential height,and humidity.This study proposes a deep learning model named QPFNet,which uses basic meteorological variables in the ERA5 dataset by fitting a non-linear mapping relationship between the basic variables and precipitation.Basic variables forecasted by the highest-resolution model(HRES)of the European Centre for Medium-Range Weather Forecasts(ECMWF)were fed into QPFNet to forecast precipitation.Evaluation results show that QPFNet achieved better QPF performance than ECMWF HRES itself.The threat score for 3-h accumulated precipitation with depths of 0.1,3,10,and 20 mm increased by 19.7%,15.2%,43.2%,and 87.1%,respectively,indicating the proposed performance QPFNet improved with increasing levels of precipitation.The sensitivities of these meteorological variables for QPF in different pressure layers were analyzed based on the output of the QPFNet,and its performance limitations are also discussed.Using DL to extract features from basic meteorological variables can provide an important reference for QPF,and avoid some uncertainties of PSs.展开更多
An extremely heavy rainfall event occurred in Zhengzhou,China,on 20 July 2021 and produced an hourly rainfall rate of 201.9 mm,which broke the station record for China's Mainland.Based on radar observations and a ...An extremely heavy rainfall event occurred in Zhengzhou,China,on 20 July 2021 and produced an hourly rainfall rate of 201.9 mm,which broke the station record for China's Mainland.Based on radar observations and a convection-permitting simulation using the WRF-ARW model,this paper investigates the multiscale processes,especially those at the mesoscale,that support the extreme observed hourly rainfall.Results show that the extreme rainfall occurred in an environment characteristic of warm-sector heavy rainfall,with abundant warm moist air transported from the ocean by an abnormally northward-displaced western Pacific subtropical high and Typhoon In-Fa(2021).However,rather than through back building and echo training of convective cells often found in warm-sector heavy rainfall events,this extreme hourly rainfall event was caused by a single,quasi-stationary storm in Zhengzhou.Scale separation analysis reveals that the extreme-rainproducing storm was supported and maintained by the dynamic lifting of low-level converging flows from the north,south,and east of the storm.The low-level northerly flow originated from a mesoscale barrier jet on the eastern slope of the Taihang Mountain due to terrain blocking of large-scale easterly flows,which reached an overall balance with the southerly winds in association with a low-level meso-β-scale vortex located to the west of Zhengzhou.The large-scale easterly inflows that fed the deep convection via transport of thermodynamically unstable air into the storm prevented the eastward propagation of the weak,shallow cold pool.As a result,the convective storm was nearly stationary over Zhengzhou,resulting in record-breaking hourly precipitation.展开更多
Knowledge of the raindrop size distribution(DSD)is crucial for disaster prevention and mitigation.The recordbreaking rainfall in the summer of 2020 caused some of the worst flooding ever experienced in China.This stud...Knowledge of the raindrop size distribution(DSD)is crucial for disaster prevention and mitigation.The recordbreaking rainfall in the summer of 2020 caused some of the worst flooding ever experienced in China.This study uses 96 Parsivel disdrometers and eight-year Global Precipitation Measurement(GPM)satellite observations to reveal the microphysical aspects of the disastrous rainfall during its northward migration over East China.The results show that the nearly twice as heavy rainfall in Jiangsu Province compared to Fujian Province can be attributed to the earlier-than-average northward jump of the summer monsoon rainband to the Yangtze-Huaihe River valley.The persistent heavy monsoon rainfall showed similar near-maritime DSD characteristics,with a higher concentration of small raindrops than the surrounding climatic regimes.During the northward movement of the rainband,the DSD variables and composite spectra between the pre-summer rainfall in Fujian and mei-yu rainfall in Jiangsu exhibited inherent similarities with slight regional variations.These are associated with similar statistical vertical precipitation structures for both convective and stratiform rain in these regions/periods.The vertical profiles of radar reflectivity and DSD parameters are typical of monsoonal rainfall features,implying the competition between coalescence,breakup,and accretion of vital warm rain processes.This study attributes the anomalously long duration of the mei-yu season for the record-breaking rainfall and reveals inherent homogeneous rainfall microphysics during the northward movement of the summer monsoon rainband.The conclusion is statistically robust and would be helpful for accurate precipitation estimation and model parameterization of summer monsoon rainfall over East China.展开更多
The northeastern China cold vortex(NCCV)plays an important role in regional rainstorms over East Asia.Using the National Centers for Environmental Prediction Final reanalysis dataset and the Global Precipitation Measu...The northeastern China cold vortex(NCCV)plays an important role in regional rainstorms over East Asia.Using the National Centers for Environmental Prediction Final reanalysis dataset and the Global Precipitation Measurement product,an objective algorithm for identifying heavy-precipitation NCCV(HPCV)events was designed,and the climatological features of 164 HPCV events from 2001 to 2019 were investigated.The number of HPCV events showed an upward linear trend,with the highest frequency of occurrence in summer.The most active region of HPCV samples was the Northeast China Plain between 40°–55°N.Most HPCV events lasted 3–5 days and had radii ranging from 250 to 1000 km.The duration of HPCV events with larger sizes was longer.About half of the HPCV events moved into(moved out of)the definition region(35°–60°N,115°–145°E),and half initiated(dissipated)within the region.The initial position was close to the western boundary of the definition region,and the final position was mainly near the eastern boundary.The locations associated with the precipitation were mostly concentrated within 2000 km southeast of the HPCV systems,and they were farther from the center in the cold season than in the warm season.展开更多
Based on the global reanalysis data of the National Centers for Environmental Prediction(NCEP)/National Center for Atmospheric Research,the surface meteorological observation data,sounding data and satellite observati...Based on the global reanalysis data of the National Centers for Environmental Prediction(NCEP)/National Center for Atmospheric Research,the surface meteorological observation data,sounding data and satellite observation data,this paper comprehensively analyzes the evolution process and formation mechanism of a persistent severe dense fog process occurred on February 15–17,2015 in Yancheng,eastern China.Through the numerical simulation experiment of Weather Research and Forecast(WRF)model,we further analyze the impact of sea-land breeze on the formation and burst reinforcement of fog.Results show that the precipitation caused by the southwesterly airflow in front of the upper-level trough and the low-pressure inverted trough are conducive to the formation of early rain fog,while the nighttime clear radiance under the control of surface cold high and the infiltration of weak cold advection are conducive to the formation and development of later radiation-advection fog.The WRF model simulates the fog evolution process,which is basically consistent with the actual fog area,and the simulation results are credible to a certain extent.The simulation results show that the establishment of sea breeze has an advection cooling effect on the near surface layer,which is conducive to the formation and development of the inversion layer on the near surface,providing stable stratification conditions for the formation and burst reinforcement of fog.On one hand,the strengthening of sea breeze circulation can continuously transport water vapor to the study area.On the other,the occurrence of ultra-low level jet is favorable for the accumulation of low-level water vapor.At the same time,the inversion intensity further strengthens,which is in favor of the burst reinforcement and long-term maintenance of fog.展开更多
Previous numerical simulations have focused mainly on the mesoscale structure of the principal rainband in tropical cyclones with a relatively coarse model resolution.In this study,the principal rainband was simulated...Previous numerical simulations have focused mainly on the mesoscale structure of the principal rainband in tropical cyclones with a relatively coarse model resolution.In this study,the principal rainband was simulated in a semi-idealized experiment at a horizontal grid spacing of 1/9 km and its convective-scale structure was examined by comparing the convective elements of the simulated principal rainband with previous observational studies.It is found that the convective scale structure of the simulated principal rainband is well comparable to the observation.The azimuthal variations of the convective scale structure were examined by dividing the simulated principal rainband into the upwind,middle and downwind portions.Some new features are found in the simulated principal rainband.First,the overturning updraft contains small-scale rolls aligned along the inward side of the outward-leaning reflectivity tower in the middle portion.Second,the inner-edge downdraft is combined with a branch of inflow from the upper levels in middle and downwind portions,carrying upper-level dry air to the region between the overturning updrafts and eyewall,and the intrusion of the upper-level dry air further limits the altitude of the overturning updrafts in the middle and downwind portions of the principal rainband.Third,from the middle to downwind portions,the strength of the secondary horizontal wind maximum is gradually replaced by a low-level maximum of the tangential wind collocated with the low-level downdraft.展开更多
Cloud microphysical properties are significantly affected by entrainment and mixing processes.However,it is unclear how the entrainment rate affects the relative dispersion of cloud droplet size distribution.Previousl...Cloud microphysical properties are significantly affected by entrainment and mixing processes.However,it is unclear how the entrainment rate affects the relative dispersion of cloud droplet size distribution.Previously,the relationship between relative dispersion and entrainment rate was found to be positive or negative.To reconcile the contrasting relationships,the Explicit Mixing Parcel Model is used to determine the underlying mechanisms.When evaporation is dominated by small droplets,and the entrained environmental air is further saturated during mixing,the relationship is negative.However,when the evaporation of big droplets is dominant,the relationship is positive.Whether or not the cloud condensation nuclei are considered in the entrained environmental air is a key factor as condensation on the entrained condensation nuclei is the main source of small droplets.However,if cloud condensation nuclei are not entrained,the relationship is positive.If cloud condensation nuclei are entrained,the relationship is dependent on many other factors.High values of vertical velocity,relative humidity of environmental air,and liquid water content,and low values of droplet number concentration,are more likely to cause the negative relationship since new saturation is easier to achieve by evaporation of small droplets.Further,the signs of the relationship are not strongly affected by the turbulence dissipation rate,but the higher dissipation rate causes the positive relationship to be more significant for a larger entrainment rate.A conceptual model is proposed to reconcile the contrasting relationships.This work enhances the understanding of relative dispersion and lays a foundation for the quantification of entrainment-mixing mechanisms.展开更多
The present climate simulation and future projection of the mixed layer depth(MLD)and subduction process in the subtropical Southeast Pacific are investigated based on the geophysical fluid dynamics laboratory earth s...The present climate simulation and future projection of the mixed layer depth(MLD)and subduction process in the subtropical Southeast Pacific are investigated based on the geophysical fluid dynamics laboratory earth system model(GFDL-ESM2 M).The MLD deepens from May and reaches its maximum(>160 m)near(24°S,104°W)in September in the historical simulation.The MLD spatial pattern in September is non-uniform in the present climate,which shows three characteristics:(1)the deep MLD extends from the Southeast Pacific to the West Pacific and leads to a"deep tongue"until 135°W;(2)the northern boundary of the MLD maximum is smoothly near 18°S,and MLD shallows sharply to the northeast;(3)there is a relatively shallow MLD zone inserted into the MLD maximum eastern boundary near(26°S,80°W)as a weak"shallow tongue".The MLD nonuniform spatial pattern generates three strong MLD fronts respectively in the three key regions,promoting the subduction rate.After global warming,the variability of MLD spatial patterns is remarkably diverse,rather than deepening consistently.In all the key regions,the MLD deepens in the south but shoals in the north,strengthing the MLD front.As a result,the subduction rate enhances in these areas.This MLD antisymmetric variability is mainly influenced by various factors,especially the potential-density horizontal advection non-uniform changes.Notice that the freshwater flux change helps to deepen the MLD uniformly in the whole basin,so it hardly works on the regional MLD variability.The study highlights that there are regional differences in the mechanisms of the MLD change,and the MLD front change caused by MLD non-uniform variability is the crucial factor in the subduction response to global warming.展开更多
Based on the comprehensive ground observation and the remote sensing data of Fengyun-4 satellite of a typical sand-dust weather process in the eastern part of the Qinghai-Tibet Plateau from November 26 to 27,2018,the ...Based on the comprehensive ground observation and the remote sensing data of Fengyun-4 satellite of a typical sand-dust weather process in the eastern part of the Qinghai-Tibet Plateau from November 26 to 27,2018,the weather situation,air mass trajectory,meteorological conditions,and pollution characteristics of this process were analyzed.The results show that the floating dust process was caused by the transmission of the northwest cold air flow in the Tarim Desert area,which caused dust and sand mixed with the Qaidam Desert particles to be transported to Xining.The wind field change caused by the difference of ground heat in the eastern plateau was a potential factor for dust transmission,and tropospheric subsidence,temperature inversion conditions,and the decrease in wind speed over Xining Station were the direct factors leading to the daily change of pollutant concentration in this process.展开更多
The Sichuan-Xizang Railway is an important part of the railway network in China, and geological disasters, such as mountain floods and landslides, frequently occur in this region. Precipitation is an important cause o...The Sichuan-Xizang Railway is an important part of the railway network in China, and geological disasters, such as mountain floods and landslides, frequently occur in this region. Precipitation is an important cause of these disasters;therefore,accurate simulation of the precipitation in this region is highly important. In this study, the descriptions for uncertain processes in the cloud microphysics scheme are improved;these processes include cloud droplet activation, cloud-rain autoconversion, rain accretion by cloud droplets, and the entrainment-mixing process. In the default scheme, the cloud water content of different sizes corresponds to the same cloud droplet concentration, which is inconsistent with the actual content;this results in excessive cloud droplet size, unreasonable related conversion rates of microphysical process(such as cloud-rain autoconversion), and an overestimation of precipitation. Our new scheme overcomes the problem of excessive cloud droplet size. The processes of cloudrain autoconversion and rain accretion by cloud droplets are similar to the stochastic collection equation, and the mixing mechanism of cloud droplets is more consistent with that occurred during the actual physical process in the cloud. Based on the new and old schemes, multiple precipitation processes in the flood season of 2021 along the Sichuan-Xizang Railway are simulated, and the results are evaluated using ground observations and satellite data. Compared to the default scheme, the new scheme is more suitable for the simulation of cloud physics, reducing the simulation deviation of the liquid water path and droplet radius from 2 times to less than 1 time and significantly alleviating the overestimation of precipitation intensity and range of precipitation center. The average root-mean-square error is reduced by 22%. Our results can provide a scientific reference for improving precipitation forecasting and disaster prevention in this region.展开更多
During 19–21 July 2021,an extreme rainfall event occurred in Henan Province,China,during which a recordbreaking maximum hourly rainfall of 201.9 mm was recorded in Zhengzhou at 09 UTC July 20.In this study,the predic...During 19–21 July 2021,an extreme rainfall event occurred in Henan Province,China,during which a recordbreaking maximum hourly rainfall of 201.9 mm was recorded in Zhengzhou at 09 UTC July 20.In this study,the predictability of this extreme rainfall event is investigated using two convection-permitting ensemble forecast systems(CEFSs):one initialized from NCEP GEFS(named CEFS_GEFS)and the other initialized from time-lagged ERA5 data(named CEFS_ERA).Both are able to reproduce the daily heavy rainfall along the Taihang Mountains,but most members have significant position biases for the extreme rainfall in Zhengzhou.For the hourly rainfall,a few members are able to capture the evolution and propagation of extreme rainfall.However,all ensemble members underestimate the extreme hourly rainfall and have position errors of a few tens to a few hundreds of kilometers.Such results suggest that the predictability of the extreme hourly rainfall at the accuracy of city scale in Zhengzhou is low,especially by deterministic forecasting models,and the occurrence of the extreme requires many favorable conditions to happen simultaneously.In terms of the Brier score,CEFS_GEFS performs better than CEFS_ERA.The latter lacks spread,especially in regions with scarce rain,resulting in less dispersion in precipitation distributions and larger probability forecast error.When a neighborhood is applied,the probability of precipitation(POP)is significantly increased over Zhengzhou.While the traditional POP shows almost no skill for hourly rainfall≥25 mm h-1,the neighborhood POP significantly improves the forecast skill score,for both daily and hourly rainfall,suggesting higher predictability when spatial error among the ensemble members is allowed.展开更多
The airborne two-dimensional stereo(2D-S) optical array probe has been operating for more than 10 yr, accumulating a large amount of cloud particle image data. However, due to the lack of reliable and unbiased classif...The airborne two-dimensional stereo(2D-S) optical array probe has been operating for more than 10 yr, accumulating a large amount of cloud particle image data. However, due to the lack of reliable and unbiased classification tools,our ability to extract meaningful morphological information related to cloud microphysical processes is limited. To solve this issue, we propose a novel classification algorithm for 2D-S cloud particle images based on a convolutional neural network(CNN), named CNN-2DS. A 2D-S cloud particle shape dataset was established by using the 2D-S cloud particle images observed from 13 aircraft detection flights in 6 regions of China(Northeast, Northwest, North,East, Central, and South China). This dataset contains 33,300 cloud particle images with 8 types of cloud particle shape(linear, sphere, dendrite, aggregate, graupel, plate, donut, and irregular). The CNN-2DS model was trained and tested based on the established 2D-S dataset. Experimental results show that the CNN-2DS model can accurately identify cloud particles with an average classification accuracy of 97%. Compared with other common classification models [e.g., Vision Transformer(ViT) and Residual Neural Network(ResNet)], the CNN-2DS model is lightweight(few parameters) and fast in calculations, and has the highest classification accuracy. In a word, the proposed CNN-2DS model is effective and reliable for the classification of cloud particles detected by the 2D-S probe.展开更多
Continuous high spatial-resolution 10-day precipitation data are essential for crop growth services and phenological research.In this study,we first use the bidimensional empirical mode decomposition(BEMD)algorithm to...Continuous high spatial-resolution 10-day precipitation data are essential for crop growth services and phenological research.In this study,we first use the bidimensional empirical mode decomposition(BEMD)algorithm to decompose the digital elevation model(DEM)data and obtain high-frequency(OR3),intermediate-frequency(OR5),and low-frequency(OR8)margin terrains.Then,we propose a refined precipitation spatialization model,which uses ground-based meteorological observation data,integrated multi-satellite retrievals for global precipitation measurement(GPM IMERG)satellite precipitation products,DEM data,terrain decomposition data,prevailing precipitation direction(PPD)data,and other multisource data,to construct China's high-resolution 10-day precipitation data from2001 to 2018.The decomposition results show mountainous terrain from fine to coarse scales;and the influences of altitude,slope,and aspect on precipitation are better represented in the model after topography is decomposed.Moreover,terrain decomposition data can be added to the model simulation to improve the quality of the simulation product;the simulation quality of the model in summer is better than that in spring and autumn,and is relatively poor in winter;and OR5 and OR8 can be improved in the simulation,with better OR5 and OR8 dynamically selected.In addition,preprocessing the data before precipitation spatialization is particularly important.For example,adding 0.01to the 0 value of precipitation,multiplying the small value of precipitation less than 1 by 10,and performing the normal distributions transform(e.g.,Yeo–Johnson)on the data can improve the simulation quality.展开更多
Terrestrial gamma-ray flashes(TGFs)are high-energy emissions in thunderstorms that were discovered first by satellite-based and then by ground-based gamma-ray detectors with photon energy up to tens of Me V.TGFs are a...Terrestrial gamma-ray flashes(TGFs)are high-energy emissions in thunderstorms that were discovered first by satellite-based and then by ground-based gamma-ray detectors with photon energy up to tens of Me V.TGFs are a natural highenergy phenomenon associated with lightning discharges that frequently occur during thunderstorms.However,their production mechanisms and associated processes are still unclear.TGF studies have already been a research spotlight in the atmospheric electricity and high-energy atmosphere research areas.In this paper,we review recent research progresses on TGF studies in the past decade,including TGF detection,the relationship between TGFs and lightning processes,and thunderstorm activities.Several unsolved important scientific questions are discussed.Results suggest that upward TGFs observed by satellite-based detectors are closely connected with the development of in-cloud upward negative leaders.They are usually generated in milliseconds of the initiation of upward negative leaders and may produce a kind of distinct radio emissions because of the generation and propagation of huge amounts of high-energy electrons.By contrast,its counterpart,i.e.,downward TGFs observed by ground-based gamma-ray detectors,is associated with different types of lightning processes,such as downward negative or upward positive leaders,the initial continuing current stage of rocket-triggered lightning flashes return stroke processes.Because of limited observations,how these downward TGFs are generated is still unclear.Benefiting from the development of state-of-the-art instruments with high temporal and spatial resolutions,new insights into the processes and mechanisms of TGFs will be achieved with coordinated observations from satellite-based and ground-based measurements.展开更多
Over the past four years,significant research has advanced our understanding of how external factors influence tropical cyclone(TC)intensity changes.Research on air-sea interactions shows that increasing the moisture di...Over the past four years,significant research has advanced our understanding of how external factors influence tropical cyclone(TC)intensity changes.Research on air-sea interactions shows that increasing the moisture disequilibrium is a very effective way to increase surface heatfluxes and that ocean salinity-stratification plays a non-negligible part in TC intensity change.Vertical wind shear from the environment induces vortex misalignment,which controls the onset of significant TC intensification.Blocking due to upper-level outflow from TCs can reduce the magnitude of vertical wind shear,making for TC intensification.Enhanced TC-trough interactions are vital for rapid intensification in some TC cases because of strengthened warm air advection,but upper-level troughs are found to limit TC intensification in other cases due to dry midlevel air intrusions and increased shear.Aerosol effects on TCs can be divided into direct effects involving aerosol-radiation interactions and indirect effects involving aerosol-cloud interactions.The radiation absorption by the aerosols can change the temperature profile and affect outer rainbands through changes in stability and microphysics.Sea spray and sea salt aerosols are more important in the inner region,where the aerosols increase precipitation and latent heating,promoting more intensification.For landfalling TCs,the intensity decay is initially more sensitive to surface roughness than soil moisture,and the subsequent decay is mainly due to the rapid reduction in surface moisturefluxes.These new insights further sharpen our understanding of the mechanisms by which external factors influence TC intensity changes.展开更多
In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometer...In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometers and two polarimetric radars.The broad distributions of specific drop size distribution(DSD) parameters are identified in heavy rainfall from the disdrometer observations, indicating obvious microphysical variability on the surface. A K-means clustering algorithm is adopted to objectively classify the disdrometer datasets into separate groups, and distinct DSD characteristics are found among these heavy rainfall groups. Combined with the supporting microphysical structures obtained through radar observations, comprehensive microphysical features of the DSD groups are derived. An extreme rainfall group is dominantly formed in the deep convection over the plain regions, where the high number of concentrations and large mean sizes of surface raindrops are underpinned by both active ice-phase processes and efficient warm-rain collision-coalescence processes in the vertical direction. Convection located near orographic regions is characterized by restricted ice-phase processes and high coalescence efficiency of liquid hydrometeors, causing the dominant DSD group to comprise negligible large raindrops. Multiple DSD groups can coexist within certain precipitation episodes at the disdrometer stations, indicating the potential microphysical variability during the passage of convective system on the plain regions.展开更多
The changes in near-surface wind speed(NWS)have a crucial influence on the wind power industry,and previous studies have indicated that NWS on global and China has declined continuously for decades under global warmin...The changes in near-surface wind speed(NWS)have a crucial influence on the wind power industry,and previous studies have indicated that NWS on global and China has declined continuously for decades under global warming.However,recently,the decreasing trend of global NWS has slowed down and even showed a recovery trend.Using the observation data of 831 weather stations of the China Meteorological Administration and the Japanese 55-year reanalysis data from 1970 to 2019,NWS changes in eastern China were analyzed and the possible influencing factors were discussed.Results show that winter NWS presented a decreasing trend from−0.29 m s^(−1) per decade(p<0.001)in 1970-1989 to−0.05 m s^(−1) per decade(p<0.01)in 1990-2019.Moreover,NWS exhibited a significant upward trend of 0.18 m s^(−1) per decade(p<0.1)in 2011-2019,resulting in a 19.6%per decade recovery of the wind power generation.A possible cause is asymmetric changes of the sea level pressure and near-surface air temperature differences between the mid-high latitudes(40°-60°N,80°-120°E)and low latitudes(20°-40°N,110°-140°E)altered the horizontal air pressure gradient.Furthermore,NWS changes were closely associated with the large-scale ocean-atmosphere circulations(LOACs).NWS at 77.4%of the stations in eastern China shows significant correlation(p<0.05)with the East Asian winter monsoon index,besides,the inter/multidecadal variability of NWS was considerably correlated to four LOACs,including Arctic oscillation(AO),North Atlantic oscillation(NAO),Pacific decadal oscillation(PDO),and El Niño-Southern Oscillation(ENSO).The time-series reconstructed by a multiple linear regression model based on above five LOACs matches well with the NWS.Interannual variability of NWS were significantly correlated to AO(−0.45,p<0.01)and NAO(−0.28,p<0.05),while the correlation between NWS and ENSO was weak.展开更多
Wide-field-of-view(WFV) imager that observes the earth environment with four solar reflective bands in a spatial resolution of 16 m is equipped on board Gaofen-1(GF-1) satellite. Chlorophyll-a(Chl-a) concentration in ...Wide-field-of-view(WFV) imager that observes the earth environment with four solar reflective bands in a spatial resolution of 16 m is equipped on board Gaofen-1(GF-1) satellite. Chlorophyll-a(Chl-a) concentration in Lake Taihu, China from 2018 to 2019 is collected and collocated with GF-1 satellite data. This study develops a general and reliable estimation of Chl-a concentration from GF-1 WFV data under turbid inland water conditions. The collocated data are classified according to season and used in random forest(RF) regression to train models for retrieving the lake Chl-a concentration. A composite index is developed to select the most important variables in the models. The models trained for each season show a better performance than the model trained by using the whole year data in terms of the coefficient of determination(R^(2)) between retrievals and observations. Specifically, the R2 values in spring, summer, autumn, and winter are 0.88, 0.88, 0.94, and 0.74, respectively;whereas that using the whole year data is only 0.71. The Chl-a concentration in Lake Taihu exhibits an obvious seasonal change with the highest in summer, followed by autumn and spring, and the lowest in winter. The Chl-a concentration also displays an obvious spatial variation with season. A high concentration occurs mainly in the northwest of the lake. The temporal and spatial changes of Chl-a concentration are almost consistent with the changes in the areas and times of cyanobacteria blooms based on Moderate Resolution Imaging Spectroradiometer(MODIS) data. The proposed algorithm can be operated without a priori knowledge on atmospheric conditions and water quality. Our study also demonstrates that GF-1 data are increasingly valuable for monitoring the Chl-a concentration of inland water bodies in China at a high spatial resolution.展开更多
基金National Natural Science Foundation of China(42175014,42205137)Open Research Fund of Institute of Meteorological Technology Innovation,Nanjing(BJG202202)+3 种基金Joint Research Project of Typhoon Research,Shanghai Typhoon Institute,China Meteorological Administration(TFJJ202209)Innovation Development Project of China Meteorological Administration(CXFZ2023P001)Open Project of KLME&CIC-FEMD(KLME202311)Jiangxi MDIA-ASI Fund。
文摘Based on the lightning observation data from the Fengyun-4A(FY-4A)Lightning Mapping Imager(FY-4A/LMI)and the Lightning Imaging Sensor(LIS)on the International Space Station(ISS),we extract the“event”type data as the lightning detection results.These observations are then compared with the cloud-to-ground(CG)lightning observation data from the China Meteorological Administration.This study focuses on the characteristics of lightning activity in Southeast China,primarily in Jiangxi Province and its adjacent areas,from April to September,2017–2022.In addition,with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis data,we further delved into the potential factors influencing the distribution and variations in lightning activity and their primary related factors.Our findings indicate that the lightning frequency and density of the FY-4A/LMI,ISS-LIS and CG data are higher in southern and central Jiangxi,central Fujian Province,and western and central Guangdong Province,while they tend to be lower in eastern Hunan Province.In general,the high-value areas of lightning density for the FY-4A/LMI are located in inland mountainous areas.The lower the latitude is,the higher the CG lightning density is.High-value areas of the CG lightning density are more likely to be located in eastern Fujian and southeastern Zhejiang Province.However,the high-value areas of lightning density for the ISS-LIS are more dispersed,with a scattered distribution in inland mountainous areas and along the coast of eastern Fujian.Thus,the mountainous terrain is closely related to the high-value areas of the lightning density.The locations of the high-value areas of the lightning density for the FY-4A/LMI correspond well with those for the CG observations,and the seasonal variations are also consistent.In contrast,the distribution of the high-value areas of the lightning density for the ISS-LIS is more dispersed.The positions of the peak frequency of the FY-4A/LMI lightning and CG lightning contrast with local altitudes,primarily located at lower altitudes or near mountainsides.K-index and convective available potential energy(CAPE)can better reflect the local boundary layer conditions,where the lightning density is higher and lightning seasonal variations are apparent.There are strong correlations in the annual variations between the dew-point temperature(Td)and CG lightning frequency,and the monthly variations of the dew-point temperature and CAPE are also strongly correlated with monthly variations of CG lightning,while they are weakly correlated with the lightning frequency for the FY-4A/LMI and ISS-LIS.This result reflects that the CAPE shows a remarkable effect on the CG lightning frequency during seasonal transitions.
基金supported by the National Natural Science Foundation of China(Grant Nos.42175099,42027804,42075073)the Innovative Project of Postgraduates in Jiangsu Province in 2023(Grant No.KYCX23_1319)+3 种基金supported by the National Natural Science Foundation of China(Grant No.42205080)the Natural Science Foundation of Sichuan(Grant No.2023YFS0442)the Research Fund of Civil Aviation Flight University of China(Grant No.J2022-037)supported by the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(Earth Lab)。
文摘The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.
基金the financial support of the National Key Research and Development Program (Grant No. 2017YFC1502000)the National Natural Science Foundation of China (Key Program, 91937301)
文摘The quantitative precipitation forecast(QPF)performance by numerical weather prediction(NWP)methods depends fundamentally on the adopted physical parameterization schemes(PS).However,due to the complexity of the physical mechanisms of precipitation processes,the uncertainties of PSs result in a lower QPF performance than their prediction of the basic meteorological variables such as air temperature,wind,geopotential height,and humidity.This study proposes a deep learning model named QPFNet,which uses basic meteorological variables in the ERA5 dataset by fitting a non-linear mapping relationship between the basic variables and precipitation.Basic variables forecasted by the highest-resolution model(HRES)of the European Centre for Medium-Range Weather Forecasts(ECMWF)were fed into QPFNet to forecast precipitation.Evaluation results show that QPFNet achieved better QPF performance than ECMWF HRES itself.The threat score for 3-h accumulated precipitation with depths of 0.1,3,10,and 20 mm increased by 19.7%,15.2%,43.2%,and 87.1%,respectively,indicating the proposed performance QPFNet improved with increasing levels of precipitation.The sensitivities of these meteorological variables for QPF in different pressure layers were analyzed based on the output of the QPFNet,and its performance limitations are also discussed.Using DL to extract features from basic meteorological variables can provide an important reference for QPF,and avoid some uncertainties of PSs.
基金supported by the National Science Foundation of China(Grant No.42122036)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(2019QZKK0105)+2 种基金the National Key R&D Programs of China(2018YFC1507300)the National Science Foundation of China(Grant No.91837207)the Beijing Climate Center(QHMS2021008).
文摘An extremely heavy rainfall event occurred in Zhengzhou,China,on 20 July 2021 and produced an hourly rainfall rate of 201.9 mm,which broke the station record for China's Mainland.Based on radar observations and a convection-permitting simulation using the WRF-ARW model,this paper investigates the multiscale processes,especially those at the mesoscale,that support the extreme observed hourly rainfall.Results show that the extreme rainfall occurred in an environment characteristic of warm-sector heavy rainfall,with abundant warm moist air transported from the ocean by an abnormally northward-displaced western Pacific subtropical high and Typhoon In-Fa(2021).However,rather than through back building and echo training of convective cells often found in warm-sector heavy rainfall events,this extreme hourly rainfall event was caused by a single,quasi-stationary storm in Zhengzhou.Scale separation analysis reveals that the extreme-rainproducing storm was supported and maintained by the dynamic lifting of low-level converging flows from the north,south,and east of the storm.The low-level northerly flow originated from a mesoscale barrier jet on the eastern slope of the Taihang Mountain due to terrain blocking of large-scale easterly flows,which reached an overall balance with the southerly winds in association with a low-level meso-β-scale vortex located to the west of Zhengzhou.The large-scale easterly inflows that fed the deep convection via transport of thermodynamically unstable air into the storm prevented the eastward propagation of the weak,shallow cold pool.As a result,the convective storm was nearly stationary over Zhengzhou,resulting in record-breaking hourly precipitation.
基金supported by the National Natural Science Foundation of China(Grant Nos.41905021,42005009).
文摘Knowledge of the raindrop size distribution(DSD)is crucial for disaster prevention and mitigation.The recordbreaking rainfall in the summer of 2020 caused some of the worst flooding ever experienced in China.This study uses 96 Parsivel disdrometers and eight-year Global Precipitation Measurement(GPM)satellite observations to reveal the microphysical aspects of the disastrous rainfall during its northward migration over East China.The results show that the nearly twice as heavy rainfall in Jiangsu Province compared to Fujian Province can be attributed to the earlier-than-average northward jump of the summer monsoon rainband to the Yangtze-Huaihe River valley.The persistent heavy monsoon rainfall showed similar near-maritime DSD characteristics,with a higher concentration of small raindrops than the surrounding climatic regimes.During the northward movement of the rainband,the DSD variables and composite spectra between the pre-summer rainfall in Fujian and mei-yu rainfall in Jiangsu exhibited inherent similarities with slight regional variations.These are associated with similar statistical vertical precipitation structures for both convective and stratiform rain in these regions/periods.The vertical profiles of radar reflectivity and DSD parameters are typical of monsoonal rainfall features,implying the competition between coalescence,breakup,and accretion of vital warm rain processes.This study attributes the anomalously long duration of the mei-yu season for the record-breaking rainfall and reveals inherent homogeneous rainfall microphysics during the northward movement of the summer monsoon rainband.The conclusion is statistically robust and would be helpful for accurate precipitation estimation and model parameterization of summer monsoon rainfall over East China.
基金supported by the National Key R&D Program of China under Grant No.2018YFC1507302the National Natural Science Foundation of China under Grant No.42175006+1 种基金Jiangsu Youth Talent Promotion Project(2021-084)the Basic Research Fund of CAMS under Grant No.2020R002.
文摘The northeastern China cold vortex(NCCV)plays an important role in regional rainstorms over East Asia.Using the National Centers for Environmental Prediction Final reanalysis dataset and the Global Precipitation Measurement product,an objective algorithm for identifying heavy-precipitation NCCV(HPCV)events was designed,and the climatological features of 164 HPCV events from 2001 to 2019 were investigated.The number of HPCV events showed an upward linear trend,with the highest frequency of occurrence in summer.The most active region of HPCV samples was the Northeast China Plain between 40°–55°N.Most HPCV events lasted 3–5 days and had radii ranging from 250 to 1000 km.The duration of HPCV events with larger sizes was longer.About half of the HPCV events moved into(moved out of)the definition region(35°–60°N,115°–145°E),and half initiated(dissipated)within the region.The initial position was close to the western boundary of the definition region,and the final position was mainly near the eastern boundary.The locations associated with the precipitation were mostly concentrated within 2000 km southeast of the HPCV systems,and they were farther from the center in the cold season than in the warm season.
基金supported by the National Natural Science Foundation of China(Grant Nos.42075063&42075066)the Open Project of State Key Laboratory of Severe Weather(Grant No.2021LASW-A07)+3 种基金the Jiangsu Meteorological Youth Fund Project(Grant No.KQ202215)the Special Fund for Basic Scientific Research Business of China Academy of Meteorological Sciences(Grant No.2022Y025)the Bei Ji Ge Open Research Fund(Grant No.BJG202307)the Science and Technology Project of Yancheng Meteorological Administration(Grant No.YQK2021016)。
文摘Based on the global reanalysis data of the National Centers for Environmental Prediction(NCEP)/National Center for Atmospheric Research,the surface meteorological observation data,sounding data and satellite observation data,this paper comprehensively analyzes the evolution process and formation mechanism of a persistent severe dense fog process occurred on February 15–17,2015 in Yancheng,eastern China.Through the numerical simulation experiment of Weather Research and Forecast(WRF)model,we further analyze the impact of sea-land breeze on the formation and burst reinforcement of fog.Results show that the precipitation caused by the southwesterly airflow in front of the upper-level trough and the low-pressure inverted trough are conducive to the formation of early rain fog,while the nighttime clear radiance under the control of surface cold high and the infiltration of weak cold advection are conducive to the formation and development of later radiation-advection fog.The WRF model simulates the fog evolution process,which is basically consistent with the actual fog area,and the simulation results are credible to a certain extent.The simulation results show that the establishment of sea breeze has an advection cooling effect on the near surface layer,which is conducive to the formation and development of the inversion layer on the near surface,providing stable stratification conditions for the formation and burst reinforcement of fog.On one hand,the strengthening of sea breeze circulation can continuously transport water vapor to the study area.On the other,the occurrence of ultra-low level jet is favorable for the accumulation of low-level water vapor.At the same time,the inversion intensity further strengthens,which is in favor of the burst reinforcement and long-term maintenance of fog.
基金the National Basic Research Program of China(Grant No.2015CB452803)the National Natural Science Foundation of China(Grant Nos.41730961,41675051,41675009,41675072,41922033 and 41905001)the Open Research Program of the State Key Laboratory of Severe Weather(Grant No.2019LASWA02).
文摘Previous numerical simulations have focused mainly on the mesoscale structure of the principal rainband in tropical cyclones with a relatively coarse model resolution.In this study,the principal rainband was simulated in a semi-idealized experiment at a horizontal grid spacing of 1/9 km and its convective-scale structure was examined by comparing the convective elements of the simulated principal rainband with previous observational studies.It is found that the convective scale structure of the simulated principal rainband is well comparable to the observation.The azimuthal variations of the convective scale structure were examined by dividing the simulated principal rainband into the upwind,middle and downwind portions.Some new features are found in the simulated principal rainband.First,the overturning updraft contains small-scale rolls aligned along the inward side of the outward-leaning reflectivity tower in the middle portion.Second,the inner-edge downdraft is combined with a branch of inflow from the upper levels in middle and downwind portions,carrying upper-level dry air to the region between the overturning updrafts and eyewall,and the intrusion of the upper-level dry air further limits the altitude of the overturning updrafts in the middle and downwind portions of the principal rainband.Third,from the middle to downwind portions,the strength of the secondary horizontal wind maximum is gradually replaced by a low-level maximum of the tangential wind collocated with the low-level downdraft.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41822504, 42175099, 42027804, 42075073 and 42075077)the National Center of Meteorology, Abu Dhabi, UAE under the UAE Research Program for Rain Enhancement Science+4 种基金LIU is supported by the U.S. Department of Energy Atmospheric System Research (ASR) Program (DE-SC00112704)Solar Energy Technologies Office (SETO) under Award 33504LUO is supported by Research Fund of Civil Aviation Flight University of China (J2022-037)LI is supported by Research Fund of Civil Aviation Flight University of China (09005001)WU is supported by Research on Key of Manmachine Ring in Plateau Flight (FZ2020ZZ03)
文摘Cloud microphysical properties are significantly affected by entrainment and mixing processes.However,it is unclear how the entrainment rate affects the relative dispersion of cloud droplet size distribution.Previously,the relationship between relative dispersion and entrainment rate was found to be positive or negative.To reconcile the contrasting relationships,the Explicit Mixing Parcel Model is used to determine the underlying mechanisms.When evaporation is dominated by small droplets,and the entrained environmental air is further saturated during mixing,the relationship is negative.However,when the evaporation of big droplets is dominant,the relationship is positive.Whether or not the cloud condensation nuclei are considered in the entrained environmental air is a key factor as condensation on the entrained condensation nuclei is the main source of small droplets.However,if cloud condensation nuclei are not entrained,the relationship is positive.If cloud condensation nuclei are entrained,the relationship is dependent on many other factors.High values of vertical velocity,relative humidity of environmental air,and liquid water content,and low values of droplet number concentration,are more likely to cause the negative relationship since new saturation is easier to achieve by evaporation of small droplets.Further,the signs of the relationship are not strongly affected by the turbulence dissipation rate,but the higher dissipation rate causes the positive relationship to be more significant for a larger entrainment rate.A conceptual model is proposed to reconcile the contrasting relationships.This work enhances the understanding of relative dispersion and lays a foundation for the quantification of entrainment-mixing mechanisms.
基金The National Natural Science Foundation of China under contract Nos 41606217 and 41620104003the Open Fund of Key Laboratory for Polar Science,Polar Research Institute of China,Ministry of Natural Resources,under contract No.KP201702the Open Fund of the Key Laboratory of Ocean Circulation and Waves,Chinese Academy of Sciences,under contract No.KLOCW1903
文摘The present climate simulation and future projection of the mixed layer depth(MLD)and subduction process in the subtropical Southeast Pacific are investigated based on the geophysical fluid dynamics laboratory earth system model(GFDL-ESM2 M).The MLD deepens from May and reaches its maximum(>160 m)near(24°S,104°W)in September in the historical simulation.The MLD spatial pattern in September is non-uniform in the present climate,which shows three characteristics:(1)the deep MLD extends from the Southeast Pacific to the West Pacific and leads to a"deep tongue"until 135°W;(2)the northern boundary of the MLD maximum is smoothly near 18°S,and MLD shallows sharply to the northeast;(3)there is a relatively shallow MLD zone inserted into the MLD maximum eastern boundary near(26°S,80°W)as a weak"shallow tongue".The MLD nonuniform spatial pattern generates three strong MLD fronts respectively in the three key regions,promoting the subduction rate.After global warming,the variability of MLD spatial patterns is remarkably diverse,rather than deepening consistently.In all the key regions,the MLD deepens in the south but shoals in the north,strengthing the MLD front.As a result,the subduction rate enhances in these areas.This MLD antisymmetric variability is mainly influenced by various factors,especially the potential-density horizontal advection non-uniform changes.Notice that the freshwater flux change helps to deepen the MLD uniformly in the whole basin,so it hardly works on the regional MLD variability.The study highlights that there are regional differences in the mechanisms of the MLD change,and the MLD front change caused by MLD non-uniform variability is the crucial factor in the subduction response to global warming.
基金the Applied Basic Research Project of Department of Science and Technology of Qinghai Province"Formation Mechanism of Salt Dust Storm in Qaidam Basin"(2018-ZJ-723).
文摘Based on the comprehensive ground observation and the remote sensing data of Fengyun-4 satellite of a typical sand-dust weather process in the eastern part of the Qinghai-Tibet Plateau from November 26 to 27,2018,the weather situation,air mass trajectory,meteorological conditions,and pollution characteristics of this process were analyzed.The results show that the floating dust process was caused by the transmission of the northwest cold air flow in the Tarim Desert area,which caused dust and sand mixed with the Qaidam Desert particles to be transported to Xining.The wind field change caused by the difference of ground heat in the eastern plateau was a potential factor for dust transmission,and tropospheric subsidence,temperature inversion conditions,and the decrease in wind speed over Xining Station were the direct factors leading to the daily change of pollutant concentration in this process.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(Grant No.2019QZKK0105)the Key Project of the National Natural Science Foundation of China(Grant No.42030611)+3 种基金the National Key Research and Development Program of China(Grant No.2022YFC3003903)the National Natural Science Foundation of China(Grant Nos.42205072&42305083)the Basic Research Fund of Chinese Academy of Meteorological Sciences(Grant No.2022Y024)the Key Research and Development Program of Science and Technology Department of Sichuan Province(Grant No.2022YFS0540)。
文摘The Sichuan-Xizang Railway is an important part of the railway network in China, and geological disasters, such as mountain floods and landslides, frequently occur in this region. Precipitation is an important cause of these disasters;therefore,accurate simulation of the precipitation in this region is highly important. In this study, the descriptions for uncertain processes in the cloud microphysics scheme are improved;these processes include cloud droplet activation, cloud-rain autoconversion, rain accretion by cloud droplets, and the entrainment-mixing process. In the default scheme, the cloud water content of different sizes corresponds to the same cloud droplet concentration, which is inconsistent with the actual content;this results in excessive cloud droplet size, unreasonable related conversion rates of microphysical process(such as cloud-rain autoconversion), and an overestimation of precipitation. Our new scheme overcomes the problem of excessive cloud droplet size. The processes of cloudrain autoconversion and rain accretion by cloud droplets are similar to the stochastic collection equation, and the mixing mechanism of cloud droplets is more consistent with that occurred during the actual physical process in the cloud. Based on the new and old schemes, multiple precipitation processes in the flood season of 2021 along the Sichuan-Xizang Railway are simulated, and the results are evaluated using ground observations and satellite data. Compared to the default scheme, the new scheme is more suitable for the simulation of cloud physics, reducing the simulation deviation of the liquid water path and droplet radius from 2 times to less than 1 time and significantly alleviating the overestimation of precipitation intensity and range of precipitation center. The average root-mean-square error is reduced by 22%. Our results can provide a scientific reference for improving precipitation forecasting and disaster prevention in this region.
基金primarily supported by the National Natural Science Foundation of China(Grant Nos.41975124,41730965)the National Key Research and Development Program of China(Grant No.2018YFC1507604)。
文摘During 19–21 July 2021,an extreme rainfall event occurred in Henan Province,China,during which a recordbreaking maximum hourly rainfall of 201.9 mm was recorded in Zhengzhou at 09 UTC July 20.In this study,the predictability of this extreme rainfall event is investigated using two convection-permitting ensemble forecast systems(CEFSs):one initialized from NCEP GEFS(named CEFS_GEFS)and the other initialized from time-lagged ERA5 data(named CEFS_ERA).Both are able to reproduce the daily heavy rainfall along the Taihang Mountains,but most members have significant position biases for the extreme rainfall in Zhengzhou.For the hourly rainfall,a few members are able to capture the evolution and propagation of extreme rainfall.However,all ensemble members underestimate the extreme hourly rainfall and have position errors of a few tens to a few hundreds of kilometers.Such results suggest that the predictability of the extreme hourly rainfall at the accuracy of city scale in Zhengzhou is low,especially by deterministic forecasting models,and the occurrence of the extreme requires many favorable conditions to happen simultaneously.In terms of the Brier score,CEFS_GEFS performs better than CEFS_ERA.The latter lacks spread,especially in regions with scarce rain,resulting in less dispersion in precipitation distributions and larger probability forecast error.When a neighborhood is applied,the probability of precipitation(POP)is significantly increased over Zhengzhou.While the traditional POP shows almost no skill for hourly rainfall≥25 mm h-1,the neighborhood POP significantly improves the forecast skill score,for both daily and hourly rainfall,suggesting higher predictability when spatial error among the ensemble members is allowed.
基金Supported by the National Key Research and Development Program of China (2019YFC1510301)Key Innovation Team Fund of the China Meteorological Administration (CMA2022ZD10)Basic Research Fund of the Chinese Academy of Meteorological Sciences(2021Y010)。
文摘The airborne two-dimensional stereo(2D-S) optical array probe has been operating for more than 10 yr, accumulating a large amount of cloud particle image data. However, due to the lack of reliable and unbiased classification tools,our ability to extract meaningful morphological information related to cloud microphysical processes is limited. To solve this issue, we propose a novel classification algorithm for 2D-S cloud particle images based on a convolutional neural network(CNN), named CNN-2DS. A 2D-S cloud particle shape dataset was established by using the 2D-S cloud particle images observed from 13 aircraft detection flights in 6 regions of China(Northeast, Northwest, North,East, Central, and South China). This dataset contains 33,300 cloud particle images with 8 types of cloud particle shape(linear, sphere, dendrite, aggregate, graupel, plate, donut, and irregular). The CNN-2DS model was trained and tested based on the established 2D-S dataset. Experimental results show that the CNN-2DS model can accurately identify cloud particles with an average classification accuracy of 97%. Compared with other common classification models [e.g., Vision Transformer(ViT) and Residual Neural Network(ResNet)], the CNN-2DS model is lightweight(few parameters) and fast in calculations, and has the highest classification accuracy. In a word, the proposed CNN-2DS model is effective and reliable for the classification of cloud particles detected by the 2D-S probe.
基金Supported by the National Key Research and Development Program of China (2019YFB2102003)National Natural Science Foundation of China (41805049 and 42075118)Postgraduate Research&Practice Innovation Program of Jiangsu Province (KYCX21_0979)。
文摘Continuous high spatial-resolution 10-day precipitation data are essential for crop growth services and phenological research.In this study,we first use the bidimensional empirical mode decomposition(BEMD)algorithm to decompose the digital elevation model(DEM)data and obtain high-frequency(OR3),intermediate-frequency(OR5),and low-frequency(OR8)margin terrains.Then,we propose a refined precipitation spatialization model,which uses ground-based meteorological observation data,integrated multi-satellite retrievals for global precipitation measurement(GPM IMERG)satellite precipitation products,DEM data,terrain decomposition data,prevailing precipitation direction(PPD)data,and other multisource data,to construct China's high-resolution 10-day precipitation data from2001 to 2018.The decomposition results show mountainous terrain from fine to coarse scales;and the influences of altitude,slope,and aspect on precipitation are better represented in the model after topography is decomposed.Moreover,terrain decomposition data can be added to the model simulation to improve the quality of the simulation product;the simulation quality of the model in summer is better than that in spring and autumn,and is relatively poor in winter;and OR5 and OR8 can be improved in the simulation,with better OR5 and OR8 dynamically selected.In addition,preprocessing the data before precipitation spatialization is particularly important.For example,adding 0.01to the 0 value of precipitation,multiplying the small value of precipitation less than 1 by 10,and performing the normal distributions transform(e.g.,Yeo–Johnson)on the data can improve the simulation quality.
基金supported by the National Key Research and Development Program of China(Grant No.2017YFC1501500)the Basic Research Fund of the Chinese Academy of Meteorological Sciences(Grants Nos.2020R004&2021Z003)the Chinese Meridian Project and the International Partnership Program of Chinese Academy of Sciences(Grant No.183311KYSB20200003)。
文摘Terrestrial gamma-ray flashes(TGFs)are high-energy emissions in thunderstorms that were discovered first by satellite-based and then by ground-based gamma-ray detectors with photon energy up to tens of Me V.TGFs are a natural highenergy phenomenon associated with lightning discharges that frequently occur during thunderstorms.However,their production mechanisms and associated processes are still unclear.TGF studies have already been a research spotlight in the atmospheric electricity and high-energy atmosphere research areas.In this paper,we review recent research progresses on TGF studies in the past decade,including TGF detection,the relationship between TGFs and lightning processes,and thunderstorm activities.Several unsolved important scientific questions are discussed.Results suggest that upward TGFs observed by satellite-based detectors are closely connected with the development of in-cloud upward negative leaders.They are usually generated in milliseconds of the initiation of upward negative leaders and may produce a kind of distinct radio emissions because of the generation and propagation of huge amounts of high-energy electrons.By contrast,its counterpart,i.e.,downward TGFs observed by ground-based gamma-ray detectors,is associated with different types of lightning processes,such as downward negative or upward positive leaders,the initial continuing current stage of rocket-triggered lightning flashes return stroke processes.Because of limited observations,how these downward TGFs are generated is still unclear.Benefiting from the development of state-of-the-art instruments with high temporal and spatial resolutions,new insights into the processes and mechanisms of TGFs will be achieved with coordinated observations from satellite-based and ground-based measurements.
基金supported by the National Natural Science Foundation of China under Grant Nos.42175005 and 41875054.
文摘Over the past four years,significant research has advanced our understanding of how external factors influence tropical cyclone(TC)intensity changes.Research on air-sea interactions shows that increasing the moisture disequilibrium is a very effective way to increase surface heatfluxes and that ocean salinity-stratification plays a non-negligible part in TC intensity change.Vertical wind shear from the environment induces vortex misalignment,which controls the onset of significant TC intensification.Blocking due to upper-level outflow from TCs can reduce the magnitude of vertical wind shear,making for TC intensification.Enhanced TC-trough interactions are vital for rapid intensification in some TC cases because of strengthened warm air advection,but upper-level troughs are found to limit TC intensification in other cases due to dry midlevel air intrusions and increased shear.Aerosol effects on TCs can be divided into direct effects involving aerosol-radiation interactions and indirect effects involving aerosol-cloud interactions.The radiation absorption by the aerosols can change the temperature profile and affect outer rainbands through changes in stability and microphysics.Sea spray and sea salt aerosols are more important in the inner region,where the aerosols increase precipitation and latent heating,promoting more intensification.For landfalling TCs,the intensity decay is initially more sensitive to surface roughness than soil moisture,and the subsequent decay is mainly due to the rapid reduction in surface moisturefluxes.These new insights further sharpen our understanding of the mechanisms by which external factors influence TC intensity changes.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos. 42025501, 42005009, 41875053, U2142203)the National Key Research and Development Program of China (Grant No. 2017YFC1501703)+1 种基金the Basic Research Fund of CAMS (Grant No. 2021Z003)the Open Research Program of the State Key Laboratory of Severe Weather (Grant No. 2020LASW-A01)。
文摘In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometers and two polarimetric radars.The broad distributions of specific drop size distribution(DSD) parameters are identified in heavy rainfall from the disdrometer observations, indicating obvious microphysical variability on the surface. A K-means clustering algorithm is adopted to objectively classify the disdrometer datasets into separate groups, and distinct DSD characteristics are found among these heavy rainfall groups. Combined with the supporting microphysical structures obtained through radar observations, comprehensive microphysical features of the DSD groups are derived. An extreme rainfall group is dominantly formed in the deep convection over the plain regions, where the high number of concentrations and large mean sizes of surface raindrops are underpinned by both active ice-phase processes and efficient warm-rain collision-coalescence processes in the vertical direction. Convection located near orographic regions is characterized by restricted ice-phase processes and high coalescence efficiency of liquid hydrometeors, causing the dominant DSD group to comprise negligible large raindrops. Multiple DSD groups can coexist within certain precipitation episodes at the disdrometer stations, indicating the potential microphysical variability during the passage of convective system on the plain regions.
基金sponsored by the National Natural Science Foundation of China(41790471)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20100304).
文摘The changes in near-surface wind speed(NWS)have a crucial influence on the wind power industry,and previous studies have indicated that NWS on global and China has declined continuously for decades under global warming.However,recently,the decreasing trend of global NWS has slowed down and even showed a recovery trend.Using the observation data of 831 weather stations of the China Meteorological Administration and the Japanese 55-year reanalysis data from 1970 to 2019,NWS changes in eastern China were analyzed and the possible influencing factors were discussed.Results show that winter NWS presented a decreasing trend from−0.29 m s^(−1) per decade(p<0.001)in 1970-1989 to−0.05 m s^(−1) per decade(p<0.01)in 1990-2019.Moreover,NWS exhibited a significant upward trend of 0.18 m s^(−1) per decade(p<0.1)in 2011-2019,resulting in a 19.6%per decade recovery of the wind power generation.A possible cause is asymmetric changes of the sea level pressure and near-surface air temperature differences between the mid-high latitudes(40°-60°N,80°-120°E)and low latitudes(20°-40°N,110°-140°E)altered the horizontal air pressure gradient.Furthermore,NWS changes were closely associated with the large-scale ocean-atmosphere circulations(LOACs).NWS at 77.4%of the stations in eastern China shows significant correlation(p<0.05)with the East Asian winter monsoon index,besides,the inter/multidecadal variability of NWS was considerably correlated to four LOACs,including Arctic oscillation(AO),North Atlantic oscillation(NAO),Pacific decadal oscillation(PDO),and El Niño-Southern Oscillation(ENSO).The time-series reconstructed by a multiple linear regression model based on above five LOACs matches well with the NWS.Interannual variability of NWS were significantly correlated to AO(−0.45,p<0.01)and NAO(−0.28,p<0.05),while the correlation between NWS and ENSO was weak.
基金Supported by the National Key Research and Development Program of China(2018YFC1506500)Foundation for Key Scientific Research of Jiangsu Meteorological Bureau(KZ202003)。
文摘Wide-field-of-view(WFV) imager that observes the earth environment with four solar reflective bands in a spatial resolution of 16 m is equipped on board Gaofen-1(GF-1) satellite. Chlorophyll-a(Chl-a) concentration in Lake Taihu, China from 2018 to 2019 is collected and collocated with GF-1 satellite data. This study develops a general and reliable estimation of Chl-a concentration from GF-1 WFV data under turbid inland water conditions. The collocated data are classified according to season and used in random forest(RF) regression to train models for retrieving the lake Chl-a concentration. A composite index is developed to select the most important variables in the models. The models trained for each season show a better performance than the model trained by using the whole year data in terms of the coefficient of determination(R^(2)) between retrievals and observations. Specifically, the R2 values in spring, summer, autumn, and winter are 0.88, 0.88, 0.94, and 0.74, respectively;whereas that using the whole year data is only 0.71. The Chl-a concentration in Lake Taihu exhibits an obvious seasonal change with the highest in summer, followed by autumn and spring, and the lowest in winter. The Chl-a concentration also displays an obvious spatial variation with season. A high concentration occurs mainly in the northwest of the lake. The temporal and spatial changes of Chl-a concentration are almost consistent with the changes in the areas and times of cyanobacteria blooms based on Moderate Resolution Imaging Spectroradiometer(MODIS) data. The proposed algorithm can be operated without a priori knowledge on atmospheric conditions and water quality. Our study also demonstrates that GF-1 data are increasingly valuable for monitoring the Chl-a concentration of inland water bodies in China at a high spatial resolution.
