The response of East Asian summer monsoon (EASM) precipitation to global warming and carbon dioxide removal (CDR) depends strongly on the model used. This study systematically analysed the response of EASM precipitation under CDR scenarios and its associated uncertainties using nine models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) participating in the Carbon Dioxide Removal Model Intercomparison Project (CDRMIP). The multi-model ensemble mean (MME) results show that precipitation in the EASM rainband region during the CO2 ramp-down period is approximately 24.8% higher than that during the ramp-up period. This change is primarily attributed to an El Niño-like warming pattern in the tropical Pacific (with a 0.82 °C increase in the Niño3.4 region). Intra-model empirical orthogonal function (EOF) analysis was conducted to further reveal the uncertainties in the EASM precipitation response across models. The first EOF mode explains approximately 30.8% of the variance, and its spatial pattern indicates that the primary variability centre is located in the region where EASM precipitation changes. Regression analysis confirms that this uncertainty is also closely related to the simulated El Niño-like sea surface temperature (SST) anomalies in the tropical Pacific. Notably, although the responses of tropical Pacific precipitation and SST to CO2 forcing exhibit consistent asymmetry across models (i.e. persistent warming and increased precipitation even after CO2 returns to initial concentrations), the EASM precipitation response shows greater intra-model discrepancies, particularly in spatial extent and magnitude. These results highlight the challenges in predicting the changes in East Asian summer precipitation under carbon neutrality scenarios.

Vegetation fires release a large fraction of light-absorbing components, which can contribute to the melting of snowpack and alpine glaciers. However, the relationship between variability in fire emissions and alpine glacier melting on the Third Pole (TP) remains poorly understood. This study provides evidence that carbon emissions from windward vegetation fires play a crucial role in comprehending glacier melting on the TP, particularly during the months of intense vegetation fires from March to May for monsoon-dominated glaciers and from June to October for westerlies-dominated glaciers. Furthermore, robust positive correlations (with p < 0.05) have been observed since 1997 across the TP between variations in glacier melting and fire carbon emissions during both annual periods and those intense fire months. In addition to climate warming, intensified fire carbon emissions could potentially accelerate the melting and mass loss of TP glaciers, especially during those traditionally nonmelting months. An urgent reassessment of the impact of fire carbon emissions on changes in TP glaciers is necessary, given that meltwater during traditionally nonmelting months can reshape freshwater resource supply patterns, and the projected increased wildfire risk in high mountainous regions in a rapidly warming climate.

Wildfire is a crucial factor in influencing the earth system. Wildfire activities in the Arctic-boreal region have received increasing attention particularly with increasing frequency and intensity under rapid climate warming in recent years. In this study, the historical simulation and future projection of the Arctic-boreal fire carbon emissions and associated surface climate conditions (surface air temperature and precipitation) are examined using 17 CMIP6 Earth System Models. For the historical period, more than half (11 out of 17) of the models underestimate similar to 40% of the observed annual mean fire carbon emissions in the Arctic-boreal region (0.20 PgC/yr) due to a wetter bias in the Arctic-boreal regions. Spatially, there is common underestimation of the fire centers in the eastern part of Eurasian Continent and overestimation of that in Europe. With respect to the model spread, it mainly shows large spread for fire carbon emissions (surface air temperature) in Europe (high-latitudes). For the future projection, the fire carbon emissions in the Arctic-boreal region is projected to exceed 100% (0.5 PgC/yr until the end of the 21st century compared with similar to 0.2 PgC/yr at present). The projected precipitation and temperature in the Arctic-boreal region land also show an upward trend during the 21st century (similar to 31% for annual mean precipitation and similar to 10 degrees C for surface air temperature). There are considerable bias and intra-model spread among different models in both historical simulation and future projection.

利用第五次和第六次国际间耦合模式比较计划(CMIP)中piControl情景下的模拟结果,结合观测资料,对比评估了19个CMIP5模式和23个CMIP6模式对太平洋年代际振荡(PDO)调制厄尔尼诺-南方涛动事件爆发频率不对称的模拟能力,并进一步揭示了PDO的调制过程.结果表明:在观测中,PDO正(负)位相下厄尔尼诺(El Ni?o)的爆发频率比拉尼娜(La Ni?a)多300%(少73%),53%(78%)的CMIP5(6)模式模拟出这一特征;尽管两个模式整体都低(高)估了PDO正(负)位相的调制能力,但CMIP6模式对PDO调制能力的模拟有所改进.进一步研究发现,在PDO正(负)位相下,赤道太平洋中西部会产生较强的西(东)风异常,风场通过平流的作用使得暖水向东流动,从而在太平洋中东部的海表面温度背景场中出现正(负)异常变化,而这有利于PDO正(负)位相下El Ni?o(La Ni?a)事件的发生.

In the first half of winter 2020/2021, several unprecedented cold events occurred in most parts of China and caused record-breaking low temperatures in many cities. However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first evaluated the short-term climate prediction skills in winter of the CAS-ESM-c global coupled model and revealed the key dynamic processes of the onset and development of 2020/2021 extreme cold events based on the ensemble forecasts starting on October 1st, 2020. Under the background provided by the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña), the model captured the abnormal meridional atmospheric pattern well, including the intensification of the Ural Blocking High and the negative phase of the Arctic Oscillation, forecasted the negative geopotential height anomalies over the Eastern Asian region, and finally, successfully predicted the outbreak of cold waves in December 2020 two months in advance. Moreover, the dominant differences in the initial ocean fields between the best and the worst forecast members were further compared to isolate the triggering factor for predicting cold events by CAS-ESM-c. The initial warm sea surface temperature over the Barents Sea can gradually form a meridional pattern between the warm Arctic and the cold Asian continent, which could lead to a reduction in the large-scale meridional temperature gradient at mid-high latitudes and weaken the atmospheric baroclinicity with more conducive to the southward outbreak of cold waves, highlighting that realistic Arctic ocean conditions in autumn can be reasonably assimilated into coupled models to stimulate the successful prediction of extreme cold events in the 2020/2021 winter.

基于1979～2022年NCEP/DOE逐月再分析资料和NOAA海面温度资料,通过合成、相关分析等统计方法,以海面温度(Sea Surface Temperature,SST)异常影响为切入点,对比分析了 2022年与La Niña年强迫作用下的我国夏季季节内环流差异,并在此基础上进一步探讨了异常高温与同期热带SST之间存在的可能联系.结果表明:1)2022年夏季,我国中东部高温区具有明显空间变化特征,6月位于华中地区、7月位于西南地区、8月影响整个长江流域.2)西太平洋副热带高压和南亚高压的同时异常加强,以及两者重叠打通并形成少见的北半球副热带高压带,是造成2022年夏季我国中东部异常高温过程的直接原因.3)在持续2年的较强La Niña背景下,2022年东亚夏季环流并未完全表现出对La Niña冷SST的响应,南海及菲律宾以东对流异常偏弱、东亚—太平洋遥相关型不显著均与La Niña年环流典型特征有较大出入.夏季同期热带SST异常对高温过程的形成具有一定贡献,热带西印度洋和热带中太平洋的冷SST异常分别有利于我国长江流域和华中地区出现高温酷暑,其中热带中太平洋冷SST异常可能是西太平洋副热带高压加强的重要原因,而热带西印度洋冷SST对南亚高压的增强有贡献作用.

中国是自然灾害频发的国家,气象灾害造成的损失占自然灾害造成损失的70％.2020年夏季出现超长梅雨期,长江和淮河发生洪水;2021年夏季,华北雨季开始早,结束晚,期间发生了"21·7"河南地区特大暴雨事件.这些气象灾害都对人民生命财产造成严重损失.因此,有必要提前对气候异常进行预测,以提高国家的防灾减灾能力.2022年3月,中国科学院大气物理研究所开展汛期(6～8月)的全国汛期气候趋势预测会商会.通过综合大气所各个数值模式和统计模型的结果,在未来4～6个月全球短期气候仍处在La Ni?a事件恢复到ENSO正常状态的背景下,预计2022年汛期(6～8月),东北东部和中部、华北大部分地区、黄河中下游、东南沿海、西北地区中部、西藏大部分地区、西南地区东部和云南大部分地区降水正常略偏多,其中环渤海湾地区降水偏多2～5成,可能发生局地洪涝灾害.全国其他大部分地区降水正常略偏少,其中长江下游地区和新疆北部降水偏少2～5成.预计今年登陆台风数正常略偏多.由于未来ENSO的趋势演变具有一定的不确定性以及夏季降水受到中高纬大气环流季节内变化的影响,因此,此次汛期预测结果具有一定的不确定性.我们将根据2022年春末、夏初大气环流和海洋等因子的实际演变趋势,做进一步补充订正预测.

In this study, we evaluate the performances of the Institute of Atmospheric Physics atmospheric general circulation model (IAP AGCM version4.1) and atmospheric component of Chinese Academy of Science Earth System Model, version 1 (CAS-ESM1) in the simulation of the cold surge (CS) events in East Asia. In general, the model can capture the main features of anomalous precipitation and circulation associated with the cold surge days. Compared with climatological means of boreal winter, on CS days, the precipitation increases in the southern part of the South China Sea (SCS), while decreases in the subtropical regions near the southern China. In addition, the climatological northeasterly wind over the SCS region strengthens on CS days. In the first day composites of CS events, it shows a dipole pattern in middle latitude over East Asia, with a positive (negative) sea level pressure (SLP) anomaly in the west (east). Based on the anomalous SLP signs in the two centers of the dipole pattern, the CS days can be further classified into two types: positive-west–negative-east-type and positive-west–positive-east-type. All these features can be reasonably reproduced by IAP AGCM4.1. Although in most CS days there is positive SLP anomaly in the East China, some negative events were investigated in this study. In these negative events the northerly anomaly in SCS is associated with an anticyclonic circulation anomaly around the eastern part of the Tibetan Plateau, rather than descending from the mid-to-high latitude cold air outbreaks. The feature can also be captured by the model.

In this study, the Chinese Academy of Sciences’ Earth System Model Version 2 (CAS-ESM2) and its atmospheric component were evaluated for the ability to simulate the East Asian summer monsoon (EASM), in terms of climatology and composites in El Niño decaying years (EN) and La Niña years (LN). The results show that the model can realistically simulate the El Niño Southern Oscillation (ENSO) annual cycle, the interannual variation, the evolution process, and the prerequisites of ENSO, but the trend of developing and decaying is faster than that of the observations. With regard to the climatological mean state in the EASM, the coupled model run can largely improve the precipitation and 850 hPa wind simulated in the atmospheric model. Moreover, the coupled run can also reduce the mid-latitude bias in the atmospheric model simulation. Composite methods were then adopted to examine performance in different phases of the ENSO, from a mature winter to a decaying summer. The atmospheric model can well reproduce the Western North Pacific Anomalous Anticyclone (WNPAC)/Western North Pacific Anomalous Cyclone (WNPC) during EN/LN well, but the westerly/easterly anomalies and the associated precipitation anomalies over the equatorial Central Eastern Pacific are somewhat overestimated. Compared with the atmospheric model, these anomalies are all underestimated in the coupled model, which may be related to the ENSO-related SST bias appearing in the Eastern Indian Ocean. Due to the ENSO and ITCZ bias in the historical simulations, the simulated ENSO-related SST and the precipitation anomaly are too equator-trapped in comparison with the observations, and the cold tongue overly extends westward. This limits the ability of the model to simulate ENSO-related EASM variability. For the subseasonal simulations, though atmospheric model simulations can reproduce the westward extension of the Western Pacific subtropic high (WPSH) in EN decaying summers, the eastward retreat of the WPSH in LN is weak. The historical simulations show limited improvement, indicating that the subseasonal variation in the EASM is still a considerable challenge for current generation models.

The Northern Hemisphere (NH) often experiences frequent cold air outbreaks and heavy snowfalls during La Niña winters. In 2022, a third-year La Niña 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 Niña. 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.

In this study, the simulations of the subseasonal evolution of the East Asian summer monsoon（EASM） by BCC-CSM2-MR and BCC-ESM1 models, two models from the Beijing Climate Center participating in the 6th phase of the Coupled Model Intercomparison Project（CMIP6）, are analyzed, including the characteristics of the climatological mean state and features in different ENSO phases. This study compares the results of the atmospheric general circulation model（AGCM） experiments, in which the AGCM is driven by observed sea ice/sea surface temperature（AMIP experiment）, with the results of the Historical experiment using the air-sea coupled model. Results show that both models can reasonably reproduce the climate mean state features of the circulation and precipitation associated with the EASM.Compared to the AGCM, the coupled model can significantly improve the simulation of the climate mean state of EASM.For instance, the coupled model simulates the subseasonal variation of the western Pacific subtropical high（WPSH） with northward and eastward shifts from June to August better. With respect to the composites for El Ni?o decaying years and La Ni?a years, the atmospheric model can simulate the westward extension（eastward retreat） of WPSH and the associated weakening（strengthening） of convection in El Ni?o decaying years（La Ni?a years） to some extent. However, there are deviations in the simulation of the location and intensity of WPSH and convection centers, particularly on a subseasonal scale. Compared to the AGCM, the coupled model does not appear to significantly improve the simulation of the subseasonal evolution of the EASM with the ENSO cycle, which may be caused by the deviation of the ENSO simulation in the coupled model. To improve the simulation of the subseasonal evolution of the EASM and its interannual variation with the ENSO phase, the simulation of ENSO in the coupled model should be enhanced.

In this study, based on an ocean data assimilation system for the coupled climate model CAS-ESM-C, how to reasonably assimilate altimetry data are explored. In sea surface height (SSH) assimilations, the mean dynamic topography (MDT) is an important factor that can coordinate the observed sea level anomalies with the modeled SSH. The SSH assimilation results are first compared through assimilation experiments using three different MDTs, including the observed reference height, the MDT from model control run, and the MDT from the assimilation experiment in CAS-ESM-C, with the climatological World Ocean Atlas (WOA) temperature assimilated into the coupled model. The results show that the third one can significantly improve the ability of the ocean data assimilation system to assimilate the SSH observations. Using this MDT, the SSH assimilation scheme of the ocean data assimilation system was established for the CAS-ESM-C, and a long-term SSH assimilation experiment from 1994 to 2017 was carried out. The results show that the SSH assimilation performs much better than the SST assimilation in reproducing the ocean states and seasonal-interannual variability. The improvements of SSH assimilation compared with SST assimilation may be due to the different properties of the two ocean variables. While SST is a thermodynamic variable used to evaluate the thermal condition of the ocean surface layer, SSH is a dynamic variable linked to the dynamical information of the whole ocean layer. Thus, SSH assimilation can constrain the ocean model with observed dynamic information, which is more important to the state estimation and temporal evolution of the ocean.

Currently, several ocean data assimilation methods have been adopted to increase the performance of air–sea coupled models, but inconsistent adjustments between the sea temperature with other oceanic fields can be introduced. In the coupled model CAS-ESM-C, inconsistent adjustments for ocean currents commonly occur in the tropical western Pacific and the eastern Indian Ocean. To overcome this problem, a new ensemble-based bias correction approach—a simple modification of the Ensemble Optimal Interpolation (EnOI) approach for multi-variable into a direct approach for a single variable—is proposed to minimize the model biases. Compared with the EnOI approach, this new approach can effectively avoid inconsistent adjustments. Meanwhile, the comparisons suggest that inconsistent adjustment mainly results from the unreasonable correlations between temperature and ocean current in the background matrix. In addition, the ocean current can be directly corrected in the EnOI approach, which can additionally generate biases for the upper ocean. These induced ocean biases can produce unreasonable ocean heat sinking and heat storage in the tropical western Pacific. It will generate incorrect ocean heat transmission toward the east, further amplifying the inconsistency introduced through the tropical air–sea interaction process.

In this study, the climatological precipitation increase from July to August over the western North Pacific (WNP) region was investigated through observations and simulations in the Coupled Model Intercomparison Project Phase 6 (CMIP6), atmospheric model simulations and historical experiments. Firstly, observational analysis showed that the precipitation increase is associated with a decrease in the local sea surface temperature (SST), indicating that the precipitation increase is not driven by the change in SST. In addition, the pattern of precipitation increase is similar to the vertical motion change at 500-hPa, suggesting that the precipitation increase is related to the circulation change. Moisture budget analysis further confirmed this relation. In addition to the observational analysis, the outputs from 26 CMIP6 models were further evaluated. Compared with atmospheric model simulations, air–sea coupled models largely improve the simulation of the climatological precipitation increase from July to August. Furthermore, model simulations confirmed that the bias in the precipitation increase is intimately associated with the circulation change bias. Thus, two factors are responsible for the bias of the precipitation increase from July to August in climate models: air–sea coupling processes and the performance in vertical motion change.

The possible influence of the Atlantic multidecadal oscillation (AMO) and the Pacific decadal oscillation (PDO) on the meteorological conditions associated with haze over central eastern China at decadal time scale was investigated using reanalysis and observational dataset for 1979–2018. Four indices, including Siberian high (SH) strength and position indices (SHI/SHPI), a normalized near-surface wind-speed index (WSI) and a potential air temperature gradient index (ATGI), are adopted to denote the meteorological conditions associated with haze. Results shown that the AMO and PDO are both highly correlated with the fluctuation of meteorological factors associated with haze on decadal scale. Although AMO and PDO were in opposite phases during the whole period, since 1997, they both changed phases (AMO shifted to a positive phase and PDO changed to negative) and became favorable for an anomalous dipole-type SLP pattern in the middle-high latitudes of East Asia. The AMO has played a leading role in decadal variation of the large-scale circulation system, while the PDO has had a closer relationship with the lower ventilation condition in eastern China. On the decadal time scale, the AMO stimulates a zonal teleconnection wave train (the AMO northern Hemisphere pattern, ANH) that originates from the North Atlantic Ocean and passes through central Europe, the northern Ural Mountains, Lake Balkhash-Baikal, and central eastern China. During the positive phase of AMO, the ANH induces a stronger and westward shifted SH, with the central eastern China controlled by the anomalous high pressure. In addition, affected by the cyclone (anticyclone) anomaly over Hetao region and North China (the Sea of Japan), southerly wind anomalies dominate over central eastern China. Compared with the AMO, the wave train generated by the negative (positive) PDO phase mainly propagates in the Pacific region, and there is a strong anticyclonic (cyclonic) anomaly over the Northeast Pacific, guiding the air flow southward (northward) along the East Asian coast and thus suppressing (encouraging) the dispersion of pollutants and resulting in above (below)-normal haze episodes.

Over the past several decades, many efforts have been devoted to increasing the simulation performance of climate models, but significant biases remain that hinder the performance of coupled systems. Hence, bias correction is regarded not only as a useful tool for improving climate simulations but also as an important step before data assimilation, which depends on the hypothesis of unbiasedness. In this study, using sea temperature climatological data, a new ensemble-based approach is proposed for correcting the biases of the sea temperature in CAS-ESM-C. Through analyzing the results of the proposed bias correction method with various intensities and time windows, its performance in suppressing the simulation biases of ocean fields is evaluated. The simulation biases of atmospheric variables are also reduced via air-sea interactions, which will improve the ocean simulation performance. Additional benefits can be realized by applying the bias correction method. For example, a superior simulation of climate variabilities in a coupled model, such as ENSO (El Nino-Southern Oscillation), is realized due to the improvement of climatological fields. The ability to assimilate various ocean observations is also significantly improved with a better background mean state.

Based on observational and reanalysis data, the relationships between the eastern Pacific (EP) and central Pacific (CP) types of El Niño-Southern Oscillation (ENSO) during the developing summer and the South Asian summer monsoon (SASM) are examined. The roles of these two types of ENSO on the SASM experienced notable multidecadal modulation in the late 1970s. While the inverse relationship between the EP type of ENSO and the SASM has weakened dramatically, the CP type of ENSO plays a far more prominent role in producing anomalous Indian monsoon rainfall after the late 1970s. The drought-producing El Niño warming of both the EP and CP types can excite anomalous rising motion of the Walker circulation concentrated in the equatorial central Pacific around 160°W to the date line. Accordingly, compensatory subsidence anomalies are evident from the Maritime Continent to the Indian subcontinent, leading to suppressed convection and decreased precipitation over these regions. Moreover, anomalously less moisture flux into South Asia associated with developing EP El Niño and significant northwesterly anomalies dominating over southern India accompanied by developing CP El Niño, may also have been responsible for the Indian monsoon droughts during the pre-1979 and post-1979 sub-periods, respectively. El Niño events with the same "flavor" may not necessarily produce consistent Indian monsoon rainfall anomalies, while similar Indian monsoon droughts may be induced by different types of El Niño, implying high sensitivity of monsoonal precipitation to the detailed configuration of ENSO forcing imposed on the tropical Pacific.

为有效改进中国科学院地球系统模式气候分量系统(CAS-ESM-C)对年际海洋变化信号的模拟,利用集合最优插值同化方法(ensemble optimal interpolation,EnOI)将海表高度(sea surface height,SSH)数据同化入CAS-ESM-C.通过对比3种不同来源的平均动力地形(mean dynamic topography,MDT)数据对SSH同化性能的影响,筛选出针对CAS-ESM-C海洋资料同化最优的MDT.在此基础上,实施了1994-2000年的SSH观测同化试验,检验其对CAS-ESM-C海洋状态模拟的改进效果.结果 表明,正是由于海洋上层(温跃层以内)的温度变化与SSH有着较强的动力相关性,同化SSH观测可以显著地改进CAS-ESM-C对海洋上层温度变化、海气耦合循环和物理过程的模拟.0 ～400 m全球平均的均方根误差能控制在1.0℃以内;温跃层深度附近的改进效果最为显著;热带太平洋上层海洋热含量的年际变化以及赤道太平洋地区海温年际异常演变明显优于仅同化海表温度(sea surface temperature,SST)的改进效果.由此可以得到,同化SSH改进了CAS-ESM-C对海洋上层年际变率的模拟,为下一步利用CAS-ESM-C开展短期气候预测奠定了基础.

2019年春夏季,赤道中东太平洋将维持弱-中等强度厄尔尼诺(El Ni?o).中国科学院大气物理研究所的全国气候趋势预测结果表明,预计2019年汛期(6—8月),长江中下游以南大部分地区降水偏多,其中江南地区偏多2—5成,可能发生局地洪涝灾害;新疆北部、东北北部、四川东部和陕西南部等地降水正常略偏多.我国其他大部分地区降水正常略偏少,其中河套地区降水偏少2—5成.预计2019年登陆台风数正常略偏多.