Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives ...Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.展开更多
Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal...Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal conditions in East Asia for up to five years.We compare temperature-based agroclimatic indicators from atmospheric reanalysis data with the firstyear prediction of the Decadal Prediction System version 4(DePreSys4),initialized annually from November 1960 to 2024.Our analysis reveals that first-year predictions accurately represent observed spatial climatological patterns,although trends in agroclimatic indicators based on daily maximum temperature are overestimated.High skill scores are observed in predicting the beginning of the growing season,frost-free days,agricultural hot days,and heat intensity in major cropping regions.However,the end of the growing season is less predictable due to longer lead times.Notably,five-year average predictions show higher skill than first-year predictions due to smoothed interannual variability.These improved climate predictions enable farmers and policymakers to make informed decisions about crop selection and agricultural infrastructure.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 provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despit...This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despite some systematic biases,all RCMs effectively capture the main features of observed temperature and precipitation means and extremes over CA,with notable variations in model performance due to differences in the driving global climate models and the RCMs themselves.Overall,REMO consistently outperforms ALARO in simulating temperature-related indices,and ALARO-0 provides more accurate simulations for precipitation-related indices,and the multimodel ensemble(MME)tends to outperform individual RCMs.Under the representative concentration pathway(RCP)scenarios of RCP2.6 and RCP8.5,the MME results indicate a clear warming trend across CA for all temperature-related indices,except for the diurnal temperature range,with annual temperatures projected to increase by 0.15℃/10 yr and 0.53℃/10 yr,respectively.Both scenarios exhibit similar spatial distributions in projected annual precipitation,characterized by peak increases of~0.2 mm per day in northern CA.The number of consecutive dry days is projected to slightly increase under RCP8.5,while it is expected to slightly decrease under RCP2.6.This study improves our understanding of the applicability of RCMs in CA and provides reliable projections of future climate change.展开更多
Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study...Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.展开更多
IN his video speech to the United Nations Climate Summit held in New York on September 24,Chinese President Xi Jinping announced China’s new Nationally Determined Contributions(NDC)—the efforts taken by each country...IN his video speech to the United Nations Climate Summit held in New York on September 24,Chinese President Xi Jinping announced China’s new Nationally Determined Contributions(NDC)—the efforts taken by each country to reduce their emissions and adapt to the impacts of climate change.展开更多
Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model versi...Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model version 6 with a machine-learning-integrated four-mode version of the Modal Aerosol Module, we quantify global BC aging responses to emission reductions for 2011–2018 and for 2050 and 2100 under carbon neutrality. During 2011–18, global trends in BC aging degree(mass ratio of coatings to BC, R_(BC)) exhibited marked regional disparities, with a significant increase in China(5.4% yr^(-1)), which contrasts with minimal changes in the USA, Europe, and India. The divergence is attributed to opposing trends in secondary organic aerosol(SOA) and sulfate coatings, driven by regional changes in the emission ratios of corresponding coating precursors to BC(volatile organic compounds-VOCs/BC and SO_(2)/BC). Projections under carbon neutrality reveal that R_(BC) will increase globally by 47%(118%) in 2050(2100), with strong convergent increases expected across major source regions. The R_(BC) increase, primarily driven by enhanced SOA coatings due to sharper BC reductions relative to VOCs, will enhance the global BC mass absorption cross-section(MAC) by 11%(17%) in 2050(2100).Consequently, although the global BC burden will decline sharply by 60%(76%), the enhanced MAC partially offsets the magnitude of the decline in the BC direct radiative effect, resulting in the moderation of global BC DRE decreases to 88%(92%) of the BC burden reductions in 2050(2100). This study highlights the globally enhanced BC aging and light absorption capacity under carbon neutrality, thereby partly offsetting the impact of BC direct emission reductions on future changes in BC radiative effects globally.展开更多
Despite its significant societal and scientific importance,projected changes in the characteristics of intraseasonal oscillations(ISOs)associated with Indian summer monsoon rainfall under increased greenhouse gas conc...Despite its significant societal and scientific importance,projected changes in the characteristics of intraseasonal oscillations(ISOs)associated with Indian summer monsoon rainfall under increased greenhouse gas concentrations remain largely unexplored.This study utilizes downscaled and bias-corrected historical simulations and projections from 17 CMIP6 models to investigate the future evolution of ISOs.Our findings reveal a twofold increase in ISO variability over India in the far future under the very high emissions scenario,raising critical concerns about its adverse socioeconomic impacts.Our analysis suggests that the increased magnitude of precipitation anomalies associated with northwardpropagating ISOs may intensify active monsoon spells,potentially triggering extreme rainfall events.Additionally,the phase speed of these northward-propagating ISOs over the Bay of Bengal is projected to accelerate owing to weakened air-sea coupling and feedback.This acceleration reduces the northwest-southeast tilt of the precipitation band,altering the spatial structure of the ISOs.Concurrently,the strengthening of circulation-precipitation feedback and warming of the Indian Ocean are projected to enhance the phase speed of monsoon ISOs,leading to more frequent active spells.This study underscores the critical role of regional ocean-atmosphere feedback in shaping future ISO characteristics,highlighting the urgent need for improved understanding and prediction of these changes in the context of a warming climate.展开更多
This study uses the International Center for Theoretical Physics(ICTP)Regional Climate Model version 5(RegCM5.0)to investigate the impact of the Fouta Djallon topography on the mean surface climate of West Africa with...This study uses the International Center for Theoretical Physics(ICTP)Regional Climate Model version 5(RegCM5.0)to investigate the impact of the Fouta Djallon topography on the mean surface climate of West Africa with a focus on the June–September(JJAS)season.Two experiments were conducted:a control simulation with current topography(REF)and a sensitivity simulation with flattened terrain(FLAT).Results show that reducing the elevation leads to decreased rainfall and increased temperatures,particularly over the Guinea Coast and the modified topographic region.Rainfall decreases by approximately 4.59%in the Guinea Coast sub-zone,while it slightly increases by about 2.76%in the Sahel.The most significant rainfall reduction,exceeding 20%,occurs over the flattened area.Temperature rises across both regions,with the strongest warming over the Fouta Jallon region.This pattern is likely due to the suppression of orographic uplift,which enhances the southwesterly monsoon flow from the Atlantic Ocean and causes a northward shift of the Intertropical Convergence Zone(ITCZ)into the Sahel.The findings highlight the key role of Fouta Jallon topography on the West African climate system.展开更多
Compound extreme climate events may profoundly affect human activity in the Yangtze River Basin.This study analyzed the long-term spatiotemporal distribution characteristics of compound heatwave-drought and heatwave-w...Compound extreme climate events may profoundly affect human activity in the Yangtze River Basin.This study analyzed the long-term spatiotemporal distribution characteristics of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin using multi-period historical observation data and future scenario climate model data.It also examined the changes in population exposure to compound extreme climate events in the basin and their driving factors by combining population statistics and forecast data.The results show that the occurrence days of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin have shown a significant upward trend both in historical periods and future scenarios,accompanied by a marked expansion in the affected areas.Compared to historical periods,population exposure in the Yangtze River Basin under future scenarios is expected to increase by 1.5–2 times,primarily concentrated in the key urban areas of the basin.The main factors driving the changes in population exposure are the increased frequency of extreme climate events and population decline in future scenarios.These findings provide scientific evidence for early mitigation of meteorological disasters in the Yangtze River Basin.展开更多
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
Based on the citrus temperature, precipitation, sunlight and climate risk degree, the article divides subtropics of China into three types： the low risk region, the moderate risk region and the high risk region. The ...Based on the citrus temperature, precipitation, sunlight and climate risk degree, the article divides subtropics of China into three types： the low risk region, the moderate risk region and the high risk region. The citrus temperature risk increases with increasing latitude （except for the western mountainous area of subtropics of China）. The citrus precipitation risk in the central part of subtropics of China is higher than that in the northern and western parts. The distributions of citrus sunlight risk are not consistent to those of the citrus precipitation risk. The citrus climate risk is mainly influenced by temperature. There is latitudinal zonal law for the distribution of the climate risk, that is, the climate risk increases with increasing latitude At the same time the climate risk in mountainous area is high and that in eastern plain area is low. There are differences in the temporal and spatial changes of the citrus climate. In recent 46 years, the citrus climate risk presents a gradual increasing trend in subtropics of China, especially it has been increasing fast since the 1980s. Because of the global warming, the low risk region in the eastern and southern parts has a gradual decreasing trend, however, the high risk region in the northern and western parts has an increasing trend and the high risk region has been extending eastward and southward. The article analyses the distribution of the citrus climate risk degree of reduction rates of 〉10%, 〉20% and 〉30% in subtropics of China, and studies their changes in different time periods. Results show that the risk is increasing from southeast to northwest.展开更多
In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift an...In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift and intensification of the western Pacific subtropical high(WPSH). Under these conditions, China experienced its hottest summer since 1961,and was hit by a series of high-impact extreme weather and climate events. From 9 June to 2 July, southern China experienced an unprecedented extreme precipitation event that exceeded the well-known 1998 summer precipitation event in both duration and impact scope, resulting in devastating floods in the Yangtze River basin. Subsequently, in early to midJuly, the Huanghe-Huaihe Basin suffered from a severe drought–flood abrupt alternation event, heavily affecting Henan and Shandong. Meanwhile, southern China underwent a widespread heatwave event lasting 74 days, ranking as the second most intense since 1961. From late July to the end of August, northern China faced unusually frequent heavy precipitation events, with cumulative precipitation reaching the second highest for the same period since 1961, causing floods in many rivers of northern China. This study provides a timely summary and assessment of the characteristics and impacts of these extreme events. It serves as a reference for climate change research, including mechanism analysis, numerical simulation,and climate event attribution, and also offers valuable insights for improving meteorological disaster prevention and mitigation strategies.展开更多
The Three Gorges Region(TGR)of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024.The annual mean temperature in the TGR was 18.6℃,which was 1.2℃above normal and marked the highest level...The Three Gorges Region(TGR)of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024.The annual mean temperature in the TGR was 18.6℃,which was 1.2℃above normal and marked the highest level since 1961.All four seasons were warmer than normal,with spring and autumn both recording their highest temperatures since 1961.Additionally,the TGR recorded 57.2 high-temperature days in 2024,reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days.Annual rainfall was 11.2%below normal,with spring,summer,and autumn all being drier than normal.However,the number of heavy rain days was slightly higher than normal.The annual mean wind speed in the TGR ranked as the second-highest since 1961,only slightly lower than in 2022.The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023.In 2024,the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration,accompanied by generally severe meteorological drought conditions.During the year,the TGR also experienced frequent and intense cooling events,an early onset of heavy rainfall(including severe convective weather),and exceptionally extreme rainstorm events.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
Coastal Bangladesh is highly vulnerable to various impacts of climate change,including rising temperatures,unpredictable precipitation,cyclones,droughts,and saltwater intrusion.These factors collectively threaten agri...Coastal Bangladesh is highly vulnerable to various impacts of climate change,including rising temperatures,unpredictable precipitation,cyclones,droughts,and saltwater intrusion.These factors collectively threaten agricultural productivity and food security.This study examines the relationship between farmers’perceptions and observable climatic trends,with a focus on the sustainability of food systems and the promotion of adaptable farming techniques in Bagerhat District,Bangladesh.A mixed-methods strategy was employed,incorporating household surveys(a total of 110 purposively selected farmers),focus group discussions,key informant interviews,and climatic data analysis.The Mann-Kendall test,Sen’s slope estimator,precipitation concentration index(PCI),and standardized rainfall anomaly index(SRAI)were employed to analyze climate trends from 1991 to 2020.The findings showed that more than 70.00%of respondents indicated that summers were becoming warmer,over 50.00%reported that winters were becoming colder,and 63.00%stated that yearly precipitation was decreasing.Farmers reported an increase in flood occurrences and a decline in the predictability of precipitation.Between 2011 and 2019,the output of most rice varieties decreased,with the exception of high-yielding Aman rice and hybrid Boro rice.The results also showed that 60.00%of respondents reported experiencing salinity intrusion,and 57.00%attributed significant yield losses to salinity.Planting salt-tolerant rice varieties(such as BRRI Dhan 67 and Binadhan-10),practicing homestead vegetable cultivation,and moderately integrating shrimp aquaculture were also common adaptive measures.To improve long-term food security in coastal Bangladesh,we suggest growing more salt-tolerant crop varieties,promoting vertical and homestead gardening,enhancing seed systems that are resilient to climate change,and educating farmers on the use of climate-smart farming methods.This study highlights the importance of aligning farmers’perceptions with observed climatic data to design effective adaptation strategies.The findings of this study can guide policy-makers and development practitioners in strengthening climate-resilient agriculture and ensuring long-term food security in coastal Bangladesh.展开更多
Forests all over the world have been dramatically impacted by climate change,which has contributed to an increase in the number of pathogen invasions and the rise in the prevalence of forest diseases.This article pres...Forests all over the world have been dramatically impacted by climate change,which has contributed to an increase in the number of pathogen invasions and the rise in the prevalence of forest diseases.This article presents a systematic review that investigates the intricate relationship between climate change and the prevalence of forest diseases.The study identifies climate-related factors that drive the rising incidence of these forest diseases.Following the PRISMA guidelines,73 studies were selected and analyzed from a pool of 3,510 articles,focusing on their spatial and temporal patterns,contextual drivers,and linkages to climate change.The findings underscore the critical role of extended drought periods and rising temperatures as key factors exacerbating forest disease outbreaks.Methodologically,only 3%of the studies utilized field sampling,indicating a predominance of laboratory analysis methods at 45%.Geographically,temperate forests accounted for 78%of the studies,forest plantations 20%,and boreal forests 2%.This review highlights the pressing need for sustainable forest management practices to counteract the adverse impacts of climate change on forest ecosystems.By identifying critical climate drivers and ecological vulnerabilities,this research provides a foundation for adaptive silviculture and pathogen management strategies.展开更多
An overview of basic research on climate change in recent years in China is presented.In the past 100 years in China,average annual mean surface air temperature(SAT)has increased at a rate ranging from 0.03℃(10 yr)-1...An overview of basic research on climate change in recent years in China is presented.In the past 100 years in China,average annual mean surface air temperature(SAT)has increased at a rate ranging from 0.03℃(10 yr)-1 to 0.12℃(10 yr)-1.This warming is more evident in northern China and is more significant in winter and spring.In the past 50 years in China,at least 27%of the average annual warming has been caused by urbanization.Overall,no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years.Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years.The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country,while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends.The frequency of tropical cyclone landfall decreased slightly,but the frequency of sand/dust storms decreased significantly.Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China,but it may not have exceeded the highest level of the Medieval Warm Period(10001300 AD).Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods,with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years.The attribution studies suggest that increasing greenhouse gas(GHG)concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide.The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years,which might have been caused by increased aerosol concentrations and cloud cover.However,natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century.Climate models generally perform well in simulating the variations of annual mean SAT in China.They have also been used to project future changes in SAT under varied GHG emission scenarios.Large uncertainties have remained in these model-based projections,however,especially for the projected trends of regional precipitation and extreme climate events.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
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
基金supported by the National Natural Science Foundation of China(Grant No.U2342208)support from NSF/Climate Dynamics Award#2025057。
文摘Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.
基金supported by a National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(Grant No.RS-2024-00342219)the Korea Meteorological Administration Research and Development Program(Grant No.RS-2025-02313090)S.-Y.JUN and B.-J.PARK were supported by Korea Polar Research Institute(KOPRI)grants funded by the Ministry of Oceans and Fisheries(Grant No.KOPRI PE25010).
文摘Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal conditions in East Asia for up to five years.We compare temperature-based agroclimatic indicators from atmospheric reanalysis data with the firstyear prediction of the Decadal Prediction System version 4(DePreSys4),initialized annually from November 1960 to 2024.Our analysis reveals that first-year predictions accurately represent observed spatial climatological patterns,although trends in agroclimatic indicators based on daily maximum temperature are overestimated.High skill scores are observed in predicting the beginning of the growing season,frost-free days,agricultural hot days,and heat intensity in major cropping regions.However,the end of the growing season is less predictable due to longer lead times.Notably,five-year average predictions show higher skill than first-year predictions due to smoothed interannual variability.These improved climate predictions enable farmers and policymakers to make informed decisions about crop selection and agricultural infrastructure.
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jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Administration Climate Change Special Program[grant number QBZ202303]。
文摘This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despite some systematic biases,all RCMs effectively capture the main features of observed temperature and precipitation means and extremes over CA,with notable variations in model performance due to differences in the driving global climate models and the RCMs themselves.Overall,REMO consistently outperforms ALARO in simulating temperature-related indices,and ALARO-0 provides more accurate simulations for precipitation-related indices,and the multimodel ensemble(MME)tends to outperform individual RCMs.Under the representative concentration pathway(RCP)scenarios of RCP2.6 and RCP8.5,the MME results indicate a clear warming trend across CA for all temperature-related indices,except for the diurnal temperature range,with annual temperatures projected to increase by 0.15℃/10 yr and 0.53℃/10 yr,respectively.Both scenarios exhibit similar spatial distributions in projected annual precipitation,characterized by peak increases of~0.2 mm per day in northern CA.The number of consecutive dry days is projected to slightly increase under RCP8.5,while it is expected to slightly decrease under RCP2.6.This study improves our understanding of the applicability of RCMs in CA and provides reliable projections of future climate change.
基金the University of Milan for funding the“ProForesta”project through the 2020 Research Support Planthe“Ente Parco Nazionale dell'Appennino Tosco-Emiliano”for having financed the project“First urgent measures to promote the adaptation of the silver fir forests of the Tuscan-Emilian Apennine National Park to the effects of climate change”。
文摘Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.
文摘IN his video speech to the United Nations Climate Summit held in New York on September 24,Chinese President Xi Jinping announced China’s new Nationally Determined Contributions(NDC)—the efforts taken by each country to reduce their emissions and adapt to the impacts of climate change.
基金supported by the National Natural Science Foundation of China (42505149,41925023,U2342223,42105069,and 91744208)the China Postdoctoral Science Foundation (2025M770303)+1 种基金the Fundamental Research Funds for the Central Universities (14380230)the Jiangsu Funding Program for Excellent Postdoctoral Talent,and Jiangsu Collaborative Innovation Center of Climate Change。
文摘Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model version 6 with a machine-learning-integrated four-mode version of the Modal Aerosol Module, we quantify global BC aging responses to emission reductions for 2011–2018 and for 2050 and 2100 under carbon neutrality. During 2011–18, global trends in BC aging degree(mass ratio of coatings to BC, R_(BC)) exhibited marked regional disparities, with a significant increase in China(5.4% yr^(-1)), which contrasts with minimal changes in the USA, Europe, and India. The divergence is attributed to opposing trends in secondary organic aerosol(SOA) and sulfate coatings, driven by regional changes in the emission ratios of corresponding coating precursors to BC(volatile organic compounds-VOCs/BC and SO_(2)/BC). Projections under carbon neutrality reveal that R_(BC) will increase globally by 47%(118%) in 2050(2100), with strong convergent increases expected across major source regions. The R_(BC) increase, primarily driven by enhanced SOA coatings due to sharper BC reductions relative to VOCs, will enhance the global BC mass absorption cross-section(MAC) by 11%(17%) in 2050(2100).Consequently, although the global BC burden will decline sharply by 60%(76%), the enhanced MAC partially offsets the magnitude of the decline in the BC direct radiative effect, resulting in the moderation of global BC DRE decreases to 88%(92%) of the BC burden reductions in 2050(2100). This study highlights the globally enhanced BC aging and light absorption capacity under carbon neutrality, thereby partly offsetting the impact of BC direct emission reductions on future changes in BC radiative effects globally.
基金supported by a National Research Foundation of Korea(NRF) grant funded by the Korean government (MSIT)(Grant No.RS-2024-00416848)SERB-DST Govt. of India for providing financial support under NPDF (Grant No.PDF/2022/001886)
文摘Despite its significant societal and scientific importance,projected changes in the characteristics of intraseasonal oscillations(ISOs)associated with Indian summer monsoon rainfall under increased greenhouse gas concentrations remain largely unexplored.This study utilizes downscaled and bias-corrected historical simulations and projections from 17 CMIP6 models to investigate the future evolution of ISOs.Our findings reveal a twofold increase in ISO variability over India in the far future under the very high emissions scenario,raising critical concerns about its adverse socioeconomic impacts.Our analysis suggests that the increased magnitude of precipitation anomalies associated with northwardpropagating ISOs may intensify active monsoon spells,potentially triggering extreme rainfall events.Additionally,the phase speed of these northward-propagating ISOs over the Bay of Bengal is projected to accelerate owing to weakened air-sea coupling and feedback.This acceleration reduces the northwest-southeast tilt of the precipitation band,altering the spatial structure of the ISOs.Concurrently,the strengthening of circulation-precipitation feedback and warming of the Indian Ocean are projected to enhance the phase speed of monsoon ISOs,leading to more frequent active spells.This study underscores the critical role of regional ocean-atmosphere feedback in shaping future ISO characteristics,highlighting the urgent need for improved understanding and prediction of these changes in the context of a warming climate.
基金supported by the Institut de Recherche pour le Développement (IRD), France (UMR IGE Imputation, Grant no. 252RA5)the Laboratoire Mixte International NEXUS (LMI-NEXUS) (Abidjan, Côte d'Ivoire)
文摘This study uses the International Center for Theoretical Physics(ICTP)Regional Climate Model version 5(RegCM5.0)to investigate the impact of the Fouta Djallon topography on the mean surface climate of West Africa with a focus on the June–September(JJAS)season.Two experiments were conducted:a control simulation with current topography(REF)and a sensitivity simulation with flattened terrain(FLAT).Results show that reducing the elevation leads to decreased rainfall and increased temperatures,particularly over the Guinea Coast and the modified topographic region.Rainfall decreases by approximately 4.59%in the Guinea Coast sub-zone,while it slightly increases by about 2.76%in the Sahel.The most significant rainfall reduction,exceeding 20%,occurs over the flattened area.Temperature rises across both regions,with the strongest warming over the Fouta Jallon region.This pattern is likely due to the suppression of orographic uplift,which enhances the southwesterly monsoon flow from the Atlantic Ocean and causes a northward shift of the Intertropical Convergence Zone(ITCZ)into the Sahel.The findings highlight the key role of Fouta Jallon topography on the West African climate system.
基金supported by the National Natural Science Foundation of China(Nos.42301029,42371354)the Scientific Research Start-up Fund for New Young Faculty,China University of Geosciences,Wuhan(No.CUGXQN2307)China Meteorological Administration Innovation and Development Project(No.CXFZ2023J051).
文摘Compound extreme climate events may profoundly affect human activity in the Yangtze River Basin.This study analyzed the long-term spatiotemporal distribution characteristics of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin using multi-period historical observation data and future scenario climate model data.It also examined the changes in population exposure to compound extreme climate events in the basin and their driving factors by combining population statistics and forecast data.The results show that the occurrence days of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin have shown a significant upward trend both in historical periods and future scenarios,accompanied by a marked expansion in the affected areas.Compared to historical periods,population exposure in the Yangtze River Basin under future scenarios is expected to increase by 1.5–2 times,primarily concentrated in the key urban areas of the basin.The main factors driving the changes in population exposure are the increased frequency of extreme climate events and population decline in future scenarios.These findings provide scientific evidence for early mitigation of meteorological disasters in the Yangtze River Basin.
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National Natural Sciences Foundation of China,No.40771033Special Item Funds of Climate Change Supported by China Meteorological Administration,No.CCSF-09-11
文摘Based on the citrus temperature, precipitation, sunlight and climate risk degree, the article divides subtropics of China into three types： the low risk region, the moderate risk region and the high risk region. The citrus temperature risk increases with increasing latitude （except for the western mountainous area of subtropics of China）. The citrus precipitation risk in the central part of subtropics of China is higher than that in the northern and western parts. The distributions of citrus sunlight risk are not consistent to those of the citrus precipitation risk. The citrus climate risk is mainly influenced by temperature. There is latitudinal zonal law for the distribution of the climate risk, that is, the climate risk increases with increasing latitude At the same time the climate risk in mountainous area is high and that in eastern plain area is low. There are differences in the temporal and spatial changes of the citrus climate. In recent 46 years, the citrus climate risk presents a gradual increasing trend in subtropics of China, especially it has been increasing fast since the 1980s. Because of the global warming, the low risk region in the eastern and southern parts has a gradual decreasing trend, however, the high risk region in the northern and western parts has an increasing trend and the high risk region has been extending eastward and southward. The article analyses the distribution of the citrus climate risk degree of reduction rates of 〉10%, 〉20% and 〉30% in subtropics of China, and studies their changes in different time periods. Results show that the risk is increasing from southeast to northwest.
基金supported by the National Natural Science Foundation of China (Grant Nos.42005029 and 41701103)the China Meteorological Administration Special Foundation for Innovation and Development (Grant No.CXFZ2024Q007)。
文摘In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift and intensification of the western Pacific subtropical high(WPSH). Under these conditions, China experienced its hottest summer since 1961,and was hit by a series of high-impact extreme weather and climate events. From 9 June to 2 July, southern China experienced an unprecedented extreme precipitation event that exceeded the well-known 1998 summer precipitation event in both duration and impact scope, resulting in devastating floods in the Yangtze River basin. Subsequently, in early to midJuly, the Huanghe-Huaihe Basin suffered from a severe drought–flood abrupt alternation event, heavily affecting Henan and Shandong. Meanwhile, southern China underwent a widespread heatwave event lasting 74 days, ranking as the second most intense since 1961. From late July to the end of August, northern China faced unusually frequent heavy precipitation events, with cumulative precipitation reaching the second highest for the same period since 1961, causing floods in many rivers of northern China. This study provides a timely summary and assessment of the characteristics and impacts of these extreme events. It serves as a reference for climate change research, including mechanism analysis, numerical simulation,and climate event attribution, and also offers valuable insights for improving meteorological disaster prevention and mitigation strategies.
基金supported by the Innovation and Development Special Project of the China Meteorological Administration[grant number CXFZ2024J071]the National Key Research and Development Program of China[grant number 2023YFC3206001].
文摘The Three Gorges Region(TGR)of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024.The annual mean temperature in the TGR was 18.6℃,which was 1.2℃above normal and marked the highest level since 1961.All four seasons were warmer than normal,with spring and autumn both recording their highest temperatures since 1961.Additionally,the TGR recorded 57.2 high-temperature days in 2024,reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days.Annual rainfall was 11.2%below normal,with spring,summer,and autumn all being drier than normal.However,the number of heavy rain days was slightly higher than normal.The annual mean wind speed in the TGR ranked as the second-highest since 1961,only slightly lower than in 2022.The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023.In 2024,the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration,accompanied by generally severe meteorological drought conditions.During the year,the TGR also experienced frequent and intense cooling events,an early onset of heavy rainfall(including severe convective weather),and exceptionally extreme rainstorm events.
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supported by the Research Grant of Military Institute of Science and Technology,Bangladesh。
文摘Coastal Bangladesh is highly vulnerable to various impacts of climate change,including rising temperatures,unpredictable precipitation,cyclones,droughts,and saltwater intrusion.These factors collectively threaten agricultural productivity and food security.This study examines the relationship between farmers’perceptions and observable climatic trends,with a focus on the sustainability of food systems and the promotion of adaptable farming techniques in Bagerhat District,Bangladesh.A mixed-methods strategy was employed,incorporating household surveys(a total of 110 purposively selected farmers),focus group discussions,key informant interviews,and climatic data analysis.The Mann-Kendall test,Sen’s slope estimator,precipitation concentration index(PCI),and standardized rainfall anomaly index(SRAI)were employed to analyze climate trends from 1991 to 2020.The findings showed that more than 70.00%of respondents indicated that summers were becoming warmer,over 50.00%reported that winters were becoming colder,and 63.00%stated that yearly precipitation was decreasing.Farmers reported an increase in flood occurrences and a decline in the predictability of precipitation.Between 2011 and 2019,the output of most rice varieties decreased,with the exception of high-yielding Aman rice and hybrid Boro rice.The results also showed that 60.00%of respondents reported experiencing salinity intrusion,and 57.00%attributed significant yield losses to salinity.Planting salt-tolerant rice varieties(such as BRRI Dhan 67 and Binadhan-10),practicing homestead vegetable cultivation,and moderately integrating shrimp aquaculture were also common adaptive measures.To improve long-term food security in coastal Bangladesh,we suggest growing more salt-tolerant crop varieties,promoting vertical and homestead gardening,enhancing seed systems that are resilient to climate change,and educating farmers on the use of climate-smart farming methods.This study highlights the importance of aligning farmers’perceptions with observed climatic data to design effective adaptation strategies.The findings of this study can guide policy-makers and development practitioners in strengthening climate-resilient agriculture and ensuring long-term food security in coastal Bangladesh.
基金supported by the UKM research grant no,SK-2022-015the Peninsular Malaysia Forestry Department through the research project titled‘Prediction of Bio-Climatic Habitat Adaptation of Diseases and Pests in Selected Forest Plantation Species in Peninsular Malaysia’,grant No.PHSB-08-2020.
文摘Forests all over the world have been dramatically impacted by climate change,which has contributed to an increase in the number of pathogen invasions and the rise in the prevalence of forest diseases.This article presents a systematic review that investigates the intricate relationship between climate change and the prevalence of forest diseases.The study identifies climate-related factors that drive the rising incidence of these forest diseases.Following the PRISMA guidelines,73 studies were selected and analyzed from a pool of 3,510 articles,focusing on their spatial and temporal patterns,contextual drivers,and linkages to climate change.The findings underscore the critical role of extended drought periods and rising temperatures as key factors exacerbating forest disease outbreaks.Methodologically,only 3%of the studies utilized field sampling,indicating a predominance of laboratory analysis methods at 45%.Geographically,temperate forests accounted for 78%of the studies,forest plantations 20%,and boreal forests 2%.This review highlights the pressing need for sustainable forest management practices to counteract the adverse impacts of climate change on forest ecosystems.By identifying critical climate drivers and ecological vulnerabilities,this research provides a foundation for adaptive silviculture and pathogen management strategies.
基金supported by the Ministry of Science and Technology of China(Grant Nos.2007BAC29B02,2007BAC03A01 and GYHY201206012)
文摘An overview of basic research on climate change in recent years in China is presented.In the past 100 years in China,average annual mean surface air temperature(SAT)has increased at a rate ranging from 0.03℃(10 yr)-1 to 0.12℃(10 yr)-1.This warming is more evident in northern China and is more significant in winter and spring.In the past 50 years in China,at least 27%of the average annual warming has been caused by urbanization.Overall,no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years.Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years.The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country,while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends.The frequency of tropical cyclone landfall decreased slightly,but the frequency of sand/dust storms decreased significantly.Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China,but it may not have exceeded the highest level of the Medieval Warm Period(10001300 AD).Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods,with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years.The attribution studies suggest that increasing greenhouse gas(GHG)concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide.The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years,which might have been caused by increased aerosol concentrations and cloud cover.However,natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century.Climate models generally perform well in simulating the variations of annual mean SAT in China.They have also been used to project future changes in SAT under varied GHG emission scenarios.Large uncertainties have remained in these model-based projections,however,especially for the projected trends of regional precipitation and extreme climate events.
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 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.
