2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

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.

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

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.

Impacts of Multi-Scale Solar Activity on Climate.Part Ⅰ:Atmospheric Circulation Patterns and Climate Extremes

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.

2021:A Year of Unprecedented Climate Extremes in Eastern Asia,North America,and Europe

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.

Changes in daily climate extremes in Xinjiang, northwestern China

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.

Climate Extremes along the Mining Chain over the Eastern Amazon: Projections to 2050

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.

Threshold of climate extremes that impact vegetation productivity over the Tibetan Plateau

Vegetation growth is adversely impacted by multiple climate extremes related to the water and thermal stress over the Tibetan Plateau(TP).However,it remains unknown at which stress level these climate extremes can trigger the abrupt shifts of vegetation response to climate extremes and result in the maximum vegetation response across TP.To fill this knowledge gap,we combined the hydrometeorological data and the satellite-derived vegetation index to detect two critical thresholds that determine the response of vegetation productivity to droughts,high-temperature extremes,and low-temperature extremes,respectively,during 2001-2018.Our results show that the response of vegetation productivity to droughts rapidly increases once crossing -1.41±0.6 standard deviation(σ)below the normal conditions of soil moisture.When crossing-2.98σ±0.9σ,vegetation productivity is maximum damaged by droughts.High-temperature extremes,which have the two thresholds of 1.34σ±0.4σand 2.31σ±0.4σover TP,are suggested to trigger the strong response of vegetation productivity at a milder stress level than low-temperature extremes(two thresholds:-1.44σ±0.5σand-2.53σ±0.8σ).Moreover,we found the compounded effects of soil moisture deficit in reducing the threshold values of both high-and low-temperature extremes.Based on the derived thresholds of climate extremes that impact vegetation productivity,Earth System Models project that southwestern TP and part of the northeastern TP will become the hotspots with a high exposure risk to climate extremes by 2100.This study deciphers the high-impact extreme climates using two important thresholds across TP,which advances the understanding of the vegetation response to different climate extremes and provides a paradigm for assessing the impacts of climate extremes on regional ecosystems.

Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.

Assessment of the Spatio-Temporal Trends of Annual Extreme Temperature Indices over Tanzania during the Period of 1982-2022

Extreme weather and climatic phenomena, such as heatwaves, cold waves, floods and droughts, are expected to become more common and have a significant impact on ecosystems, biodiversity, and society. Devastating disasters are mostly caused by record-breaking extreme events, which are becoming more frequent throughout the world, including Tanzania. A clear global signal of an increase in warm days and nights and a decrease in cold days and nights has been observed. The present study assessed the trends of annual extreme temperature indices during the period of 1982 to 2022 from 29 meteorological stations in which the daily minimum and maximum data were obtained from NASA/POWER. The Mann-Kendall and Sen slope estimator were employed for trend analysis calculation over the study area. The analyzed data have indicated for the most parts, the country has an increase in warm days and nights, extreme warm days and nights and a decrease in cold days and nights, extreme cold days and nights. It has been disclosed that the number of warm nights and days is on the rise, with the number of warm nights trending significantly faster than the number of warm days. The percentile-based extreme temperature indices exhibited more noticeable changes than the absolute extreme temperature indices. Specifically, 66% and 97% of stations demonstrated positive increasing trends in warm days (TX90p) and nights (TN90p), respectively. Conversely, the cold indices demonstrated 41% and 97% negative decreasing trends in TX10p and TN10p, respectively. The results are seemingly consistent with the observed temperature extreme trends in various parts of the world as indicated in IPCC reports.

Spatiotemporal variation of ecological environment quality and extreme climate drivers on the Qinghai-Tibetan Plateau

Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological environment of the QTP.However,there are few studies that explored the effects of climate extremes on ecological environment quality of the QTP,and few researchers have made quantitative analysis.Hereby,this paper proposed the Ecological Environmental Quality Index(EEQI)for analyzing the spatial and temporal variation of ecological environment quality on the QTP from 2000 to 2020,and explored the effects of climate extremes on EEQI based on Geographically and Temporally Weighted Regression(GTWR)model.The results showed that the ecological environment quality in QTP was poor in the west,but good in the east.Between 2000 and 2020,the area of EEQI variation was large(34.61%of the total area),but the intensity of EEQI variation was relatively low and occurred mainly by a slightly increasing level(EEQI change range of 0.05-0.1).The overall ecological environment quality of the QTP exhibited spatial and temporal fluctuations,which may be attributed to climate extremes.Significant spatial heterogeneity was observed in the effects of the climate extremes on ecological environment quality.Specifically,the effects of daily temperature range(DTR),number of frost days(FD0),maximum 5-day precipitation(RX5day),and moderate precipitation days(R10)on ecological environment quality were positive in most regions.Furthermore,there were significant temporal differences in the effects of consecutive dry days(CDD),consecutive wet days(CWD),R10,and FD0 on ecological environment quality.These differences may be attributed to variances in ecological environment quality,climate extremes,and vegetation types across different regions.In conclusion,the impact of climate extremes on ecological environment quality exhibits complex patterns.These findings will assist managers in identifying changes in the ecological environment quality of the QTP and addressing the effects of climate extremes.

Extreme climate events over northern China during the last 50 years

Climate extremes for agriculture-pasture transitional zone, northern China, are analyzed on the basis of daily mean temperature and precipitation observations for 31 stations in the period 1956-2001. Analysis season for precipitation is May-September, i.e., the rainy season. For temperature is the hottest three months, i.e., June through August. Heavy rain events, defined as those with daily precipitation equal to or larger than 50 mm, show no significant secular trend. A jump-like change, however, is found occurring in about 1980. For the period 1980-1993, the frequency of heavy rain events is significantly lower than the previous periods. Simultaneously, the occurring time of heavy rains expanded, commencing about one month early and ending one month later. Long dry spells are defined as those with longer than 10 days without rainfall. The frequency of long dry spells displays a significant (at the 99% confidence level) trend at the value of +8.3% /10a. That may be one of the major causes of the frequent droughts emerging over northern China during the last decades. Extremely hot and low temperature events are defined as the uppermost 10% daily temperatures and the lowest 10% daily temperatures, respectively. There is a weak and non-significant upward trend in frequency of extremely high temperatures from the 1950s to the mid-1990s. But the number of hot events increases as much as twice since 1997. That coincides well with the sudden rise in mean summer temperature for the same period. Contrary to that, the frequency of low temperature events have been decreasing steadily since the 1950s, with a significant linear trend of-15%/10a.

Climate extremes,variability,and trade shape biogeographical patterns of alien species

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.

Changes in climate extremes in a typical glacierized region in central Eastern Tianshan Mountains and their relationship with observed glacier mass balance

As an icon of anthropogenic climate change,alpine glaciers are highly sensitive to climate change.However,there remain research gaps regarding trends in climate extremes in glacierized regions and their relationship with local glacier mass balance.In this study,these relationships and their underlying links were explored in a typical glacierized region in the Eastern Tianshan Mountains,China,from 1959 to 2018.All warm extremes exhibited increasing trends that intensified dramatically from the 1990s.Meanwhile,decreasing trends were found for all cold extremes except for the temperatures of the coldest days and coldest nights.All of the precipitation extremes demonstrated increasing trends,except for consecutive dry days and consecutive wet days.Statistically significant positive/negative correlations were detected between glacier mass balance and six warm extremes(TN90p,TX90p,SU99p,TR95p,TXx,and TNx)/four cold extremes(TN10p,TX10p,FD0,and ID0).Simulation results showed that the impact of the intensity/frequency of the warm extremes(TN90p,TX90p,SU99p,and TR95p)on glacier ablation was remarkable and the effect of the cold extremes(FD0 and ID0)on accumulation was also significant.Additionally,the increases in the intensity and frequency of most climate extremes seemed more remarkable in glacierized regions than in non-glacierized regions.Hence,studies on glacier-climate interactions should focus greater attention on the impacts of climate extremes on glacier evolution.

Variability and change of climate extremes from indigenous herder knowledge and at meteorological stations across central Mongolia

In semi-arid regions,air temperatures have increased in the last decades more than in many other parts of the world.Mongolia has an arid/semi-arid climate and much of the population are herders whose livelihoods depend upon limited water resources that fluctuate with a variable climate.Herders were surveyed to identify their observations of changes in climate extremes for two soums of central Mongolia,Ikh-Tamir in the forest steppe north of the Khangai Mountains and Jinst in the desert steppe south of the mountains.The herders’indigenous knowledge of changes in climate extremes mostly aligned with the station-based analyses of change.Temperatures were warming with more warm days and nights at all stations.There were fewer cool days and nights observed at the mountain stations both in the summer and winter,yet more cool days and nights were observed in the winter at the desert steppe station.The number of summer days is increasing while the number of frost days is decreasing at all stations.The results of this study support further use of local knowledge and meteorological observations to provide more holistic analysis of climate change in different regions of the world.

Analyses of Extreme Climate Events over China Based on CMIP5 Historical and Future Simulations

Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 （CMIP5） models, cli- matic extremes and their changes over China in the past and under the future scenarios of three Representative Concentration Pathways （RCPs） are analyzed. In observations, frost days （FD） and low-temperature threshold days （TN10P） show a de- creasing trend, and summer days （SU）, high-temperature threshold days （TX90P）, heavy precipitation days （R20）, and the contribution of heavy precipitation days （P95T） show an increasing trend. Most models are able to simulate the main char- acteristics of most extreme indices. In particular, the mean FD and TX90P are reproduced the best, and the basic trends of FD, TN10P, SU and TX90P are represented. For the FD and SU indexes, most models show good ability in capturing the spatial differences between the mean state of the periods 1986--2005 and 1961-80; however, for other indices, the simulation abilities for spatial disparity are less satisfactory and need to be improved. Under the high emissions scenario of RCP8.5, the century-scale linear changes of the multi-model ensemble （MME） for FD, SU, TN10P, TX90P, R20 and P95T are -46.9, 46.0, -27.1, 175.4, and 2.9 days, and 9.9%, respectively; and the spatial change scope for each index is consistent with the emissions intensity. Due to the complexities of physical process pararneterizations and the limitation of forcing data, great uncertainty still exists with respect to the simulation of climatic extremes.

Spatial and Temporal Variations of Extreme Climate Events in Xinjiang, China during 1961-2010

Daily maximum/minimum temperature and precipitation data from 35 weather stations in Xinjiang during 1961-2010 were examined using kriging spatial analysis, linear tendency estimation, and correlation analysis. Temporal trends and spatial distribution patterns of extreme temperature and precipitation in this area were then analyzed using 12 extreme temperature and 7 extreme precipitation indices. The following results were obtained. 1) Over the past 50 years, extreme cold indices, excepting the monthly maximum temperature minimum value and monthly extreme minimum temperature, showed slight decreasing trends. These indices include the maximum number of consecutive frost days, icy days, cold-nighttime days, and cold-daytime days. 2) Extreme warm events generally showed significant increasing trends (P < 0.01), including the indices of summertime days, warm-nighttime days, warm-daytime days, monthly extreme maximum temperature, and monthly minimum temperature maximum value. 3) The spatial distributions of threshold values of extreme warm and cold events showed notable regional differences. A reducing trend of extreme cold events and an increase in extreme warm events has occurred mainly in northern Xinjiang. 4) For the past 50 years, six extreme precipitation indices, aside from consecutive dry days, showed significant increasing trends in Xinjiang (P < 0.05) and notable differences in spatial distribution. The increase in extreme precipitation events was more rapid at northern than at southern sites. Extreme precipitation intensity was greater in mountainous areas, and precipitation frequency increased in the plain region. 5) Factor analysis revealed good correlations among extreme temperature indices, excepting extreme temperature days.

Workshop on Polar Climate Changes and Extreme Events

Polar climate systems have experienced a number of dramatic changes （Wang et al., 2017; Turner et al., 2016; Gordon, 2014; Rignot et al., 2013; Meier et al., 2012; Kwok and Rothrock, 2009; Thompson and Solomon, 2002）, which have influenced climatic conditions across large parts of the globe through large-scale atmospheric and oceanic teleconnections （Dou and Wu, 2018; Zhang et al., 2018;

Detecting Climate Change in Using Extreme Data from Two Surface Weather Stations: Case Study Valle of Comitan and La Esperanza, Chiapas, Mexico

The study area is located between the cities of Comitan (16°10'43"N and 92°04'20''W) a city with 150,000 inhabitants and La Esperanza (16°9'15''N and 91°52'5''W) a town with 3000 inhabitants. Both weather stations are 30 km from each other in the Chiapas State, México. 54 years of daily records of the series of maximum (tmax) and minimum temperatures (tmin) of the weather station 07205 Comitan that is on top of a house and 30 years of daily records of the weather station 07374 La Esperanza were analyzed. The objective is to analyze the evidence of climate change in the Comitan valley. 2.07% and 19.04% of missing data were filled, respectively, with the WS method. In order to verify homogeneity three methods were used: Standard Normal Homogeneity Test (SNHT), the Von Neumann method and the Buishand method. The heterogeneous series were homogenized using climatol. The trends of tmax and tmin for both weather stations were analyzed by simple linear regression, Sperman’s rho and Mann-Kendall tests. The Mann-Kendal test method confirmed the warming trend at the Comitan station for both variables with ZMK statistic values equal to 1.57 (statistically not significant) and 4.64 (statistically significant). However, for the Esperanza station, it determined a cooling trend for tmin and a slight non-significant warming for tmax with a ZMK statistic of -2.27 (statistically significant) and 1.16 (statistically not significant), for a significance level α = 0.05.

Habitat heterogeneity and biotic interactions mediate climate influences on seedling survival in a temperate forest

Seedling stage has long been recognized as the bottleneck of forest regeneration,and the biotic and abiotic processes that dominate at seedling stage largely affect the dynamics of forest.Seedlings might be particularly vulnerable to climate stress,so elucidating the role of interannual climate variation in fostering community dynamics is crucial to understanding the response of forest to climate change.Using seedling survival data of 69 woody species collected for five consecutive years from a 25-ha permanent plot in a temperate deciduous forest,we identified the effects of biotic interactions and habitat factors on seedling survival,and examined how those effects changed over time.We found that interannual climate variations,followed by biotic interactions and habitat conditions,were the most significant predictors of seedling survival.Understory light showed a positive impact on seedling mortality,and seedling survival responded differently to soil and air temperature.Effects of conspecific neighbor density were significantly strengthened with the increase of maximum air temperature and vapor pressure deficits in the growing season,but were weakened by increased maximum soil temperature and precipitation in the non-growing season.Surprisingly,seedling survival was strongly correlated with interannual climate variability at all life stages,and the strength of the correlation increased with seedling age.In addition,the importance of biotic and abiotic factors on seedling survival differed significantly among species-trait groups.Thus,the neighborhood-mediated effects on mortality might be significantly contributing or even inverting the direct effects of varying abiotic conditions on seedling survival,and density-dependent effects could not be the only important factor influencing seedling survival at an early stage.

Overview of China Polar Climate Change Annual Report(2022)

The China Meteorological Administration recently released China Polar Climate Change Annual Report(2022)in Chinese,with the following main conclusions.Using the China Reanalysis-40 dataset(CRA-40),rapid warming has been observed in the Antarctic Peninsula and West Antarctica since 1979,with some parts of East Antarctica also experiencing warming.In 2022,the regional average temperature in Antarctica based on observational data was close to the long-term average(1991-2020).The Arctic,on the other hand,has experienced a warming trend at a rate of 0.63℃per decade from 1979 to 2022 based on CRA-40,which is 3.7 times the global mean during the same period(0.17℃per decade).In 2022,the overall temperature in the Arctic,using station data,was 1.10℃above the long-term average(1991-2020).In recent years,both the Antarctic and Arctic regions have witnessed an increase in the frequency and intensity of extreme weather events.In 2022,based on the sea ice extent from National Snow and Ice Data Center,USA,Antarctic sea ice reached its lowest extent on record since 1979,and on 18 March,the most rapid surface warming event ever recorded on Earth occurred in the Antarctic,with a temperature increase of 49℃within 3 d.This report has been integrated into China's National Climate Change Bulletin system,to contribute to raising public awareness of polar climate change and providing valuable scientific references to address climate change.