Modulation of El Niño Southern Oscillation and its impacts by the mean climate state

厄尔尼诺/南方涛动（ENSO）是热带地区年际气候变化的主要模式，影响着地球仪的区域气候。在厄尔尼诺/南方涛动事件期间，受海面温度扰动影响的大气环流和降水模式发生变化，导致远距离气候效应，这种效应因区域和季节而异。年际气候变率的内部模态，如太平洋十年涛动（PDO）和大西洋多年十年变率（AMV），沿着人为源的辐射强迫（如：温室气体排放和气溶胶浓度）在年际和年代际时间尺度上改变全球气候环流，因此必须包括在未来气候条件下ENSO影响的研究中。一个很大程度上未探索的研究领域是ENSO事件对气候极端事件的影响是否会在未来更温暖的气候中发生变化。气候变化可能会影响气候极端事件的频率，增加方差，并影响平均值，改变未来某个变量的分布形状（Lavell等人，2012年）。在较温暖的气候中，大气湿度的增加可能会加剧与ENSO相关的降水变化（Christensen等人，2013年）。然而，一般很少有人试图审查厄尔尼诺/南方涛动对极端变化的具体影响。气候模式相互比较模式第6阶段（CMIP 6）中包含的最新气候模式模拟将意味着ENSO代表性的重大改进（柯林斯等人，2014）。该项目的一个特别重点将是评价北大西洋平均状态对厄尔尼诺/南方涛动的影响及其气候影响。这将通过对比模拟之间的ENSO影响来解决，其中北大西洋SST将受到温暖或寒冷条件的约束。最近的文献表明，大西洋的年代际变化（AMV）可以改变热带太平洋的平均状态（McGregor等人，2014，Li等人，2016年，Ruprich-Robert等人，2017年）。然而，太平洋平均状态的这些变化如何转化为ENSO行为的变化仍然不清楚（例如Wang等人，2017年）。此外，最近的研究表明，即使不改变ENSO本身，AMV也可以影响ENSO遥相关（Lopez-Parages et al.，2015年）。更好地了解AMV对ENSO及其遥相关的影响将提高极端影响评估和季节预报的可信度。从不同的模式分辨率研究ENSO及其影响。特别是，对比这些在低和高分辨率的模拟，包括那些在高分辨率模型相互比较项目（HighResMIP）和其他非常高的分辨率模拟BSC进行。这种方法在高分辨率运行方面具有很大的优势，可以评估小规模的气候影响。通过比较模拟的ENSO影响与世纪末的模拟，评估不同平均状态对ENSO及其影响（包括降水和温度极值）的影响.利用CMIP 6.4的十年期气候预测项目C部分实验，评估厄尔尼诺/南方涛动对不同北大西洋背景条件的影响。从阶跃变化扰动实验中确定ENSO和不同人为强迫水平之间的关系。确定最易受未来厄尔尼诺/南方涛动事件影响的区域，并对极端事件的影响进行评估。

The El Niño Southern Oscillation (ENSO) is the leading mode of interannual climate variability in the tropics and affects regional climates around the globe. During ENSO events, changes to atmospheric circulation and precipitation patterns in response to perturbed sea surface temperature lead to remote climate effects that vary regionally and by season. Internal modes of interannual climate variability such as the Pacific Decadal Oscillation (PDO) and the Atlantic multidecadal variability (AMV), along with anthropogenic sources of radiative forcing (eg. greenhouse gases emission and aerosol concentration) alter the global climate circulation on interannual and decadal timescales and therefore must be included in the study of ENSO impacts under future climate conditions.A largely unexplored research area is whether the effects of ENSO events on climate extremes may change in a future, warmer climate. Climate change may affect both the frequency of climate extremes, increasing the variance, and the mean, changing the shape of the distribution of a certain variable in the future (Lavell et al., 2012). In a warmer climate, the increase in atmospheric moisture may intensify the variability in precipitation associated with ENSO (Christensen et al., 2013). However, generally few attempts have been made to examine the specific contribution of ENSO to changing extremes. The latest climate model simulations encompassed in the Climate Model Intercomparison Model Phase 6 (CMIP6) will mean significant improvements in the representation of ENSO (Collins et al., 2014). A especial focus of the project will be on evaluating the influence of the North Atlantic mean state on ENSO and its climate impacts. This will be addressed by contrasting ENSO impacts between simulations in which the North Atlantic SST will be constraint to warm or cold conditions. Recent literature suggests that Atlantic multidecadal variability (AMV) can modify the tropical Pacific mean state (McGregor et al., 2014, Li et al., 2016, Ruprich-Robert et al., 2017). However, it is still not clear how those changes in the Pacific mean state translate into changes of ENSO behaviours (e.g. Wang et al., 2017). In addition, recent studies suggested that the AMV can also influence ENSO teleconnections even without changing ENSO itself (Lopez-Parages et al., 2015). A better understanding of the AMV influences on ENSO and its teleconnections will increase the level of confidence of extreme impacts assessments and seasonal forecasts.The specific objectives of the project are: 1. Investigate ENSO and its impacts from different model resolutions. In particular, contrasting these in low and high resolution simulations, including those performed within the High Resolution Model Intercomparison project (HighResMIP) and other very high resolution simulations performed by BSC. This approach represents a great advantage in terms of high-resolution runs that will allow to assess small-scale climate impacts.2. Evaluate the influence of different mean states on ENSO and its impacts (including precipitation and temperature extremes) by comparing simulated ENSO impacts from present day with end of 21th century simulations.3. Assess ENSO impacts with different North Atlantic background conditions using the Decadal Climate Prediction Project (DCPP) Component C experiments of CMIP6.4. Determine relationships between ENSO and different anthropogenic forcing levels from step change perturbation experiments.5. Determine the most vulnerable regions to future ENSO events and make an impact assessment of extremes.