Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023?

In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter.In this report,as shown in the multi-model ensemble mean(MME)prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences,a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months,which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection,thus serving to modulate the winter climate in East Asia and North America.Despite some uncertainty due to unpredictable internal atmospheric variability,the global mean surface temperature(GMST)in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend.Specifically,the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter,and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991.Moreover,the necessary early warnings are still reliable in the timely updated mediumterm numerical weather forecasts and sub-seasonal-to-seasonal prediction.

Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

Convection-Permitting Simulations of Current and Future Climates over the Tibetan Plateau

The Tibetan Plateau(TP)region,also known as the“Asian water tower”,provides a vital water resource for downstream regions.Previous studies of water cycle changes over the TP have been conducted with climate models of coarse resolution in which deep convection must be parameterized.In this study,we present results from a first set of highresolution climate change simulations that permit convection at approximately 3.3-km grid spacing,with a focus on the TP,using the Icosahedral Nonhydrostatic Weather and Climate Model(ICON).Two 12-year simulations were performed,consisting of a retrospective simulation(2008–20)with initial and boundary conditions from ERA5 reanalysis and a pseudoglobal warming projection driven by modified reanalysis-derived initial and boundary conditions by adding the monthly CMIP6 ensemble-mean climate change under the SSP5-8.5 scenario.The retrospective simulation shows overall good performance in capturing the seasonal precipitation and surface air temperature.Over the central and eastern TP,the average biases in precipitation(temperature)are less than−0.34 mm d−1(−1.1℃)throughout the year.The simulated biases over the TP are height-dependent.Cold(wet)biases are found in summer(winter)above 5500 m.The future climate simulation suggests that the TP will be wetter and warmer under the SSP5-8.5 scenario.The general features of projected changes in ICON are comparable to the CMIP6 ensemble projection,but the added value from kilometer-scale modeling is evident in both precipitation and temperature projections over complex topographic regions.These ICON-downscaled climate change simulations provide a high-resolution dataset to the community for the study of regional climate changes and impacts over the TP.

Future changes in precipitation and water availability over the Tibetan Plateau projected by CMIP6 models constrained by climate sensitivity

Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.

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.

Insights from the Second Tibetan Plateau Scientific Expedition: Unveiling the westerly–monsoon synergy and hydroclimate changes

The Tibetan Plateau(TP),often referred to as the“Asian Water Tower”,holds vast reserves of glaciers,snow,and permafrost,serving as the crucial source for major rivers that support billions of people across Asia.The TP’s unique geographical positioning fosters significant interplay between the westerly and monsoon systems,the hydroclimate changes on the TP and its interactions with these two major atmospheric circulation systems through both the thermodynamic and dynamic processes,as well as the atmospheric water cycle of the TP.These interactions have far-reaching impacts on the weather and climate of China,Asia,and even the global atmospheric circulation.

中国东部地区大气水汽稳定同位素的影响因子追踪研究

大气水汽稳定同位素是现代水循环的重要示踪剂,可以有效地追踪水汽来源及其输送过程。在中低纬度季风区,局地“降水量效应”是大气水汽稳定同位素的主要特征,但是近期研究表明,水汽来源及其输送过程等非局地因素也有重要影响。因此,本文基于拉格朗日粒子扩散模式和卫星遥感观测的大气水汽稳定氘同位素数据(数值表示为千分差,δD),针对前人研究较少的中国东部石笋氧同位素区域,进行水汽源地追踪,并在季节和年际尺度上分析水汽δD的主要影响因素。结果表明,在季节尺度上,水汽δD在夏末秋初较低,冬春季较高,这种特征与局地气象因子、水汽源地贡献的关系较弱,水汽输送路径上的累积降水是影响水汽δD季节变化的主要因素,两者为显著的负相关关系。在年际尺度上,厄尔尼诺(El Nino)年夏季中国东部水汽δD较高,拉尼娜(La Nina)年夏季水汽δD较低。水汽源地贡献在ENSO(厄尔尼诺—南方涛动)不同位相的变化较小,而水汽输送路径上的累积降水在La Nina年较之El Nino年偏多,表明La Nina年热带对流活动和水汽输送过程的贫化作用更强,导致目标区域的水汽δD更低。因此,代表热带对流活动的累积降水是水汽δD季节和年际变化的主要影响因素,热带对流活动增强(减弱)将降低(增加)目标区域的水汽δD。

Seasonal Prediction of the Record-Breaking Northward Shift of the Western Pacific Subtropical High in July 2021

The unprecedented Zhengzhou heavy rainfall in July 2021 occurred under the background of a northward shift of the western Pacific subtropical high(WPSH).Although the occurrence of this extreme event could not be captured by seasonal predictions,a skillful prediction of the WPSH variation might have warned us of the increased probability of extreme weather events in Central and Northern China.However,the mechanism for the WPSH variation in July 2021 and its seasonal predictability are still unknown.Here,the observed northward shift of the WPSH in July 2021 is shown to correspond to a meridional dipole pattern of the 850-hPa geopotential height to the east of China,the amplitude of which became the strongest since 1979.The meridional dipole pattern is two nodes of the Pacific–Japan pattern.To investigate the predictability of the WPSH variation,a 21-member ensemble of seasonal predictions initiated from the end of June 2021 was conducted.The predictable and unpredictable components of the meridional dipole pattern were identified from the ensemble simulations.Its predictable component is driven by positive precipitation anomalies over the tropical western Pacific.The positive precipitation anomalies are caused by positive horizonal advection of the mean moist enthalpy by southwesterly anomalies to the northwestern flank of anticyclonic anomalies excited by the existing La Niña,which is skillfully predicted by the model.The leading mode of the unpredictable component is associated with the atmospheric internal intraseasonal oscillations,which are not initialized in the simulations.The relative contributions of the predictable and unpredictable components to the observed northward shift of the WPSH at 850 hPa are 28.0%and 72.0%,respectively.

Understanding and Attribution of Extreme Heat and Drought Events in 2022: Current Situation and Future Challenges

Extreme weather events and their consequential impacts have been a key feature of the climate in recent years in many parts of the world,with many partly attributed to ongoing global-scale warming.The past year,2022,has been no exception,with further records being broken.The year was marked by unprecedented heatwaves and droughts with highly unusual spatial extent,duration and intensity,with one measure indicating an aggregated and overall intensity of extreme heat events worldwide not seen since at least 1950.The extreme drought measured by surface soil moisture covered 47.3%of global land areas in 2022,which was the second most widespread year since 1980.Here,we examine notable events of the year in five major regions of the world:China’s Yangtze River region,western Europe,the western U.S.,the Horn of Africa and central South America.For each event,we review the potential roles of circulation,oceanic forcing(especially the“triple-dip”La Niña)and anthropogenic climate change,with an aim of understanding the extreme events in 2022 from a global perspective.This will serve as a reference for mechanism understanding,prediction and attribution of extreme events.

Extreme Cold Events in North America and Eurasia in November-December 2022: A Potential Vorticity Gradient Perspective

From 17 November to 27 December 2022, extremely cold snowstorms frequently swept across North America and Eurasia. Diagnostic analysis reveals that these extreme cold events were closely related to the establishment of blocking circulations. Alaska Blocking(AB) and subsequent Ural Blocking(UB) episodes are linked to the phase transition of the North Atlantic Oscillation(NAO) and represent the main atmospheric regimes in the Northern Hemisphere. The downstream dispersion and propagation of Rossby wave packets from Alaska to East Asia provide a large-scale connection between AB and UB episodes. Based on the nonlinear multi-scale interaction(NMI) model, we found that the meridional potential vorticity gradient(PVy) in November and December of 2022 was anomalously weak in the mid-high latitudes from North America to Eurasia and provided a favorable background for the prolonged maintenance of UB and AB events and the generation of associated severe extreme snowstorms. However, the difference in the UB in terms of its persistence,location, and strength between November and December is related to the positive(negative) NAO in November(December). During the La Ni?a winter of 2022, the UB and AB events are related to the downward propagation of stratospheric anomalies, in addition to contributions by La Ni?a and low Arctic sea ice concentrations as they pertain to reducing PVyin mid-latitudes.

Can Eurasia Experience a Cold Winter under a Third-Year La Nina in 2022/23?

The Northern Hemisphere(NH)often experiences frequent cold air outbreaks and heavy snowfalls during La Nina winters.In 2022,a third-year La Nina event has exceeded both the oceanic and atmospheric thresholds since spring and is predicted to reach its mature phase in December 2022.Under such a significant global climate signal,whether the Eurasian Continent will experience a tough cold winter should not be assumed,despite the direct influence of mid-to high-latitude,large-scale atmospheric circulations upon frequent Eurasian cold extremes,whose teleconnection physically operates by favoring Arctic air invasions into Eurasia as a consequence of the reduction of the meridional background temperature gradient in the NH.In the 2022/23 winter,as indicated by the seasonal predictions from various climate models and statistical approaches developed at the Institute of Atmospheric Physics,abnormal warming will very likely cover most parts of Europe under the control of the North Atlantic Oscillation and the anomalous anticyclone near the Ural Mountains,despite the cooling effects of La Nina.At the same time,the possibility of frequent cold conditions in mid-latitude Asia is also recognized for this upcoming winter,in accordance with the tendency for cold air invasions to be triggered by the synergistic effect of a warm Arctic and a cold tropical Pacific on the hemispheric scale.However,how the future climate will evolve in the 2022/23 winter is still subject to some uncertainty,mostly in terms of unpredictable internal atmospheric variability.Consequently,the status of the mid-to high-latitude atmospheric circulation should be timely updated by medium-term numerical weather forecasts and sub-seasonal-to-seasonal prediction for the necessary date information and early warnings.

CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment

The outputs of the Chinese Academy of Sciences(CAS)Flexible Global Ocean-Atmosphere-Land System(FGOALSf3-L)model for the decadal climate prediction project(DCPP)of the Coupled Model Intercomparison Project Phase 6(CMIP6)are described in this paper.The FGOALS-f3-L was initialized through the upgraded,weakly coupled data assimilation scheme,referred to as EnOI-IAU,which assimilates observational anomalies of sea surface temperature(SST)and upper-level(0–1000-m)ocean temperature and salinity profiles into the coupled model.Then,nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year over the period of 1960–2021,based on initial conditions produced by three initialization experiments.The hindcast and forecast experiments follow the experiment designs of the Component-A and Component-B of the DCPP,respectively.The decadal prediction output datasets contain a total of 44 monthly mean atmospheric and oceanic variables.The preliminary evaluation indicates that the hindcast experiments show significant predictive skill for the interannual variations of SST in the north Pacific and multi-year variations of SST in the subtropical Pacific and the southern Indian Ocean.

Negligible Warming Caused by Nord Stream Methane Leaks

Unanticipated sabotage of two underwater pipelines in the Baltic Sea(Nord Stream 1 and 2)happened on 26September 2022.Massive quantities of natural gas,primarily methane,were released into the atmosphere,which lasted for about one week.As a more powerful greenhouse gas than CO_(2),the potential climatic impact of methane is a global concern.Using multiple methods and datasets,a recent study reported a relatively accurate magnitude of the leaked methane at 0.22±0.03 million tons(Mt),which was lower than the initial estimate in the immediate aftermath of the event.Under an energy conservation framework used in IPCC AR6,we derived a negligible increase in global surface air temperature of 1.8×10^(-5)℃ in a 20-year time horizon caused by the methane leaks with an upper limit of 0.25 Mt.Although the resultant warming from this methane leak incident was minor,future carbon release from additional Earth system feedbacks,such as thawing permafrost,and its impact on the methane mitigation pathways of the Paris Agreement,warrants investigation.

Preface to the 2nd Special Issue on Climate Science for Service Partnership China

It is a great pleasure to introduce this second special issue of Advances in Atmospheric Sciences with new highlights from the Climate Science for Service Partnership(CSSP,Scaife et al.,2021)between China and the UK.The CSSP harnesses expertise in the China Meteorological Administration’s National Climate Centre(CMA NCC),the Institute of Atmospheric Physics(IAP)at the Chinese Academy of Sciences and the Met Office,plus key UK and Chinese universities and institutes to deliver a vibrant programme of collaborative research.

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.

Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models

Precipitation over the Tibetan Plateau(TP)is important to local and downstream ecosystems.Based on a weighting method considering model skill and independence,changes in the TP precipitation for near-term(2021-40),mid-term(2041-60)and long-term(2081-2100)under shared socio-economic pathways(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSSP3-7.0,SSP5-8.5)are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project.The annual mean precipitation is projected to increase by 7.4%-21.6%under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology.Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation,except for the drying trend in winter precipitation along the southern edges of the TP.Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections.The effect of weighting exhibits spatial and seasonal differences.Seasonally,weighting leads to a prevailing enhancement of increase in spring precipitation over the TP.Spatially,the influence of weighting is more remarkable over the northwestern TP regarding the annual,summer and autumn precipitation.Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP,especially for the season of spring and the region of the northwestern TP,which requires additional attention in decision making.

Moisture Origins and Transport Processes for the 2020 Yangtze River Valley Record-Breaking Mei-yu Rainfall

The summer of 2020 recorded a record-breaking flood due to excessive mei-yu rain falling over the Yangtze River Valley(YRV).Using the Lagrangian model FLEXPART,this paper investigates moisture sources and transport processes behind this extreme event.Based on climate data from 1979 to 2019,the air-particle(an infinitesimally small air parcel)trajectories reaching the YRV show sectors that correspond to five main moisture sources:the Indian monsoon region(IND,27.5%of the total rainfall),the local evaporation(27.4%),the Western Pacific Ocean(WPO,21.3%),the Eurasian continent(8.5%)and Northeast Asia(4.4%).In the 2020 mei-yu season,moisture from all source regions was above normal except that from Northeast Asia.A record-breaking moisture source from the IND and WPO dominated this extreme mei-yu flood in 2020,which was 1.5 and 1.6 times greater than the climate mean,respectively.This study reveals a significant relationship between the moisture source with three moisture transport processes,i.e.,trajectory density,moisture content,and moisture uptake of air-particles.A broad anomalous anticyclonic circulation over the Indo-Northwestern Pacific(Indo-NWP)provides a favorable environment to enhance the moisture transport from the IND and WPO into the YRV.In the 2020 mei-yu season,a record-breaking Indo-NWP anomalous anticyclonic circulation contributed to a higher trajectory density as well as higher moisture content and moisture uptake of air-particles from the IND and WPO regions.This collectively resulted in unprecedented moisture transport from source origins,thus contributing to the mei-yu flood over the YRV in 2020.

A Robustness Analysis of CMIP5 Models over the East Asia-Western North Pacific Domain

The Coupled Model Intercomparison Project （CMIP） is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Improving the performance of climate models over East Asia and the western North Pacific has been a challenge for the climate-modeling community. In this paper, we provide a synthesis robustness analysis of the climate models participating in CMIP-Phase 5 （CMIP5）. The strengths and weaknesses of the CMIP5 models are assessed from the perspective of climate mean state, interannual variability, past climate change during the mid-Pliocene （MP） and the last millennium, and climate projection. The added values of regional climate models relative to the driving global climate models are also assessed. Although an encouraging increase in credibility and an improvement in the simulation of mean states, interannual variability, and past climate changes are visible in the progression from CMIP3 to CMIPS, some previously noticed biases such as the ridge position of the western North Pacific subtropical high and the associated rainfall bias are still evident in CMIP5 models. Weaknesses are also evident in simulations of the interannual amplitude, such as El Nino- Southern Oscillation （ENSO）-monsoon relationships. Coupled models generally show better results than standalone atmospheric models in simulating both mean states and interannual variability. Multi-model intercomparison indicates significant uncertainties in the future projection of climate change, although precipitation increases consistently across models constrained by the Clausius-Clapeyron relation. Regional ocean-atmosphere coupled models are recommended for the dynamical downscaling of climate change oroiections over the East Asia-western North Pacific domain.

CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments

The Chinese Academy of Sciences(CAS)Flexible Global Ocean Atmosphere Land System(FGOALS-f3-L)model datasets prepared for the sixth phase of the Coupled Model Intercomparison Project(CMIP6)Global Monsoons Model Intercomparison Project(GMMIP)Tier-1 and Tier-3 experiments are introduced in this paper,and the model descriptions,experimental design and model outputs are demonstrated.There are three simulations in Tier-1,with different initial states,and five simulations in Tier-3,with different topographies or surface thermal status.Specifically,Tier-3 contains four orographic perturbation experiments that remove the Tibetan Iranian Plateau,East African and Arabian Peninsula highlands,Sierra Madre,and Andes,and one thermal perturbation experiment that removes the surface sensible heating over the Tibetan Iranian Plateau and surrounding regions at altitudes above 500 m.These datasets will contribute to CMIP6’s value as a benchmark to evaluate the importance of long-term and short-term trends of the sea surface temperature in monsoon circulations and precipitation,and to a better understanding of the orographic impact on the global monsoon system over highlands.

Volcanoes and Climate:Sizing up the Impact of the Recent Hunga Tonga-Hunga Ha'apai Volcanic Eruption from a Historical Perspective

An undersea volcano at Hunga Tonga-Hunga Ha'apai(HTHH)near the South Pacific island nation of Tonga,erupted violently on 15 January 2022.Potential climate impact of the HTHH volcanic eruption is of great concern to the public;here,we intend to size up the impact of the HTHH eruption from a historical perspective.The influence of historical volcanic eruptions on the global climate are firstly reviewed,which are thought to have contributed to decreased surface temperature,increased stratospheric temperature,suppressed global water cycle,weakened monsoon circulation and El Niño-like sea surface temperature.Our understanding of the impacts of past volcanic eruptions on global-scale climate provides potential implication to evaluate the impact of the HTHH eruption.Based on historical simulations,we estimate that the current HTHH eruption with an intensity of 0.4 Tg SO_(2)injection will decrease the global mean surface temperature by only 0.004℃in the first year after eruption,which is within the amplitude of internal variability at the interannual time scale and thus not strong enough to have significant impacts on the global climate.