A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions...A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs,all at the same forecast valid time.This lagged average forecast （LAF） method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean.Our analyses of the Equitable Threat Score,the Hanssen and Kuipers Score,and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d-1 and 5 mm d-1 in many regions of China,and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members.In particular,significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40％-50％ in the summer season; these regions include northeastern and central to southern China,and the southeastem Tibetan Plateau.展开更多
Most terrestrial models synchronously calculate net primary productivity(NPP)using the input climate variable,without the consideration of time-lag effects,which may increase the uncertainty of NPP simulation.Based on...Most terrestrial models synchronously calculate net primary productivity(NPP)using the input climate variable,without the consideration of time-lag effects,which may increase the uncertainty of NPP simulation.Based on Normalized Difference Vegetation Index(NDVI)and climate data,we used the time lag cross-correlation method to investigate the time-lag effects of temperature,precipitation,and solar radiation in different seasons on NDVI values.Then,we selected the Carnegie-Ames-Stanford approach(CASA)model to estimate the NPP of China from 2002 to 2017.The results showed that the response of vegetation growth to climate factors had an obvious lag effect,with the longest time lag in solar radiation and the shortest time lag in temperature.The time lag of vegetation to the climate variable showed great tempo-spatial heterogeneities among vegetation types,climate types,and vegetation growth periods.Based on the validation using eddy covariance data,the results showed that the simulation accuracy of the CASA model considering the time-lag effects was effectively improved.By considering the time-lag effects,the average total amount of NPP modeled by CASA during 2001-2017 in China was 3.977 PgC a^(−1),which is 11.37%higher than that of the original model.This study highlights the importance of considering the time lag for the simulation of vegetation growth,and provides a useful tool for the improvement of the vegetation productivity model.展开更多
Originated in the early 1990s, SCGM(1, m ) c model has enjoyed widespread application in the fields of urban planning, society economy prediction and modal control in recent years. However, none of these applications ...Originated in the early 1990s, SCGM(1, m ) c model has enjoyed widespread application in the fields of urban planning, society economy prediction and modal control in recent years. However, none of these applications have taken account of time lag effects in the modeling process. Aiming at overcoming the defect, the authors introduced time lag items into SCGM(1, m ) c model and developed a SCGM(1, m ) c model with time lag, then discusses in detail some principal problems in the model, such as parameters estimation, model verifying, model prediction, etc. The model was used on a real slope monitoring project and compared with the conventional SCGM(1, m ) c model. The results show an improvement of average models precision from 1.321 to 0.238 and total average of relative prediction errors from 12.41% to 7.98% when the modeling data length ranges from 29 to 48 in the slope monitoring case.展开更多
This paper investigates the nonlinear prediction of monthly rainfall time series which consists of phase space continuation of one-dimensional sequence, followed by least-square determination of the coefficients for t...This paper investigates the nonlinear prediction of monthly rainfall time series which consists of phase space continuation of one-dimensional sequence, followed by least-square determination of the coefficients for the terms ofthe time-lag differential equation model and then fitting of the prognostic expression is made to 1951-1980 monthlyrainfall datasets from Changsha station. Results show that the model is likely to describe the nonlinearity of the allnual cycle of precipitation on a monthly basis and to provide a basis for flood prevention and drought combating forthe wet season.展开更多
Conditions are given for controllability, output controllability and local identifiabitity of a parametrization in a subset of of linear differential systems with time-lags.
The daily intake of total dietary fiber (TDF) was evaluated from data of the National Nutrition Survey (NNS) in Japan for 41 years since 1947. An interrelationship between the nutrient intake, including TDF, and the m...The daily intake of total dietary fiber (TDF) was evaluated from data of the National Nutrition Survey (NNS) in Japan for 41 years since 1947. An interrelationship between the nutrient intake, including TDF, and the mortality from colon cancer in Japanese people was calculated by a simple correlation coefficient and time-series correlation coeffcient.TDF intake per capita decreased rapidly from 27.4 g in 1947 to 15.8 g in 1963, and subsequently decreased by a lesser rate to 15.3 g in 1987. Fat intake increased rapidly from 18.0 g in 1950 to 56.6 g in 1987.The age-adjusted mortality from colon cancer shows a significant positive correlation with both the intakes of animal protein and of total fat, and the fat energy ratio. A time-series analysis indicates that the mortality from colon cancer was negatively correlated with TDF with a 15-27 year delay, the maximum correlation existing with a 23-year lag (r = -0.947). The TDF intake was less than 17.9 g in 1965. At the same time, the mortality from colon cancer increased rapidly. A fat/TDF ratio above 3.0 resulted in a rapid increase in colon cancer mortality.The non-adjusted mortality from colon cancer has much the same interrelationship with TDF and fat intake as the adjusted figures. It is suggested that the cause of the increased mortality from colon cancer in Japan is positively related to the increased intake of fat and protein. In addition, the decrease in TDF intake has accelerated the mortality of colon cancer after a delay of 23-24 years. The importance of fat/TDF as a nutritional criterion for the incidence of colon cancer needs to be better recognized展开更多
Given a non-equidistant sequence or an equidistant series with one or more outliers, a grey interpolation approach considering the time lags is established for producing the missing data or correcting the abnormal val...Given a non-equidistant sequence or an equidistant series with one or more outliers, a grey interpolation approach considering the time lags is established for producing the missing data or correcting the abnormal values. To accomplish this, a new grey incidence model, called the grey dynamic incidence model GDIM(t), is constructed for determining whether the factors are effective to the known factor and what the time lag is between a useful factor and the specified sequence. Based on the results of the GDIM(t) model, two programming problems are designed to obtain the upper and lower bounds of the unknown or abnormal values which are regarded as grey numbers. The solutions based on the particle swarm optimization(PSO) for the nonlinear programming problems are given. To explain how it can be used in practice, this new grey interpolation approach is applied to correct an abnormal value in the sequence of an agriculture environment problem.展开更多
Scientific understanding of the trade-offs between services is crucial for the scientific management and protection of ecosys-tems and the formulation of resource management policies.This study integrated meteorologic...Scientific understanding of the trade-offs between services is crucial for the scientific management and protection of ecosys-tems and the formulation of resource management policies.This study integrated meteorological,land use,and soil data to assess the ecosystem services,namely,water yield(WY),soil erosion(SE),and carbon sinks(CS),in peak-cluster depression basins on the Sino-Vietnamese border in China during 2000-2020.It analyzed the trade-offs and synergistic relationships among the three ecosystem ser-vices and their time-lag effects and driving mechanisms with the help of pixel-by-pixel time-lag intercorrelation and geographical de-tector methods.Results show that:1)from 2000 to 2020,the key ecosystem service indicators in the peak-cluster depression basins on the Sino-Vietnamese border in China demonstrated a significant and synergistic trend of positive change.The WY increased at a rate of 11.99 mm/yr,CS increased at a rate of 2.44 g C/(m^(2)∙yr),and SE decreased at a rate of 0.06 t/(ha∙yr).2)Most areas showed a synergistic relationship across the three ecosystem services,and the areas with a trade-off relationship were mostly concentrated in Baise City and the southwest of Chongzuo City,Guangxi.3)The time-lag effect between SE and WY was mostly concentrated in 0 yr,that between SE and CS was mostly concentrated in 5 yr,and that between CS and WY was mostly concentrated in 1 yr.4)Population density was the controlling factor between SE and WY.Vegetation coverage factor is the main controlling factor between SE and CS.The lithologic factor is the main controlling factor between CS and WY.Studying the trade-off relationship of ecosystem services at spatial and tem-poral scales on the Sino-Vietnamese border in China karst areas can provide a basis for regional ecological construction and develop-ment strategies,and it is conducive to meeting regional interest needs,maximizing comprehensive benefits,balancing the ecological en-vironment,and achieving regional sustainable development.展开更多
During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face ...During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face challenges when dealing with rapidly changing reservoir conditions over time.Additionally,TC models struggle with complex,random noise primarily caused by measurement errors in production and injection rates.To address these challenges,this study introduces a dynamic capacitance(SV-DC)model based on state variables.By integrating the extended Kalman filter(EKF)algorithm,the SV-DC model provides more flexible predictions of inter-well connectivity and time-lag efficiency compared to the TC model.The robustness of the SV-DC model is verified by comparing relative errors between preset and calculated values through Monte Carlo simulations.Sensitivity analysis was performed to compare the model performance with the benchmark,using the Qinhuangdao Oilfield as a case study.The results show that the SV-DC model accurately predicts water breakthrough times.Increases in the liquid production index and water cut in two typical wells indicate the development time of ineffective circulation channels,further confirming the accuracy and reliability of the model.The SV-DC model offers significant advantages in addressing complex,dynamic oilfield production scenarios and serves as a valuable tool for the efficient and precise planning and management of future oilfield developments.展开更多
基金supported by the National Basic Research Program of China (973 Program: Grant No. 2010CB951902)the Special Program for China Meteorology Trade (Grant No. GYHY201306020)the Technology Support Program of China (Grant No. 2009BAC51B03)
文摘A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs,all at the same forecast valid time.This lagged average forecast （LAF） method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean.Our analyses of the Equitable Threat Score,the Hanssen and Kuipers Score,and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d-1 and 5 mm d-1 in many regions of China,and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members.In particular,significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40％-50％ in the summer season; these regions include northeastern and central to southern China,and the southeastem Tibetan Plateau.
基金National Natural Science Foundation of China,No.42161058The State Key Laboratory of Cryospheric Science,No.SKLCS-ZZ-2022The West Light Foundation of the Chinese Academy of Sciences。
文摘Most terrestrial models synchronously calculate net primary productivity(NPP)using the input climate variable,without the consideration of time-lag effects,which may increase the uncertainty of NPP simulation.Based on Normalized Difference Vegetation Index(NDVI)and climate data,we used the time lag cross-correlation method to investigate the time-lag effects of temperature,precipitation,and solar radiation in different seasons on NDVI values.Then,we selected the Carnegie-Ames-Stanford approach(CASA)model to estimate the NPP of China from 2002 to 2017.The results showed that the response of vegetation growth to climate factors had an obvious lag effect,with the longest time lag in solar radiation and the shortest time lag in temperature.The time lag of vegetation to the climate variable showed great tempo-spatial heterogeneities among vegetation types,climate types,and vegetation growth periods.Based on the validation using eddy covariance data,the results showed that the simulation accuracy of the CASA model considering the time-lag effects was effectively improved.By considering the time-lag effects,the average total amount of NPP modeled by CASA during 2001-2017 in China was 3.977 PgC a^(−1),which is 11.37%higher than that of the original model.This study highlights the importance of considering the time lag for the simulation of vegetation growth,and provides a useful tool for the improvement of the vegetation productivity model.
基金TheNationalNaturalScienceFoundationofChina! (No .497742 0 9)
文摘Originated in the early 1990s, SCGM(1, m ) c model has enjoyed widespread application in the fields of urban planning, society economy prediction and modal control in recent years. However, none of these applications have taken account of time lag effects in the modeling process. Aiming at overcoming the defect, the authors introduced time lag items into SCGM(1, m ) c model and developed a SCGM(1, m ) c model with time lag, then discusses in detail some principal problems in the model, such as parameters estimation, model verifying, model prediction, etc. The model was used on a real slope monitoring project and compared with the conventional SCGM(1, m ) c model. The results show an improvement of average models precision from 1.321 to 0.238 and total average of relative prediction errors from 12.41% to 7.98% when the modeling data length ranges from 29 to 48 in the slope monitoring case.
文摘This paper investigates the nonlinear prediction of monthly rainfall time series which consists of phase space continuation of one-dimensional sequence, followed by least-square determination of the coefficients for the terms ofthe time-lag differential equation model and then fitting of the prognostic expression is made to 1951-1980 monthlyrainfall datasets from Changsha station. Results show that the model is likely to describe the nonlinearity of the allnual cycle of precipitation on a monthly basis and to provide a basis for flood prevention and drought combating forthe wet season.
文摘Conditions are given for controllability, output controllability and local identifiabitity of a parametrization in a subset of of linear differential systems with time-lags.
文摘The daily intake of total dietary fiber (TDF) was evaluated from data of the National Nutrition Survey (NNS) in Japan for 41 years since 1947. An interrelationship between the nutrient intake, including TDF, and the mortality from colon cancer in Japanese people was calculated by a simple correlation coefficient and time-series correlation coeffcient.TDF intake per capita decreased rapidly from 27.4 g in 1947 to 15.8 g in 1963, and subsequently decreased by a lesser rate to 15.3 g in 1987. Fat intake increased rapidly from 18.0 g in 1950 to 56.6 g in 1987.The age-adjusted mortality from colon cancer shows a significant positive correlation with both the intakes of animal protein and of total fat, and the fat energy ratio. A time-series analysis indicates that the mortality from colon cancer was negatively correlated with TDF with a 15-27 year delay, the maximum correlation existing with a 23-year lag (r = -0.947). The TDF intake was less than 17.9 g in 1965. At the same time, the mortality from colon cancer increased rapidly. A fat/TDF ratio above 3.0 resulted in a rapid increase in colon cancer mortality.The non-adjusted mortality from colon cancer has much the same interrelationship with TDF and fat intake as the adjusted figures. It is suggested that the cause of the increased mortality from colon cancer in Japan is positively related to the increased intake of fat and protein. In addition, the decrease in TDF intake has accelerated the mortality of colon cancer after a delay of 23-24 years. The importance of fat/TDF as a nutritional criterion for the incidence of colon cancer needs to be better recognized
基金supported by the National Natural Science Foundation of China(7137109871071077)+4 种基金Funding of Jiangsu Innovation Program for Graduate Education(KYZZ15 0093)Fundamental Research Funds for the Central Universities(2017301)Natural Science Fund Project of Colleges in Jiangsu Province(16KJD120001)Funding for Major Project of Jiangsu Social Science(16GLA001)Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics(BCXJ15-10)
文摘Given a non-equidistant sequence or an equidistant series with one or more outliers, a grey interpolation approach considering the time lags is established for producing the missing data or correcting the abnormal values. To accomplish this, a new grey incidence model, called the grey dynamic incidence model GDIM(t), is constructed for determining whether the factors are effective to the known factor and what the time lag is between a useful factor and the specified sequence. Based on the results of the GDIM(t) model, two programming problems are designed to obtain the upper and lower bounds of the unknown or abnormal values which are regarded as grey numbers. The solutions based on the particle swarm optimization(PSO) for the nonlinear programming problems are given. To explain how it can be used in practice, this new grey interpolation approach is applied to correct an abnormal value in the sequence of an agriculture environment problem.
基金Under the auspices of National Natural Science Foundation of China(No.42061020)Natural Science Foundation of Guangxi Zhuang Autonomous Region(No.2018JJA150135)+2 种基金Guangxi Key Research and Development Program(No.AA18118038)Science and Technology Department of Guangxi Zhuang Autonomous Region(No.2019AC20088)High Level Talent Introduction Project of Beibu Gulf University(No.2019KYQD28)。
文摘Scientific understanding of the trade-offs between services is crucial for the scientific management and protection of ecosys-tems and the formulation of resource management policies.This study integrated meteorological,land use,and soil data to assess the ecosystem services,namely,water yield(WY),soil erosion(SE),and carbon sinks(CS),in peak-cluster depression basins on the Sino-Vietnamese border in China during 2000-2020.It analyzed the trade-offs and synergistic relationships among the three ecosystem ser-vices and their time-lag effects and driving mechanisms with the help of pixel-by-pixel time-lag intercorrelation and geographical de-tector methods.Results show that:1)from 2000 to 2020,the key ecosystem service indicators in the peak-cluster depression basins on the Sino-Vietnamese border in China demonstrated a significant and synergistic trend of positive change.The WY increased at a rate of 11.99 mm/yr,CS increased at a rate of 2.44 g C/(m^(2)∙yr),and SE decreased at a rate of 0.06 t/(ha∙yr).2)Most areas showed a synergistic relationship across the three ecosystem services,and the areas with a trade-off relationship were mostly concentrated in Baise City and the southwest of Chongzuo City,Guangxi.3)The time-lag effect between SE and WY was mostly concentrated in 0 yr,that between SE and CS was mostly concentrated in 5 yr,and that between CS and WY was mostly concentrated in 1 yr.4)Population density was the controlling factor between SE and WY.Vegetation coverage factor is the main controlling factor between SE and CS.The lithologic factor is the main controlling factor between CS and WY.Studying the trade-off relationship of ecosystem services at spatial and tem-poral scales on the Sino-Vietnamese border in China karst areas can provide a basis for regional ecological construction and develop-ment strategies,and it is conducive to meeting regional interest needs,maximizing comprehensive benefits,balancing the ecological en-vironment,and achieving regional sustainable development.
基金the National Natural Science Foundation of China(Grant No.52374051)the Joint Fund for Enterprise Innovation and Development of NSFC(Grant No.U24B2037).
文摘During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face challenges when dealing with rapidly changing reservoir conditions over time.Additionally,TC models struggle with complex,random noise primarily caused by measurement errors in production and injection rates.To address these challenges,this study introduces a dynamic capacitance(SV-DC)model based on state variables.By integrating the extended Kalman filter(EKF)algorithm,the SV-DC model provides more flexible predictions of inter-well connectivity and time-lag efficiency compared to the TC model.The robustness of the SV-DC model is verified by comparing relative errors between preset and calculated values through Monte Carlo simulations.Sensitivity analysis was performed to compare the model performance with the benchmark,using the Qinhuangdao Oilfield as a case study.The results show that the SV-DC model accurately predicts water breakthrough times.Increases in the liquid production index and water cut in two typical wells indicate the development time of ineffective circulation channels,further confirming the accuracy and reliability of the model.The SV-DC model offers significant advantages in addressing complex,dynamic oilfield production scenarios and serves as a valuable tool for the efficient and precise planning and management of future oilfield developments.
