In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly explo...In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.展开更多
Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps ...Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps to formulate differential scientific carbon mitigation policies.In this regard,this study constructs an integrated model of SD-PLUS-InVEST to simulate LUCs and CS changes under multi-climate change-based scenarios(SSP126,SSP245,SSP585)for three major urban agglomerations(3UAs)in the Yangtze River Economic Belt.Results demonstrate that land use demand in the 3UAs changes considerably in each scenario.Construction land in the 3UAs remains the most important growth category for the coming decade,but its increase varies in different scenarios.CS in the Yangtze River Delta Urban Agglomeration(YRDUA)and Mid-Yangtze River Urban Agglomeration(MYRUA)shows a similar downward trend under different scenarios,with scenario SSP245 decreasing the most,to 184,713.526 Tg and 384,459.729 Tg,respectively.CS in the Cheng-Yu(Chengdu-Chongqing)Urban Agglomeration(CYUA)exhibits the opposite upward trend,with scenario SSP126 increasing the most to 153,007.973 Tg.The major cause of CS loss remains the conversion of forest land to construction land in the YRDUA and MYRUA under different scenarios.However,in the CYUA,the conversion of forest land to cultivated land is the major driver of CS loss under scenario SSP126.In contrast,the conversion of cultivated land to construction land dominantly drives CS loss under scenarios SSP245 and SSP585.The conversion of water body to other land use types is the major cause of CS gain in the YRDUA and MYRUA under different scenarios.At the same time,in the CYUA,the driver is the conversion of cultivated land to forest land.These findings demonstrate the significance of the low-carbon development in urban agglomerations at different development stages at home and abroad.展开更多
In research on the legendary Xia Dynasty of ancient China,the famous archaeological site of Erlitou and its culture are the most debated topics.A key question is whether this ancient culture is truly related to the Xi...In research on the legendary Xia Dynasty of ancient China,the famous archaeological site of Erlitou and its culture are the most debated topics.A key question is whether this ancient culture is truly related to the Xia Dynasty.This study combines traditional literature(Xia Xiao Zheng),archaeological evidence(on alligators),and climate simulation(of autumn rains)to demonstrate that the ancient Chinese phenological calendar,Xia Xiao Zheng,likely originated in the same region as the Erlitou culture.A logical explanation of these findings is that both Xia Xiao Zheng and the Erlitou culture are indeed closely related to the Xia Dynasty.展开更多
The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of th...The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.展开更多
West Africa was hit by an unprecedented drought in the 1970’s and 1980’s years, with dramatic consequences for surface and groundwater resources. In the context of climate change, there are many studies for the pred...West Africa was hit by an unprecedented drought in the 1970’s and 1980’s years, with dramatic consequences for surface and groundwater resources. In the context of climate change, there are many studies for the prediction of the increase in the occurrence of these droughts. To predict this situation in the Senegalese region, it is necessary to use regional climate models, which carrying out the study. This work deals with the interest to examine the capacity of the RCMs (regional climate models) in order to reproduce the deficit on the 1970’s year rainfall in Senegal. In this work, we used daily precipitation data from five (5) regional climate models to characterize the droughts in Senegal by using the SPI (Standardized Precipitation Index) on different time scales (3, 6, 12 and 24 months). For this purpose, the index was calculated over two distinct periods: 1951-1969 and 1970-1990. The results show that the period 1970-1990 was drier than the period 1951-1969. For the zonal average, the results show that the North of Senegal was more affected by this deficit rainfall than the South part. The analysis of the interannual variability of rainfall for some stations in Senegal shows that the drought did not start at the same time throughout the zone.展开更多
The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to...The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to investigate the interactions among atmospheric CO_(2),the physical climate system,and the carbon cycle of the underlying surface for a better understanding of the Earth system.Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations.The Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0)has successfully fixed a two-way coupling of atmospheric CO_(2)with the climate and carbon cycle on land and in the ocean.Using CAS-ESM2.0,we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment.This paper examines the modeled CO_(2)by comparison with observed CO_(2)at the sites of Mauna Loa and Barrow,and the Greenhouse Gases Observing Satellite(GOSAT)CO_(2)product.The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO_(2)during the period 1850-2014,and in capturing the seasonal cycle of CO_(2)at the two baseline sites,as well as over northern high latitudes.These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions,even though uncertainties remain in the processes involved.This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate,which will provide significant scientific support for climate research and China’s goal of carbon neutrality.展开更多
Phenology shifts influence regional climate by altering energy,and water fluxes through biophysical processes.However,a quantitative understanding of the phenological control on vegetation’s biophysical feedbacks to ...Phenology shifts influence regional climate by altering energy,and water fluxes through biophysical processes.However,a quantitative understanding of the phenological control on vegetation’s biophysical feedbacks to re gional climate remains elusive.Using long-term remote sensing observations and Weather Research and Fore casting(WRF)model simulations,we investigated vegetation phenology changes from 2003 to 2020 and quan tified their biophysical controls on the regional climate in Northeast China.Our findings elucidated that earlier green-up contributed to a prolonged growing season in forests,while advanced green-up and delayed dormancy extended the growing season in croplands.This prolonged presence and increased maximum green cover in tensified climate-vegetation interactions,resulting in more significant surface cooling in croplands compared to forests.Surface cooling from forest phenology changes was prominent during May’s green-up(-0.53±0.07°C),while crop phenology changes induced cooling throughout the growing season,particularly in June(-0.47±0.15°C),July(-0.48±0.11°C),and September(-0.28±0.09°C).Furthermore,we unraveled the contributions of different biophysical pathways to temperature feedback using a two-resistance attribution model,with aero dynamic resistance emerging as the dominant factor.Crucially,our findings underscored that the land surface temperature(LST)sensitivity,exhibited substantially higher values in croplands rather than temperate forests.These strong sensitivities,coupled with the projected continuation of phenology shifts,portend further growing season cooling in croplands.These findings contribute to a more comprehensive understanding of the intricate feedback mechanisms between vegetation phenology and surface temperature,emphasizing the significance of vegetation phenology dynamics in shaping regional climate pattern and seasonality.展开更多
Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustaina...Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.展开更多
Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regime...Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.展开更多
As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate c...As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate change.The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts.展开更多
Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer ...Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.展开更多
This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has ...This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.展开更多
Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather an...Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.展开更多
We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other ...We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.展开更多
基金This study was supported by the National Natural Science Foundation of China(Grant No.U2342228)the National Key Program for Developing Basic Sciences(Grant No.2020YFA0608902)+1 种基金the National Natural Science Foundation of China(Grant Nos.92358302,and 42242018)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0500303).
文摘In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.
基金Key Project of National Social Science Fund,No.23AZD032National Natural Science Foundation of China No.42371258Program of China Scholarship Council No.202306850036。
文摘Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps to formulate differential scientific carbon mitigation policies.In this regard,this study constructs an integrated model of SD-PLUS-InVEST to simulate LUCs and CS changes under multi-climate change-based scenarios(SSP126,SSP245,SSP585)for three major urban agglomerations(3UAs)in the Yangtze River Economic Belt.Results demonstrate that land use demand in the 3UAs changes considerably in each scenario.Construction land in the 3UAs remains the most important growth category for the coming decade,but its increase varies in different scenarios.CS in the Yangtze River Delta Urban Agglomeration(YRDUA)and Mid-Yangtze River Urban Agglomeration(MYRUA)shows a similar downward trend under different scenarios,with scenario SSP245 decreasing the most,to 184,713.526 Tg and 384,459.729 Tg,respectively.CS in the Cheng-Yu(Chengdu-Chongqing)Urban Agglomeration(CYUA)exhibits the opposite upward trend,with scenario SSP126 increasing the most to 153,007.973 Tg.The major cause of CS loss remains the conversion of forest land to construction land in the YRDUA and MYRUA under different scenarios.However,in the CYUA,the conversion of forest land to cultivated land is the major driver of CS loss under scenario SSP126.In contrast,the conversion of cultivated land to construction land dominantly drives CS loss under scenarios SSP245 and SSP585.The conversion of water body to other land use types is the major cause of CS gain in the YRDUA and MYRUA under different scenarios.At the same time,in the CYUA,the driver is the conversion of cultivated land to forest land.These findings demonstrate the significance of the low-carbon development in urban agglomerations at different development stages at home and abroad.
基金National Key Research and Development Program of China,No.2023YFF0804704National Natural Science Foundation of China,No.42130604,No.42105044+1 种基金Major Projects of the Ministry of Education's Key Research Bases of Humanities and Social Sciences,No.22JJD770020Social Scienceof Northwest University,No.21XNFH007。
文摘In research on the legendary Xia Dynasty of ancient China,the famous archaeological site of Erlitou and its culture are the most debated topics.A key question is whether this ancient culture is truly related to the Xia Dynasty.This study combines traditional literature(Xia Xiao Zheng),archaeological evidence(on alligators),and climate simulation(of autumn rains)to demonstrate that the ancient Chinese phenological calendar,Xia Xiao Zheng,likely originated in the same region as the Erlitou culture.A logical explanation of these findings is that both Xia Xiao Zheng and the Erlitou culture are indeed closely related to the Xia Dynasty.
基金supported by the Second Comprehensive Scientific Research Survey on the Tibetan Plateau[grant number 2019QZKK0103]the National Natural Science Foundation of China[grant numbers 42375071 and 42230610].
文摘The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.
文摘West Africa was hit by an unprecedented drought in the 1970’s and 1980’s years, with dramatic consequences for surface and groundwater resources. In the context of climate change, there are many studies for the prediction of the increase in the occurrence of these droughts. To predict this situation in the Senegalese region, it is necessary to use regional climate models, which carrying out the study. This work deals with the interest to examine the capacity of the RCMs (regional climate models) in order to reproduce the deficit on the 1970’s year rainfall in Senegal. In this work, we used daily precipitation data from five (5) regional climate models to characterize the droughts in Senegal by using the SPI (Standardized Precipitation Index) on different time scales (3, 6, 12 and 24 months). For this purpose, the index was calculated over two distinct periods: 1951-1969 and 1970-1990. The results show that the period 1970-1990 was drier than the period 1951-1969. For the zonal average, the results show that the North of Senegal was more affected by this deficit rainfall than the South part. The analysis of the interannual variability of rainfall for some stations in Senegal shows that the drought did not start at the same time throughout the zone.
基金the National Key Research and Development Program of China(Grant No.2022YFE0106500)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.2022076)+1 种基金the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab2023-EL-ZD-00012)。
文摘The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to investigate the interactions among atmospheric CO_(2),the physical climate system,and the carbon cycle of the underlying surface for a better understanding of the Earth system.Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations.The Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0)has successfully fixed a two-way coupling of atmospheric CO_(2)with the climate and carbon cycle on land and in the ocean.Using CAS-ESM2.0,we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment.This paper examines the modeled CO_(2)by comparison with observed CO_(2)at the sites of Mauna Loa and Barrow,and the Greenhouse Gases Observing Satellite(GOSAT)CO_(2)product.The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO_(2)during the period 1850-2014,and in capturing the seasonal cycle of CO_(2)at the two baseline sites,as well as over northern high latitudes.These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions,even though uncertainties remain in the processes involved.This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate,which will provide significant scientific support for climate research and China’s goal of carbon neutrality.
基金supported by the Strategic Pri-ority Research Program(A)of the Chinese Academy of Sciences(Grant No.XDA28080503)the National Natural Science Foundation of China(Grant No.42071025)+1 种基金the Youth Innovation Promotion Associa-tion of Chinese Academy of Sciences(Grant No.2023240)the Pacific Northwest National Laboratory which is operated for DOE by Battelle Memorial Institute under Contract DE-A06-76RLO 1830.
文摘Phenology shifts influence regional climate by altering energy,and water fluxes through biophysical processes.However,a quantitative understanding of the phenological control on vegetation’s biophysical feedbacks to re gional climate remains elusive.Using long-term remote sensing observations and Weather Research and Fore casting(WRF)model simulations,we investigated vegetation phenology changes from 2003 to 2020 and quan tified their biophysical controls on the regional climate in Northeast China.Our findings elucidated that earlier green-up contributed to a prolonged growing season in forests,while advanced green-up and delayed dormancy extended the growing season in croplands.This prolonged presence and increased maximum green cover in tensified climate-vegetation interactions,resulting in more significant surface cooling in croplands compared to forests.Surface cooling from forest phenology changes was prominent during May’s green-up(-0.53±0.07°C),while crop phenology changes induced cooling throughout the growing season,particularly in June(-0.47±0.15°C),July(-0.48±0.11°C),and September(-0.28±0.09°C).Furthermore,we unraveled the contributions of different biophysical pathways to temperature feedback using a two-resistance attribution model,with aero dynamic resistance emerging as the dominant factor.Crucially,our findings underscored that the land surface temperature(LST)sensitivity,exhibited substantially higher values in croplands rather than temperate forests.These strong sensitivities,coupled with the projected continuation of phenology shifts,portend further growing season cooling in croplands.These findings contribute to a more comprehensive understanding of the intricate feedback mechanisms between vegetation phenology and surface temperature,emphasizing the significance of vegetation phenology dynamics in shaping regional climate pattern and seasonality.
基金funded by the National Natural Science Foundation of China(32372546)Shenzhen Science and Technology Program(KQTD20180411143628272)+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences and STI 2030-Major Projects(2022ZD04021)the National Key Research and Development Program of China(2023YFD2200700)。
文摘Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.
基金supported by the funding Riset Unggulan Daerah 2022 of the Bureau of Development Planning and Research in Central Java Province(BAPPEDA Provinsi Jawa Tengah).
文摘Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.
基金supported by the National Natural Science Foundation of China(No.82025030,No.72394404)the National Key Research and Development Program of China(No.2022YFC3702700)the National Research Program for Key Issues in Air Pollution Control of China(No.DQGG0401).
文摘As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate change.The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts.
基金Opening Foundation of Key Laboratory of Explosive Energy Utilization and Control,Anhui Province(BP20240104)Graduate Innovation Program of China University of Mining and Technology(2024WLJCRCZL049)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2701)。
文摘Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.42422502 and 42275038)the China Meteorological Administration Climate Change Special Program (Grant No.QBZ202306)funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)。
文摘This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.
基金in part supported by the National Natural Science Foundation of China(Grant Nos.42288101,42405147 and 42475054)in part by the China National Postdoctoral Program for Innovative Talents(Grant No.BX20230071)。
文摘Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.
文摘We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.
