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
Texas experienced the worst drought in its 100-year history in 2011,resulting in the death of approximately 300 million trees.The high number of sudden deaths had a significant impact on forest ecosystems.This study a...Texas experienced the worst drought in its 100-year history in 2011,resulting in the death of approximately 300 million trees.The high number of sudden deaths had a significant impact on forest ecosystems.This study aimed to gain insight into the long-term and combined impacts of drought-induced forest tree deaths and their effects on biomass.This study used data obtained from 1797 National Forest Inventory(NFI)plots to analyze trends and major causes of changes in tree biomass at the sample plot level in East Texas forests over the past 20 years(2000-2019).In this study,forest trees in East Texas were divided into diameter at breast height(dbh),height,stand types,latitude,elevation,ecological zones,and FIA Unit.Principal component analysis(PCA)was also performed using drought intensity,drought duration,the four competing factor indicators,and the biomass loss rate of forest trees to better understand r drought impacts on forest trees.The results showed the lowest biomass loss rate of Pine species.Similarly,trees with shorter height and smaller dbh experienced a higher biomass loss rate.A higher biomass loss rate was observed in natural forests,West Gulf Coastal Plain and Plain and Southern East Texas ecoregion experienced higher biomass loss.Principal component analyses of drought intensity,drought duration,and the four competing metrics revealed that overall drought was the main contributor to biomass loss rates,and that drought intensity and drought duration had comparable effects on biomass loss rates.展开更多
Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(...Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5),are assessed in terms of spatial distribution and interannual variability.The CMIP6 multi-model ensemble mean(CMIP6-MME)can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature,and minimum daily minimum temperature.However,CMIP6-MME has difficulties in reproducing cold nights and warm days,and has large cold biases over the Tibetan Plateau.Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices.Compared to CMIP5,CMIP6 models show improvements in the simulation of climate indices over China.This is particularly true for precipitation indices for both the climatological pattern and the interannual variation,except for the consecutive dry days.The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME)to 79%(CMIP6-MME).The most striking feature is that the dry biases in southern China,very persistent and general in CMIP5-MME,are largely reduced in CMIP6-MME.Stronger ascent together with more abundant moisture can explain this reduction in dry biases.Wet biases for total precipitation,heavy precipitation,and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME,but smaller,compared to CMIP5-MME.展开更多
Daily precipitation for 1960-2011 and maximum/minimum temperature extremes for 1960-2008 recorded at 549 stations in China are utilized to investigate climate extreme variations.A set of indices is derived and analyze...Daily precipitation for 1960-2011 and maximum/minimum temperature extremes for 1960-2008 recorded at 549 stations in China are utilized to investigate climate extreme variations.A set of indices is derived and analyzed with a main focus on the trends and variabilities of daily extreme occurrences.Results show significant increases in daily extreme warm temperatures and decreases in daily extreme cold temperatures,defined as the number of days in which daily maximum temperature （Tmax） and daily minimum temperature （Tmin） are greater than the 90th percentile and less than thel0th percentile,respectively.Generally,the trend magnitudes are larger in indices derived from Tmin than those from Tmax.Trends of percentile-based precipitation indices show distinct spatial patterns with increases in heavy precipitation events,defined as the top 95th percentile of daily precipitation,in westem and northeastern China and in the low reaches of the Yangtze River basin region,and slight decreases in other areas.Light precipitation,defined as the tail of the 5th percentile of daily precipitation,however,decreases in most areas.The annual maximum consecutive dry days （CDD） show an increasing trend in southem China and the middle-low reach of the Yellow River basin,while the annual maximum consecutive wet days （CWD） displays a downtrend over most regions except western China.These indices vary significantly with regions and seasons.Overall,occurrences of extreme events in China are more frequent,particularly the night time extreme temperature,and landmasses in China become warmer and wetter.展开更多
The year 2021 was recorded as the 6th warmest since 1880.In addition to large-scale warming,2021 will be remembered for its unprecedented climate extremes.Here,a review of selected high-impact climate extremes in 2021...The year 2021 was recorded as the 6th warmest since 1880.In addition to large-scale warming,2021 will be remembered for its unprecedented climate extremes.Here,a review of selected high-impact climate extremes in 2021,with a focus on China,along with an extension to extreme events in North America and Europe is presented.Nine extreme events that occurred in 2021 in China are highlighted,including a rapid transition from cold to warm extremes and sandstorms in spring,consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year,extremely heavy rainfall over Henan Province and Hubei Province during summer,as well as heatwaves,persistent heavy rainfall,and a cold surge during fall.Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here,providing insights to understand climate extremes from a global perspective.This serves as a reference for climate event attribution,process understanding,and high-resolution modeling of extreme events.展开更多
The impacts of solar activity on climate are explored in this two-part study. Based on the principles of atmospheric dynamics, Part I propose an amplifying mechanism of solar impacts on winter climate extremes through...The impacts of solar activity on climate are explored in this two-part study. Based on the principles of atmospheric dynamics, Part I propose an amplifying mechanism of solar impacts on winter climate extremes through changing the atmospheric circulation patterns. This mechanism is supported by data analysis of the sunspot number up to the predicted Solar Cycle 24, the historical surface temperature data, and atmospheric variables of NCEP/NCAR Reanalysis up to the February 2011 for the Northern Hemisphere winters. For low solar activity, the thermal contrast between the low- and high-latitudes is enhanced, so as the mid-latitude baroclinic ultra-long wave activity. The land-ocean thermal contrast is also enhanced, which amplifies the topographic waves. The enhanced mid-latitude waves in turn enhance the meridional heat transport from the low to high latitudes, making the atmospheric "heat engine" more efficient than normal. The jets shift southward and the polar vortex is weakened. The Northern Annular Mode (NAM) index tends to be negative. The mid-latitude surface exhibits large-scale convergence and updrafts, which favor extreme weather/climate events to occur. The thermally driven Siberian high is enhanced, which enhances the East Asian winter monsoon (EAWM). For high solar activity, the mid-latitude circulation patterns are less wavy with less meridional transport. The NAM tends to be positive, and the Siberian high and the EAWM tend to be weaker than normal. Thus the extreme weather/climate events for high solar activity occur in different regions with different severity from those for low solar activity. The solar influence on the mid- to high-latitude surface temperature and circulations can stand out after removing the influence from the E1 Nifio-Southern Oscillation. The atmospheric amplifying mechanism indicates that the solar impacts on climate should not be simply estimated by the magnitude of the change in the solar radiation over solar cycles when it is compared with other external radiative forcings that do not influence the climate in the same way as the sun does.展开更多
Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more...Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.展开更多
Understanding how alien species assemble is crucial for predicting changes to community structure caused by biological invasions and for directing management strategies for alien species,but patterns and drivers of al...Understanding how alien species assemble is crucial for predicting changes to community structure caused by biological invasions and for directing management strategies for alien species,but patterns and drivers of alien species assemblages remain poorly understood relative to native species.Climate has been suggested as a crucial filter of invasion-driven homogenization of biodiversity.However,it remains unclear which climatic factors drive the assemblage of alien species.Here,we compiled global data at both grid scale(2,653 native and 2,806 current grids with a resolution of 2°x 2°)and administrative scale(271 native and 297 current nations and sub-nations)on the distributions of 361 alien amphibians and reptiles(herpetofauna),the most threatened vertebrate group on the planet.We found that geographical distance,proxy for natural dispersal barriers,was the dominant variable contributing to alien herpetofaunal assemblage in native ranges.In contrast,climatic factors explained more unique variation in alien herpetofaunal assemblage after than before invasions.This pattern was driven by extremely high temperatures and precipitation seasonality,2 hallmarks of global climate change,and bilateral trade which can account for the alien assemblage after invasions.Our results indicated that human-assisted species introductions combined with climate change may accelerate the reorganization of global species distributions.展开更多
Based on daily maximum and minimum surface air temperature and precipitation records at 48 meteorological stations in Xinjiang, the spatial and temporal distributions of climate extreme indices have been analyzed duri...Based on daily maximum and minimum surface air temperature and precipitation records at 48 meteorological stations in Xinjiang, the spatial and temporal distributions of climate extreme indices have been analyzed during 1961-2008. Twelve temperature ex- treme indices and six precipitation extreme indices are studied. Temperature extremes are highly correlated to annual mean tem- perature, which appears to be significantly increasing by 0.08 ℃ per year, indicating that changes in temperature extremes reflect consistent warming. The warming tendency is clearer at stations in northern Xinjiang as reflected by mean temperature. The fre- quencies of cold days and nights have both decreased, respectively by -0.86 and -2.45 d/decade, but the frequencies of warm days and nights have both increased, respectively by ＋1.62 and ＋4.85 d/decade. Over the same period, the number of frost days shows a statistically significant decreasing trend of-2.54 d/decade. The growing season length and the number of summer days exhibit significant increasing trends at rates of ＋2.62 and ＋2.86 d/decade, respectively. The diumal temperature range has de- creased by -0.28 ℃/decade. Both annual extreme low and high temperatures exhibit significant increasing trend, with the former clearly larger than the latter. For precipitation indices, regional annual total precipitation shows an increasing trend and most other precipitation indices are strongly correlated with annual total precipitation. Average wet day precipitation, maximum 1-day and 5-day precipitation, and heavy precipitation days show increasing trends, but only the last is statistically significant. A decreasing trend is found for consecutive dry days. For all precipitation indices, stations in northwestern Xinjiang have the largest positive trend magnitudes, while stations in northern Xiniiang have the largest negative magnitudes.展开更多
Against the backdrop of global warming,climate extremes and drought events have become more severe,especially in arid and semi-arid areas.This study forecasted the characteristics of climate extremes in the Xilin Rive...Against the backdrop of global warming,climate extremes and drought events have become more severe,especially in arid and semi-arid areas.This study forecasted the characteristics of climate extremes in the Xilin River Basin(a semi-arid inland river basin)of China for the period of 2021–2100 by employing a multi-model ensemble approach based on three climate Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)from the latest Coupled Model Intercomparison Project Phase 6(CMIP6).Furthermore,a linear regression,a wavelet analysis,and the correlation analysis were conducted to explore the response of climate extremes to the Standardized Precipitation Evapotranspiration Index(SPEI)and Streamflow Drought Index(SDI),as well as their respective trends during the historical period from 1970 to 2020 and during the future period from 2021 to 2070.The results indicated that extreme high temperatures and extreme precipitation will further intensify under the higher forcing scenarios(SSP5-8.5>SSP2-4.5>SSP1-2.6)in the future.The SPEI trends under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios were estimated as–0.003/a,–0.004/a,and–0.008/a,respectively,indicating a drier future climate.During the historical period(1970–2020),the SPEI and SDI trends were–0.003/a and–0.016/a,respectively,with significant cycles of 15 and 22 a,and abrupt changes occurring in 1995 and 1996,respectively.The next abrupt change in the SPEI was projected to occur in the 2040s.The SPEI had a significant positive correlation with both summer days(SU)and heavy precipitation days(R10mm),while the SDI was only significantly positively correlated with R10mm.Additionally,the SPEI and SDI exhibited a strong and consistent positive correlation at a cycle of 4–6 a,indicating a robust interdependence between the two indices.These findings have important implications for policy makers,enabling them to improve water resource management of inland river basins in arid and semi-arid areas under future climate uncertainty.展开更多
The mineral industry is of great importance for the economy and for the development of Brazil. However, climate change further accentuates the impacts caused by extreme weather and climate events on the logistics and ...The mineral industry is of great importance for the economy and for the development of Brazil. However, climate change further accentuates the impacts caused by extreme weather and climate events on the logistics and operation processes of the mineral production chain (from the mine to the port). In order to reduce these effects, it is essential to have information about the future climate that will help this economic sector to carry out better long-term planning of its activities. However, the current scientific literature still lacks studies with this approach applied to the mineral industry. Therefore, the purpose of this study was to evaluate the future seasonal patterns of climate extremes in eastern Amazonia, exploring their impacts on the mineral production chain in the near future (2019-2050). To categorize the dry and rainy climate extremes, the Standard Precipitation Index (SPI) was calculated for the precipitation data series of Climate Prediction Center (CPC) observations and the PRECIS regional modeling system, considering the IPCC RCP4.5. The 1981-2005 period was defined as the present climate and used to assess the performance of the modeling system in reproducing the extremes. The analyses were based on the relative frequency of the categories of dry and rainy extremes. The performance evaluation of PRECIS showed that it had better accuracy in representing seasonal extremes of drought than extremes of rain. Along the mineral chain in eastern Amazonia, its accuracy was better over the port region, except for the dry extremes experienced from June to August (JJA), and from December to February (DJF) and March to May (MAM) for rainy extremes. The analysis of the frequency of occurrence of these events for the future indicates a greater probability of rain extremes along the mineral chain compared to another category of extremes. In addition, JJA will be the most suitable period to optimize operational processes in eastern Amazonia, as extremes are less likely to occur. On the other hand, the greater probability of extreme rain events from September through to November (SON) and MAM make these two periods less suitable for activity in the mining regions and areas north of the railway. The results of this study suggest an increasing risk to the processes of the mineral chain until 2050 associated with the occurrence of climate extremes, since it is susceptible to adverse weather conditions.展开更多
Since the industrial revolution,multivariate climate extremes(e.g.,concurrent heatwaves and droughts)have caused irreversible damage to ecosystems and placed immense strain on human health and public resources in a wa...Since the industrial revolution,multivariate climate extremes(e.g.,concurrent heatwaves and droughts)have caused irreversible damage to ecosystems and placed immense strain on human health and public resources in a warming climate[1,2].A stark example occurred in the summer of 2022 when the SichuanChongqing region endured prolonged drought,extreme heat,associated wildfires,and subsequent heavy rainfall.These events resulted in direct economic losses of approximately 10 billion Chinese Yuan(CNY)and affected around 9.8 million people in Sichuan Province alone[3].展开更多
Whether the previous vegetation greening trend in China has persisted into the recent warmest decade and how the exceptional climate conditions of 2023 affected long-term change in vegetation greenness remain unexplor...Whether the previous vegetation greening trend in China has persisted into the recent warmest decade and how the exceptional climate conditions of 2023 affected long-term change in vegetation greenness remain unexplored.Here we integrated two decades of remotely sensed normalized difference vegetation index data with climate records to reveal a persistent greening(referring to the increasing trend of vegetation greenness)of China,occurring at a rate triple the global average,while the greening signal varies geographically.A prominent greening trend is primarily driven by the greening of humid and subhumid regions,consistent with the expected effects of rising CO_(2)on vegetation growth and intensified human practices including agricultural intensification and ambitious afforestation programs.By contrast,semi-arid and arid ecosystems showed non-significant greenness change due to drastic warming and precipitation fluctuations.The exceptional warming and precipitation reduction in 2023 did not trigger a record-high decrease in vegetation greenness when integrated across China.The vegetation greenness in 2023 instead reached the third highest on record which is contributed by enhancement in North China,Northeast China,and the Tibetan Plateau.Climatic extremes in 2023 induced significant browning in the Loess Plateau,Inner Mongolia,and Southwest China.While ecosystems especially in the southern China demonstrated relatively high resilience to climatic extreme events like high-temperature extremes and droughts,autumn greenness in 2023 can recover to levels even higher than the 2020–2022 average,despite significant browning in spring and summer.We,therefore,suggested that the 2023 climate extremes would not produce a new baseline from which vegetation growth will transition towards a state of degradation at both regional and national scales.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
Quantitative studies on the national-scale effects of extreme climatic events on soil organic carbon(SOC)remain scarce,thus limiting our understanding of SOC dynamics.This study utilized 4515 publicly available soil s...Quantitative studies on the national-scale effects of extreme climatic events on soil organic carbon(SOC)remain scarce,thus limiting our understanding of SOC dynamics.This study utilized 4515 publicly available soil samples to quantify the impacts of 19 extreme climatic indices(ECIs)onΔSOC reservoirs in China through a hybrid space-for-time and meta-analysis approach.Overall,16/19 ECIs were negatively correlated withΔSOC,with the minimum temperature of the coldest night(TNn)showing the strongest negative correlation.Notably,topographic factors played a pivotal role in the modeling process,contributing an average of 25%,followed by ECIs.Under the influence of the ECIs,SOC exhibited spatial variation.Extreme heat resulted in the greatest SOC losses in cold regions,such as North China,with average reductions of>5%,whereas its impact was weaker in South China,with SOC losses of∼3%.Extreme cold and wet indices promoted SOC accumulation in the Northeast China,with increases of∼3%,but showed a weaker response in the humid region,where the SOC increased by only 1%.At the national scale,the impacts of extreme climatic events on SOC in the0–20 cm ranged from-2.36 Pg to 2.34 Pg.Different ecosystems responded variably,with forest and grassland ecosystems being more sensitive to ECIs,potentially due to higher organic matter inputs and greater ecosystem complexity.In contrast,bare land exhibited weaker responses due to limited vegetation cover and organic inputs.These findings provide valuable insights into SOC dynamics at national scale during extreme climatic events.展开更多
Climate change severely challenges our ecosystem and society,affecting urban residents’socioeconomic activities.Thus,assessing severe weather risk is crucial for evaluating urban sustainability;understanding trends,c...Climate change severely challenges our ecosystem and society,affecting urban residents’socioeconomic activities.Thus,assessing severe weather risk is crucial for evaluating urban sustainability;understanding trends,causes,and impacts on socioeconomic development;and supporting the United Nations Sustainable Development Goal(SDG)13.Using meteorological data from 1980 to 2020,we investigate five disaster-causing severe weather events in China and construct a comprehensive index of extreme climate risk(CIECR)at the county,city,province,and national levels.The CIECR can identify high-risk regions and primary severe weather events and provide early warnings.We empirically test the impact of extreme climate risks on agricultural production,industrial structure,and labor employment.The results show high risks in Xinjiang,northern Inner Mongolia,and southern regions,with high temperatures,low temperatures,and high winds as the leading risks.At the national level,the extreme climate risk fluctuates,indicating climate warming.While risks reduce agricultural production and employment,they promote modern agriculture,industrial production,and urbanization.The novelty of the study lies in its development of the county-level CIECR,which can capture heterogeneity characteristics and provide microdata support for urban climate change research and efforts toward SDG 13.This study aids in mitigating climate risks;responding to climate change;and comprehensively analyzing the causes,trends,and impacts of extreme climate risks.展开更多
The net primary productivity(NPP) is an important indicator for assessing the carbon sequestration capacities of different ecosystems and plays a crucial role in the global biosphere carbon cycle. However, in the cont...The net primary productivity(NPP) is an important indicator for assessing the carbon sequestration capacities of different ecosystems and plays a crucial role in the global biosphere carbon cycle. However, in the context of the increasing frequency, intensity, and duration of global extreme climate events, the impacts of extreme climate and vegetation phenology on NPP are still unclear, especially on the Qinghai-Xizang Plateau(QXP), China. In this study, we used a new data fusion method based on the MOD13A2 normalized difference vegetation index(NDVI) and the Global Inventory Modeling and Mapping Studies(GIMMS) NDVI_(3g) datasets to obtain a NDVI dataset(1982–2020) on the QXP. Then, we developed a NPP dataset across the QXP using the Carnegie-Ames-Stanford Approach(CASA) model and validated its applicability based on gauged NPP data. Subsequently, we calculated 18 extreme climate indices based on the CN05.1 dataset, and extracted the length of vegetation growing season using the threshold method and double logistic model based on the annual NDVI time series. Finally, we explored the spatiotemporal patterns of NPP on the QXP and the impact mechanisms of extreme climate and the length of vegetation growing season on NPP. The results indicated that the estimated NPP exhibited good applicability. Specifically, the correlation coefficient, relative bias, mean error, and root mean square error between the estimated NPP and gauged NPP were 0.76, 0.17, 52.89 g C/(m^(2)·a), and 217.52 g C/(m^(2)·a), respectively. The NPP of alpine meadow, alpine steppe, forest, and main ecosystem on the QXP mainly exhibited an increasing trend during 1982–2020, with rates of 0.35, 0.38, 1.40, and 0.48 g C/(m^(2)·a), respectively. Spatially, the NPP gradually decreased from southeast to northwest across the QXP. Extreme climate had greater impact on NPP than the length of vegetation growing season on the QXP. Specifically, the increase in extremely-wet-day precipitation(R99p), simple daily intensity index(SDII), and hottest day(TXx) increased the NPP in different ecosystems across the QXP, while the increases in the cold spell duration index(CSDI) and warm spell duration index(WSDI) decreased the NPP in these ecosystems. The results of this study provide a scientific basis for relevant departments to formulate future policies addressing the impact of extreme climate on vegetation in different ecosystems on the QXP.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
This paper presents projections of climate extremes over China under global warming of 1.5,2,and 3℃ above pre-industrial(1861–1900),based on the latest Coupled Model Intercomparison Project phase 6(CMIP6)simulations...This paper presents projections of climate extremes over China under global warming of 1.5,2,and 3℃ above pre-industrial(1861–1900),based on the latest Coupled Model Intercomparison Project phase 6(CMIP6)simulations.Results are compared with what produced by the precedent phase of the project,CMIP5.Model evaluation for the reference period(1985–2005)indicates that CMIP6 models outperform their predecessors in CMIP5,especially in simulating precipitation extremes.Areal averages for changes of most indices are found larger in CMIP6 than in CMIP5.The emblematic annual mean temperature,when averaged over the whole of China in CMIP6,increases by 1.49,2.21,and 3.53℃(relative to1985–2005)for 1.5,2,and 3℃ above-preindustrial global warming levels,while the counterpart in CMIP5 is 1.20,1.93 and 3.39℃ respectively.Similarly,total precipitation increases by 5.3%,8.6%,and16.3%in CMIP6 and by 4.4%,7.0%and 12.8%in CMIP5,respectively.The spatial distribution of changes for extreme indices is generally consistent in both CMIP5 and CMIP6,but with significantly higher increases in CMIP6 over Northeast and Northwest China for the hottest day temperature,and South China for the coldest night temperature.In the south bank of the Yangtze River,and most regions around40°N,CMIP6 shows higher increases for both total precipitation and heavy precipitation.The projected difference between CMIP6 and CMIP5 is mainly attributable to the physical upgrading of climate models and largely independent from their emission scenarios.展开更多
A wide variety of studies have estimated the magnitude of global terrestrial net primary production （NPP）, but its variations, both spatially and temporally, still remain uncertain. By using an improved process-base...A wide variety of studies have estimated the magnitude of global terrestrial net primary production （NPP）, but its variations, both spatially and temporally, still remain uncertain. By using an improved process-based terrestrial ecosystem model （DLEM, Dynamic Land Ecosystem Model）, we provide an estimate of global terrestrial NPP induced by multiple environmental factors and examine the response of terrestrial NPP to climate variability at biome and global levels and along latitudes throughout the first decade of the 21st century. The model simulation estimates an average global terrestrial NPP of 54.6 Pg C yr-1 during 2000-2009, varying from 52.8 Pg C yr-1 in the dry year of 2002 to 56.4 Pg C yr-1 in the wet year of 2008. In wet years, a large increase in terrestrial NPP compared to the decadal mean was prevalent in Amazonia, Africa and Australia. In dry years, however, we found a 3.2% reduction in global terrestrial NPP compared to the decadal mean, primarily due to limited moisture supply in tropical regions. At a global level, precipitation explained approximately 63% of the variation in terrestrial NPP, while the rest was attributed to changes in temperature and other environmental factors. Precipitation was the major factor determining inter-annual variation in terrestrial NPP in low-latitude regions. However, in midand high-latitude regions, temperature variability largely controlled the magnitude of terrestrial NPP. Our results imply that pro- jected climate warming and increasing climate extreme events would alter the magnitude and spatiotemporal patterns of global terrestrial NPP.展开更多
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 a Forest Health Monitoring(FHM)award from the USDA Forest Service(Grant No.:19-DG-11083150-030)to Dr.Weimin Xi。
文摘Texas experienced the worst drought in its 100-year history in 2011,resulting in the death of approximately 300 million trees.The high number of sudden deaths had a significant impact on forest ecosystems.This study aimed to gain insight into the long-term and combined impacts of drought-induced forest tree deaths and their effects on biomass.This study used data obtained from 1797 National Forest Inventory(NFI)plots to analyze trends and major causes of changes in tree biomass at the sample plot level in East Texas forests over the past 20 years(2000-2019).In this study,forest trees in East Texas were divided into diameter at breast height(dbh),height,stand types,latitude,elevation,ecological zones,and FIA Unit.Principal component analysis(PCA)was also performed using drought intensity,drought duration,the four competing factor indicators,and the biomass loss rate of forest trees to better understand r drought impacts on forest trees.The results showed the lowest biomass loss rate of Pine species.Similarly,trees with shorter height and smaller dbh experienced a higher biomass loss rate.A higher biomass loss rate was observed in natural forests,West Gulf Coastal Plain and Plain and Southern East Texas ecoregion experienced higher biomass loss.Principal component analyses of drought intensity,drought duration,and the four competing metrics revealed that overall drought was the main contributor to biomass loss rates,and that drought intensity and drought duration had comparable effects on biomass loss rates.
基金This research was supported by the National Key Research and Development Program of China(Grant Nos.2017YFA0603804 and 2018YFC1507704)the Natural Science Foundation of China(Grant No.41805048).
文摘Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5),are assessed in terms of spatial distribution and interannual variability.The CMIP6 multi-model ensemble mean(CMIP6-MME)can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature,and minimum daily minimum temperature.However,CMIP6-MME has difficulties in reproducing cold nights and warm days,and has large cold biases over the Tibetan Plateau.Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices.Compared to CMIP5,CMIP6 models show improvements in the simulation of climate indices over China.This is particularly true for precipitation indices for both the climatological pattern and the interannual variation,except for the consecutive dry days.The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME)to 79%(CMIP6-MME).The most striking feature is that the dry biases in southern China,very persistent and general in CMIP5-MME,are largely reduced in CMIP6-MME.Stronger ascent together with more abundant moisture can explain this reduction in dry biases.Wet biases for total precipitation,heavy precipitation,and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME,but smaller,compared to CMIP5-MME.
基金supported by the Department of Science and Technology of China(2009CB421403 and2010CB428403)by the National Natural Science Foundation of China(41275110)
文摘Daily precipitation for 1960-2011 and maximum/minimum temperature extremes for 1960-2008 recorded at 549 stations in China are utilized to investigate climate extreme variations.A set of indices is derived and analyzed with a main focus on the trends and variabilities of daily extreme occurrences.Results show significant increases in daily extreme warm temperatures and decreases in daily extreme cold temperatures,defined as the number of days in which daily maximum temperature （Tmax） and daily minimum temperature （Tmin） are greater than the 90th percentile and less than thel0th percentile,respectively.Generally,the trend magnitudes are larger in indices derived from Tmin than those from Tmax.Trends of percentile-based precipitation indices show distinct spatial patterns with increases in heavy precipitation events,defined as the top 95th percentile of daily precipitation,in westem and northeastern China and in the low reaches of the Yangtze River basin region,and slight decreases in other areas.Light precipitation,defined as the tail of the 5th percentile of daily precipitation,however,decreases in most areas.The annual maximum consecutive dry days （CDD） show an increasing trend in southem China and the middle-low reach of the Yellow River basin,while the annual maximum consecutive wet days （CWD） displays a downtrend over most regions except western China.These indices vary significantly with regions and seasons.Overall,occurrences of extreme events in China are more frequent,particularly the night time extreme temperature,and landmasses in China become warmer and wetter.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0102)the K.C.WONG Education Foundation.This work also contributes to the U.K.-China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund.
文摘The year 2021 was recorded as the 6th warmest since 1880.In addition to large-scale warming,2021 will be remembered for its unprecedented climate extremes.Here,a review of selected high-impact climate extremes in 2021,with a focus on China,along with an extension to extreme events in North America and Europe is presented.Nine extreme events that occurred in 2021 in China are highlighted,including a rapid transition from cold to warm extremes and sandstorms in spring,consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year,extremely heavy rainfall over Henan Province and Hubei Province during summer,as well as heatwaves,persistent heavy rainfall,and a cold surge during fall.Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here,providing insights to understand climate extremes from a global perspective.This serves as a reference for climate event attribution,process understanding,and high-resolution modeling of extreme events.
基金provided by the LASG State Key Laboratory Special Fund for this research project
文摘The impacts of solar activity on climate are explored in this two-part study. Based on the principles of atmospheric dynamics, Part I propose an amplifying mechanism of solar impacts on winter climate extremes through changing the atmospheric circulation patterns. This mechanism is supported by data analysis of the sunspot number up to the predicted Solar Cycle 24, the historical surface temperature data, and atmospheric variables of NCEP/NCAR Reanalysis up to the February 2011 for the Northern Hemisphere winters. For low solar activity, the thermal contrast between the low- and high-latitudes is enhanced, so as the mid-latitude baroclinic ultra-long wave activity. The land-ocean thermal contrast is also enhanced, which amplifies the topographic waves. The enhanced mid-latitude waves in turn enhance the meridional heat transport from the low to high latitudes, making the atmospheric "heat engine" more efficient than normal. The jets shift southward and the polar vortex is weakened. The Northern Annular Mode (NAM) index tends to be negative. The mid-latitude surface exhibits large-scale convergence and updrafts, which favor extreme weather/climate events to occur. The thermally driven Siberian high is enhanced, which enhances the East Asian winter monsoon (EAWM). For high solar activity, the mid-latitude circulation patterns are less wavy with less meridional transport. The NAM tends to be positive, and the Siberian high and the EAWM tend to be weaker than normal. Thus the extreme weather/climate events for high solar activity occur in different regions with different severity from those for low solar activity. The solar influence on the mid- to high-latitude surface temperature and circulations can stand out after removing the influence from the E1 Nifio-Southern Oscillation. The atmospheric amplifying mechanism indicates that the solar impacts on climate should not be simply estimated by the magnitude of the change in the solar radiation over solar cycles when it is compared with other external radiative forcings that do not influence the climate in the same way as the sun does.
基金jointly supported by the National Natural Science Foundation of China (42275038)China Meteorological Administration Climate Change Special Program (QBZ202306)Robin CLARK was funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)
文摘Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.
基金supported by grants from National Science Foundation of China(31870507 and 31530088)the Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0501)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Y201920).
文摘Understanding how alien species assemble is crucial for predicting changes to community structure caused by biological invasions and for directing management strategies for alien species,but patterns and drivers of alien species assemblages remain poorly understood relative to native species.Climate has been suggested as a crucial filter of invasion-driven homogenization of biodiversity.However,it remains unclear which climatic factors drive the assemblage of alien species.Here,we compiled global data at both grid scale(2,653 native and 2,806 current grids with a resolution of 2°x 2°)and administrative scale(271 native and 297 current nations and sub-nations)on the distributions of 361 alien amphibians and reptiles(herpetofauna),the most threatened vertebrate group on the planet.We found that geographical distance,proxy for natural dispersal barriers,was the dominant variable contributing to alien herpetofaunal assemblage in native ranges.In contrast,climatic factors explained more unique variation in alien herpetofaunal assemblage after than before invasions.This pattern was driven by extremely high temperatures and precipitation seasonality,2 hallmarks of global climate change,and bilateral trade which can account for the alien assemblage after invasions.Our results indicated that human-assisted species introductions combined with climate change may accelerate the reorganization of global species distributions.
基金supported by a special scientific research project(GYHY200706008)in the public welfare industry(meteorology)the"Western Light"Project(RCPY200902)of the Chinese Academy of Sciencesthe Oasis Scholar"Doctor"Talent Training Program(0771021) of Xinjiang Institute of Ecology and Geography
文摘Based on daily maximum and minimum surface air temperature and precipitation records at 48 meteorological stations in Xinjiang, the spatial and temporal distributions of climate extreme indices have been analyzed during 1961-2008. Twelve temperature ex- treme indices and six precipitation extreme indices are studied. Temperature extremes are highly correlated to annual mean tem- perature, which appears to be significantly increasing by 0.08 ℃ per year, indicating that changes in temperature extremes reflect consistent warming. The warming tendency is clearer at stations in northern Xinjiang as reflected by mean temperature. The fre- quencies of cold days and nights have both decreased, respectively by -0.86 and -2.45 d/decade, but the frequencies of warm days and nights have both increased, respectively by ＋1.62 and ＋4.85 d/decade. Over the same period, the number of frost days shows a statistically significant decreasing trend of-2.54 d/decade. The growing season length and the number of summer days exhibit significant increasing trends at rates of ＋2.62 and ＋2.86 d/decade, respectively. The diumal temperature range has de- creased by -0.28 ℃/decade. Both annual extreme low and high temperatures exhibit significant increasing trend, with the former clearly larger than the latter. For precipitation indices, regional annual total precipitation shows an increasing trend and most other precipitation indices are strongly correlated with annual total precipitation. Average wet day precipitation, maximum 1-day and 5-day precipitation, and heavy precipitation days show increasing trends, but only the last is statistically significant. A decreasing trend is found for consecutive dry days. For all precipitation indices, stations in northwestern Xinjiang have the largest positive trend magnitudes, while stations in northern Xiniiang have the largest negative magnitudes.
基金funded by the Central Guidance on Local Science and Technology Development Fund of Inner Mongolia Autonomous Region,China(2022ZY0153)the“One Region Two Bases”Supercomputing Capacity Building Project of Inner Mongolia University,China(21300-231510).
文摘Against the backdrop of global warming,climate extremes and drought events have become more severe,especially in arid and semi-arid areas.This study forecasted the characteristics of climate extremes in the Xilin River Basin(a semi-arid inland river basin)of China for the period of 2021–2100 by employing a multi-model ensemble approach based on three climate Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)from the latest Coupled Model Intercomparison Project Phase 6(CMIP6).Furthermore,a linear regression,a wavelet analysis,and the correlation analysis were conducted to explore the response of climate extremes to the Standardized Precipitation Evapotranspiration Index(SPEI)and Streamflow Drought Index(SDI),as well as their respective trends during the historical period from 1970 to 2020 and during the future period from 2021 to 2070.The results indicated that extreme high temperatures and extreme precipitation will further intensify under the higher forcing scenarios(SSP5-8.5>SSP2-4.5>SSP1-2.6)in the future.The SPEI trends under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios were estimated as–0.003/a,–0.004/a,and–0.008/a,respectively,indicating a drier future climate.During the historical period(1970–2020),the SPEI and SDI trends were–0.003/a and–0.016/a,respectively,with significant cycles of 15 and 22 a,and abrupt changes occurring in 1995 and 1996,respectively.The next abrupt change in the SPEI was projected to occur in the 2040s.The SPEI had a significant positive correlation with both summer days(SU)and heavy precipitation days(R10mm),while the SDI was only significantly positively correlated with R10mm.Additionally,the SPEI and SDI exhibited a strong and consistent positive correlation at a cycle of 4–6 a,indicating a robust interdependence between the two indices.These findings have important implications for policy makers,enabling them to improve water resource management of inland river basins in arid and semi-arid areas under future climate uncertainty.
文摘The mineral industry is of great importance for the economy and for the development of Brazil. However, climate change further accentuates the impacts caused by extreme weather and climate events on the logistics and operation processes of the mineral production chain (from the mine to the port). In order to reduce these effects, it is essential to have information about the future climate that will help this economic sector to carry out better long-term planning of its activities. However, the current scientific literature still lacks studies with this approach applied to the mineral industry. Therefore, the purpose of this study was to evaluate the future seasonal patterns of climate extremes in eastern Amazonia, exploring their impacts on the mineral production chain in the near future (2019-2050). To categorize the dry and rainy climate extremes, the Standard Precipitation Index (SPI) was calculated for the precipitation data series of Climate Prediction Center (CPC) observations and the PRECIS regional modeling system, considering the IPCC RCP4.5. The 1981-2005 period was defined as the present climate and used to assess the performance of the modeling system in reproducing the extremes. The analyses were based on the relative frequency of the categories of dry and rainy extremes. The performance evaluation of PRECIS showed that it had better accuracy in representing seasonal extremes of drought than extremes of rain. Along the mineral chain in eastern Amazonia, its accuracy was better over the port region, except for the dry extremes experienced from June to August (JJA), and from December to February (DJF) and March to May (MAM) for rainy extremes. The analysis of the frequency of occurrence of these events for the future indicates a greater probability of rain extremes along the mineral chain compared to another category of extremes. In addition, JJA will be the most suitable period to optimize operational processes in eastern Amazonia, as extremes are less likely to occur. On the other hand, the greater probability of extreme rain events from September through to November (SON) and MAM make these two periods less suitable for activity in the mining regions and areas north of the railway. The results of this study suggest an increasing risk to the processes of the mineral chain until 2050 associated with the occurrence of climate extremes, since it is susceptible to adverse weather conditions.
基金supported by the National Natural Science Foundation of China(42288101)the National Key Research and Development Program(2022YFF0801703).
文摘Since the industrial revolution,multivariate climate extremes(e.g.,concurrent heatwaves and droughts)have caused irreversible damage to ecosystems and placed immense strain on human health and public resources in a warming climate[1,2].A stark example occurred in the summer of 2022 when the SichuanChongqing region endured prolonged drought,extreme heat,associated wildfires,and subsequent heavy rainfall.These events resulted in direct economic losses of approximately 10 billion Chinese Yuan(CNY)and affected around 9.8 million people in Sichuan Province alone[3].
基金supported by the National Natural Science Foundation of China(Grant No.41988101)。
文摘Whether the previous vegetation greening trend in China has persisted into the recent warmest decade and how the exceptional climate conditions of 2023 affected long-term change in vegetation greenness remain unexplored.Here we integrated two decades of remotely sensed normalized difference vegetation index data with climate records to reveal a persistent greening(referring to the increasing trend of vegetation greenness)of China,occurring at a rate triple the global average,while the greening signal varies geographically.A prominent greening trend is primarily driven by the greening of humid and subhumid regions,consistent with the expected effects of rising CO_(2)on vegetation growth and intensified human practices including agricultural intensification and ambitious afforestation programs.By contrast,semi-arid and arid ecosystems showed non-significant greenness change due to drastic warming and precipitation fluctuations.The exceptional warming and precipitation reduction in 2023 did not trigger a record-high decrease in vegetation greenness when integrated across China.The vegetation greenness in 2023 instead reached the third highest on record which is contributed by enhancement in North China,Northeast China,and the Tibetan Plateau.Climatic extremes in 2023 induced significant browning in the Loess Plateau,Inner Mongolia,and Southwest China.While ecosystems especially in the southern China demonstrated relatively high resilience to climatic extreme events like high-temperature extremes and droughts,autumn greenness in 2023 can recover to levels even higher than the 2020–2022 average,despite significant browning in spring and summer.We,therefore,suggested that the 2023 climate extremes would not produce a new baseline from which vegetation growth will transition towards a state of degradation at both regional and national scales.
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supported by the Open Project of Technology Innovation Center for Natural Ecosystem Carbon Sink(Grant No.CS2023D02)the Open Research Fund of Key Laboratory of Digital Earth Science,Aerospace Information Research Institute Chinese Academy of Sciences,Chinese Academy of Sciences(Grant No.2022LDE007)+5 种基金the Talent Program“Tianchi Talent(Young Doctor)”in Xinjiang Uygur Autonomous Region,National Natural Science Foundation of China(Grant No.42401065)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011273)Shenzhen Polytechnic University Research Fund(Grant No.6025310064K)the Innovation Training Program for Undergraduates at the Autonomous Region Level in 2024(Grant No.S202410755009)the Innovation Training Program for Undergraduates at the University Level in 2024(Grant No.XJUSRT-24008)the National Innovation Training Program for College Students in 2024(Grant No.202410755009)。
文摘Quantitative studies on the national-scale effects of extreme climatic events on soil organic carbon(SOC)remain scarce,thus limiting our understanding of SOC dynamics.This study utilized 4515 publicly available soil samples to quantify the impacts of 19 extreme climatic indices(ECIs)onΔSOC reservoirs in China through a hybrid space-for-time and meta-analysis approach.Overall,16/19 ECIs were negatively correlated withΔSOC,with the minimum temperature of the coldest night(TNn)showing the strongest negative correlation.Notably,topographic factors played a pivotal role in the modeling process,contributing an average of 25%,followed by ECIs.Under the influence of the ECIs,SOC exhibited spatial variation.Extreme heat resulted in the greatest SOC losses in cold regions,such as North China,with average reductions of>5%,whereas its impact was weaker in South China,with SOC losses of∼3%.Extreme cold and wet indices promoted SOC accumulation in the Northeast China,with increases of∼3%,but showed a weaker response in the humid region,where the SOC increased by only 1%.At the national scale,the impacts of extreme climatic events on SOC in the0–20 cm ranged from-2.36 Pg to 2.34 Pg.Different ecosystems responded variably,with forest and grassland ecosystems being more sensitive to ECIs,potentially due to higher organic matter inputs and greater ecosystem complexity.In contrast,bare land exhibited weaker responses due to limited vegetation cover and organic inputs.These findings provide valuable insights into SOC dynamics at national scale during extreme climatic events.
基金supported by the National Key Research and Development Program of China under the theme“Construction of a data representation framework for sustainable development indicators”[Grant No.2022YFC3802903-01]the National Natural Science Foundation of China“An economic theory based on the new production function in carbon neutrality”[Grant No.72250064]the National Natural Science Foundation of China“Macroeconomics”[Grant No.72122011].
文摘Climate change severely challenges our ecosystem and society,affecting urban residents’socioeconomic activities.Thus,assessing severe weather risk is crucial for evaluating urban sustainability;understanding trends,causes,and impacts on socioeconomic development;and supporting the United Nations Sustainable Development Goal(SDG)13.Using meteorological data from 1980 to 2020,we investigate five disaster-causing severe weather events in China and construct a comprehensive index of extreme climate risk(CIECR)at the county,city,province,and national levels.The CIECR can identify high-risk regions and primary severe weather events and provide early warnings.We empirically test the impact of extreme climate risks on agricultural production,industrial structure,and labor employment.The results show high risks in Xinjiang,northern Inner Mongolia,and southern regions,with high temperatures,low temperatures,and high winds as the leading risks.At the national level,the extreme climate risk fluctuates,indicating climate warming.While risks reduce agricultural production and employment,they promote modern agriculture,industrial production,and urbanization.The novelty of the study lies in its development of the county-level CIECR,which can capture heterogeneity characteristics and provide microdata support for urban climate change research and efforts toward SDG 13.This study aids in mitigating climate risks;responding to climate change;and comprehensively analyzing the causes,trends,and impacts of extreme climate risks.
基金supported by the National Natural Science Foundation of China (U2243227)。
文摘The net primary productivity(NPP) is an important indicator for assessing the carbon sequestration capacities of different ecosystems and plays a crucial role in the global biosphere carbon cycle. However, in the context of the increasing frequency, intensity, and duration of global extreme climate events, the impacts of extreme climate and vegetation phenology on NPP are still unclear, especially on the Qinghai-Xizang Plateau(QXP), China. In this study, we used a new data fusion method based on the MOD13A2 normalized difference vegetation index(NDVI) and the Global Inventory Modeling and Mapping Studies(GIMMS) NDVI_(3g) datasets to obtain a NDVI dataset(1982–2020) on the QXP. Then, we developed a NPP dataset across the QXP using the Carnegie-Ames-Stanford Approach(CASA) model and validated its applicability based on gauged NPP data. Subsequently, we calculated 18 extreme climate indices based on the CN05.1 dataset, and extracted the length of vegetation growing season using the threshold method and double logistic model based on the annual NDVI time series. Finally, we explored the spatiotemporal patterns of NPP on the QXP and the impact mechanisms of extreme climate and the length of vegetation growing season on NPP. The results indicated that the estimated NPP exhibited good applicability. Specifically, the correlation coefficient, relative bias, mean error, and root mean square error between the estimated NPP and gauged NPP were 0.76, 0.17, 52.89 g C/(m^(2)·a), and 217.52 g C/(m^(2)·a), respectively. The NPP of alpine meadow, alpine steppe, forest, and main ecosystem on the QXP mainly exhibited an increasing trend during 1982–2020, with rates of 0.35, 0.38, 1.40, and 0.48 g C/(m^(2)·a), respectively. Spatially, the NPP gradually decreased from southeast to northwest across the QXP. Extreme climate had greater impact on NPP than the length of vegetation growing season on the QXP. Specifically, the increase in extremely-wet-day precipitation(R99p), simple daily intensity index(SDII), and hottest day(TXx) increased the NPP in different ecosystems across the QXP, while the increases in the cold spell duration index(CSDI) and warm spell duration index(WSDI) decreased the NPP in these ecosystems. The results of this study provide a scientific basis for relevant departments to formulate future policies addressing the impact of extreme climate on vegetation in different ecosystems on the QXP.
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 National Key Research and Development Program of China(2017YFA0603804,2016YFA0600402,and 2018YFC1507704)。
文摘This paper presents projections of climate extremes over China under global warming of 1.5,2,and 3℃ above pre-industrial(1861–1900),based on the latest Coupled Model Intercomparison Project phase 6(CMIP6)simulations.Results are compared with what produced by the precedent phase of the project,CMIP5.Model evaluation for the reference period(1985–2005)indicates that CMIP6 models outperform their predecessors in CMIP5,especially in simulating precipitation extremes.Areal averages for changes of most indices are found larger in CMIP6 than in CMIP5.The emblematic annual mean temperature,when averaged over the whole of China in CMIP6,increases by 1.49,2.21,and 3.53℃(relative to1985–2005)for 1.5,2,and 3℃ above-preindustrial global warming levels,while the counterpart in CMIP5 is 1.20,1.93 and 3.39℃ respectively.Similarly,total precipitation increases by 5.3%,8.6%,and16.3%in CMIP6 and by 4.4%,7.0%and 12.8%in CMIP5,respectively.The spatial distribution of changes for extreme indices is generally consistent in both CMIP5 and CMIP6,but with significantly higher increases in CMIP6 over Northeast and Northwest China for the hottest day temperature,and South China for the coldest night temperature.In the south bank of the Yangtze River,and most regions around40°N,CMIP6 shows higher increases for both total precipitation and heavy precipitation.The projected difference between CMIP6 and CMIP5 is mainly attributable to the physical upgrading of climate models and largely independent from their emission scenarios.
基金NSF Decadal and Regional Climate Prediction using Earth System Models,No.AGS-1243220NSF Dynamics of Coupled Natural and Human Systems,No.1210360+2 种基金NSF Computer and Network Systems,No.CNS-1059376NASA Land Cover/Land Use Change Program,No.NNX08AL73G S01NASA Interdisciplinary Science Program,No.NNX10AU06G,No.NNX11AD47G
文摘A wide variety of studies have estimated the magnitude of global terrestrial net primary production （NPP）, but its variations, both spatially and temporally, still remain uncertain. By using an improved process-based terrestrial ecosystem model （DLEM, Dynamic Land Ecosystem Model）, we provide an estimate of global terrestrial NPP induced by multiple environmental factors and examine the response of terrestrial NPP to climate variability at biome and global levels and along latitudes throughout the first decade of the 21st century. The model simulation estimates an average global terrestrial NPP of 54.6 Pg C yr-1 during 2000-2009, varying from 52.8 Pg C yr-1 in the dry year of 2002 to 56.4 Pg C yr-1 in the wet year of 2008. In wet years, a large increase in terrestrial NPP compared to the decadal mean was prevalent in Amazonia, Africa and Australia. In dry years, however, we found a 3.2% reduction in global terrestrial NPP compared to the decadal mean, primarily due to limited moisture supply in tropical regions. At a global level, precipitation explained approximately 63% of the variation in terrestrial NPP, while the rest was attributed to changes in temperature and other environmental factors. Precipitation was the major factor determining inter-annual variation in terrestrial NPP in low-latitude regions. However, in midand high-latitude regions, temperature variability largely controlled the magnitude of terrestrial NPP. Our results imply that pro- jected climate warming and increasing climate extreme events would alter the magnitude and spatiotemporal patterns of global terrestrial NPP.
