Spatiotemporal characteristics of water exchange between the Andaman Sea and the Bay of Bengal

A high-resolution customized numerical model is used to analyze the water transport in the three major water passages between the Andaman Sea(AS)and the Bay of Bengal,i.e.,the Preparis Channel(PC),the Ten Degree Channel(TDC),and the Great Channel(GC),based on the daily averaged simulation results ranging from 2010 to 2019.Spectral analysis and Empirical Orthogonal Function(EOF)methods are employed to investigate the spatiotemporal variability of the water exchange and controlling mechanisms.The results of model simulation indicate that the net average transports of the PC and GC,as well as their linear trend,are opposite to that of the TDC.This indicates that the PC and the GC are the main inflow channels of the AS,while the TDC is the main outflow channel of the AS.The transport variability is most pronounced at surface levels and between 100 m and 200 m depth,likely affected by monsoons and circulation.A 182.4-d semiannual variability is consistently seen in all three channels,which is also evident in their second principal components.Based on sea level anomalies and EOF analysis results,this is primarily due to equatorial winds during the monsoon transition period,causing eastward movement of Kelvin waves along the AS coast,thereby affecting the spatiotemporal characteristics of the flow in the AS.The first EOF of the PC flow field section shows a split at 100 m deep,likely due to topography.The first EOF of the TDC flow field section is steady but has potent seasonal oscillations in its time series.Meanwhile,the first EOF of the GC flow field section indicates a stable surface inflow,probably influenced by the equatorial Indian Ocean’s eastward current.

Measurement of spatiotemporal characteristics of femtosecond laser pulses by a modified single-shot autocorrelation

To overcome the shortcomings of the single-shot autocorrelation SSA where only one pulse width is obtained when the SSA is applied to measure the pulse width of ultrashort laser pulses a modified SSA for measuring the spatiotemporal characteristics of ultrashort laser pulses at different spatial positions is proposed. The spatiotemporal characteristics of femtosecond laser pulses output from the Ti sapphire regenerative amplifier system are experimentally measured by the proposed method. It was found that the complex spatial characteristics are measured accurately.The pulse widths at different spatial positions are various which obey the Gaussian distribution.The pulse width at the same spatial position becomes narrow with the increase in input average power when femtosecond laser pulses pass through a carbon disulfide CS2 nonlinear medium.The experimental results verify that the proposed method is valid for measuring the spatiotemporal characteristics of ultrashort laser pulses at different spatial positions.

Spatiotemporal Characteristics of Rural Labor Migration in China: Evidence from the Migration Stability under New-type Urbanization

Although the factors affecting rural-to-urban migration have been discussed and analyzed in detail, few studies have examined the spatiotemporal dynamic characteristics of rural migrants’ employment and working-cities in the post-immigrate era, which is essential for the citizenization and social integration of new-type urbanization in China. This study uses survey data from rural migration laborers across the eastern, central, and western China to construct a comprehensive labor migration stability index, and compares the determinants of the migration stability of rural labor among cities and industries using Geodetector. The results are as follows: 1) Compared with the midwestern cities, eastern cities have attracted younger and more skilled rural labor, and industries with higher technical content have higher migration stability among rural laborers. 2) Rural laborers more often adapt to changes by changing employment instead of changing working-cities. 3) The individual experiences of rural laborers and urban characteristics have significant impacts on the stability of migration, and family and societal guanxi(Chinese interpersonal relationships) enhance migration stability. 4) A unified labor market and convenient transportation have somewhat slowed industrial transfers and labor backflow. This study enhances our understanding of the roles of industrial transfer and new-type urbanization in shaping the labor geography landscape and provides policy implications for the promotion of people-oriented urbanization.

Spatiotemporal characteristics of wind energy resources from 1960 to 2016 over China

In the paper,daily near-surface wind speed data from 462 stations are used to study the spatiotemporal characteristics of the annual and seasonal mean wind speed(MWS)and effective wind energy density(EWED)from 1960 to 2016,through the methods of kriging interpolation,leastsquares,correlation coefficient testing,and empirical orthogonal function(EOF)analysis.The results show that the annual MWS is larger than 3 m s-1 and the EWED is larger than 75 W m-2 in northern China and parts of coastal areas.However,the MWS and EWED values in southern China are all smaller than in northern China.Over the past 50 years,the annual and seasonal MWS in China has shown a significant decreasing trend,with the largest rate of decline in spring for northern China and winter for coastal areas.The annual MWS in some areas of Guangdong has an increasing trend,but it shows little change in southwestern China,South China,and west of Central China.Where the MWS is high,the rate of decline is also high.The main spatial distributions of the annual MWS and the annual EWED show high consistency,with a decreasing trend year by year.The decreasing trend of wind speed and wind energy resources in China is mainly related to global warming and land use/cover change.

Identifying the spatiotemporal characteristics of individual red bed landslides: a case study in Western Yunnan, China

Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach combining small baseline subset interferometric synthetic aperture radar(SBAS-InSAR), deep displacement monitoring, and engineering geological surveying to identify the deformation mechanisms and spatiotemporal characteristics of the Abi landslide, an individual landslide that occurred in the red bed area of Western Yunnan, China. Surface deformation time series indicated that a basic deformation range developed by March 2020. Based on In SAR results and engineering geological analysis, the landslide surface could be divided into three zones: an upper sliding zone(US), a lower uplifted zone(LU), and a toe zone(Toe). LU was affected by the structure of the sliding bed with variable inclination. Using deep displacement curves combined with the geological profile, a set of sliding surfaces were identified between different lithology. The groundwater level standardization index(GLSI) and deformation normalization index(DNI) showed different quadratic relationships between US and LU. Verification using the Pearson correlation analysis shows that the correlation coefficients between model calculated results and measured data are 0.7933 and 0.7577, respectively, indicating that the DNI-GLSI models are applicable. A fast and short-lived deformation sub stage(ID-Fast) in the initial deformation stage was observed, and ID-Fast was driven by concentrated rainfall.

Spatiotemporal characteristics and water budget of water cycle elements in different seasons in northeast China

In this paper, we study the spatiotemporal characteristics of precipitable water, precipitation, evaporation, and watervapor flux divergence in different seasons over northeast China and the water balance of that area. The data used in this paper is provided by the European Center for Medium-Range Weather Forecasts （ECMWF）. The results show that the spatial distributions of precipitable water, precipitation, and evaporation feature that the values of elements above in the southeastern area are larger than those in the northwestern area; in summer, much precipitation and evaporation occur in the Changbai Mountain region as a strong moisture convergence region; in spring and autumn, moisture divergence dominates the northeast of China; in winter, the moisture divergence and convergence are weak in this area. From 1979 to 2010, the total precipitation of summer and autumn in northeast China decreased significantly; especially from 1999 to 2010, the summer precipitation always demonstrated negative anomaly. Additionally, other elements in different seasons changed in a truly imperceptible way. In spring, the evaporation exceeded the precipitation in northeast China; in summer, the precipitation was more prominent; in autumn and winter, precipitation played a more dominating role than the evaporation in the northern part of northeast China, while the evaporation exceeded the precipitation in the southern part. The Interim ECMWF Re-Analysis （ERA-Interim） data have properly described the water balance of different seasons in northeast China. Based on ERA-Interim data, the moisture sinks computed through moisture convergence and moisture local variation are quite consistent with those computed through precipitation and evaporation, which proves that ERA- Interim data can be used in the research of water balance in northeast China. On a seasonal scale, the moisture convergence has a greater influence than the local moisture variation on a moisture sink, and the latter is variable slightly, generally as a constant. Likewise, in different seasons, the total precipitation has a much greater influence than the evaporation on the moisture sink.

Evaluation and spatiotemporal characteristics of glacier service value in the Qilian Mountains

Glaciers provide essential resources and services for human well-being and socio-economic development in arid regions.It is of great significance for regional socioeconomic sustainable development and environmental protection to conduct a glacier service value assessment and to analyze its spatiotemporal characteristics.Based on the first and second Chinese glacier inventories of the Qilian Mountains,a glacier service value evaluation system was established.Then the glacier service value and its spatiotemporal variation were assessed by combining the methods of unit area service price,value equivalent factor,and the glacier service value change index(GSCI).Three key results were obtained.(1)The total service value of glaciers in the Qilian Mountains for 2016 was 24.354 billion yuan.The main services provided were climate regulation and runoff regulation,which accounted for 60.58%and 33.14%of the total service value,respectively.Minor services were freshwater supply and hydropower,which accounted for 3.47%and 1.75%of the total value,respectively.The value of other types of services was about 0.259 billion yuan.(2)Among the various river systems in the Qilian Mountains,the Shule River basin had the highest glacier service value(7.771 billion yuan,31.91%),followed by the Haltang River basin(4.321 billion yuan,17.74%)and the Beida River basin(3.281 billion yuan,13.47%).In terms of administrative divisions,the glacier service value of the Qilian Mountains in Qinghai Province was 1.138 billion yuan higher than that of Gansu Province at 11.608 billion yuan,of which the services in the Haixi Mongol and Tibetan Autonomous Prefecture and Jiuquan City were valued at 11.124(45.68%)and 7.758(31.86%)billion yuan,respectively.(3)During the period from 1956 to 2010,the service value of glaciers in the Qilian Mountains declined by 435 million yuan,with an acceleration in the decreasing trend from west to east.

Quantifying the spatiotemporal characteristics of ecosystem services and livelihoods in China’s poverty-stricken counties

Understanding the coupling relationship between ecosystem services and poverty livelihoods is a prerequisite for poverty eradication and ecological protection in China.In this paper,we intended to quantify the coupling relationship between ecosystem services and poverty livelihoods in 717 poverty-stricken counties in China.First,we identified distinct levels of ecosystem services and poverty respectively in the poverty-stricken areas based on the ecosystem services subsystem index and poverty livelihoods subsystem index.Then,we calculated the coupling degree and coupling coordination degree between the ecosystem services and the poverty livelihoods in China^poverty-stricken counties from 2000 to 2015.Finally,we analyzed the temporal and spatial evolution of the coupling between ecosystem services and poverty livelihoods.The results indicate that the ecosystem services showed a trend of first decreasing and then increasing,while the poverty level showed an increased trend.In addition,the coupling relationship between ecosystem services and poverty livelihoods in poverty-stricken counties was also improved from 2000 to 2015.However,the coupling degree value or coupling coordination degree values in some counties or contiguous impoverished areas showed a decreased trend,the coupling relationship between ecosystem services and poverty livelihoods in those counties or areas was higher conflict.Future more,the coupling relationship in China's poverty-stricken counties was mainly intermediate conflict and low conflict,which need to improve in the future.Thus,it is suggested that effective measures are required to lift ecosystem services out of the poverty trap and into sustainable livelihoods.

Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin,China

Precipitable Water Vapor(PWV),as an important indicator of atmospheric water vapor,can be derived from Global Navigation Satellite System(GNSS)observations with the advantages of high precision and all-weather capacity.GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in mete-orology,particularly for severe weather conditions,for water vapor is not well sampled in the current meteorological observing systems.In this study,an empirical atmospheric weighted mean temperature(Tm)model for Guilin is estab-lished using the radiosonde data from 2012 to 2017.Then,the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017.The results show that the new Tm model in Guilin has better performance with the mean bias and Root Mean Square(RMS)of−0.51 and 2.12 K,respectively,compared with other widely used models.Moreover,the GNSS PWV estimates are validated with the data at Guilin radiosonde station.Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of−0.9 and 3.53 mm,respectively.Finally,an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed.It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements,and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall.It also reveals the moisture variation in several regions of Guilin during a heavy rainfall,which is significant for the moni-toring of rainfalls and weather forecast.

Spatiotemporal distribution characteristics of bridge deck runoff

The spatiotemporal characteristics of bridge deck runoff under a natural rainfall event are explored. The Taizhou Bridge is taken as a study case,and a hydrodynamic model based on the two-dimensional shallow water equations is used to analyze the runoff characteristics. The results indicate that the runoff velocity rate and depth are positively related to rainfall intensity,yet they have different response degrees to it. The inlet’s effect degree on lane water film has a positive relationship with rainfall intensity. A natural logarithm function( R^2= 0.706) can illustrate this relationship. However,the inlet’s effect degree on ponding at the curb shows a negative relationship with the rainfall intensity. A negative exponential function( R^2= 0.824) can reveal this relationship. With the decrease in the longitudinal slope SL,the ponding depth at the curb increases significantly at the bridge approach slab,whereas the lane water film thickness( WFT) is almost unchanged,but the lane WFT increases greatly at the location with the minimum longitudinal slope. It is concluded that the characteristics of the bridge deck runoff present apparent spatiotemporal differences,the inlet ’s effects on bridge deck runoff are quantitatively correlated with rainfall intensity, and the effective drainage measures are necessary for the bridge approach slab.

Variation Characteristics of Hydrothermal Resources Effectiveness Under the Background of Climate Change in Southern Rice Production Area of China

The spatiotemporal characteristics of hydrothermal resources in southern rice production area of China have changed under the background of climate change,and this change would affect the effectiveness of hydrothermal resources during local rice growing period.According to the cropping system subdivision in southern rice production area of China during 1980s,this study used climate data from 254 meteorological stations and phonological data from 168 agricultural observation stations in the south of China,and adopted 6 international evaluation indices about the effectiveness of hydrothermal resources to analyze the temporal and spatial characteristics of hydrothermal resources during the growing period of single cropping rice system and double cropping rice system for 16 planting zones in the whole study area.The results showed that：in southern rice production area of China,the effectiveness of thermal resources of single cropping rice area（SCRA） was less than that of double cropping rice area（DCRA）,whereas the effectiveness of thermal resources of both SARA and DCRA showed a decreasing trend.The index value of effective precipitation satisfaction of SCRA was higher than that of DCRA,nevertheless the index value of effective precipitation satisfaction of both SCRA and DCRA showed a decreasing trend.There was a significant linear relationship between effective thermal resource and water demand,likely water demand increased by 18 mm with every 100°C d increase of effective heat.Effective precipitation satisfaction index（EPSI） showed a negative correlation with effective heat,yet showed a positive correlation with effective precipitation.EPSI reduced by 1% when effective heat resource increased by 125°C d.This study could provide insights for policy makers,land managers or farmers to improve water and heat resource uses and rationally arrange rice production activities under global climate change condition.

Characteristics and chemical reactivity of biogenic volatile organic compounds from dominant forest species in the Jing-Jin-Ji area,China

Background:Biogenic volatile organic compounds(BVOCs)play an essential role in tropospheric atmospheric chemical reactions.There are few studies conducted on BVOCs emission of dominant forest species in the Jing-Jin-Ji area of China.Based on the field survey,forest resources data and the measured standard emission factors,the Guenther model developed in 1993(G93)was applied in this paper to estimate the emission of BVOCs from several dominant forest species(Platycladus orientalis,Quercus variabilis,Betula platyphylla,Populus tomentosa,Pinus tabuliformis,Robinia pseudoacacia,Ulmus pumila,Salix babylonica and Larix gmelinii)in the Jing-Jin-Ji area in 2017.Then the spatiotemporal emission characteristics and atmospheric chemical reactivity of these species were extensively evaluated.Results:The results showed that the total annual BVOCs emission was estimated to be 70.8 Gg C·year^(−1),consisting 40.5%(28.7 Gg C·year^(−1))of isoprene,36.0%(25.5 Gg C·year^(−1))of monoterpenes and 23.4%(16.6 Gg C·year^(−1))of other VOCs.The emissions from Platycladus orientalis,Quercus variabilis,Populus tomentosa and Pinus tabulaeformis contributed 56.1%,41.2%,36.0% and 31.1%,respectively.The total BVOCs emission from the Jing-Jin-Ji area accounted for 61.9% and 1.8%in summer and winter,respectively.Up to 28.8% of emission was detected from Chengde followed by Beijing with 24.9%,that mainly distributed in the Taihang Mountains and the Yanshan Mountains.Additionally,the Robinia pseudoacacia,Populus tomentosa,Quercus variabilis,and Pinus tabulaeformis contributed mainly to BVOCs reaction activity.Conclusions:The BVOCs emission peaked in summer(June,July,and August)and bottomed out in winter(December,January,and February).Chengde contributed the most,followed by Beijing.Platycladus orientalis,Quercus variabilis,Populus tomentosa,Pinus tabulaeformis and Robinia pseudoacacia represent the primary contributors to BVOCs emission and atmospheric reactivity,hence the planting of these species should be reduced.

GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems

Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.These characteristics can provide effective support in coordinated security control.However,traditional model-based frequencyprediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models.Therefore,this study presents a rolling frequency-prediction model based on a graph convolutional network(GCN)and a long short-term memory(LSTM)spatiotemporal network and named as STGCN-LSTM.In the proposed method,the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input.An improved GCN embedded with topology information is used to extract the spatial features,while the LSTM network is used to extract the temporal features.The spatiotemporal-network-regression model is further trained,and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information.The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response.The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems.

Spatial-temporal Evolution and Influencing Factors of Digital Financial Inclusion: County-level Evidence from China

The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.

Flow Direction Level Traffic Flow Prediction Based on a GCN-LSTM Combined Model

Traffic flow prediction plays an important role in intelligent transportation systems and is of great significance in the applications of traffic control and urban planning.Due to the complexity of road traffic flow data,traffic flow prediction has been one of the challenging tasks to fully exploit the spatiotemporal characteristics of roads to improve prediction accuracy.In this study,a combined flow direction level traffic flow prediction graph convolutional network(GCN)and long short-term memory(LSTM)model based on spatiotemporal characteristics is proposed.First,a GCN model is employed to capture the topological structure of the data graph and extract the spatial features of road networks.Additionally,due to the capability to handle long-term dependencies,the longterm memory is used to predict the time series of traffic flow and extract the time features.The proposed model is evaluated using real-world data,which are obtained from the intersection of Liuquan Road and Zhongrun Avenue in the Zibo High-Tech Zone of China.The results show that the developed combined GCNLSTM flow direction level traffic flow prediction model can perform better than the single models of the LSTM model and GCN model,and the combined ARIMA-LSTM model in traffic flow has a strong spatiotemporal correlation.

Changes of spring wind erosion based on wind erosion climate factor in the black soil region of Northeast China

The dry and windy climate and low ground cover in spring in the black soil region of Northeast China make the soil strongly affected by wind erosion,which seriously threatens the food security and ecological security of this region.In this paper,based on the daily observation data of 124 meteorological stations in study area from 1961 to 2020,seasonal and monthly wind erosion climate factor(C)in spring(March to May)were calculated by using the method proposed by the Food and Agriculture Organization of the United Nations(FAO),the wind erosion characterization in spring were systematically analyzed based on C by various statistical analysis methods.The results showed that in the past 60 years,spring wind erosion climate factor(CSp)and monthly C of the whole region and each province(region)all showed highly significant decreasing trend,but they began to show rebounded trend in the middle or late 2000s.CSp of the study area showed a significant upward trend since 2008 with an increase of 4.59(10a)^(-1).The main contributors to this upward trend are the changes of C in March and in April.For the four provinces(regions),CSp in Heilongjiang,Jilin,Liaoning and eastern Inner Mongolia all showed rebounded since 2008,2011,2008 and 2009,respectively.The rebounded trend of CSp in eastern Inner Mongolia was the most obvious with a tendency rate of 11.27(10a)^(-1),and its mutation occurred after 1984.The rebound trend of CSp in Heilongjiang Province takes the second place,with a trend rate of 4.72(10a)^(-1),but there’s no obvious time mutation characteristics.The spatial characteristics of CSpand monthly C are similar,showing decreasing characteristics centered on the typical black soil belt of Northeast China.Compared with 1961-1990,in the period from 1991 to 2020,the proportion of high value areas(CSp>35,monthly C>10)has decreased to varying degrees,while the proportion of low value areas(CSp≤10,monthly C≤4)has increased.The trends of seasonal and monthly C in 82.2%~87.7%of the stations show significant decreases at 95%confidence level.CSp is closely related to wind speed at 2m height,temperature difference,minimum temperature and precipitation in the same period,of which the correlation between CSp and wind speed is the strongest,indicating that the main control factor for CSp in the study area is wind speed,but the impact of the change of temperature and precipitation on CSp cannot be ignored.

Analysis of the Winter Cloud-to-Ground Lightning Activity and Its Synoptic Background in China during 2010-20

Cloud-to-ground(CG)lightning data and the ECMWF ERA-Interim reanalysis dataset are analyzed to gain insight into the spatiotemporal distribution and synoptic background of winter-season CG flashes between December 2010 and February 2020 in China.We identify three Winter Lightning Frequent Areas(WLAs):the southwest side of the Yunnan-Guizhou Plateau(WLA1),the east side of the Yunnan-Guizhou Plateau(WLA2),and the Poyang Lake Plain(WLA3).The CG lightning flashes most frequently occur at local midnight and have a monthly peak in February.The CG lightning in WLA1 is mostly generated in non-frontal weather;however,the lightning in WLA2 and WLA3 mostly occurs in frontal systems.The frontal circulation situation is divided into four typical types:transversal trough after high pressure,low vortex,confrontational convergence,and asymptotic convergence.In all typical weather patterns,the lightning occurs downstream of a 500 hPa trough and is accompanied by a southwesterly low-level jet.The convective parameters of winter thunderstorms differ greatly from those of summer thunderstorms.The maximum convective available potential energy(MCAPE)and K-index(KI)are more useful metrics than convective available potential energy(CAPE)and Showalter index(SI)during winter.This study further deepens the understanding of the distribution characteristics of winter CG lightning in China,which motivates further research to improve the ability of winter thunderstorm prediction.

SPATIAL DISTRIBUTION AND VARIATION TENDENCY OF DROUGHTS AND FLOODS IN HUNAN PROVINCE DURING THE PAST 36 YEARS

Using the 1970-2005 annual precipitation and evaporation data at 80 gauge stations across Hunan province,this work analyzes the spatial distribution and variation tendency of the local droughts and floods using linear regression,wavelet analysis,abrupt change,clusters,Empirical Orthogonal Function (EOF) and rotated EOF (REOF).Results show that there are four dry areas and three wet areas in Hunan.The whole province exhibits a moistening trend except some small areas in western,eastern and southern Hunan.The most prominent feature of annual precipitation is that the whole province basically displays a consistent variation tendency,as far as the dominant EOF mode is concerned.In addition,the spatial features of the other EOF modes include dry-wet differences,e.g.wet (or dry) in the north versus dry (or wet) in the south,wet (or dry) in the center and dry (or wet) in the surrounding areas.The distribution of the ratios of evaporation to precipitation exhibits both common features as well as spatial differences,which can be classified into four types:South Hunan,North Hunan,Northeast Hunan,and Central Hunan.There is an abrupt change from dry to wet patterns in the early 1990s.Generally,the drought-flood distribution presents variations of three periods.In the late 2000s,Hunan province will be in a period of drought,followed by a period of flood.

The Common Principal Component Analyses of Multi-RCMs

Based on a 10-year simulation of six Regional Climate Models(RCMs) in phase II of the Regional Climate Model Inter-Comparison Project(RMIP) for Asia,the multivariate statistical method of common principal components(CPCs) is used to analyze and compare the spatiotemporal characteristics of temperature and precipitation simulated by multi-RCMs over China,including the mean climate states and their seasonal transition,the spatial distribution of interannual variability,and the interannual variation.CPC is an effective statistical tool for analyzing the results of different models.Compared with traditional statistical methods,CPC analyses provide a more complete statistical picture for observation and simulation results.The results of CPC analyses show that the climatological means and the characteristics of seasonal transition over China can be accurately simulated by RCMs.However,large biases exist in the interannual variation in certain years or for individual models.

长三角城市群多情景暴雨人口暴露度时空演变分析

Population exposure is a dominant representation of rainstorm hazard risks. However, the refined precipitation data in temporal resolution and the comparison of exposure to different rainstorm events remain relatively unexplored. Hourly precipitation data from 165meteorological stations w used to investigate the spatiotemporal evolution of population exposure to different rainstorm scenarios in the prefecture-level cities for different periods and age groups. The Geographical Detector was adopted to quantitatively analyze the influencing factors and contribution rates to changes in population exposure during each period. The results revealed that population exposure to persistent rainstorms and abrupt rainstorms was low in the center and high in the surrounding areas, and the high exposure value decreased significantly in the 2010s. Additionally, as the duration of rainstorm events increased, the center of the high-value area of population exposure shifted southward. The distribution of population exposure was closely related to the age structure, demonstrating strong consistency with the distribution of different age groups. Except for abrupt rainstorms, the contribution rates of the average land GDP and urbanization rate to the exposure of all rainstorm scenarios increased significantly. This implies that the main factors influencing population exposure have shifted from meteorological to socioeconomic factors.