By using the mathematical statistics and classification,the artificial precipitation enhancement cases in Shenyang area were analyzed.The results showed that the precipitation enhancement weather systems mainly includ...By using the mathematical statistics and classification,the artificial precipitation enhancement cases in Shenyang area were analyzed.The results showed that the precipitation enhancement weather systems mainly included the northeast cold vortex,high-altitude trough,North China low-pressure,high-pressure rear and cold front cloud system.The appropriate height of precipitation enhancement was about 3 000-6 000 m in the middle and upper part of the cloud layer.The timing of precipitation enhancement should be in the radar's monitoring.The systems moved slowly or maintained stably in the developing or mature stages.The aircraft rainfall enhancement should be used in the stable and deep cloud layers.The rocket and antiaircraft gun rainfall enhancement should be used in the unstable move.展开更多
A brief assessment is provided of both the case against and the case for assigning priority to research on large-scale weather systems （LSWS）. The three-fold case against is based upon： the emergence of new overarc...A brief assessment is provided of both the case against and the case for assigning priority to research on large-scale weather systems （LSWS）. The three-fold case against is based upon： the emergence of new overarching themes in environmental science; the fresh emphasis upon other sub-disciplines of the atmospheric science; and the mature state of research and prediction of LSWS. The case for is also supported by three arguments. First is the assertion that LSWS research should not merely be an integral but a major component of future research related to both the new overarching themes and the other sub-disciplines. Second recent major developments in LSWS research, as epitomized by the paradigm shifts in the prediction strategy for LSWS and the emergence of the potential vorticity perspective, testify to the theme＇s on-going vibrancy. Third the field＇s future development, as exemplified by the new international THORPEX （The Observing System Research and Predictability Experiment） programme, embodies a perceptive dovetailing of intellectually challenging fundamental research with directed application（s） of societal and economic benefit. It is thus inferred that LSWS research, far from being in demise, will feature at the forefront of the new relationship between science and society.展开更多
Tropical Cyclones have their origins from areas of low atmospheric pressure over warm waters in the tropics or subtropics.We have carefully studied the interconnection between the West African Weather Systems(WAWS)and...Tropical Cyclones have their origins from areas of low atmospheric pressure over warm waters in the tropics or subtropics.We have carefully studied the interconnection between the West African Weather Systems(WAWS)and their subsequent development into Tropical Cyclones.Between 2004 and 2005,we studied the interconnection and the teleconnexion between the WAWS and the various occurrences展开更多
To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the ...To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.展开更多
Contemporary power network planning faces critical challenges from intensifying climate variability,including greenhouse effect amplification,extreme precipitation anomalies,and persistent thermal extremes.These meteo...Contemporary power network planning faces critical challenges from intensifying climate variability,including greenhouse effect amplification,extreme precipitation anomalies,and persistent thermal extremes.These meteorological disruptions compromise the reliability of renewable energy generation forecasts,particularly in photovoltaic(PV)systems.However,current predictive methodologies exhibit notable deficiencies in extreme weather monitoring,systematic transient phenomena analysis,and preemptive operational strategies,especially for cold-wave weather.In order to address these limitations,we propose a dual-phase data enhancement protocol that takes advantage of Time-series Generative Adversarial Networks(TimeGAN)for temporal pattern expansion and the K-medoids clustering algorithm for synthetic data quality verification.In order to better extract the spatiotemporal features of the model input simultaneously,we develop a hybrid neural architecture integrating Convolutional Neural Networks with Long Short-Term Memory modules(CNN-LSTM).To avoid the problem of hyperparameters getting trapped in local optimal solutions,we use the Whale Optimization Algorithm(WOA)algorithm to obtain the global optimal solution by simulating the hunting of humpback whales,further enhancing the generalization ability of the model.Experimental validation demonstrates performance improvements,with the proposed model achieving 30%higher prediction accuracy compared to Genetic Algorithm-Backpropagation Neural Network(GA-BPNN)and Radial Basis Function-Support Vector Regression(RBF-SVR)benchmarks,promoting the renewable energy prediction in data-constrained extreme weather scenarios for future power networks.展开更多
In recent years,there has been a pronounced increase in the frequency of extreme weather events.To compre hensively examine the impact of extreme weather on ecosystem services within the Wuhan Urban Agglomera tion(WUA...In recent years,there has been a pronounced increase in the frequency of extreme weather events.To compre hensively examine the impact of extreme weather on ecosystem services within the Wuhan Urban Agglomera tion(WUA),this study utilized meteorological station data,the Mann-Kendall(MK)test,and the Standardized Precipitation-Evapotranspiration Index(SPEI)to quantify the variation trends in heatwaves(HW)and droughts from 1961 to 2020.Then the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model was employed to evaluate and compare the differences in water yield and climate regulation ecosystem services un der various HW,droughts,and HW-drought combination scenarios.The results show that over the past 60 years,the temperature,duration,and frequency of HW have significantly increased in the WUA.Specifically,the high est HW temperature,total HW days,HW frequency,and average HW temperature showed changing trend of+0.17℃/decade,+1.4 day/decade,+0.19 event/decade,and+0.07℃/decade,respectively.The year 2000 was identified as a mutation year for HW,characterized by increased frequency and heightened severity thereafter.The SPEI value exhibited an insignificant upward trend,with 1980 marked as a mutation year,indicating a de creasing trend in drought occurrences after 1980.Heatwaves have a weakening effect on both water yield and climate regulation services,while drought significantly weakened water yield and had a relatively modest effect on climate regulation.During HW-drought composite period,the average monthly water yield showed a notable discrepancy of 60 mm compared to humid years.Besides,as heatwaves intensify,the area of low aggregation for ecosystem services expands,whereas the area of high aggregation decreases.This study provides a preliminary understanding of the impact of urban extreme weather on urban ecosystem services under changing climatic conditions.展开更多
Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and dr...Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.展开更多
In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to...In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.展开更多
Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC rec...Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.展开更多
Since the efficiency of photovoltaic(PV) power is closely related to the weather,many PV enterprises install weather instruments to monitor the working state of the PV power system.With the development of the soft mea...Since the efficiency of photovoltaic(PV) power is closely related to the weather,many PV enterprises install weather instruments to monitor the working state of the PV power system.With the development of the soft measurement technology,the instrumental method seems obsolete and involves high cost.This paper proposes a novel method for predicting the types of weather based on the PV power data and partial meteorological data.By this method,the weather types are deduced by data analysis,instead of weather instrument A better fault detection is obtained by using the support vector machines(SVM) and comparing the predicted and the actual weather.The model of the weather prediction is established by a direct SVM for training multiclass predictors.Although SVM is suitable for classification,the classified results depend on the type of the kernel,the parameters of the kernel,and the soft margin coefficient,which are difficult to choose.In this paper,these parameters are optimized by particle swarm optimization(PSO) algorithm in anticipation of good prediction results can be achieved.Prediction results show that this method is feasible and effective.展开更多
A drilling process monitor （DPM） for ground characterization of weathered granite is presented. The monitor is portable and can be mounted on a hydraulic rotary drilling rig to record various drilling parameters in ...A drilling process monitor （DPM） for ground characterization of weathered granite is presented. The monitor is portable and can be mounted on a hydraulic rotary drilling rig to record various drilling parameters in real time during normal subsurface investigation. The identification method for dominative and subsidiary interfaces has been established. The study reveals that the monitored drilling parameters are dependent on geotechnical materials and can be further applied to characterize ground interfaces. The t-test between manual logging and DPM logging has been carried out. The results show that the DPM has high accuracy in interfaces detection and well agreement with the manual logging. The findings show that the device and data analysis method are of potential application in subsurface drilling exploration in weathered granites. It also seems to have prospective uses in the determination of orebody boundary as well as in the detection of geohazards.展开更多
We present major and trace and Nd-isotopic data of the^1.67 Ga Buanji Group of southwestern Tanzania in order to constrain the nature of their protolith and the intensity of chemical weathering in the source terranes ...We present major and trace and Nd-isotopic data of the^1.67 Ga Buanji Group of southwestern Tanzania in order to constrain the nature of their protolith and the intensity of chemical weathering in the source terranes and make inferences on the nature of climatic conditions during the late Paleoproterozoic in the region. Major and trace element contents of the shales from three stratigraphic formations are comparable to those of the post-Archaean Australian Shale(PAAS) and the average Proterozoic Shale(PS). They are characterized by enrichments in LREE relative to HREE((La/Yb)_(CN)=9.07-13.2;(Gd/Yb)cN = 1.51-1.85) and negative Eu anomalies(Eu/Eu~* = 0.61-0.81); features which are comparable to those of PAAS and PS, indicating upper continental sources. Provenance proxy ratios,together with abundances of Cr, Ni, Co and V that increase up-stratigraphy suggest a decreasing input of felsic detritus up-stratigraphy. Chemical Indices of Alteration(CIA) for the lower, middle and upper Buanji formations are 81. 76 and 79, respectively. These indices largely indicate intermediate(ca. 60-80)to extreme(>80) weathering intensities of the precursor rocks. These observations may suggest the prevalence of warm, humid climates during the late Paleoproterozoic in the region.The lower Buanji Formation yielded a depleted mantle Nd model age(T_(DM)) of 、2100 Ma which indicates an Eburnean parentage. T_(DM) ages of 2486-2155 Ma and 2535-2379 Ma obtained from middle and upper Buanji formations, respectively, suggest a progressive increase of sedimentary input from the Tanzania Craton up-stratigraphy. The Eburnean T_(DM) ages of the lower Buanji rocks are attributed to their derivation through denudation of a decaying topographic high composed predominantly of rocks that were generated during the Palaeoproterozoic Ubendian orogenesis, possibly in the realm of Columbian Supercontinent assembly. Overlapping T_(DM) ages between the middle and upper Buanji formations suggest multiple sources involving mixing of detritus from Archaean cratonic rocks and the Palaeoproterozoic Ubendian belt. However, the Archaean signal is relatively more pronounced in the upper Buanji Formation, suggesting sediments derivation from the craton, to the north of the basin. The middle Buanji Formation suggests more diverse protolith,given the relatively larger spread in the T_(DM) ages. The Nb/Ta, Zr/Sm and Ce/Pb ratios coupled with the negative Nb and Ta anomalies, relative to primitive mantle, suggest that the tectonic setting of the source rocks for the Buanji sediments was a subduction zone akin to that generating modern sland Arc Basalts. Thus, we suggest that the Buanji's palaeogeography is consistent with an extensional continental backarc basin during the late Paleoproterozoic.展开更多
Double-maize cropping system is an effective option for coping with climate change in the North China Plain. However, the effects of changes in climate on the growth and yield of maize in the two seasons are poorly un...Double-maize cropping system is an effective option for coping with climate change in the North China Plain. However, the effects of changes in climate on the growth and yield of maize in the two seasons are poorly understood. Forty-six cultivars of maize with different requirements for growing degree days (GDD), categorized as high (H), medium (M) or low (L), and three cultivar combinations for two seasons as LH (using JD27 and DMY1 from category L in the first season;and YD629 and XD22 from category H in the second season), MM (using JX1 and LC3 from category M in the first season;and ZD958 and JX1 from category M in the second season) and HL (using CD30 and QY9 from category H in the first season;and XK10 and DMY3 from category L in the second season) were tested to examine the eco-physiological determinants of maize yield from 2015 to 2017. The correlations between the combinations of cultivars and grain yield were examined. The combination LH produced the highest annual grain yield and total biomass, regardless of the year. It was followed, in decreasing order, by MM and HL. Higher grain yield and biomass in LH were mainly due to the greater grain yield and biomass in the second season, which were influenced mainly by the lengths of the pre- and post-silking periods and the rate of plant growth (PGR). Temperature was the primary factor that influenced dry matter accumulation. In the first season, low temperatures during pre-silking decreased both the duration and PGR in LH, whereas high temperatures during post-silking decreased the PGR in MM and HL, resulting in no significant differences in biomass being observed among the three combinations. In the second season, high temperatures decreased both the PGR and pre- and post-silking duration in MM and HL, and consequently, the biomass of those two combinations were lower than that in LH. Moreover, because of lower GDD and radiation in the first season and higher grain yield in the second season, production efficiency of temperature and radiation (Ra) was the highest in LH. More importantly, differences in temperature and radiation in the two seasons significantly affected the rate and duration of growth in maize, and thereby affecting both dry matter and grain yield. Our study indicated that the combination of LH is the best for optimizing the double-maize system under changing climatic conditions in the North China Plain.展开更多
The feature bends and tunnels of mountainous expressways are often affected by bad weather,specif-ically rain and fog,which significantly threaten expressway safety and traffic efficiency.In order to solve this proble...The feature bends and tunnels of mountainous expressways are often affected by bad weather,specif-ically rain and fog,which significantly threaten expressway safety and traffic efficiency.In order to solve this problem,a vehicle–road coordination system based on the Internet of Things(IoT)is developed that can share vehicle–road information in real time,expand the environmental perception range of vehicles,and realize vehicle–road collaboration.It helps improve traffic safety and efficiency.Further,a vehicle–road cooperative driving assistance system model is introduced in this study,and it is based on IoT for improving the driving safety of mountainous expressways.Considering the influence of rain and fog on driving safety,the interaction between rainfall,water film,and adhesion coefficient is analyzed.An intelligent vehicle–road coordination assistance system is constructed that takes in information on weather,road parameters,and vehicle status,and takes the stopping sight distance model as well as rollover and sideslip model as boundary constraints.Tests conducted on a real expressway demonstrated that the assistance system model is helpful in bad weather conditions.This system could promote intelligent development of mountainous expressways.展开更多
In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Rea...In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Reanalysis（CFSR） data in the hydrologic simulation of watersheds, the Bahe River Basin was used as a case study. Two types of weather data（conventional weather data and CFSR weather data） were considered to establish a Soil and Water Assessment Tool（SWAT） model, which was used to simulate runoff from 2001 to 2012 in the basin at annual and monthly scales. The effect of both datasets on the simulation was assessed using regression analysis, Nash-Sutcliffe Efficiency（NSE）, and Percent Bias（PBIAS）. A CFSR weather data correction method was proposed. The main results were as follows.（1） The CFSR climate data was applicable for hydrologic simulation in the Bahe River Basin（R^2 of the simulated results above 0.50, NSE above 0.33, and ｜PBIAS｜ below 14.8. Although the quality of the CFSR weather data is not perfect, it achieved a satisfactory hydrological simulation after rainfall data correction.（2） The simulated streamflow using the CFSR data was higher than the observed streamflow, which was likely because the estimation of daily rainfall data by CFSR weather data resulted in more rainy days and stronger rainfall intensity than was actually observed. Therefore, the data simulated a higher base flow and flood peak discharge in terms of the water balance, except for some individual years.（3） The relation between the CFSR rainfall data（x） and the observed rainfall data（y） could berepresented by a power exponent equation： y=1.4789x0.8875（R2=0.98,P〈0.001）. There was a slight variation between the fitted equations for each station. The equation provides a theoretical basis for the correction of CFSR rainfall data.展开更多
Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling lo...Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.展开更多
A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid N...A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid NLS-4DVar data assimilation scheme,the operational Gridpoint Statistical Interpolation(GSI)−based data-processing and observation operators,and the widely used Weather Research and Forecasting numerical model.Drawing upon lessons learned from the superiority of the operational GSI analysis system,for its various observation operators and the ability to assimilate multiple-source observations,SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations.The multigrid NLS-4DVar assimilation framework is used for the analysis,which can adequately correct errors from large to small scales and accelerate iteration solutions.The analysis variables are model state variables,rather than the control variables adopted in the conventional 4DVar system.Currently,we have achieved the assimilation of conventional observations,and we will continue to improve the assimilation of radar and satellite observations in the future.SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments.In the case evaluation experiments,two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites.This showed that SNAP can absorb observations and improve the initial field,thereby improving the precipitation forecast.In the one-week cycling assimilation experiments,six-hourly assimilation cycles were run in one week.SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar(Four-dimensional Ensemble Variational)as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.展开更多
Air pollution has ever become a global major public health problem.Previous studies showed that air pollution is associated with excessive mortality and morbidity of respiratory disease[1-2].The extreme weather temper...Air pollution has ever become a global major public health problem.Previous studies showed that air pollution is associated with excessive mortality and morbidity of respiratory disease[1-2].The extreme weather temperature can impact human health and the thermal stresses can lead not only to direct deaths and illnesses,but also to aggravation of respiratory disease[3-4].Though the independent展开更多
Composite radar reflectivity data during April-September 2011-2015 are used to investigate and classify storms in south China(18-27°N;105-120°E). The storms appear most frequently in May. They are either lin...Composite radar reflectivity data during April-September 2011-2015 are used to investigate and classify storms in south China(18-27°N;105-120°E). The storms appear most frequently in May. They are either linear;cellular or nonlinear systems, taking up 29.45%, 24.51% and 46.04%, respectively, in terms of morphology. Linear systems are subdivided into six morphologies: trailing stratiform precipitation(TS), bow echoes(BE), leading stratiform precipitation(LS), embedded line(EL), no stratiform precipitation(NS) and parallel stratiform precipitation(PS). The TS and NS modes have the highest frequencies but there are only small samples of LS(0.61%) and PS(0.79%) modes.Severe convective wind(≥17m s-1at surface level) accounts for the highest percentage(35%) of severe convective weather events produced by cellular systems including individual cells(IC) and clusters of cells(CC). Short-duration heavy rainfall(≥50 mm h-1) and severe convective wind are the most common severe weather associated with TS and BE modes. Comparison of environmental physical parameters shows that cellular convection systems tend to occur in the environment with favorable thermal condition, substantial unstable energy and low precipitable water from the surface to300 hPa(PWAT). However, the environmental conditions favoring the initiation of linear systems feature strong vertical wind shear, high PWAT, and intense convective inhibition. The environmental parameters favoring the initiation of nonlinear systems are between those of the other two types of morphology.展开更多
文摘By using the mathematical statistics and classification,the artificial precipitation enhancement cases in Shenyang area were analyzed.The results showed that the precipitation enhancement weather systems mainly included the northeast cold vortex,high-altitude trough,North China low-pressure,high-pressure rear and cold front cloud system.The appropriate height of precipitation enhancement was about 3 000-6 000 m in the middle and upper part of the cloud layer.The timing of precipitation enhancement should be in the radar's monitoring.The systems moved slowly or maintained stably in the developing or mature stages.The aircraft rainfall enhancement should be used in the stable and deep cloud layers.The rocket and antiaircraft gun rainfall enhancement should be used in the unstable move.
文摘A brief assessment is provided of both the case against and the case for assigning priority to research on large-scale weather systems （LSWS）. The three-fold case against is based upon： the emergence of new overarching themes in environmental science; the fresh emphasis upon other sub-disciplines of the atmospheric science; and the mature state of research and prediction of LSWS. The case for is also supported by three arguments. First is the assertion that LSWS research should not merely be an integral but a major component of future research related to both the new overarching themes and the other sub-disciplines. Second recent major developments in LSWS research, as epitomized by the paradigm shifts in the prediction strategy for LSWS and the emergence of the potential vorticity perspective, testify to the theme＇s on-going vibrancy. Third the field＇s future development, as exemplified by the new international THORPEX （The Observing System Research and Predictability Experiment） programme, embodies a perceptive dovetailing of intellectually challenging fundamental research with directed application（s） of societal and economic benefit. It is thus inferred that LSWS research, far from being in demise, will feature at the forefront of the new relationship between science and society.
文摘Tropical Cyclones have their origins from areas of low atmospheric pressure over warm waters in the tropics or subtropics.We have carefully studied the interconnection between the West African Weather Systems(WAWS)and their subsequent development into Tropical Cyclones.Between 2004 and 2005,we studied the interconnection and the teleconnexion between the WAWS and the various occurrences
基金National Key R&D Program of China of the 13th Five-Year Plan(No.2018YFD1100704)。
文摘To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.
基金supported by Science and Technology Projects of Jiangsu Province(No.BE2022003)Science and Technology Projects of Jiangsu Province(No.BE2022003-5).
文摘Contemporary power network planning faces critical challenges from intensifying climate variability,including greenhouse effect amplification,extreme precipitation anomalies,and persistent thermal extremes.These meteorological disruptions compromise the reliability of renewable energy generation forecasts,particularly in photovoltaic(PV)systems.However,current predictive methodologies exhibit notable deficiencies in extreme weather monitoring,systematic transient phenomena analysis,and preemptive operational strategies,especially for cold-wave weather.In order to address these limitations,we propose a dual-phase data enhancement protocol that takes advantage of Time-series Generative Adversarial Networks(TimeGAN)for temporal pattern expansion and the K-medoids clustering algorithm for synthetic data quality verification.In order to better extract the spatiotemporal features of the model input simultaneously,we develop a hybrid neural architecture integrating Convolutional Neural Networks with Long Short-Term Memory modules(CNN-LSTM).To avoid the problem of hyperparameters getting trapped in local optimal solutions,we use the Whale Optimization Algorithm(WOA)algorithm to obtain the global optimal solution by simulating the hunting of humpback whales,further enhancing the generalization ability of the model.Experimental validation demonstrates performance improvements,with the proposed model achieving 30%higher prediction accuracy compared to Genetic Algorithm-Backpropagation Neural Network(GA-BPNN)and Radial Basis Function-Support Vector Regression(RBF-SVR)benchmarks,promoting the renewable energy prediction in data-constrained extreme weather scenarios for future power networks.
基金supported by the National Natural Science Foundation of China(Grants No.42371354,42375129,42371115)the Fundamental Research Funds for National Universities,China Uni-versity of Geosciences,Wuhan.
文摘In recent years,there has been a pronounced increase in the frequency of extreme weather events.To compre hensively examine the impact of extreme weather on ecosystem services within the Wuhan Urban Agglomera tion(WUA),this study utilized meteorological station data,the Mann-Kendall(MK)test,and the Standardized Precipitation-Evapotranspiration Index(SPEI)to quantify the variation trends in heatwaves(HW)and droughts from 1961 to 2020.Then the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model was employed to evaluate and compare the differences in water yield and climate regulation ecosystem services un der various HW,droughts,and HW-drought combination scenarios.The results show that over the past 60 years,the temperature,duration,and frequency of HW have significantly increased in the WUA.Specifically,the high est HW temperature,total HW days,HW frequency,and average HW temperature showed changing trend of+0.17℃/decade,+1.4 day/decade,+0.19 event/decade,and+0.07℃/decade,respectively.The year 2000 was identified as a mutation year for HW,characterized by increased frequency and heightened severity thereafter.The SPEI value exhibited an insignificant upward trend,with 1980 marked as a mutation year,indicating a de creasing trend in drought occurrences after 1980.Heatwaves have a weakening effect on both water yield and climate regulation services,while drought significantly weakened water yield and had a relatively modest effect on climate regulation.During HW-drought composite period,the average monthly water yield showed a notable discrepancy of 60 mm compared to humid years.Besides,as heatwaves intensify,the area of low aggregation for ecosystem services expands,whereas the area of high aggregation decreases.This study provides a preliminary understanding of the impact of urban extreme weather on urban ecosystem services under changing climatic conditions.
基金funded by the National Natural Science Foundation of China(42571311).
文摘Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.
基金supported by Institute of Information and Communications Technology Planning and Evaluation(IITP)grant funded by the Korean government(MSIT)(No.2019-0-01842,Artificial Intelligence Graduate School Program(GIST))supported by Korea Planning&Evaluation Institute of Industrial Technology(KEIT)grant funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea)(RS-2025-25448249+1 种基金Automotive Industry Technology Development(R&D)Program)supported by the Regional Innovation System&Education(RISE)programthrough the(Gwangju RISE Center),funded by the Ministry of Education(MOE)and the Gwangju Metropolitan City,Republic of Korea(2025-RISE-05-001).
文摘In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.
基金supported by the National Natural Science Foundation of China(Grant Nos.42077242 and 42171407)the Graduate Innovation Fund of Jilin University.
文摘Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.
基金supported by the National Natural Science Foundation of China(61433004,61473069)IAPI Fundamental Research Funds(2013ZCX14)+1 种基金supported by the Development Project of Key Laboratory of Liaoning Provincethe Enterprise Postdoctoral Fund Projects of Liaoning Province
文摘Since the efficiency of photovoltaic(PV) power is closely related to the weather,many PV enterprises install weather instruments to monitor the working state of the PV power system.With the development of the soft measurement technology,the instrumental method seems obsolete and involves high cost.This paper proposes a novel method for predicting the types of weather based on the PV power data and partial meteorological data.By this method,the weather types are deduced by data analysis,instead of weather instrument A better fault detection is obtained by using the support vector machines(SVM) and comparing the predicted and the actual weather.The model of the weather prediction is established by a direct SVM for training multiclass predictors.Although SVM is suitable for classification,the classified results depend on the type of the kernel,the parameters of the kernel,and the soft margin coefficient,which are difficult to choose.In this paper,these parameters are optimized by particle swarm optimization(PSO) algorithm in anticipation of good prediction results can be achieved.Prediction results show that this method is feasible and effective.
基金This work is financially supported by the Research Grant Council of HKSAR Government and Hong Kong Jockey Club CharitiesTrust.
文摘A drilling process monitor （DPM） for ground characterization of weathered granite is presented. The monitor is portable and can be mounted on a hydraulic rotary drilling rig to record various drilling parameters in real time during normal subsurface investigation. The identification method for dominative and subsidiary interfaces has been established. The study reveals that the monitored drilling parameters are dependent on geotechnical materials and can be further applied to characterize ground interfaces. The t-test between manual logging and DPM logging has been carried out. The results show that the DPM has high accuracy in interfaces detection and well agreement with the manual logging. The findings show that the device and data analysis method are of potential application in subsurface drilling exploration in weathered granites. It also seems to have prospective uses in the determination of orebody boundary as well as in the detection of geohazards.
基金the Swedish International Development Agency (Sida) (Contribution No.75000515) through the "Geology and mineralization of the Precambrian volcanic and associated plutonic rocks of SW Tanzania" project under the Earth Science Programme of CoNAS, University of Dar es Salaam (2009-2013 extended to June 2015)
文摘We present major and trace and Nd-isotopic data of the^1.67 Ga Buanji Group of southwestern Tanzania in order to constrain the nature of their protolith and the intensity of chemical weathering in the source terranes and make inferences on the nature of climatic conditions during the late Paleoproterozoic in the region. Major and trace element contents of the shales from three stratigraphic formations are comparable to those of the post-Archaean Australian Shale(PAAS) and the average Proterozoic Shale(PS). They are characterized by enrichments in LREE relative to HREE((La/Yb)_(CN)=9.07-13.2;(Gd/Yb)cN = 1.51-1.85) and negative Eu anomalies(Eu/Eu~* = 0.61-0.81); features which are comparable to those of PAAS and PS, indicating upper continental sources. Provenance proxy ratios,together with abundances of Cr, Ni, Co and V that increase up-stratigraphy suggest a decreasing input of felsic detritus up-stratigraphy. Chemical Indices of Alteration(CIA) for the lower, middle and upper Buanji formations are 81. 76 and 79, respectively. These indices largely indicate intermediate(ca. 60-80)to extreme(>80) weathering intensities of the precursor rocks. These observations may suggest the prevalence of warm, humid climates during the late Paleoproterozoic in the region.The lower Buanji Formation yielded a depleted mantle Nd model age(T_(DM)) of 、2100 Ma which indicates an Eburnean parentage. T_(DM) ages of 2486-2155 Ma and 2535-2379 Ma obtained from middle and upper Buanji formations, respectively, suggest a progressive increase of sedimentary input from the Tanzania Craton up-stratigraphy. The Eburnean T_(DM) ages of the lower Buanji rocks are attributed to their derivation through denudation of a decaying topographic high composed predominantly of rocks that were generated during the Palaeoproterozoic Ubendian orogenesis, possibly in the realm of Columbian Supercontinent assembly. Overlapping T_(DM) ages between the middle and upper Buanji formations suggest multiple sources involving mixing of detritus from Archaean cratonic rocks and the Palaeoproterozoic Ubendian belt. However, the Archaean signal is relatively more pronounced in the upper Buanji Formation, suggesting sediments derivation from the craton, to the north of the basin. The middle Buanji Formation suggests more diverse protolith,given the relatively larger spread in the T_(DM) ages. The Nb/Ta, Zr/Sm and Ce/Pb ratios coupled with the negative Nb and Ta anomalies, relative to primitive mantle, suggest that the tectonic setting of the source rocks for the Buanji sediments was a subduction zone akin to that generating modern sland Arc Basalts. Thus, we suggest that the Buanji's palaeogeography is consistent with an extensional continental backarc basin during the late Paleoproterozoic.
基金This study was supported by the National Key Research and Development Program of China(2016YFD0300207 and 2017YFD0300305).
文摘Double-maize cropping system is an effective option for coping with climate change in the North China Plain. However, the effects of changes in climate on the growth and yield of maize in the two seasons are poorly understood. Forty-six cultivars of maize with different requirements for growing degree days (GDD), categorized as high (H), medium (M) or low (L), and three cultivar combinations for two seasons as LH (using JD27 and DMY1 from category L in the first season;and YD629 and XD22 from category H in the second season), MM (using JX1 and LC3 from category M in the first season;and ZD958 and JX1 from category M in the second season) and HL (using CD30 and QY9 from category H in the first season;and XK10 and DMY3 from category L in the second season) were tested to examine the eco-physiological determinants of maize yield from 2015 to 2017. The correlations between the combinations of cultivars and grain yield were examined. The combination LH produced the highest annual grain yield and total biomass, regardless of the year. It was followed, in decreasing order, by MM and HL. Higher grain yield and biomass in LH were mainly due to the greater grain yield and biomass in the second season, which were influenced mainly by the lengths of the pre- and post-silking periods and the rate of plant growth (PGR). Temperature was the primary factor that influenced dry matter accumulation. In the first season, low temperatures during pre-silking decreased both the duration and PGR in LH, whereas high temperatures during post-silking decreased the PGR in MM and HL, resulting in no significant differences in biomass being observed among the three combinations. In the second season, high temperatures decreased both the PGR and pre- and post-silking duration in MM and HL, and consequently, the biomass of those two combinations were lower than that in LH. Moreover, because of lower GDD and radiation in the first season and higher grain yield in the second season, production efficiency of temperature and radiation (Ra) was the highest in LH. More importantly, differences in temperature and radiation in the two seasons significantly affected the rate and duration of growth in maize, and thereby affecting both dry matter and grain yield. Our study indicated that the combination of LH is the best for optimizing the double-maize system under changing climatic conditions in the North China Plain.
基金the Project of Zhejiang Provincial Transportation Department(No.2020059)。
文摘The feature bends and tunnels of mountainous expressways are often affected by bad weather,specif-ically rain and fog,which significantly threaten expressway safety and traffic efficiency.In order to solve this problem,a vehicle–road coordination system based on the Internet of Things(IoT)is developed that can share vehicle–road information in real time,expand the environmental perception range of vehicles,and realize vehicle–road collaboration.It helps improve traffic safety and efficiency.Further,a vehicle–road cooperative driving assistance system model is introduced in this study,and it is based on IoT for improving the driving safety of mountainous expressways.Considering the influence of rain and fog on driving safety,the interaction between rainfall,water film,and adhesion coefficient is analyzed.An intelligent vehicle–road coordination assistance system is constructed that takes in information on weather,road parameters,and vehicle status,and takes the stopping sight distance model as well as rollover and sideslip model as boundary constraints.Tests conducted on a real expressway demonstrated that the assistance system model is helpful in bad weather conditions.This system could promote intelligent development of mountainous expressways.
基金International Partnership Program of Chinese Academy of Sciences,No.131551KYSB20160002 National Natural Science Foundation of China,No.41401602+2 种基金 Natural Science Basic Research Plan in Shaanxi Province of China,No.2014JQ2-4021 Key Scientific and Technological Innovation Team Plan of Shaanxi Province,No.2014KCT-27 Graduate Student Innovation Project of Northwest University,No.YZZ15011
文摘In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Reanalysis（CFSR） data in the hydrologic simulation of watersheds, the Bahe River Basin was used as a case study. Two types of weather data（conventional weather data and CFSR weather data） were considered to establish a Soil and Water Assessment Tool（SWAT） model, which was used to simulate runoff from 2001 to 2012 in the basin at annual and monthly scales. The effect of both datasets on the simulation was assessed using regression analysis, Nash-Sutcliffe Efficiency（NSE）, and Percent Bias（PBIAS）. A CFSR weather data correction method was proposed. The main results were as follows.（1） The CFSR climate data was applicable for hydrologic simulation in the Bahe River Basin（R^2 of the simulated results above 0.50, NSE above 0.33, and ｜PBIAS｜ below 14.8. Although the quality of the CFSR weather data is not perfect, it achieved a satisfactory hydrological simulation after rainfall data correction.（2） The simulated streamflow using the CFSR data was higher than the observed streamflow, which was likely because the estimation of daily rainfall data by CFSR weather data resulted in more rainy days and stronger rainfall intensity than was actually observed. Therefore, the data simulated a higher base flow and flood peak discharge in terms of the water balance, except for some individual years.（3） The relation between the CFSR rainfall data（x） and the observed rainfall data（y） could berepresented by a power exponent equation： y=1.4789x0.8875（R2=0.98,P〈0.001）. There was a slight variation between the fitted equations for each station. The equation provides a theoretical basis for the correction of CFSR rainfall data.
文摘Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.
基金the National Key Research and Development Program of China(Grant No.2016YFA0600203)the National Natural Science Foundation of China(Grant No.41575100)+1 种基金the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.QYZDY-SSW-DQC012)the CMA Special Public Welfare Research Fund(Grant No.GYHY201506002).
文摘A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid NLS-4DVar data assimilation scheme,the operational Gridpoint Statistical Interpolation(GSI)−based data-processing and observation operators,and the widely used Weather Research and Forecasting numerical model.Drawing upon lessons learned from the superiority of the operational GSI analysis system,for its various observation operators and the ability to assimilate multiple-source observations,SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations.The multigrid NLS-4DVar assimilation framework is used for the analysis,which can adequately correct errors from large to small scales and accelerate iteration solutions.The analysis variables are model state variables,rather than the control variables adopted in the conventional 4DVar system.Currently,we have achieved the assimilation of conventional observations,and we will continue to improve the assimilation of radar and satellite observations in the future.SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments.In the case evaluation experiments,two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites.This showed that SNAP can absorb observations and improve the initial field,thereby improving the precipitation forecast.In the one-week cycling assimilation experiments,six-hourly assimilation cycles were run in one week.SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar(Four-dimensional Ensemble Variational)as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.
基金supported by the Gong-Yi Program of China Meteorological Administration(GYHY201106034)National Natural Science Foundation of China(41075103)
文摘Air pollution has ever become a global major public health problem.Previous studies showed that air pollution is associated with excessive mortality and morbidity of respiratory disease[1-2].The extreme weather temperature can impact human health and the thermal stresses can lead not only to direct deaths and illnesses,but also to aggravation of respiratory disease[3-4].Though the independent
基金National Key Research and Development Program of China(2019YFC1510400)National Natural Science Foundation of China(41975056,41675045)。
文摘Composite radar reflectivity data during April-September 2011-2015 are used to investigate and classify storms in south China(18-27°N;105-120°E). The storms appear most frequently in May. They are either linear;cellular or nonlinear systems, taking up 29.45%, 24.51% and 46.04%, respectively, in terms of morphology. Linear systems are subdivided into six morphologies: trailing stratiform precipitation(TS), bow echoes(BE), leading stratiform precipitation(LS), embedded line(EL), no stratiform precipitation(NS) and parallel stratiform precipitation(PS). The TS and NS modes have the highest frequencies but there are only small samples of LS(0.61%) and PS(0.79%) modes.Severe convective wind(≥17m s-1at surface level) accounts for the highest percentage(35%) of severe convective weather events produced by cellular systems including individual cells(IC) and clusters of cells(CC). Short-duration heavy rainfall(≥50 mm h-1) and severe convective wind are the most common severe weather associated with TS and BE modes. Comparison of environmental physical parameters shows that cellular convection systems tend to occur in the environment with favorable thermal condition, substantial unstable energy and low precipitable water from the surface to300 hPa(PWAT). However, the environmental conditions favoring the initiation of linear systems feature strong vertical wind shear, high PWAT, and intense convective inhibition. The environmental parameters favoring the initiation of nonlinear systems are between those of the other two types of morphology.
