The net primary productivity(NPP)of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change.While the temporal effect driven by ecosystem processes on NPP variatio...The net primary productivity(NPP)of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change.While the temporal effect driven by ecosystem processes on NPP variations is well-documented,spatial variations(from local to regional scales)remain inadequately understood.To evaluate the scale-dependent effects of productivity,predictions from the Biome-BGC model were compared with moderate-resolution imaging spectroradiometer(MODIS)and biometric NPP data in a large temperate forest region at both local and regional levels.Linear mixed-effect models and variance partitioning analysis were used to quantify the effects of environmental heterogeneity and trait variation on simulated NPP at varying spatial scales.Results show that NPP had considerable predictability at the local scale,with a coefficient of determination(R^(2))of 0.37,but this predictability declined significantly to 0.02 at the regional scale.Environmental heterogeneity and photosynthetic traits collectively explained 94.8%of the local variation in NPP,which decreased to 86.7%regionally due to the reduced common effects among these variables.Locally,the leaf area index(LAI)predominated(34.6%),while at regional scales,the stomatal conductance and maximum carboxylation rate were more influential(41.1%).Our study suggests that environmental heterogeneity drives the photosynthetic processes that mediate NPP variations across spatial scales.Incorporating heterogeneous local conditions and trait variations into analyses could enhance future research on the relationship between climate and carbon cycles at larger scales.展开更多
Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation ...Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.展开更多
The variability of the sea surface temperature（SST） in the China seas has been studied in seasonal,interannual and interdecadal scales based on the monthly data of HadISST spanning from 1870 to 2007. The main result...The variability of the sea surface temperature（SST） in the China seas has been studied in seasonal,interannual and interdecadal scales based on the monthly data of HadISST spanning from 1870 to 2007. The main results obtained are SST in the China offshore changes most actively at the seasonal scale with the intensity diminishing from north to south,as the temperature differences between summer and winter reaching 17 and 4 C in the northern and southern areas,respectively. Moreover,seasonal variation near the coastal regions seems relatively stronger than that far from the coastline;significant interannual variations are detected,with the largest positive anomaly occurring in 1998 in the overall area. But as far as different domains are concerned,there exists great diversity,and the difference is also found between winter and summer. Differed from the seasonal variations,where the strongest interannual variability takes place,resides to the south of that of the seasonal ones in the northern section,nevertheless in the South China Sea,the most significant interannual variability is found in the deep basin;interdecadal changes of summer,winter and annual mean SST in different domains likewise present various features. In addition,a common dominant warming in recent 20 a are found in the overall China offshore with the strongest center located in the vicinity of the Changjiang Estuary in the East China Sea,which intensifies as high as 1.3 C during the past 130 a.展开更多
With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and ...With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.展开更多
Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this ...Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.展开更多
Based on the annual frequency data of tropical cyclones from 1960 to 2005 and by the polynomial fit and statistical analysis, this work has discovered that TC activity in the 46a exhibits significant decadal-scale var...Based on the annual frequency data of tropical cyclones from 1960 to 2005 and by the polynomial fit and statistical analysis, this work has discovered that TC activity in the 46a exhibits significant decadal-scale variability. It has two high frequency periods (HFP) and two low frequency periods (LFP). Significant differences in the number of TCs between HFP and LFP are found in active TC seasons from July to October. Differences of large-scale circulation during HFP and LFP have been investigated with NCEP/NOAA data for the season. In HFP, the condition includes not only higher sea surface temperature, lower sea level pressure, larger divergence of upper air, larger relative vorticity at low levels and smaller vertical shear, but also 500-hPa wind vector being more available for TC activity and moving to western North Pacific, the position of the subtropical anticyclone over the western Pacific shifting more northward, and South Asian Anticyclone at 100-hPa being much smaller than that in LFP. The precipitation of western North Pacific has no clear influence on TC activity.展开更多
The Medieval Climate Anomaly(MCA,AD950-1250)is the most recent warm period lasting for several hundred years and is regarded as a reference scenario when studying the impact of and adaptation to global and regional wa...The Medieval Climate Anomaly(MCA,AD950-1250)is the most recent warm period lasting for several hundred years and is regarded as a reference scenario when studying the impact of and adaptation to global and regional warming.In this study,we investigated the characteristics of temperature variations on decadal-centennial scales during the MCA for four regions(Northeast,Northwest,Central-east,and Tibetan Plateau)in China,based on high-resolution temperature reconstructions and related warm-cold records from historical documents.The ensemble empirical mode decomposition method is used to analyze the time series.The results showed that for China as a whole,the longest warm period during the last 2000 years occurred in the 10th-13th centuries,although there were multi-decadal cold intervals in the middle to late 12th century.However,in the beginning and ending decades,warm peaks and phases on the decadal scale of the MCA for different regions were not consistent with each other.On the inter-decadal scale,regional temperature variations were similar from 950 to 1130;moreover,their amplitudes became smaller,and the phases did not agree well from 1130 to 1250.On the multi-decadal to centennial scale,all four regions began to warm in the early 10th century and experienced two cold intervals during the MCA.However,the Northwest and Central-east China were in step with each other while the warm periods in the Northeast China and Tibetan Plateau ended about 40-50 years earlier.On the multi-centennial scale,the mean temperature difference between the MCA and Little Ice Age was significant in Northeast and Central-east China but not in the Northwest China and Tibetan Plateau.Compared to the mean temperature of the 20th century,a comparable warmth in the MCA was found in the Central-east China,but there was a little cooling in Northeast China;meanwhile,there were significantly lower temperatures in Northwest China and Tibetan Plateau.展开更多
Phase delays between two Nino indices-sea surface temperatures in Nino regions 1+2 and 3.4 (1950-2001)-at different time scales are detected by wavelet analysis. Analysis results show that there are two types of perio...Phase delays between two Nino indices-sea surface temperatures in Nino regions 1+2 and 3.4 (1950-2001)-at different time scales are detected by wavelet analysis. Analysis results show that there are two types of period bifurcations in the Nino indices and that period bifurcation points exist only in the region where the wavelet power is small. Interdecadal variation features of phase delays between the two indices vary with different time scales. In the periods of 40-72 months, the phase delay changes its sign in 1977: Nino 1+2 indices are 2-4 months earlier than Nino 3.4 indices before 1977, but 3-6 months later afterwards. In the periods of 20-40 months, however, the phase delay changes its sign in another way: Nino 1+2 indices are 1-4 months earlier before 1980 and during 1986-90, but 1-4 months later during 1980-83 and 1993-2001.展开更多
As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and m...As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.展开更多
Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a ...Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.展开更多
Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be ass...Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational （4DVAR） data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems （MCS） along the mei-yu front in China. The experiments with GPS-PWV assimilation cluster and also eliminated the erroneous rainfall successfully simulated the evolution of the observed MCS systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.展开更多
The relationship between the ENSO and abnormal variation of precipitation and temperature in China is investigated based on the monthly data. Firstly, interannual variability of precipitation and temperature are discu...The relationship between the ENSO and abnormal variation of precipitation and temperature in China is investigated based on the monthly data. Firstly, interannual variability of precipitation and temperature are discussed in different sub-areas using Rotational EOF (REOF). Then, the variation of precipitation and temperature in different phases of ENSO cycle is each investigated with Complex Singular Value Decomposition (CSVD). Results show that, during the period of El Nio, precipitation in the eastern China, especially in the northeastern China and Yangtze River valley, is much more than normal and is apt to flood. Precipitation in northern China and Huanghe River valley, especially in the middle reach of Huanghe River, is less than normal and is apt to be less. Precipitation in the Yangtze River valley is closely related to the SSTA in the central and eastern tropical Pacific on the QFO scale, and the precipitation variation lags behind SSTA by about 3 months. For the variation of surface temperature, during the period of El Nio, it is usually colder than normal in northeastern China, and in other regions, especially in the region of Great Bend of the Yellow River and southwestern China, is warmer than normal. The temperature in northeast China is closely associated with SSTA in eastern Pacific on the QFO scale and the surface temperature variation in the northeast China lags behind that of SSTA about 2 months.展开更多
This paper focuses on the problem of traffic flow forecasting,with the aim of forecasting future traffic conditions based on historical traffic data.This problem is typically tackled by utilizing spatio-temporal graph...This paper focuses on the problem of traffic flow forecasting,with the aim of forecasting future traffic conditions based on historical traffic data.This problem is typically tackled by utilizing spatio-temporal graph neural networks to model the intricate spatio-temporal correlations among traffic data.Although these methods have achieved performance improvements,they often suffer from the following limitations:These methods face challenges in modeling high-order correlations between nodes.These methods overlook the interactions between nodes at different scales.To tackle these issues,in this paper,we propose a novel model named multi-scale dynamic hypergraph convolutional network(MSDHGCN)for traffic flow forecasting.Our MSDHGCN can effectively model the dynamic higher-order relationships between nodes at multiple time scales,thereby enhancing the capability for traffic forecasting.Experiments on two real-world datasets demonstrate the effectiveness of the proposed method.展开更多
In order to decrease the sensitivity of the constant scale parameter, adaptively optimize the scale parameter in the iteration regularization model （IRM） and attain a desirable level of applicability for image denoi...In order to decrease the sensitivity of the constant scale parameter, adaptively optimize the scale parameter in the iteration regularization model （IRM） and attain a desirable level of applicability for image denoising, a novel IRM with the adaptive scale parameter is proposed. First, the classic regularization item is modified and the equation of the adaptive scale parameter is deduced. Then, the initial value of the varying scale parameter is obtained by the trend of the number of iterations and the scale parameter sequence vectors. Finally, the novel iterative regularization method is used for image denoising. Numerical experiments show that compared with the IRM with the constant scale parameter, the proposed method with the varying scale parameter can not only reduce the number of iterations when the scale parameter becomes smaller, but also efficiently remove noise when the scale parameter becomes bigger and well preserve the details of images.展开更多
Soil seed banks play an important role in the distribution and composition of plant communities in semiarid grassland ecosystems. However, information on how spatial scale influences the spatial heterogeneity of soil ...Soil seed banks play an important role in the distribution and composition of plant communities in semiarid grassland ecosystems. However, information on how spatial scale influences the spatial heterogeneity of soil seed banks in a grassland under grazing disturbance is still lacking. Based on field sampling and greenhouse germination, we measured the species composition and seed density of soil seed banks at different spatial scales （30 mx30 m, 30 mx60 m and 30 mx90 m） along a topographical gradient in a sandy grassland in Horqin Sand Land, Northern China. By applying geostatistical methods, we examined how spatial scale and topography affected the spatial distribution of soil seed banks in the study area. Our results showed that the total number of species in soil seed banks, as well as the number of dominant annuals, increased with the increase of spatial scales. Seed density in soil seed banks decreased with the increase of spatial scales due to an increase in the slopes and relative heights of the sampling points. Geostatistical analysis showed that the relative structural variance （C/（C0＋C）） of seed density and species richness were over 65% for all spatial scales, indicating that these variables had an ob- vious spatial autocorrelation and the spatial structured variance accounted for the largest proportion of the total sample variance. Spatial autocorrelation of seed density in soil seed banks increased with the increase of measured scales, while that of species richness showed a reverse trend. These results suggest that the total number of spe- cies in soil seed banks is spatial scale dependent and lower topography may accommodate more seeds. Spatial distribution of seed density in soil seed banks is also scale dependent due to topographic variation. Grassland management, therefore, needs to consider local grazing disturbance regime, spatial scale and topography.展开更多
Characterizing trait variation across different ecological scales in plant communities has been viewed as a way to gain insights into the mechanisms driving species coexistence.However,little is known about how change...Characterizing trait variation across different ecological scales in plant communities has been viewed as a way to gain insights into the mechanisms driving species coexistence.However,little is known about how changes in intraspecific and interspecific traits across sites influence species richness and community assembly,especially in understory herbaceous communities.Here we partitioned the variance of four functional traits(maximum height,leaf thickness,leaf area and specific leaf area)across four nested biological scales:individual,species,plot,and elevation to quantify the scale-dependent distributions of understory herbaceous trait variance.We also integrated the comparison of the trait variance ratios to null models to investigate the effects of different ecological processes on community assembly and functional diversity along a 1200-m elevational gradient in Yulong Mountain.We found interspecific trait variation was the main trait variation component for leaf traits,although intraspecific trait variation ranged from 10% to 28% of total variation.In particular,maximum height exhibited high plasticity,and intraspecific variation accounted for 44% of the total variation.Despite the fact that species composition varied across elevation and species richness decreased dramatically along the elevational gradient,there was little variance at our largest(elevation)scale in leaf traits and functional diversity remained constant along the elevational gradient,indicating that traits responded to smaller scale influences.External filtering was only observed at high elevations.However,strong internal filtering was detected along the entire elevational gradient in understory herbaceous communities,possibly due to competition.Our results provide evidence that species coexistence in understory herbaceous communities might be structured by differential niche-assembled processes.This approach ee integrating different biological scales of trait variation ee may provide a better understanding of the mechanisms involved in the structure of communities.展开更多
We focus on Mei symmetry for time scales nonshifted mechanical systems within Lagrangian framework and its resulting new conserved quantities.Firstly,the dynamic equations of time scales nonshifted holonomic systems a...We focus on Mei symmetry for time scales nonshifted mechanical systems within Lagrangian framework and its resulting new conserved quantities.Firstly,the dynamic equations of time scales nonshifted holonomic systems and time scales nonshifted nonholonomic systems are derived from the generalized Hamilton’s principle.Secondly,the definitions of Mei symmetry on time scales are given and its criterions are deduced.Finally,Mei’s symmetry theorems for time scales nonshifted holonomic conservative systems,time scales nonshifted holonomic nonconservative systems and time scales nonshifted nonholonomic systems are established and proved,and new conserved quantities of above systems are obtained.Results are illustrated with two examples.展开更多
Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evalua...Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.展开更多
Aerial photographs and 3-D laser scans of a 90-m high star dune at the Crescent Moon Spring scenic spot in Dunhuang,China,are used to investigate the changes in dune morphology on timescales from months to decades.The...Aerial photographs and 3-D laser scans of a 90-m high star dune at the Crescent Moon Spring scenic spot in Dunhuang,China,are used to investigate the changes in dune morphology on timescales from months to decades.The result revealed that relative-equilibrium airflow strength in three wind directions of northeast,west and south was an important condition for the stability of star dunes with limited migration.Transverse and longitudinal airflows exerted a crucial impact on variation processes of star dune morphology.Controlled by transverse airflows,the easterly winds,the east side was dominated by wind erosion;and strong deposition occurred on the south-south-east arm with a maximum deposition rate of 0.44 m/a in the 46-a monitoring period,causing the east side becoming steep and high.Controlled by longitudinal airflows,the westerly winds,the west-north-west side was mainly eroded and the north arm migrated from west to east with a rate of 0.30 m/a,causing the dune slope becoming gentle and elongate.The local air circulation(southerly winds)exerted a significant impact on the development process of the star dune.Due to the influence of human activities,the south side present surface processes from a concave profile to a convex profile in 46 a,which is a potential threat to the Crescent Moon Spring.The results indicate that rehabilitating the airflow field at most is a crucial strategy to the protection of Crescent Moon Spring from burial.Opening up the passage of easterly,westerly and southerly winds through intermediately cutting the protection forest,demolishing the enclosed wall and changing the pavilion into a porous pattern have been suggested to protect the Crescent Moon Spring from burial.展开更多
This paper proposes a model for image restoration by combining the wavelet shrinkage and inverse scale space （ISS） method. The ISS is applied to the wavelet representation to modify the retained wavelet coefficients...This paper proposes a model for image restoration by combining the wavelet shrinkage and inverse scale space （ISS） method. The ISS is applied to the wavelet representation to modify the retained wavelet coefficients, and the coefficients smaller than the threshold are set to zero. The curvature term of the ISS can remove the edge artifacts and preserve sharp edges. For the multiscale interpretation of the ISS and the multiscale property of the wavelet representation, small details are preserved. This paper illustrates that the wavelet ISS model can be deduced from the wavelet based on a total variation minimization problem. A stopping criterion is obtained from this minimization in the sense of the Bregman distance in the wavelet domain. Numerical examples show the improvement for the image denoising with the proposed method in the sense of the signal to noise ratio and with fewer details remained in the residue.展开更多
基金supported by the National Key R&D Program of China(No.2023YFF1304001-01)the Science and Technology Project of the Department of Transportation of Heilongjiang Province(No.HJK2023B024-3)the Program of National Natural Science Foundation of China(No.32371870).
文摘The net primary productivity(NPP)of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change.While the temporal effect driven by ecosystem processes on NPP variations is well-documented,spatial variations(from local to regional scales)remain inadequately understood.To evaluate the scale-dependent effects of productivity,predictions from the Biome-BGC model were compared with moderate-resolution imaging spectroradiometer(MODIS)and biometric NPP data in a large temperate forest region at both local and regional levels.Linear mixed-effect models and variance partitioning analysis were used to quantify the effects of environmental heterogeneity and trait variation on simulated NPP at varying spatial scales.Results show that NPP had considerable predictability at the local scale,with a coefficient of determination(R^(2))of 0.37,but this predictability declined significantly to 0.02 at the regional scale.Environmental heterogeneity and photosynthetic traits collectively explained 94.8%of the local variation in NPP,which decreased to 86.7%regionally due to the reduced common effects among these variables.Locally,the leaf area index(LAI)predominated(34.6%),while at regional scales,the stomatal conductance and maximum carboxylation rate were more influential(41.1%).Our study suggests that environmental heterogeneity drives the photosynthetic processes that mediate NPP variations across spatial scales.Incorporating heterogeneous local conditions and trait variations into analyses could enhance future research on the relationship between climate and carbon cycles at larger scales.
基金National Key Project of ScientificTechnical Supporting Programs Funded by Ministry of Science & Technology of China during the 11th Five-Year Plan Period (Grant No. 2006BCA01A07-2).
文摘Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.
基金The National Natural Science Foundation of China under contract No. 40805035China COPES Program under contract Nos GYHY-200706005 and NSF 90711003
文摘The variability of the sea surface temperature（SST） in the China seas has been studied in seasonal,interannual and interdecadal scales based on the monthly data of HadISST spanning from 1870 to 2007. The main results obtained are SST in the China offshore changes most actively at the seasonal scale with the intensity diminishing from north to south,as the temperature differences between summer and winter reaching 17 and 4 C in the northern and southern areas,respectively. Moreover,seasonal variation near the coastal regions seems relatively stronger than that far from the coastline;significant interannual variations are detected,with the largest positive anomaly occurring in 1998 in the overall area. But as far as different domains are concerned,there exists great diversity,and the difference is also found between winter and summer. Differed from the seasonal variations,where the strongest interannual variability takes place,resides to the south of that of the seasonal ones in the northern section,nevertheless in the South China Sea,the most significant interannual variability is found in the deep basin;interdecadal changes of summer,winter and annual mean SST in different domains likewise present various features. In addition,a common dominant warming in recent 20 a are found in the overall China offshore with the strongest center located in the vicinity of the Changjiang Estuary in the East China Sea,which intensifies as high as 1.3 C during the past 130 a.
基金supported partly by the National Key R&D Program of China(2018YFA0702200)the Science and Technology Project of State Grid Shandong Electric Power Company(520604190002)。
文摘With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.
基金supported by the Program for Innovative Research Team(in Science and Technology)in University of Henan Province(No.22IRTSTHN016)the Hubei Natural Science Foundation(No.2021CFB156)the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)(No.JP21K17737).
文摘Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.
基金National Key Fundamental Research and Development Plan of China (2004CB418303)Natural Science Foundation of China (40425009 40233028)
文摘Based on the annual frequency data of tropical cyclones from 1960 to 2005 and by the polynomial fit and statistical analysis, this work has discovered that TC activity in the 46a exhibits significant decadal-scale variability. It has two high frequency periods (HFP) and two low frequency periods (LFP). Significant differences in the number of TCs between HFP and LFP are found in active TC seasons from July to October. Differences of large-scale circulation during HFP and LFP have been investigated with NCEP/NOAA data for the season. In HFP, the condition includes not only higher sea surface temperature, lower sea level pressure, larger divergence of upper air, larger relative vorticity at low levels and smaller vertical shear, but also 500-hPa wind vector being more available for TC activity and moving to western North Pacific, the position of the subtropical anticyclone over the western Pacific shifting more northward, and South Asian Anticyclone at 100-hPa being much smaller than that in LFP. The precipitation of western North Pacific has no clear influence on TC activity.
基金National Key R&D Program of China,No.2017YFA0603300National Natural Science Foundation of China,No.41671036,No.41831174The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA 19040101。
文摘The Medieval Climate Anomaly(MCA,AD950-1250)is the most recent warm period lasting for several hundred years and is regarded as a reference scenario when studying the impact of and adaptation to global and regional warming.In this study,we investigated the characteristics of temperature variations on decadal-centennial scales during the MCA for four regions(Northeast,Northwest,Central-east,and Tibetan Plateau)in China,based on high-resolution temperature reconstructions and related warm-cold records from historical documents.The ensemble empirical mode decomposition method is used to analyze the time series.The results showed that for China as a whole,the longest warm period during the last 2000 years occurred in the 10th-13th centuries,although there were multi-decadal cold intervals in the middle to late 12th century.However,in the beginning and ending decades,warm peaks and phases on the decadal scale of the MCA for different regions were not consistent with each other.On the inter-decadal scale,regional temperature variations were similar from 950 to 1130;moreover,their amplitudes became smaller,and the phases did not agree well from 1130 to 1250.On the multi-decadal to centennial scale,all four regions began to warm in the early 10th century and experienced two cold intervals during the MCA.However,the Northwest and Central-east China were in step with each other while the warm periods in the Northeast China and Tibetan Plateau ended about 40-50 years earlier.On the multi-centennial scale,the mean temperature difference between the MCA and Little Ice Age was significant in Northeast and Central-east China but not in the Northwest China and Tibetan Plateau.Compared to the mean temperature of the 20th century,a comparable warmth in the MCA was found in the Central-east China,but there was a little cooling in Northeast China;meanwhile,there were significantly lower temperatures in Northwest China and Tibetan Plateau.
基金This work was supported by the National Natural Science Foundation of China under Grant No．40035010
文摘Phase delays between two Nino indices-sea surface temperatures in Nino regions 1+2 and 3.4 (1950-2001)-at different time scales are detected by wavelet analysis. Analysis results show that there are two types of period bifurcations in the Nino indices and that period bifurcation points exist only in the region where the wavelet power is small. Interdecadal variation features of phase delays between the two indices vary with different time scales. In the periods of 40-72 months, the phase delay changes its sign in 1977: Nino 1+2 indices are 2-4 months earlier than Nino 3.4 indices before 1977, but 3-6 months later afterwards. In the periods of 20-40 months, however, the phase delay changes its sign in another way: Nino 1+2 indices are 1-4 months earlier before 1980 and during 1986-90, but 1-4 months later during 1980-83 and 1993-2001.
基金supported by the State Grid Science and Technology Project (Title: Technology Research On Large Scale EMT Real-time simulation customized platform, FX71-17-001)
文摘As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.
文摘Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.
文摘Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational （4DVAR） data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems （MCS） along the mei-yu front in China. The experiments with GPS-PWV assimilation cluster and also eliminated the erroneous rainfall successfully simulated the evolution of the observed MCS systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.
基金“Effect of sea-land-air interactions in the Asian monsoon region on the climate change in China”——a project of the Knowledge Innovation Project by the Chinese Academy of Sciences(ZKCX2-SW-210)National Natural Science Foundation of China(40023001,49775270)
文摘The relationship between the ENSO and abnormal variation of precipitation and temperature in China is investigated based on the monthly data. Firstly, interannual variability of precipitation and temperature are discussed in different sub-areas using Rotational EOF (REOF). Then, the variation of precipitation and temperature in different phases of ENSO cycle is each investigated with Complex Singular Value Decomposition (CSVD). Results show that, during the period of El Nio, precipitation in the eastern China, especially in the northeastern China and Yangtze River valley, is much more than normal and is apt to flood. Precipitation in northern China and Huanghe River valley, especially in the middle reach of Huanghe River, is less than normal and is apt to be less. Precipitation in the Yangtze River valley is closely related to the SSTA in the central and eastern tropical Pacific on the QFO scale, and the precipitation variation lags behind SSTA by about 3 months. For the variation of surface temperature, during the period of El Nio, it is usually colder than normal in northeastern China, and in other regions, especially in the region of Great Bend of the Yellow River and southwestern China, is warmer than normal. The temperature in northeast China is closely associated with SSTA in eastern Pacific on the QFO scale and the surface temperature variation in the northeast China lags behind that of SSTA about 2 months.
基金the National Key Research and Development Program of China(No.2021ZD0112400)。
文摘This paper focuses on the problem of traffic flow forecasting,with the aim of forecasting future traffic conditions based on historical traffic data.This problem is typically tackled by utilizing spatio-temporal graph neural networks to model the intricate spatio-temporal correlations among traffic data.Although these methods have achieved performance improvements,they often suffer from the following limitations:These methods face challenges in modeling high-order correlations between nodes.These methods overlook the interactions between nodes at different scales.To tackle these issues,in this paper,we propose a novel model named multi-scale dynamic hypergraph convolutional network(MSDHGCN)for traffic flow forecasting.Our MSDHGCN can effectively model the dynamic higher-order relationships between nodes at multiple time scales,thereby enhancing the capability for traffic forecasting.Experiments on two real-world datasets demonstrate the effectiveness of the proposed method.
基金The National Natural Science Foundation of China(No.60702069)the Research Project of Department of Education of Zhe-jiang Province (No.20060601)+1 种基金the Natural Science Foundation of Zhe-jiang Province (No.Y1080851)Shanghai International Cooperation onRegion of France (No.06SR07109)
文摘In order to decrease the sensitivity of the constant scale parameter, adaptively optimize the scale parameter in the iteration regularization model （IRM） and attain a desirable level of applicability for image denoising, a novel IRM with the adaptive scale parameter is proposed. First, the classic regularization item is modified and the equation of the adaptive scale parameter is deduced. Then, the initial value of the varying scale parameter is obtained by the trend of the number of iterations and the scale parameter sequence vectors. Finally, the novel iterative regularization method is used for image denoising. Numerical experiments show that compared with the IRM with the constant scale parameter, the proposed method with the varying scale parameter can not only reduce the number of iterations when the scale parameter becomes smaller, but also efficiently remove noise when the scale parameter becomes bigger and well preserve the details of images.
基金funded by the National Natural Science Foundation of China(41171414)the Knowledge Innovation Program of Chinese Academy of Sciences(KZCX2-EW-QN313)+2 种基金the National Science and Technology Support Program (2011BAC07B02)the National Basic Research Program of China(2009CB421303)the West Light Foundation of the Chinese Academy of Sciences(0928711001)
文摘Soil seed banks play an important role in the distribution and composition of plant communities in semiarid grassland ecosystems. However, information on how spatial scale influences the spatial heterogeneity of soil seed banks in a grassland under grazing disturbance is still lacking. Based on field sampling and greenhouse germination, we measured the species composition and seed density of soil seed banks at different spatial scales （30 mx30 m, 30 mx60 m and 30 mx90 m） along a topographical gradient in a sandy grassland in Horqin Sand Land, Northern China. By applying geostatistical methods, we examined how spatial scale and topography affected the spatial distribution of soil seed banks in the study area. Our results showed that the total number of species in soil seed banks, as well as the number of dominant annuals, increased with the increase of spatial scales. Seed density in soil seed banks decreased with the increase of spatial scales due to an increase in the slopes and relative heights of the sampling points. Geostatistical analysis showed that the relative structural variance （C/（C0＋C）） of seed density and species richness were over 65% for all spatial scales, indicating that these variables had an ob- vious spatial autocorrelation and the spatial structured variance accounted for the largest proportion of the total sample variance. Spatial autocorrelation of seed density in soil seed banks increased with the increase of measured scales, while that of species richness showed a reverse trend. These results suggest that the total number of spe- cies in soil seed banks is spatial scale dependent and lower topography may accommodate more seeds. Spatial distribution of seed density in soil seed banks is also scale dependent due to topographic variation. Grassland management, therefore, needs to consider local grazing disturbance regime, spatial scale and topography.
基金supported by the National Key Basic Research Program of China (2014CB954100)the Ministry of Science and Technology of the People's Republic of China (2012FY110800)the Applied Fundamental Research Foundation of Yunnan Province (2014GA003)
文摘Characterizing trait variation across different ecological scales in plant communities has been viewed as a way to gain insights into the mechanisms driving species coexistence.However,little is known about how changes in intraspecific and interspecific traits across sites influence species richness and community assembly,especially in understory herbaceous communities.Here we partitioned the variance of four functional traits(maximum height,leaf thickness,leaf area and specific leaf area)across four nested biological scales:individual,species,plot,and elevation to quantify the scale-dependent distributions of understory herbaceous trait variance.We also integrated the comparison of the trait variance ratios to null models to investigate the effects of different ecological processes on community assembly and functional diversity along a 1200-m elevational gradient in Yulong Mountain.We found interspecific trait variation was the main trait variation component for leaf traits,although intraspecific trait variation ranged from 10% to 28% of total variation.In particular,maximum height exhibited high plasticity,and intraspecific variation accounted for 44% of the total variation.Despite the fact that species composition varied across elevation and species richness decreased dramatically along the elevational gradient,there was little variance at our largest(elevation)scale in leaf traits and functional diversity remained constant along the elevational gradient,indicating that traits responded to smaller scale influences.External filtering was only observed at high elevations.However,strong internal filtering was detected along the entire elevational gradient in understory herbaceous communities,possibly due to competition.Our results provide evidence that species coexistence in understory herbaceous communities might be structured by differential niche-assembled processes.This approach ee integrating different biological scales of trait variation ee may provide a better understanding of the mechanisms involved in the structure of communities.
基金supported by the National Natural Science Foundation of China(Grants 11972241 and 11572212)the Natural Science Foundation of Jiangsu Province of China(Grant BK20191454).
文摘We focus on Mei symmetry for time scales nonshifted mechanical systems within Lagrangian framework and its resulting new conserved quantities.Firstly,the dynamic equations of time scales nonshifted holonomic systems and time scales nonshifted nonholonomic systems are derived from the generalized Hamilton’s principle.Secondly,the definitions of Mei symmetry on time scales are given and its criterions are deduced.Finally,Mei’s symmetry theorems for time scales nonshifted holonomic conservative systems,time scales nonshifted holonomic nonconservative systems and time scales nonshifted nonholonomic systems are established and proved,and new conserved quantities of above systems are obtained.Results are illustrated with two examples.
基金Under the auspices of National Natural Science Foundation of China (No. 40925003, 40930528, 40801041)
文摘Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.
基金funded by the National Natural Science Foundation of China(41271023)
文摘Aerial photographs and 3-D laser scans of a 90-m high star dune at the Crescent Moon Spring scenic spot in Dunhuang,China,are used to investigate the changes in dune morphology on timescales from months to decades.The result revealed that relative-equilibrium airflow strength in three wind directions of northeast,west and south was an important condition for the stability of star dunes with limited migration.Transverse and longitudinal airflows exerted a crucial impact on variation processes of star dune morphology.Controlled by transverse airflows,the easterly winds,the east side was dominated by wind erosion;and strong deposition occurred on the south-south-east arm with a maximum deposition rate of 0.44 m/a in the 46-a monitoring period,causing the east side becoming steep and high.Controlled by longitudinal airflows,the westerly winds,the west-north-west side was mainly eroded and the north arm migrated from west to east with a rate of 0.30 m/a,causing the dune slope becoming gentle and elongate.The local air circulation(southerly winds)exerted a significant impact on the development process of the star dune.Due to the influence of human activities,the south side present surface processes from a concave profile to a convex profile in 46 a,which is a potential threat to the Crescent Moon Spring.The results indicate that rehabilitating the airflow field at most is a crucial strategy to the protection of Crescent Moon Spring from burial.Opening up the passage of easterly,westerly and southerly winds through intermediately cutting the protection forest,demolishing the enclosed wall and changing the pavilion into a porous pattern have been suggested to protect the Crescent Moon Spring from burial.
基金supported by the National Natural Science Foundation of China (61101208)
文摘This paper proposes a model for image restoration by combining the wavelet shrinkage and inverse scale space （ISS） method. The ISS is applied to the wavelet representation to modify the retained wavelet coefficients, and the coefficients smaller than the threshold are set to zero. The curvature term of the ISS can remove the edge artifacts and preserve sharp edges. For the multiscale interpretation of the ISS and the multiscale property of the wavelet representation, small details are preserved. This paper illustrates that the wavelet ISS model can be deduced from the wavelet based on a total variation minimization problem. A stopping criterion is obtained from this minimization in the sense of the Bregman distance in the wavelet domain. Numerical examples show the improvement for the image denoising with the proposed method in the sense of the signal to noise ratio and with fewer details remained in the residue.
