Ecosystem is a fundamental organizational unit of the biosphere in which biological communities interact with their non-biological environment through energy flows and material cycles.Ecosystem science is the study of...Ecosystem is a fundamental organizational unit of the biosphere in which biological communities interact with their non-biological environment through energy flows and material cycles.Ecosystem science is the study of patterns,processes,and services of ecosystems.Since the 1990s,rising concerns regarding global climate change,biodiversity loss,ecosystem degradation,and sustainability of the human-dominated biosphere have stimulated the growth of ecosystem science,which is expected to provide systematic solutions to many of these major issues facing human societies.This paper provides a comprehensive review of the current progress in ecosystem science and identifies some key research challenges facing this discipline.We demonstrate that a key feature of the current progress in ecosystem science is its evolution from primarily theoretical explorations toward more systematic,integrative and application-oriented studies.Specifically,five major changes in the discipline over the past several decades can be identified.These include:(1)the expansion of the primary goal from understanding nature to include human activities;(2)the broadening of the research focus from single ecosystem types to macro-ecosystems comprising multiple regional ecosystems;(3)the shifting of research methods from small-scale observations and experiments to large-scale observations,network experiments,and model simulations;(4)the increasing attention to comprehensive integration of ecosystem components,processes,and scales;and(5)the shifting from a primarily biology-oriented focus to an integrated multi-disciplinary scientific field.While ecosystem science still faces many challenges in the future,these directional changes,along with the rapidly enriched research tools and data acquisition capabilities,lay a promising ground for the discipline’s future as a fundamental scientific basis for solving many environmental challenges facing human societies.展开更多
This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficien...There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.展开更多
Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air poll...Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.展开更多
This research presents an advanced study on the modeling and stability analysis of electro-hydraulic control modules used in intelligent chassis systems.Firstly,a comprehensive nonlinear mathematical model of the elec...This research presents an advanced study on the modeling and stability analysis of electro-hydraulic control modules used in intelligent chassis systems.Firstly,a comprehensive nonlinear mathematical model of the electro-hydraulic power-shift system is developed,incorporating pipeline characteristics through impedance analysis and examining coupling effects between the pilot solenoid valve,main valve,and pipeline.Then,the model’s accuracy is validated through experimental testing,demonstrating high precision and minimal model errors.A comparative analysis between simulation data(both with and without pipeline characteristics)and experimental results reveals that the model considering pipeline parameters aligns more closely with experimental data,highlighting its superior accuracy.The research further explores the influence of key factors on system stability,including damping coefficient,feedback cavity orifice diameter,spring stiffness,pipeline length,and pipeline diameter.Significant findings include the critical impact of damping coefficient,orifice diameter,and pipeline length on stability,while spring stiffness has a minimal effect.These findings provide valuable insights for optimizing electro-hydraulic control modules in intelligent chassis systems,with practical implications for automotive and construction machinery applications.展开更多
Genome-wide association study(GWAS)data are used to explore the associations between blood metabolites and 5 respiratory diseases:asthma,tuberculosis(TB),chronic obstructive pulmonary disease(COPD),cor pulmonale,and b...Genome-wide association study(GWAS)data are used to explore the associations between blood metabolites and 5 respiratory diseases:asthma,tuberculosis(TB),chronic obstructive pulmonary disease(COPD),cor pulmonale,and bronchitis.The main method of analysis used is the inverse-variance weighted(IVW)approach,complemented by several sensitivity analyses,including MR-Egger regression,the weighted median,the weighted mode,Cochran’s Q test,and the pleiotropy test.Additional directional tests,Meta-analysis and metabolic pathway analyses are conducted for deeper insights.3 metabolites showing significant causal relationships are identified.Catechol glucuronide levels as a protective factor have a positive causal relationship with asthma;the creatine to carnitine ratio has a negative causal relationship with COPD as a risk factor;and the adenosine 5’-diphosphate(ADP)to N-acetylglucosamine to N-acetylgalactosamine ratio as a protective factor has a positive causal relationship with bronchitis.Additionally,13 metabolites demonstrate strong causal relationships.Furthermore,we delineate 14 metabolic pathways related to the outcomes,including 6 associated with asthma,2 with TB,1 with COPD,4 with cor pulmonale,and 1 with bronchitis.A causal relationship between blood metabolites and 5 respiratory diseases has been established.The identified metabolites and pathways offer new insights into the underlying mechanisms of these diseases,necessitating further experimental validation.展开更多
This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,i...This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.展开更多
Traditional psychiatric diagnosis relies on subjective symptom assessment,lacking objective biomarkers that hinder early detection and personalized treatment.Plasma proteins and polygenic risk score(PRS),as potential ...Traditional psychiatric diagnosis relies on subjective symptom assessment,lacking objective biomarkers that hinder early detection and personalized treatment.Plasma proteins and polygenic risk score(PRS),as potential predictive tools,hold promise for advancing early diagnosis of mental disorders.This study aims to evaluate the predictive potential of proteomic features and PRS in multiple mental illnesses(depression,schizophrenia,and post-traumatic stress disorder(PTSD)).Using participant data from the UK Biobank-Pharma Proteomics Project,we screen protein associations with mental disorders through least absolute shrinkage and selection operator(LASSO)analysis and construct a Cox regression risk prediction model by integrating the PRS.Additionally,we evaluate predictive performance using 6 machine learning methods and Kaplan-Meier survival curves.Our findings reveal distinct predictive patterns across dis-orders.For depression,integrating plasma proteins with PRS significantly improves prediction beyond the clinical model(C-index=0.6322).For schizophrenia,adding plasma proteins enhances predictive performance,whereas PRS provides no significant improvement.For PTSD,neither plasma proteins nor PRS add substantial predictive value beyond clinical variables.Risk stratification analysis demonstrat that all three mental disorders models can clearly distinguish high-risk from low-risk groups(depression:HR=2.34,P<0.001;schizophrenia:HR=5.47,P<0.001;PTSD:HR=3.02,P<0.001).Al-though it shows good performance in short-term prediction,its long-term prediction ability has decreased,and it needs to be further optimized in the future.This study underscores the differential utility of biomarkers across mental disorders and provides a rationale for disorder-specific predictive modeling in precision psychiatry.展开更多
Phosphorus(P)is an essential nutrient for primary production and frequently acts as a limiting factor in estuaries.The Changjiang River Estuary,recognized as one of the largest estuaries globally,has experienced signi...Phosphorus(P)is an essential nutrient for primary production and frequently acts as a limiting factor in estuaries.The Changjiang River Estuary,recognized as one of the largest estuaries globally,has experienced significant changes in nutrient dynamics due to anthropogenic activities.The recent reduction in P loading from the Changjiang River may have significant implications for the dynamics of dissolved inorganic phosphorus(DIP)within this estuarine system.Based on DIP data collected in 2017,2019,and 2023,combined with historical datasets,we aim to identify the drivers of DIP concentration changes in the Changjiang Estuary under the change in river inputs.The results indicate significant spatiotemporal variations in the distribution of DIP in the Changjiang Estuary,with the highest average concentration in winter.DIP exhibits non-conservative behavior along the salinity gradient,primarily influenced by biological utilization.Long-term DIP variations can be divided into three stages:a low-concentration period(1984–1987),a significant increase(1987–2014),and a decline(since 2015),with a current decreasing trend of 0.024μmol/(L·yr)(R^(2)=0.97,P<0.05).A discernible trend of P depletion in estuarine environments is observed,attributed to diminished riverine load and enhanced phytoplankton fixation.The reduction,and in some cases depletion,of DIP in the Changjiang Estuary has significantly altered the nitrogen-to-phosphorus ratio.The recent changes in total phosphorus(TP)compositions in the Changjiang Estuary are also attributed to a decrease in riverine input.Ongoing terrestrial nutrient management may further lower DIP concentrations,potentially impacting the estuarine ecosystem.展开更多
Worldwide radiation records suggest that the amount of sunlight received at the Earth's surface(surface solar radiation, SSR) has not been stable over the years, but underwent significant decadal variations, popul...Worldwide radiation records suggest that the amount of sunlight received at the Earth's surface(surface solar radiation, SSR) has not been stable over the years, but underwent significant decadal variations, popularly also known as “global dimming and brightening”. These variations have been particularly evident in China, where the SSR substantially declined from the 1960s to the 1990s(dimming), with indications for a trend reversal in the 2000s and a slight recovery(brightening) in recent years. This perspective/review paper will discuss recent updates and remaining challenges regarding our knowledge of the magnitudes, causes, and implications of these variations in SSR worldwide, with a particular emphasis on the developments in China.展开更多
The paleo-geothermal gradient is a crucial parameter for converting the thermal history to the exhumation history.However,the precise estimation of this parameter has been a challenge.This paper presents a simple two-...The paleo-geothermal gradient is a crucial parameter for converting the thermal history to the exhumation history.However,the precise estimation of this parameter has been a challenge.This paper presents a simple two-step method to model the paleo-geothermal gradient using low-temperature thermochronology.(1)It uses the Monte Carlo approach to generate thermal histories in a vertical section randomly and calculates the entire thermal history within the goodnessof-fit thresholds based on different paleo-geothermal gradients.(2)It selects the optimum paleogeothermal gradient by comparing the entire thermal history within different goodness-of-fit thresholds.We validated the method with apatite(U-Th)/He and fission track data collected from two drill cores in the Haiyuan-Liupanshan region.The result revealed that the best-fit paleo-geothermal gradient was~42℃/km during the Early Cretaceous–Miocene and has decreased rapidly to 20℃/km since~10 Ma.The crust thickening in the study area may explain the rapid reduction in the paleogeothermal gradient since~10 Ma.Our results are consistent with earlier studies in the region,suggesting that our simple and more intuitive approach provides an alternative method for paleogeothermal gradient modeling.展开更多
The dust cycle is a crucial component of the present-day Martian climate system.This study examines its multitimescale variability using an optimized 50-year simulation with the fully interactive scheme from the Globa...The dust cycle is a crucial component of the present-day Martian climate system.This study examines its multitimescale variability using an optimized 50-year simulation with the fully interactive scheme from the Global Open Planetary Atmospheric Model for Mars(GoMars),a newly developed Mars General Circulation Model(MGCM).GoMars is able to reproduce the diurnal,seasonal,and interannual characteristics of the dust cycle in several key aspects,with high repeatability in diurnal and seasonal variations during non-global dust storm(non-GDS)years.The model’s“climatology”(non-GDS years ensemble mean)captures the seasonal pattern and magnitude of the vertical–meridional dust distribution,validated against Mars Climate Database and Mars Climate Sounder observations.In the absence of direct observations,the GoMars-simulated near-surface wind stress lifting flux is evaluated through comparisons with other MGCMs(e.g.,MarsWRF),revealing consistent seasonal and spatial patterns.As for the diurnal cycle,the peak dust devil lifting flux occurs at 1200–1300 local time,matching the Mars Pathfinder measurements.The model also successfully captures the intense dust devil activity in Amazonis,a region identified as a major dust devil hotspot based on observational data.In GDS years,GoMars effectively reproduces spontaneous GDSs,capturing their observed onset times,locations,and dust transport patterns as exhibited in specific Martian years.The model also simulates significant interannual variability,with irregular GDS intervals along with reasonable dust–atmosphere interactions.展开更多
Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between...Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).展开更多
This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model： Grid-point Version 2 （FGOALS-g2） and the preliminary evaluations of its performances based on re- sults from t...This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model： Grid-point Version 2 （FGOALS-g2） and the preliminary evaluations of its performances based on re- sults from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project （CMIP5） experiment design. The results suggest that many obvi- ous improvements have been achieved by the FGOALS-g2 compared with the previous version, FGOALS-gl, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example, FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.展开更多
This research classified vegetation types and evaluated net primary productivity （NPP） of southern China＇s grasslands based on the improved comprehensive and sequential classification system （CSCS）, and proposed ...This research classified vegetation types and evaluated net primary productivity （NPP） of southern China＇s grasslands based on the improved comprehensive and sequential classification system （CSCS）, and proposed 5 thermal grades and 6 humidity grades. Four classes of grasslands vegetation were recognized by improved CSCS, namely, tundra grassland class, typical grassland class, mixed grassland class and alpine grassland class. At the type level, 14 types of vegetations （9 grasslands and 5 forests） were classified. The NPP had a trend to decrease from east to west and south to north, and the annual mean NPP was estimated to be 656.3 g C m-2 yr-1. The NPP value of alpine grassland class was relatively high, generally more than 1200 g C m2 yr-1. The NPP value of mixed grassland class was in a range from 1 000 to 1200 g C m-2 yr-1. Tundra grassland class was located in southeastern Tibet with high elevation, and its NPP value was the lowest （〈600 g C m＇2yrl）. The typical grassland class distributed in most of the area, and its NPP value was generally from 600 to 1000 g C m-2 yr-1. The total NPP value in the study area was 68.46 Tg C. The NPP value of typical grassland class was the highest （48.44 Tg C）, and mixed grassland class was the second （16.54 Tg C）, followed by alpine grassland class （3.22 Tg C）, with tundra grassland class being the lowest （0.25 Tg C）. For all the grasslands types, the total NPP of forest meadow was the highest （34.81 Tg C）, followed by sparse forest brush （16.54 Tg C）, and montane meadow was the lowest （0.01 Tg C）.展开更多
ABSTRACT The spatial and temporal global distribution of deep clouds was analyzed using a four-year dataset （2007-10） based on observations from CloudSat and CALIPSO. Results showed that in the Northern Hemisphere,...ABSTRACT The spatial and temporal global distribution of deep clouds was analyzed using a four-year dataset （2007-10） based on observations from CloudSat and CALIPSO. Results showed that in the Northern Hemisphere, the number of deep cloud systems （DCS） reached a maximum in summer and a minimum in winter. Seasonal variations in the number of DCS varied zonally in the Southern Hemisphere. DCS occurred most frequently over central Africa, the northern parts of South America and Australia, and Tibet. The mean cloud-top height of deep cloud cores （TDCC） decreased toward high latitudes in all seasons. DCS with the highest TDCC and deepest cores occurred over east and south Asian monsoon regions, west-central Africa and northern South America. The width of DCS （WDCS） increased toward high latitudes in all seasons. In general, DCS were more developed in the horizontal than in the vertical direction over high latitudes and vice versa over lower lat- itudes. Findings from this study show that different mechanisms are behind the development of DCS at different latitudes. Most DCS at low latitudes are deep convective clouds which are highly developed in the vertical direction but cover a rela tively small area in the horizontal direction; these DCS have the highest TDCC and smallest WDCS. The DCS at midlatitudes are more likely to be caused by cyclones, so they have less vertical development than DCS at low latitudes. DCS at high latitudes are mainly generated by large frontal systems, so they have the largest WDCS and the smallest TDCC.展开更多
The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, ...The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.展开更多
This paper addresses the adaptive synchronization for uncertain Liu system via a nonlinear input. By using a single nonlinear controller, the approach is utilized to implement the synchronization of Liu system with to...This paper addresses the adaptive synchronization for uncertain Liu system via a nonlinear input. By using a single nonlinear controller, the approach is utilized to implement the synchronization of Liu system with total parameters unknown. This method is simple and can be easily designed. What is more, it improves the existing conclusions in Ref [12]. Simulation results prove that the controller is effective and feasible in the end.展开更多
If a system is not disturbed （or invaded） by some law, there is no doubt that each system will move according to the expected law and keep stable. Although such a fact often appears, some unknown law breaks into the...If a system is not disturbed （or invaded） by some law, there is no doubt that each system will move according to the expected law and keep stable. Although such a fact often appears, some unknown law breaks into the system and leads it into turbulence. Using function one direction S-rough sets, this article gives the concept of the F-generation law in the system, the generation model of the F-generation law and the recognition method of the system law. Function one direction singular rough sets is a new theory and method in recognizing the disturbance law existing in the system and recognizing the system law.展开更多
The Cloud Aerosol- Radiation （CAR） ensemble modeling system has recently been built to better un- derstand cloud/aerosol/radiation processes and determine the uncertainties caused by different treatments of cloud/ae...The Cloud Aerosol- Radiation （CAR） ensemble modeling system has recently been built to better un- derstand cloud/aerosol/radiation processes and determine the uncertainties caused by different treatments of cloud/aerosol/radiation in climate models. The CAR system comprises a large scheme collection of cloud, aerosol, and radiation processes available in the literature, including those commonly used by the world＇s leading GCMs. In this study, detailed analyses of the overall accuracy and efficiency of the CAR system were performed. Despite the different observations used, the overall accuracies of the CAR ensemble means were found to be very good for both shortwave （SW） and longwave （LW） radiation calculations. Taking tile percentage errors for July 2004 compared to ISCCP （International Satellite Cloud Climatology Project） data over （60~N, 60~S） as an example, even among the 448 CAR members selected here, those errors of the CAR ensemble means were only about -0.67% （-0.6 W m-2） and -0.82% （-2.0 W m-2） for SW and LW upward fluxes at the top of atmosphere, and 0.06% （0.1 W m-2） and -2.12% （-7.8 W m 2） for SW and LW downward fluxes at the surface, respectively. Furthermore, model SW frequency distributions in July 2004 covered the observational ranges entirely, with ensemble means located in the middle of the ranges. Moreover, it was found that the accuracy of radiative transfer calculations can be significantly enhanced by＂ using certain combinations of cloud schemes for the cloud cover fraction, particle effective size, water path, and optical properties, along with better explicit treatments for unresolved cloud structures.展开更多
文摘Ecosystem is a fundamental organizational unit of the biosphere in which biological communities interact with their non-biological environment through energy flows and material cycles.Ecosystem science is the study of patterns,processes,and services of ecosystems.Since the 1990s,rising concerns regarding global climate change,biodiversity loss,ecosystem degradation,and sustainability of the human-dominated biosphere have stimulated the growth of ecosystem science,which is expected to provide systematic solutions to many of these major issues facing human societies.This paper provides a comprehensive review of the current progress in ecosystem science and identifies some key research challenges facing this discipline.We demonstrate that a key feature of the current progress in ecosystem science is its evolution from primarily theoretical explorations toward more systematic,integrative and application-oriented studies.Specifically,five major changes in the discipline over the past several decades can be identified.These include:(1)the expansion of the primary goal from understanding nature to include human activities;(2)the broadening of the research focus from single ecosystem types to macro-ecosystems comprising multiple regional ecosystems;(3)the shifting of research methods from small-scale observations and experiments to large-scale observations,network experiments,and model simulations;(4)the increasing attention to comprehensive integration of ecosystem components,processes,and scales;and(5)the shifting from a primarily biology-oriented focus to an integrated multi-disciplinary scientific field.While ecosystem science still faces many challenges in the future,these directional changes,along with the rapidly enriched research tools and data acquisition capabilities,lay a promising ground for the discipline’s future as a fundamental scientific basis for solving many environmental challenges facing human societies.
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
基金supported by the Ecological Conservation and High-Quality Development of the Yellow River Basin Program,China(2022-YRUC-010102)the Second Tibetan Plateau Scientific Expedition and Research Program,China(20190ZKK0405)the Basic Research Fund Project of Innovation Team of Novel Forage Germplasm and Sustainable Utilization of Grassland Resources,China(BR22-12-07)。
文摘There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.
基金supported by the National Natural Science Foundation of China(42277087,42130708,42471021,42277482,and 42361144876)the Natural Science Foundation of Guangdong Province(2024A1515012550)+3 种基金the Hainan Institute of National Park grant(KY-23ZK01)the Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan(JC2022011)the Shenzhen Science and Technology Program(JCYJ20240813112106009 and ZDSYS20220606100806014)the Scientific Research Start-up Funds(QD2021030C)from Tsinghua Shenzhen International Graduate School。
文摘Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.
基金Supported by the Basic Product Innovation Plan for Vehicle Power Scientific Research Project(Grant No.JCCPCX201704).
文摘This research presents an advanced study on the modeling and stability analysis of electro-hydraulic control modules used in intelligent chassis systems.Firstly,a comprehensive nonlinear mathematical model of the electro-hydraulic power-shift system is developed,incorporating pipeline characteristics through impedance analysis and examining coupling effects between the pilot solenoid valve,main valve,and pipeline.Then,the model’s accuracy is validated through experimental testing,demonstrating high precision and minimal model errors.A comparative analysis between simulation data(both with and without pipeline characteristics)and experimental results reveals that the model considering pipeline parameters aligns more closely with experimental data,highlighting its superior accuracy.The research further explores the influence of key factors on system stability,including damping coefficient,feedback cavity orifice diameter,spring stiffness,pipeline length,and pipeline diameter.Significant findings include the critical impact of damping coefficient,orifice diameter,and pipeline length on stability,while spring stiffness has a minimal effect.These findings provide valuable insights for optimizing electro-hydraulic control modules in intelligent chassis systems,with practical implications for automotive and construction machinery applications.
基金The National Natural Science Foundation of China-Regional Science Foundation Project“Research on constructing cell communication networks based on single-cell and spatial transcriptomics data”(62362062)The Multimodal Major Chronic Disease Prevention and Control Science and Engineering Key Laboratory Project of MIIT“Identification of novel drug targets for lung cancer via Mendelian randomization analysis based on blood proteomics”(MCD-2023-1-15).
文摘Genome-wide association study(GWAS)data are used to explore the associations between blood metabolites and 5 respiratory diseases:asthma,tuberculosis(TB),chronic obstructive pulmonary disease(COPD),cor pulmonale,and bronchitis.The main method of analysis used is the inverse-variance weighted(IVW)approach,complemented by several sensitivity analyses,including MR-Egger regression,the weighted median,the weighted mode,Cochran’s Q test,and the pleiotropy test.Additional directional tests,Meta-analysis and metabolic pathway analyses are conducted for deeper insights.3 metabolites showing significant causal relationships are identified.Catechol glucuronide levels as a protective factor have a positive causal relationship with asthma;the creatine to carnitine ratio has a negative causal relationship with COPD as a risk factor;and the adenosine 5’-diphosphate(ADP)to N-acetylglucosamine to N-acetylgalactosamine ratio as a protective factor has a positive causal relationship with bronchitis.Additionally,13 metabolites demonstrate strong causal relationships.Furthermore,we delineate 14 metabolic pathways related to the outcomes,including 6 associated with asthma,2 with TB,1 with COPD,4 with cor pulmonale,and 1 with bronchitis.A causal relationship between blood metabolites and 5 respiratory diseases has been established.The identified metabolites and pathways offer new insights into the underlying mechanisms of these diseases,necessitating further experimental validation.
基金supported by the National Natural Science Foundation of China(62373317)the Tianshan Talent Training Program(2022TSYCCX0013)+3 种基金the Key Project of Natural Science Foundation of Xinjiang(2021D01D10)the Basic Research Foundation for Universities of Xinjiang(XJEDU2023P023)the Xinjiang Key Laboratory of Applied Mathematics(XJDX1401)the Intelligent Control and Optimization Research Platform in Xinjiang University.
文摘This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.
基金The National Natural Science Foundation of China-Regional Science“Identification of novel drug targets for lung cancer via Mendelian randomization analysis based on blood proteomics”(62362062)The 2025 Xinjiang University Excellent Graduate Innovation Project“Research on identification of therapeutic targets and predictive factors for mental disorders based on proteomics”(XJDX2025YJS151)。
文摘Traditional psychiatric diagnosis relies on subjective symptom assessment,lacking objective biomarkers that hinder early detection and personalized treatment.Plasma proteins and polygenic risk score(PRS),as potential predictive tools,hold promise for advancing early diagnosis of mental disorders.This study aims to evaluate the predictive potential of proteomic features and PRS in multiple mental illnesses(depression,schizophrenia,and post-traumatic stress disorder(PTSD)).Using participant data from the UK Biobank-Pharma Proteomics Project,we screen protein associations with mental disorders through least absolute shrinkage and selection operator(LASSO)analysis and construct a Cox regression risk prediction model by integrating the PRS.Additionally,we evaluate predictive performance using 6 machine learning methods and Kaplan-Meier survival curves.Our findings reveal distinct predictive patterns across dis-orders.For depression,integrating plasma proteins with PRS significantly improves prediction beyond the clinical model(C-index=0.6322).For schizophrenia,adding plasma proteins enhances predictive performance,whereas PRS provides no significant improvement.For PTSD,neither plasma proteins nor PRS add substantial predictive value beyond clinical variables.Risk stratification analysis demonstrat that all three mental disorders models can clearly distinguish high-risk from low-risk groups(depression:HR=2.34,P<0.001;schizophrenia:HR=5.47,P<0.001;PTSD:HR=3.02,P<0.001).Al-though it shows good performance in short-term prediction,its long-term prediction ability has decreased,and it needs to be further optimized in the future.This study underscores the differential utility of biomarkers across mental disorders and provides a rationale for disorder-specific predictive modeling in precision psychiatry.
基金supported by the National Natural Science Foundation of China(No.42176048)Qingdao Postdoctoral Applied Research Project(No.QDBSH20230102100)Shandong Postdoctoral Science Foundation(No.SDCX-ZG-202303054).
文摘Phosphorus(P)is an essential nutrient for primary production and frequently acts as a limiting factor in estuaries.The Changjiang River Estuary,recognized as one of the largest estuaries globally,has experienced significant changes in nutrient dynamics due to anthropogenic activities.The recent reduction in P loading from the Changjiang River may have significant implications for the dynamics of dissolved inorganic phosphorus(DIP)within this estuarine system.Based on DIP data collected in 2017,2019,and 2023,combined with historical datasets,we aim to identify the drivers of DIP concentration changes in the Changjiang Estuary under the change in river inputs.The results indicate significant spatiotemporal variations in the distribution of DIP in the Changjiang Estuary,with the highest average concentration in winter.DIP exhibits non-conservative behavior along the salinity gradient,primarily influenced by biological utilization.Long-term DIP variations can be divided into three stages:a low-concentration period(1984–1987),a significant increase(1987–2014),and a decline(since 2015),with a current decreasing trend of 0.024μmol/(L·yr)(R^(2)=0.97,P<0.05).A discernible trend of P depletion in estuarine environments is observed,attributed to diminished riverine load and enhanced phytoplankton fixation.The reduction,and in some cases depletion,of DIP in the Changjiang Estuary has significantly altered the nitrogen-to-phosphorus ratio.The recent changes in total phosphorus(TP)compositions in the Changjiang Estuary are also attributed to a decrease in riverine input.Ongoing terrestrial nutrient management may further lower DIP concentrations,potentially impacting the estuarine ecosystem.
基金supported by a sequence of Swiss National Science Foundation Grants (Grant Nos.200021_135395,200020_159938,200020_188601)funding from the Federal Office of Meteorology and Climatology Meteo Swiss within the framework of GCOS Switzerland in support of the Global Energy Balance Archive (GEBA) hosted at ETH Zurich。
文摘Worldwide radiation records suggest that the amount of sunlight received at the Earth's surface(surface solar radiation, SSR) has not been stable over the years, but underwent significant decadal variations, popularly also known as “global dimming and brightening”. These variations have been particularly evident in China, where the SSR substantially declined from the 1960s to the 1990s(dimming), with indications for a trend reversal in the 2000s and a slight recovery(brightening) in recent years. This perspective/review paper will discuss recent updates and remaining challenges regarding our knowledge of the magnitudes, causes, and implications of these variations in SSR worldwide, with a particular emphasis on the developments in China.
基金supported by the National Natural Science Foundation of China(Nos.42072229,42030301,41102131,41972049,41972302 and 41977231)the Guangdong Basic and Applied Basic Research Foundation(No.2025A1515010724)+3 种基金the Guangdong Natural Science Foundation(No.2021A1515011658)the Science and Technology Program of Guangzhou(No.202002030184)the Special Fund for Basic Scientific Research of Central Colleges,Chang'an University(No.300102260502)the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(No.2024ZD1001003)。
文摘The paleo-geothermal gradient is a crucial parameter for converting the thermal history to the exhumation history.However,the precise estimation of this parameter has been a challenge.This paper presents a simple two-step method to model the paleo-geothermal gradient using low-temperature thermochronology.(1)It uses the Monte Carlo approach to generate thermal histories in a vertical section randomly and calculates the entire thermal history within the goodnessof-fit thresholds based on different paleo-geothermal gradients.(2)It selects the optimum paleogeothermal gradient by comparing the entire thermal history within different goodness-of-fit thresholds.We validated the method with apatite(U-Th)/He and fission track data collected from two drill cores in the Haiyuan-Liupanshan region.The result revealed that the best-fit paleo-geothermal gradient was~42℃/km during the Early Cretaceous–Miocene and has decreased rapidly to 20℃/km since~10 Ma.The crust thickening in the study area may explain the rapid reduction in the paleogeothermal gradient since~10 Ma.Our results are consistent with earlier studies in the region,suggesting that our simple and more intuitive approach provides an alternative method for paleogeothermal gradient modeling.
基金jointly supported by the National Natural Science Foundation of China(Grant No.42475135)the Key Technology Research Project of TW-3(TW3006)the IAP’s basic scientific research project during the 14th Five-Year Plan Period.
文摘The dust cycle is a crucial component of the present-day Martian climate system.This study examines its multitimescale variability using an optimized 50-year simulation with the fully interactive scheme from the Global Open Planetary Atmospheric Model for Mars(GoMars),a newly developed Mars General Circulation Model(MGCM).GoMars is able to reproduce the diurnal,seasonal,and interannual characteristics of the dust cycle in several key aspects,with high repeatability in diurnal and seasonal variations during non-global dust storm(non-GDS)years.The model’s“climatology”(non-GDS years ensemble mean)captures the seasonal pattern and magnitude of the vertical–meridional dust distribution,validated against Mars Climate Database and Mars Climate Sounder observations.In the absence of direct observations,the GoMars-simulated near-surface wind stress lifting flux is evaluated through comparisons with other MGCMs(e.g.,MarsWRF),revealing consistent seasonal and spatial patterns.As for the diurnal cycle,the peak dust devil lifting flux occurs at 1200–1300 local time,matching the Mars Pathfinder measurements.The model also successfully captures the intense dust devil activity in Amazonis,a region identified as a major dust devil hotspot based on observational data.In GDS years,GoMars effectively reproduces spontaneous GDSs,capturing their observed onset times,locations,and dust transport patterns as exhibited in specific Martian years.The model also simulates significant interannual variability,with irregular GDS intervals along with reasonable dust–atmosphere interactions.
基金J.YANG was supported by funding from the National Natural Science Foundation of China(Grant Nos.42475022,42261144671)the National Key R&D Program of China(Project No.2024YFC3013100)+2 种基金the Fundamental Research Funds for the Central UniversitiesM.LU was supported by the Otto Poon Centre of Climate Resilience and Sustainability at HKUST and the Hong Kong Research Grant Committee(Project No.16300424)Data processing and storage were supported by the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab).
文摘Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).
基金supported by the National"863"Project(Grant No.2010AA012304)the"973"Project(Grant No.2010CB951904)+1 种基金the China Meteorological Administration R&D Special Fund for Public Welfare(meteorology)(Grant No.GYHY201006014)the National Natural Science Foundation of China(Grant Nos.40923002 and 41005053)
文摘This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model： Grid-point Version 2 （FGOALS-g2） and the preliminary evaluations of its performances based on re- sults from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project （CMIP5） experiment design. The results suggest that many obvi- ous improvements have been achieved by the FGOALS-g2 compared with the previous version, FGOALS-gl, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example, FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.
基金the National Basic Research Program of China(2010CB950702)the National High-Technology Reaearch and Development Program of China(2007AA10Z231)the Asia-Pacific Network for Global Change Research Project(ARCP201106CMY-Li)
文摘This research classified vegetation types and evaluated net primary productivity （NPP） of southern China＇s grasslands based on the improved comprehensive and sequential classification system （CSCS）, and proposed 5 thermal grades and 6 humidity grades. Four classes of grasslands vegetation were recognized by improved CSCS, namely, tundra grassland class, typical grassland class, mixed grassland class and alpine grassland class. At the type level, 14 types of vegetations （9 grasslands and 5 forests） were classified. The NPP had a trend to decrease from east to west and south to north, and the annual mean NPP was estimated to be 656.3 g C m-2 yr-1. The NPP value of alpine grassland class was relatively high, generally more than 1200 g C m2 yr-1. The NPP value of mixed grassland class was in a range from 1 000 to 1200 g C m-2 yr-1. Tundra grassland class was located in southeastern Tibet with high elevation, and its NPP value was the lowest （〈600 g C m＇2yrl）. The typical grassland class distributed in most of the area, and its NPP value was generally from 600 to 1000 g C m-2 yr-1. The total NPP value in the study area was 68.46 Tg C. The NPP value of typical grassland class was the highest （48.44 Tg C）, and mixed grassland class was the second （16.54 Tg C）, followed by alpine grassland class （3.22 Tg C）, with tundra grassland class being the lowest （0.25 Tg C）. For all the grasslands types, the total NPP of forest meadow was the highest （34.81 Tg C）, followed by sparse forest brush （16.54 Tg C）, and montane meadow was the lowest （0.01 Tg C）.
基金supported by the National Natural Science Foundation of China (Grant No.41375080)the National Program on Key Basic Research Project of China (Grant Nos.2011CB403405 and 2013CB955804)the US Department of Energy Atmospheric System Research Program (DESC0007171)
文摘ABSTRACT The spatial and temporal global distribution of deep clouds was analyzed using a four-year dataset （2007-10） based on observations from CloudSat and CALIPSO. Results showed that in the Northern Hemisphere, the number of deep cloud systems （DCS） reached a maximum in summer and a minimum in winter. Seasonal variations in the number of DCS varied zonally in the Southern Hemisphere. DCS occurred most frequently over central Africa, the northern parts of South America and Australia, and Tibet. The mean cloud-top height of deep cloud cores （TDCC） decreased toward high latitudes in all seasons. DCS with the highest TDCC and deepest cores occurred over east and south Asian monsoon regions, west-central Africa and northern South America. The width of DCS （WDCS） increased toward high latitudes in all seasons. In general, DCS were more developed in the horizontal than in the vertical direction over high latitudes and vice versa over lower lat- itudes. Findings from this study show that different mechanisms are behind the development of DCS at different latitudes. Most DCS at low latitudes are deep convective clouds which are highly developed in the vertical direction but cover a rela tively small area in the horizontal direction; these DCS have the highest TDCC and smallest WDCS. The DCS at midlatitudes are more likely to be caused by cyclones, so they have less vertical development than DCS at low latitudes. DCS at high latitudes are mainly generated by large frontal systems, so they have the largest WDCS and the smallest TDCC.
基金Supported by the "973" Project of P. R. China (G1998020300)
文摘The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.
基金Project supported by the Educational Commission of Hubei Province of China,(Grant No 080056)
文摘This paper addresses the adaptive synchronization for uncertain Liu system via a nonlinear input. By using a single nonlinear controller, the approach is utilized to implement the synchronization of Liu system with total parameters unknown. This method is simple and can be easily designed. What is more, it improves the existing conclusions in Ref [12]. Simulation results prove that the controller is effective and feasible in the end.
基金This project was supported by the Ministry of Education of China (206089)Shangdong Provincial Natural Science Foundation of China (Y2004A04)Fujian Provincial Natural Science Foundation of China (Z051049).
文摘If a system is not disturbed （or invaded） by some law, there is no doubt that each system will move according to the expected law and keep stable. Although such a fact often appears, some unknown law breaks into the system and leads it into turbulence. Using function one direction S-rough sets, this article gives the concept of the F-generation law in the system, the generation model of the F-generation law and the recognition method of the system law. Function one direction singular rough sets is a new theory and method in recognizing the disturbance law existing in the system and recognizing the system law.
基金supported by the National Basic Research Program of China (973 Program) (Grant No. 2010CB951901)the U.S. DOE office of Biological and Environmental Research (BER) (Grant No. DE-SC0001683)+2 种基金the National Natural Science Foundation of China (Grant Nos. 40605026 and 40830103)the "Strategic Priority Research Program-Climate Change: Carbon Budget and Relevant Issues" of the Chinese Academy of Sciences (Grant No. XDA05110101)the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231
文摘The Cloud Aerosol- Radiation （CAR） ensemble modeling system has recently been built to better un- derstand cloud/aerosol/radiation processes and determine the uncertainties caused by different treatments of cloud/aerosol/radiation in climate models. The CAR system comprises a large scheme collection of cloud, aerosol, and radiation processes available in the literature, including those commonly used by the world＇s leading GCMs. In this study, detailed analyses of the overall accuracy and efficiency of the CAR system were performed. Despite the different observations used, the overall accuracies of the CAR ensemble means were found to be very good for both shortwave （SW） and longwave （LW） radiation calculations. Taking tile percentage errors for July 2004 compared to ISCCP （International Satellite Cloud Climatology Project） data over （60~N, 60~S） as an example, even among the 448 CAR members selected here, those errors of the CAR ensemble means were only about -0.67% （-0.6 W m-2） and -0.82% （-2.0 W m-2） for SW and LW upward fluxes at the top of atmosphere, and 0.06% （0.1 W m-2） and -2.12% （-7.8 W m 2） for SW and LW downward fluxes at the surface, respectively. Furthermore, model SW frequency distributions in July 2004 covered the observational ranges entirely, with ensemble means located in the middle of the ranges. Moreover, it was found that the accuracy of radiative transfer calculations can be significantly enhanced by＂ using certain combinations of cloud schemes for the cloud cover fraction, particle effective size, water path, and optical properties, along with better explicit treatments for unresolved cloud structures.
