Abstract:The choice of socioeconomic development pathways will affect the urban and rural development trend and bring a new urban and rural population distribution pattern in the future.Under the framework of IPCC Shared Socioeconomic Pathways (SSPs),this study applies the Sixth National Population Census data with consideration of demographic policy and current migration situation of mainland China to localize the fertility,mortality and migration parameters in the PDE model.Subsequently,the national and provincial scale urban and rural population in mainland China were projected under five SSPs.Research results show that:(1) urban population in mainland China will increase under the all five SSPs,with an increase of 220 million (SSP3) to 370 million (SSP5) people in 2015-2050.The rural population will decline continuously,with a decrease of about 110 million (SSP3) to 400 million (SSP5).The urbanization rate in mainland China will reach 67%-86% by 2050.(2) In the future,the urban population in the majority of provinces will increase,with the higher growth rate in the provinces of western China than eastern provinces.On the contrary,rural population of all provinces of mainland China will reduce significantly,with the decrease being more obvious in eastern provinces than that in western provinces.With relative to 2015,urban population in provinces including Tibet,Xinjiang,etc.can increase by more than two times in 2050.Meanwhile,rural population of most provinces will reduce by more than 60%.(3) In the future,the effect of natural growth on both urban and rural population will gradually change from positive to negative.The mechanical growth will have a positive effect on increase of urban population but negatively effects the size of rural population with a gradual decreasing impact.The difference of natural variability between eastern and western provinces is the main factor leading to the different changes of urban and rural population.

Abstract:Precipitation nowcasting is an important and challenging worldwide problem.Various techniques have been used to predict precipitation,but the accuracy of precipitation nowcasting is not high due to the highly nonlinear,random,and complex nature of precipitation.In recent years,with the rapid development of artificial intelligence technology,it has gradually penetrated into all aspects of people's lives,and the meteorological fields are no exception.Compared to traditional methods,such as numerical weather forecasting and optical flow methods,artificial neural networks can model non-linear systems,which makes the accuracy of precipitation nowcasting being greatly improved.In this article,we review the traditional methods and summarize the latest artificial intelligence methods used for short-term precipitation forecasting,and analyze the research directions to provide useful references for various types of researchers.

Abstract:With the rapid development of techniques such as cloud computing,mobile application and IoT,information technology nowadays has been fully integrated into our daily life.The need for security professionals and experts is growing due to the emerging security related issues.Information security education is the key to solve these problems.This paper gives a systematic description of the recent progress on research of information security teaching,which includes the difficulties faced by information security teaching,the issues to resolve,course curriculum design and course construction,teaching method research and practical experimental construction.Finally,future direction for information security teaching is given.

Abstract:The genesis potential index of the tropical cyclones in North and South Indian Oceans is calculated using monthly ERA5 reanalysis data from 1979-2019,and compared with the IBTrACS observations,in order to investigate the applicability of the genesis potential index to the study of the tropical cyclone characteristics in North and South Indian Oceans.It is found that the tropical cyclone genesis potential index can characterize the spatial distribution of tropical cyclones in North and South Indian Oceans,the bimodal structure of the seasonal variations of tropical cyclone frequency in North Indian Ocean,and the higher probability of tropical cyclone genesis in the South Indian Ocean than that in the North Indian Ocean.The latest IBTrACS v4.0 observations show that the annual number of tropical cyclones in the North Indian Ocean has increased by an average of 1.3 per decade over the past 40 years,which is mainly from the tropical depressions and tropical storms,while the annual number of tropical cyclones in the South Indian Ocean has decreased by an average of 2.8 per decade.The genesis potential index of the tropical cyclone can well describe the upward trend of the tropical cyclone number in North Indian Ocean,but the depiction of the trend of the tropical cyclone number in South Indian Ocean is inconsistent with observations,which merits further investigation in the future.

Abstract:The temporal-spatial distribution characteristics of summer water vapor transport over Tropical Indian Ocean (TIO) and its impact on precipitation over South Asia were investigated using monthly datasets of NCEP/NCAR,CMAP precipitation,and NOAA SST datasets.The first leading mode (EOF1) shows that anomalous water vapor transports from South China Sea to the Bay of Bengal,then separates into two branches.Anomalous water vapor in one branch transports westward to Indian Peninsula and the Arabian Sea,and weakens the westerly water vapor transport in the southern tip of the Indian Peninsula and the Indochina Peninsula,resulting in the decrease of precipitation in these regions.The second leading mode (EOF2) shows anomalous anticyclonic water vapor transport from tropical eastern Indian Ocean across western Indian Ocean,Arabian Sea,Indian Peninsula,and Indochina Peninsula.The southern part of the Bay of Bengal and India were controlled by anticyclonic anomalous water vapor transportation with anomalous water vapor divergence,which leads to less precipitation.Meanwhile,the cyclonic water varpor transport over northeast India leads to anomalous water vapor convergence.As a result,more precipitation occurred in northeast India.Furthermore,possible causes for these two modes were discussed.The EOF1 is closely associated with SST warming in the whole tropical Indian Ocean,and the EOF2 is linked with the tropical Indian Ocean Dipole (IOD).

Abstract:Based on rainfall data from Tropical Rainfall Measuring Mission (TRMM) satellite,and data such as potential height,wind speed,and vertical speed from the Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) satellite,the moving path of typhoon 1909 (Lekima) and its rainstorm in Zhejiang,Jiangsu and Shandong provinces are analyzed.It is found that Lekima is a northward typhoon,and its moving path is mainly affected by the subtropical anticyclone and typhoon 1910 (Krosa).During its moving north,the typhoon inverted trough and the cold air in westerly trough cooperated and caused a large amount of unstable energy,which result in heavy precipitation.In addition,the low-altitude jet stream and the westerly trough provide favorable dynamic rising conditions for precipitation.The southwest monsoon and typhoon Krosa,as sources of water vapor and energy for typhoon Lekima,provide abundant water vapor for the rainstorm.

Abstract:Two tropical cyclones (TCs) during spring 2017 have been selected as case studies to examine the effect of spring mini-warm pool (MWP) on TCs in the Bay of Bengal (BoB).The TC Maarutha existed over the BoB from 14^th to 17^th April of 2017,while TC Mora existed from 27^th to 30^th May of 2017.Existing datasets have been utilized to analyze major factors which influence TC activity in the region.It is identified that the TC-induced sea surface temperature (SST) cooling is evident during spring,but SST is relatively high just before the landfall of the TC Mora in the BoB.This observed warmer conditions are primarily due to the existence of spring MWP in the BoB.When the spring MWP is stronger (SST> 31℃),TC Mora induced mixing does not have any major influence on removing of the TC energy.In addition,the study reveals that the spring MWP suppresses the TC-induced negative effect by deepening the mixed-layer,decreasing cyclone heat potential and latent heat flux during spring in the BoB.

Abstract:The study mainly focuses on the seasonal variation of mass transport in the Eastern Indian Ocean (EIO) using ECCO2 model simulation data covering 20 yr period of 1992-2012.Three sections are selected at the equator,80°E,and 6°N in the EIO.The study reveals that the major seasonal transport across the equator and 80°E are roughly compensated.Most of the mass transport across the equator is confined to the upper 100 m,whereas that across 80°E it has complex structure associated with prominent monsoon currents,WJs,EUC and so on.Although the net upper mass transport across 6°N is small,there are strong boundary current and relatively weak interior currents.Significant changes of zonal current occur at 80°E.During the prevailing monsoon season,mass transport near the equator is dominated by westward gradient current due to WJs relaxation,while monsoon current dominates the rest region in the upper 100 m.Similarly,there is transition between westward gradient current due to EUC relaxation and eastward EUC for subsurface layer.During transition seasons,monsoon currents weaken.Instead,WJs and EUC dominate in upper 100 m and subsurface layer,respectively.Besides,the saline and warm water exchanges are discussed associated with monsoon currents,WJs,and EUC,which is helpful to understand both horizontal and vertical structures of temperature and salinity in the study domain.

Abstract:The rainfall is modeled and predicted based on the radar echo intensity data during January to October of 2016 in Zhejiang province,and the prediction results are compared between random forest method,BP neural network model,and convolutional neural network (CNN) model.The results show that the random forest model is relatively low in accuracy,and is easy to underestimate large rainfall intensity.The BP neural network and the CNN method perform better than random forest method,especially the convolutional neural network model.Compared with the other two machine learning methods,the CNN is better in prediction accuracy and large rainfall intensity fitting.

Abstract:The spatiotemporal distribution characteristics of different duration precipitations in Guangdong province were analyzed based on the hourly rain-gauge data from Guangdong's 86 National Weather Stations for period of 2001-2018.Results show that the accumulated precipitation would probably rise with the increase of averaged annual precipitation hours in most area of Guangdong,except in northern mountainous area.Annual hourly precipitation intensities show a decreasing trend from the southern coastal area to the northern inland area.Short duration precipitation is the main precipitation type in flood seasons,accounting for 65.3% of the annual precipitation events.While long duration precipitation contributes more (56.7%) to the annual accumulated precipitation.In the pre-flood seasons,short/moderate/long duration precipitations mostly occur in west/both sides of the Pearl River Delta and northwest/east and north of Guangdong,respectively.While in the post-flood season,short duration precipitation mostly occurs in Guangdong's inland area,with frequencies decreasing from northwest to southeast;moderate duration precipitation is unevenly distributed,and long duration precipitation mostly occurs in coastal area.In flood seasons,a two-peak pattern presents in diurnal variation of precipitation hours,and a single peak pattern inhabits in the diurnal variation of hourly precipitation intensity.The peak values of hourly precipitation intensities tend to occur in afternoon in inland area,or in time after midnight till next morning in areas along coast,some mountainous areas and the Pearl River Delta.

Abstract:Traditional control theory does not consider some uncertain factors in the industrial process,which has a significant impact on energy loss and system accuracy in production process.This paper considers the data-based optimization control strategies for non-Gaussian stochastic systems.Kernel density estimation was used to estimate the output probability density functions (PDFs) on the basis of collected output data.Firstly,the performance index function was established based on the control objectives.Secondly,the performance index function was optimized by a genetic algorithm.The simulation takes the grinding system as a model and uses PDFs to characterize the particle size distribution.Simulation results show that the genetic algorithm-based stochastic distribution control for non-Gaussian systems can effectively achieve the control target of the stochastically distributed control system and provides reference for practical industrial production.

Abstract:The problem of environmental pollution in meteorological information center has emerged with the continuous application and replacement of electronic equipments.The concept of sustainable development was introduced into management of meteorological information center in this paper.Inevitable contradictions and conflicts exist between the three pillars of sustainable development,namely the economy,the environment,and the society.Bipolar fuzzy set has powerful capabilities to describe such conflict information.Considering the dynamic process of multi-year sustainable development evaluation,a bipolar PROMETHEE dynamic approach is proposed to evaluate the sustainability of meteorological information centers in this paper.Examples are given to demonstrate its feasibility and effectiveness.

Abstract:The excitation and valve control of synchronous generator is described by a multi-variable nonlinear differential-algebraic subsystem model.A stabilization controller is designed based-on backstepping control method for such systems.Firstly,if the vector relative degree exists,then the controlled systems can be decoupled and transformed equivalently by a diffeomorphism and a feedback control.Then the backstepping method is adopted for the equivalent system to design the stabilization controller,through which the whole closed-loop systems is made asymptotically stable.Finally the simulation is conducted based on MATLAB,and the results show the validity of the method proposed in this paper.