Roles of Upper-Level Descending Inflow in Moat Development in Simulated Tropical Cyclones with Secondary Eyewall Formation

This study investigated the effects of upper-level descending inflow(ULDI)associated with inner-eyewall convection on the formation of the moat in tropical cyclones(TCs)with secondary eyewall formation(SEF).In our numerical experiments,a clear moat with SEF occurred in TCs with a significant ULDI,while no SEF occurred in TCs without a significant ULDI.The eyewall convection developed more vigorously in the control run.A ULDI occurred outside the inner-eyewall convection,where it was symmetrically unstable.The ULDI was initially triggered by the diabatic warming released by the inner eyewall and later enhanced by the cooling below the anvil cloud.The ULDI penetrated the outer edge of the inner eyewall with relatively dry air and prevented excessive solid-phase hydrometeors from being advected further outward.It produced extensive sublimation cooling of falling hydrometeors between the eyewall and the outer convection.The sublimation cooling resulted in negative buoyancy and further induced strong subsidence between the eyewall and the outer convection.As a result,a clear moat was generated.Development of the moat in the ongoing SEF prevented the outer rainband from moving farther inward,helping the outer rainband to symmetrize into an outer eyewall.In the sensitivity experiment,no significant ULDI formed since the eyewall convection was weaker,and the eyewall anvil developed relatively lower,meaning the formation of a moat and thus an outer eyewall was less likely.This study suggests that a better-represented simulation of inner-eyewall convective structures and distribution of the solid-phase hydrometeors is important to the prediction of SEF.

Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts

This study investigated the growth of forecast errors stemming from initial conditions(ICs),lateral boundary conditions(LBCs),and model(MO)perturbations,as well as their interactions,by conducting seven 36 h convectionallowing ensemble forecast(CAEF)experiments.Two cases,one with strong-forcing(SF)and the other with weak-forcing(WF),occurred over the Yangtze-Huai River basin(YHRB)in East China,were selected to examine the sources of uncertainties associated with perturbation growth under varying forcing backgrounds and the influence of these backgrounds on growth.The perturbations exhibited distinct characteristics in terms of temporal evolution,spatial propagation,and vertical distribution under different forcing backgrounds,indicating a dependence between perturbation growth and forcing background.A comparison of the perturbation growth in different precipitation areas revealed that IC and LBC perturbations were significantly influenced by the location of precipitation in the SF case,while MO perturbations were more responsive to convection triggering and dominated in the WF case.The vertical distribution of perturbations showed that the sources of uncertainties and the performance of perturbations varied between SF and WF cases,with LBC perturbations displaying notable case dependence.Furthermore,the interactions between perturbations were considered by exploring the added values of different source perturbations.For the SF case,the added values of IC,LBC,and MO perturbations were reflected in different forecast periods and different source uncertainties,suggesting that the combination of multi-source perturbations can yield positive interactions.In the WF case,MO perturbations provided a more accurate estimation of uncertainties downstream of the Dabie Mountain and need to be prioritized in the research on perturbation development.

Characteristics of Lightning Activity in Southeast China and its Relation to the Atmospheric Background

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.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

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.

Quantitative Precipitation Forecast Experiment Based on Basic NWP Variables Using Deep Learning

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.

On the Key Dynamical Processes Supporting the 21.7 Zhengzhou Record-breaking Hourly Rainfall in China

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.

Objective Identification and Climatic Characteristics of Heavy-Precipitation Northeastern China Cold Vortexes

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.

Near Homogeneous Microphysics of the Record-Breaking 2020 Summer Monsoon Rainfall during the Northward Migration over East China

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.

Influence of sea-land breeze on the formation and dissipation of severe dense fog and its burst reinforcement in the Yellow Sea coastal area,China

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.

Impact of Atmospheric Transmittance and NLTE Correction on Simulation of High Spectral Infrared Atmospheric Sounder onboard FY-3E

With the launch of the first civilian early-morning orbit satellite Fengyun-3E(FY-3E),higher demands are placed on the accuracy of radiative transfer simulations for hyperspectral infrared data.Therefore,several key issues are investigated in the paper.First,the accuracy of the fast atmospheric transmittance model implemented in the Advanced Research and Modeling System(ARMS)has been evaluated with both the line-by-line radiative transfer model(LBLRTM)and the actual satellite observations.The results indicate that the biases are generally less than 0.25 K when compared to the LBLRTM,while below 1.0 K for the majority of the channels when compared to the observations.However,during both comparisons,significant biases are observed in certain channels.The accuracy of Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard FY-3E is comparable to,and even superior to that of the Cross-track Infrared Sounder(CrIS)onboard NOAA-20.Furthermore,apodization is a crucial step in the processing of hyperspectral data in that the apodization function is utilized as the instrument channel spectral response function to produce the satellite channel-averaged transmittance.To further explore the difference between the apodized and unapodized simulations,Sinc function is adopted in the fast transmittance model.It is found that the use of Sinc function can make the simulations fit the original satellite observations better.When simulating with apodized observations,the use of Sinc function exhibits larger deviations compared to the Hamming function.Moreover,a correction module is applied to minimize the impact of Non-Local Thermodynamic Equilibrium(NLTE)in the shortwave infrared band.It is verified that the implementation of the NLTE correction model leads to a significant reduction in the bias between the simulation and observation for this band.

Azimuthal Variations of the Convective-scale Structure in a Simulated Tropical Cyclone Principal Rainband

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.

Relationships between Cloud Droplet Spectral Relative Dispersion and Entrainment Rate and Their Impacting Factors

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.

Simulation and future projection of the mixed layer depth and subduction process in the subtropical Southeast Pacific

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.

Meteorological Characteristics of a Typical Dust Weather Process in the Eastern Qinghai-Tibet Plateau

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.

Anomalies of Precipitation over China on Days with Tropical Cyclone Activity over the Bay of Bengal: Role of Moisture Transport

Tropical cyclones over the Bay of Bengal(BoBTC)affect the precipitation over China,with distinct seasonal and daily variabilities.This study quantitatively examines the daily standardized precipitation anomalies(SPAs)over China on the days with BoBTC activities(storm-days)and related circulations,based on rainfall measurements at surface meteorological stations and ECMWF reanalysis data on a 0.25°×0.25°resolution during 1979-2019.Significant positive SPA is found over the stations in the two adjacent regions around BoB(Southwest China in May/November and southern Tibetan Plateau in October)and three distant regions(Southeast China and the northeastern boundary of the Qinghai-Tibet Plateau in May,and central North China in October).The SPA distributions are remarkably consistent with the integrated water vapor transport(IVT)anomalies.Enhanced IVT is found associated with the interaction between southwesterly(southerly)of the BoBTC circulation and low-level monsoonal flow in May(midlevel westerly in winter months).The probabilities of extreme precipitation(EP)occurrences over the above regions all increase on storm-days.For adjacent regions,EP is significantly correlated with the northward IVT anomalies to the east of BoBTC circulation,which strengthen the water vapor input through the southern border.Such IVT anomalies are stronger in May,benefited by the deep monsoonal southwesterlies than those in November.For distant regions,EP is more closely related to the IVT anomaly extending back from BoB.Enhanced moisture from BoB concentrates along a local low-level convergence line over Southeast China,being further facilitated by coexistence of the BoBTC depression and midlevel westerly trough in midlatitudes.Our results highlight the interactions between BoBTCs and local weather systems that influence the general precipitation anomalies and occurrence of EP over China,especially over distant regions.

Improvement of cloud microphysical parameterization and its advantages in simulating precipitation along the Sichuan-Xizang Railway

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.

Predictability and skill of convection-permitting ensemble forecast systems in predicting the record-breaking“21·7”extreme rainfall event in Henan Province,China

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.

A review of recent research progress on the effect of external influences on tropical cyclone intensity change

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.

Shape Classification of Cloud Particles Recorded by the 2D-S Imaging Probe Using a Convolutional Neural Network

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.

Refined Spatialization of 10-Day Precipitation in China Based on GPM IMERG Data and Terrain Decomposition Using the BEMD Algorithm

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.