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.

Variation of Surface Temperature during the Last Millennium in a Simulation with the FGOALS-gl Climate System Model

A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model （FGOALS-gl） developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics （LASG/IAP）. The model presents a reasonable performance in comparison with reconstructions of surface temperature. Differentiated from significant changes in the 20th century at the global scale, changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere. Seasonally, modeled significant changes are more pronounced during the wintertime at higher latitudes. This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback. The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period, especially at decadal timescales. Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability. The model response to specified external forcings is modulated by cloud radiative forcing （CRF）. The CRF acts against the fluctuations of external forcings. Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period, but mainly in longwave radiation by a decrease in cloud amount in the ant hropogenic- forcing-dominant period.

北京气候中心气候系统模式研发进展——在气候变化研究中的应用

较全面地介绍了北京气候中心气候系统模式(BCC_CSM)研发所取得的一些进展及其在气候变化研究中的应用,重点介绍了全球近280 km较低分辨率的全球海-陆-气-冰-生物多圈层耦合的气候系统模式BCC_CSM1.1和110 km中等大气分辨率的BCC_CSM1.1(m),以及大气、陆面、海洋、海冰各分量模式的发展。BCC_CSM1.1和BCC_CSM1.1(m)气候系统模式均包含了全球碳循环和动态植被过程。当给定全球人类活动导致的碳源排放后,就可以模拟和预估人类活动对气候变化的影响。BCC_CSM1.1和BCC_CSM1.1(m)已应用于IPCC AR5模式比较,为中外开展气候变化机理分析和未来气候变化预估提供了大量的试验数据。还介绍了BCC_CSM1.1和BCC_CSM1.1(m)参与国际耦合模式比较计划(CMIP5)的大量试验分析评估结果,BCC_CSM能够较好地模拟20世纪气温和降水等气候平均态和季节变化特征,以及近1000年的历史气候变化,所预估的未来100年气候变化与国际上其他模式的CMIP5试验预估结果相当。初步的分析表明,分辨率相对高的BCC_CSM1.1(m)在区域气候平均态的模拟上优于分辨率较低的BCC_CSM1.1。

Evaluation of Spring Persistent Rainfall over East Asia in CMIP3/CMIP5 AGCM Simulations

The progress made fi＇om Phase 3 to Phase 5 of the Coupled Model Intercomparison Project （CMIP3 to CMIP5） in simulating spring persistent rainfall （SPR） over East Asia was examined from the outputs of nine atmospheric general circulation models （AGCMs）. The majority of the models overestimated the precipitation over the SPR domain, with the mean latitude of the SPR belt shifting to the north. The overestimation was about 1mm d-1 in the CMIP3 ensemble, and the northward displacement was about 3°, while in the CMIP5 ensemble the overestimation was suppressed to 0.7 mm d-i and the northward shift decreased to 2.5°. The SPR features a northeast-southwest extended rain belt with a slope of 0.4°N/°E. The CMIP5 ensemble yielded a smaller slope （0.2°N/°E）, whereas the CMIP3 ensemble featured an unre- alistic zonally-distributed slope. The CMIP5 models also showed better skill in simulating the interannual variability of SPR. Previous studies have suggested that the zonal land-sea thermal contrast and sensible heat flux over the southeastern Tibetan Plateau are important for the existence of SPR. These two ther- mal factors were captured well in the CMIP5 ensemble, but underestimated in the CMIP3 ensemble. The variability of zonal land-sea thermal contrast is positively correlated with the rainfall amount over the main SPR center, but it was found that an overestimated thermal contrast between East Asia and South China Sea is a common problem in most of the CMIP3 and CMIP5 models. Simulation of the meridional thermal contrast is therefore important for the future improvement of current AGCMs.

Bias correction and projection of surface air temperature in LMDZ multiple simulation over central and eastern China

Based on LMDZ4 daily temperature dataset,equidistant cumulative distribution function matching method(EDCDFm)and cumulative distribution function-transform method(CDF-t)are used to evaluate the ability of models in simulating extreme temperature over central and eastern China.The future temperature change is then projected.The results show that the EDCDFm and CDF-t methods function effectively correct the spatial distribution of daily mean temperature and extreme temperature,significantly reduce the biases of the model simulation and effectively improve the capacity of models for spatial pattern of extreme temperature.However,the cold bias of the CDF-t method in winter is obviously higher than that of the EDCDFm method,and the temperature change curve of the EDCDFm method is closer to the observation than that of the CDF-t method.The projection based on the EDCDFm method shows that under the RCP4.5 emission scenario,the temperature in the study area shows a warming trend.Relative to 1986e2005,the mean temperature is projected to increase by 0.76,1.84,and 2.10℃during 2017e2036,2046e2065,and 2080e2099,respectively.The spatial change for the mean,maximum,and minimum temperature in the three future periods have good consistency;warming in northern China is higher than that in the south.Uncertainties in temperature projection are large in the Tibetan Plateau and Sichuan Basin.Frost days decrease significantly,especially in the Tibetan Plateau,and the frost days in the three periods decrease by more than 15,30,and 40 d,respectively.The variation of heat wave indice is the smallest;the increase of heat wave is mainly in eastern China,and the increase in South China is more than 2 d.Besides,under the global warming of 1.5℃and 2℃,the response characteristics of extreme temperature over central and eastern China are also analyzed.The results show that the mean temperature,maximum temperature and minimum temperature in the study area increase by more than 0.75℃under 1.5℃target and over 1.25℃under 2℃target,especially in the northwestern China and the Tibetan Plateau,relative to 1986e2005.Additionally,comparing two warming targets,the difference of three temperature indices in parts of northeastern China is over 1.5℃,while more than 3 d for heat wave.

Intercomparison of multi-model ensemble-processing strategies within a consistent framework for climate projection in China

Climate change adaptation and relevant policy-making need reliable projections of future climate.Methods based on multi-model ensemble are generally considered as the most efficient way to achieve the goal.However,their efficiency varies and inter-comparison is a challenging task,as they use a variety of target variables,geographic regions,time periods,or model pools.Here,we construct and use a consistent framework to evaluate the performance of five ensemble-processing methods,i.e.,multimodel ensemble mean(MME),rank-based weighting(RANK),reliability ensemble averaging(REA),climate model weighting by independence and performance(ClimWIP),and Bayesian model averaging(BMA).We investigate the annual mean temperature(Tav)and total precipitation(Prcptot)changes(relative to 1995–2014)over China and its seven subregions at 1.5 and 2℃warming levels(relative to pre-industrial).All ensemble-processing methods perform better than MME,and achieve generally consistent results in terms of median values.But they show different results in terms of inter-model spread,served as a measure of uncertainty,and signal-to-noise ratio(SNR).ClimWIP is the most optimal method with its good performance in simulating current climate and in providing credible future projections.The uncertainty,measured by the range of 10th–90th percentiles,is reduced by about 30%for Tav,and 15%for Prcptot in China,with a certain variation among subregions.Based on ClimWIP,and averaged over whole China under 1.5/2℃global warming levels,Tav increases by about 1.1/1.8℃(relative to 1995–2014),while Prcptot increases by about 5.4%/11.2%,respectively.Reliability of projections is found dependent on investigated regions and indices.The projection for Tav is credible across all regions,as its SNR is generally larger than 2,while the SNR is lower than 1 for Prcptot over most regions under 1.5℃warming.The largest warming is found in northeastern China,with increase of 1.3(0.6–1.7)/2.0(1.4–2.6)℃(ensemble’s median and range of the 10th–90th percentiles)under 1.5/2℃warming,followed by northern and northwestern China.The smallest but the most robust warming is in southwestern China,with values exceeding 0.9(0.6–1.1)/1.5(1.1–1.7)℃.The most robust projection and largest increase is achieved in northwestern China for Prcptot,with increase of 9.1%(–1.6–24.7%)/17.9%(0.5–36.4%)under 1.5/2℃warming.Followed by northern China,where the increase is 6.0%(–2.6–17.8%)/11.8%(2.4–25.1%),respectively.The precipitation projection is of large uncertainty in southwestern China,even with uncertain sign of variation.For the additional half-degree warming,Tav increases more than 0.5℃throughout China.Almost all regions witness an increase of Prcptot,with the largest increase in northwestern China.

An Overview of BCC Climate System Model Development and Application for Climate Change Studies

This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model （BCC_CSM） and its four component models （atmosphere, land surface, ocean, and sea ice）. Two recent versions are described： BCC_CSMI.1 with coarse resolution （approximately 2.8125°× 2.8125°） and BCC_CSMI.I（m） with moderate resolution （approximately 1.125°×1.125°）. Both versions are fully cou- pled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation. Both models well simulate the concentration and temporal evolution of atmospheric CO2 during the 20th century with anthropogenic CO2 emissions prescribed. Simulations using these two versions of the BCC_CSM model have been contributed to the Coupled Model Intercomparison Project phase five （CMIP5） in support of the Intergovernmental Panel on Climate Change （1PCC） Fifth Assessment Report （AR5）. These simulations are available for use by both national and international communities for investigating global climate change and for future climate projections. Simulations of the 20th century climate using BCC-CSMI.1 and BCC_CSMI.I（m） are presented and validated, with particular focus on the spatial pattern and seasonal evolution of precipitation and surface air temperature on global and continental scales. Simulations of climate during the last millennium and projections of climate change during the next century are also presented and discussed. Both BCC_CSMI.1 and BCC_CSMI.I（m） perform well when compared with other CMIP5 models. Preliminary analyses in- dicate that the higher resolution in BCC CSMI.I（m） improves the simulation of mean climate relative to BCC_CSMI.1, particularly on regional scales.

Additional risk in extreme precipitation in China from 1.5℃to 2.0℃global warming levels

To avoid dangerous climate change impact, the Paris Agreement sets out two ambitious goals: to limit the global warming to be well below 2 ℃ and to pursue effort for the global warming to be below 1.5 ℃ above the pre-industrial level. As climate change risks may be region-dependent, changes in magnitude and probability of extreme precipitation over China are investigated under those two global warming levels based on simulations from the Coupled Model Inter-Comparison Projects Phase 5. The focus is on the added changes due to the additional half a degree warming from 1.5 ℃ to 2 ℃ . Results show that regional average changes in the magnitude do not depend on the return periods with a relative increase around 7% and 11% at the 1.5 ℃ and 2 ℃ global warming levels, respectively. The additional half a degree global warming adds an additional increase in the magnitude by nearly 4%. The regional average changes in term of occurrence probabilities show dependence on the return periods, with rarer events(longer return periods) having larger increase of risk. For the 100-year historical event, the probability is projected to increase by a factor of 1.6 and 2.4 at the 1.5 ℃ and 2 ℃ global warming levels, respectively.The projected changes in extreme precipitation are independent of the RCP scenarios.

Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2℃ with Consideration of Model Performance and Independence

A weighting scheme jointly considering model performance and independence(PI-based weighting scheme) is employed to deal with multi-model ensemble prediction of precipitation over China from 17 global climate models. Four precipitation metrics on mean and extremes are used to evaluate the model performance and independence. The PIbased scheme is also compared with a rank-based weighting scheme and the simple arithmetic mean(AM) scheme. It is shown that the PI-based scheme achieves notable improvements in western China, with biases decreasing for all parameters. However, improvements are small and almost insignificant in eastern China. After calibration and validation, the scheme is used for future precipitation projection under the 1.5 and 2℃ global warming targets(above preindustrial level). There is a general tendency to wetness for most regions in China, especially in terms of extreme precipitation. The PI scheme shows larger inhomogeneity in spatial distribution. For the total precipitation PRCPTOT(95 th percentile extreme precipitation R95 P), the land fraction for a change larger than 10%(20%) is 22.8%(53.4%)in PI, while 13.3%(36.8%) in AM, under 2℃ global warming. Most noticeable increase exists in central and east parts of western China.

Risks of temperature extremes over China under 1.5℃ and 2℃ global warming

The Paris Agreement aims to keep global warming to well below 2℃ above pre-industrial levels and to pursue efforts to limit it to 1.5℃,recognizing this will reduce the risks of natural disasters significantly.As changes in the risks of temperature extremes are often associated with changes in the temperature probability distribution,further analysis is still needed to improve understanding of the warm extremes over China.In this study,changes in the occurrence probability of temperature extremes and statistic characteristics of the temperature distribution are investigated using the fifth phase of the Coupled Model Intercomparison Project(CMIP5)multimodel simulations from 1861 to 2100.The risks of the once-in-100-year TXx and TNx events are projected to increase by 14.4 and 31.4 times at 1.5℃ warming.Even,the corresponding risks under 2℃ global warming are 23.3 and 50.6,implying that the once-in-100-year TXx and TNx events are expected to occur about every 5 and 2 years over China,respectively.The Tibetan Plateau,Northwest China and south of the Yangtze River are in greater risks suffering hot extremes(both day and night extremes).Changes in the occurrence probability of warm extremes are generally well explained by the combination of the shifts in location and scale parameters in areas with grown variability,i.e.,the Tibetan Plateau for TXx,south of the Yangtze River for both TXx and TNx.The location(scale)parameter leading the risks of once-in-20-year TXx to increase by more than 5(0.25)and 3(0.75)times under 2℃ warming in the Tibetan Plateau and south of the Yangtze River,respectively.The location parameter is more important for regions with decreased variability e.g.,the Tibetan Plateau for TNx,Northwest China for both TXx and TNx,with risks increase by more than 3,6 and 4 times due to changes in location.