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Long‐standing simulation errors limit the utility of climate models. Overlooked are tropical‐wide errors, with sea surface temperature (SST) biasing high or low across all the tropical ocean basins. Our analysis based on Coupled Model Intercomparison Project (CMIP) multi‐model ensembles shows that such SST biases can be classified into two types: one with a broad meridional structure and of the same sign across all basins that is highly correlated with the tropical mean; and one with large inter‐model variability in the cold tongues of the equatorial Pacific and Atlantic. The first type can be traced back to biases in atmospheric simulations of cloud cover, with cloudy models biasing low in tropical‐wide SST. The second type originates from the diversity among models in representing the thermocline depth; models with a deep thermocline feature a warm cold tongue on the equator. Implications for inter‐model variability in precipitation climatology and SST threshold for convection are discussed. Key Points Our analysis suggests two types of tropical‐wide SST biases in climate models The first type originates from biases in atmospheric simulations of cloud cover The second type is linked to oceanic representation of the thermocline depth

Changes to the El Niño/Southern Oscillation (ENSO) and its atmospheric teleconnections under climate change are investigated using simulations conducted for the Coupled Model Intercomparison Project (CMIP5). The overall response to CO2increases is determined using 27 models, and the ENSO amplitude change based on the multi‐model mean is indistinguishable from zero. However, changes between ensembles run with a given model are sometimes significant: for four of the eleven models having ensemble sizes larger than three, the 21st century change to ENSO amplitude is statistically significant. In these four models, changes to SST and wind stress do not differ substantially from those in the models with no ENSO response, indicating that mean changes are not predictive of the ENSO sensitivity to climate change. Also, ocean vertical stratification is less (more) sensitive to CO2in models where ENSO strengthens (weakens), likely due to a regulation of the subsurface temperature structure by ENSO‐related poleward heat transport. Atmospheric teleconnections also show differences between models where ENSO amplitude does and does not respond to climate change; in the former case El Niño/La Niña‐related sea level pressure anomalies strengthen with CO2, and in the latter they weaken and shift polewards and eastwards. These results illustrate the need for large ensembles to isolate significant ENSO climate change responses, and for future work on diagnosing the dynamical causes of inter‐model teleconnection differences. Key Points ENSO amplitude is insignificant in the majority of IPCC‐class models ENSO amplitude change is not due to mean state or seasonal cycle changes The teleconnection response is sensitive to the ENSO amplitude change

The new emerging type of El Niño brings challenges to the state-of-the-art coupled models to simulated features of El Niño - Southern Oscillation (ENSO) diversity. The Coupled Model Intercomparison Project (CMIP), containing the advanced worldwide coupled models, has recently released the model outputs in phase 6. In this paper, the characteristics of two types of ENSO in 19 models from CMIP phase 5 and their counterparts in phase 6 are assessed regarding the spatial and temporal features and the seasonal cycle features. The weaker amplitude of Eastern Pacific (EP) and Central Pacific (CP) ENSO in CMIP5 is increased and the spatial structure of CP ENSO is better depicted in CMIP6. However, no significant improvement in the ENSO periodicity and the ENSO phase-locking behavior compared to CMIP5. A synthetic ENSO score, containing eight metrics, is defined and employed to evaluate the performance of each CMIP model. The average ENSO score for CMIP6 is 2.375, indicating modest improvement compared to the average score of 2.441 for CMIP5. Furthermore, the slight improvement in the ENSO score is partly related to the reduced climatology bias of sea surface temperature in the Niño4 region. The overall evaluation provides necessary information for future investigation about the mechanism exploration of the ENSO diversity based on the models with better performance.

Purpose of Review This review brings together recent research on the structure, characteristics, dynamics, and impacts of extratropical cyclones in the future. It draws on research using idealized models and complex climate simulations, to evaluate what is known and unknown about these future changes. Recent Findings There are interacting processes that contribute to the uncertainties in future extratropical cyclone changes, e.g., changes in the horizontal and vertical structure of the atmosphere and increasing moisture content due to rising temperatures. Summary While precipitation intensity will most likely increase, along with associated increased latent heating, it is unclear to what extent and for which particular climate conditions this will feedback to increase the intensity of the cyclones. Future research could focus on bridging the gap between idealized models and complex climate models, as well as better understanding of the regional impacts of future changes in extratropical cyclones.

In this study, we apply the moist static energy for first baroclinic mode (MSEB) model to examine the drivers of the mean tropical atmospheric circulation biases over oceanic regions. The model diagnoses the vertical motion in an air column of the tropical regions based on net energy heat flux and advection of moisture or heat into the air column in relation to the stability of the air column due to the gradients in moist static energy. Analysis of Coupled Model Intercomparison Project (CMIP) and Atmospheric Model Intercomparison Project (AMIP) simulations helped to identified errors intrinsic to the atmospheric models or errors due to atmosphere–ocean coupling process. Despite some limitations of the MSEB model, our multi-model mean analysis over the entire tropical ocean reveals that the primary drivers of the tropical circulation biases mostly result from intrinsic atmospheric model errors in top of the atmosphere longwave radiation and surface latent heats fluxes, suggesting a link to biases in the hydrological cycle. Oceanic coupling significantly enhanced some of the biases. Biases in the advection of moist static energy also play an important role, while biases in the gross moist stability profiles play only a minor role. Further, we examine the inter-model variations in four main regional large-scale biases (double-ITCZ, Pacific cold tongue, southward shift of ITCZ over the Atlantic, and dipole bias over the Indian Ocean). The analysis suggests that regional bias patterns across general circulation models are primarily driven by coupling errors, except for the bias in the Indian Ocean, which is intrinsic to the atmospheric model but amplified by coupling. Notably, longwave radiation biases at the top of the atmosphere are prevalent among the four bias patterns, as well as biases in moisture advection over the Atlantic. Our results underscore the significant role of net longwave radiation at the top of the atmosphere, an aspect not sufficiently emphasized in previous studies.

The north and central coast of Chile is influenced by El Niño-Southern Oscillation (ENSO) through oceanic and atmospheric teleconnections. However, it also experiences episodic oceanic warmings off central Chile (30°S) lasting a few months that are not necessarily associated with ENSO. These episodes, called “Chile Niño” events, besides their ecological and socio-economical impacts, have also the potential to influence tropical Pacific variability. Here, we investigate how realistically the models in the Coupled Model Intercomparison Project (CMIP, Phases 5 and 6) simulate Chile Niño/Niña (CN) events, and quantify their changes under anthropogenic forcing. Despite limitations of the global models in simulating realistically coastal upwelling dynamics, we show that they simulate reasonably well the observed spatial pattern, amplitude and seasonal evolution of CN events. They however fail to properly represent the positive skewness from observations. The analysis of a sub-group of models (36) that simulate ENSO realistically reveals that CN events increase in amplitude and variance in the future climate with no changes in their frequency of occurence. This is interpreted as resulting from compensating effects amongst changes in remote drivers and local feedbacks. In particular, ENSO variance increases while that of the South Pacific Oscillation decreases. Conversely, we found that while the Wind-Evaporation-SST feedback tends to increase and the coupling between mixed-layer depth and SST weakens, favoring the development of CN events, the thermocline and wind-SST feedbacks decrease. However, only the change in the thermocline feedback is correlated to changes in CN variance amongst the models, suggesting a dominant role of local oceanic stratification changes in constraining the sensitivity of CN to global warming.

Low-frequency variability of the Pacific Subtropical Cells (STCs) is investigated using outputs from several models included in the two latest phases of Coupled Model Intercomparison Project (CMIP), CMIP5 and CMIP6, as well as ocean reanalysis products. Our analysis focuses on historical simulations and an idealised future scenario integration. Mass and heat transport diagnostics are employed to assess how coupled models and ocean reanalyses reproduce Pacific STCs total and interior transport convergence at the equator and their relationship with equatorial Pacific sea surface temperature (SST). Trends of mass and heat transport are also evaluated, in order to study how the STCs are expected to change in a warming climate. A large spread is obtained across models in simulated mass transports, confirming that coupled models do not agree on reproducing observed Pacific STCs dynamics, with very limited improvement by CMIP6 models. Compared to ocean reanalysis products, coupled models tend to underestimate the STCs interior transport convergence, and are less efficient on propagating the signal generated by the subtropical wind stress towards the equator. Also, mass transport obtained from ocean reanalyses exhibit larger variability, and these products also better reproduce the STCs-SST relationship. Future scenario simulations suggest a weakening (strengthening) of the heat transport by the North (South) Pacific cell under warmer conditions, with a general agreement across models. Equatorward mass transport trends do not confirm this for total and interior components, but they do for the western boundary component.

We provide a methodology to estimate possible extreme changes in seasonal rainfall for the coming decades. We demonstrate this methodology using Indian summer monsoon rainfall as an example. We use an ensemble of 1669 realizations of Indian summer monsoon rainfall from selected seasonal prediction systems to estimate internal variability and show how it can exacerbate or alleviate forced climate change. Our estimates show that for the next decade there is a ∼60% chance of wetting trends, whereas the chance of drying is ∼40%. Wetting trends are systematically more favoured than drying with the increasing length of the period. However, internal variability can easily negate or overwhelm the wetting trends to give temporary drying trends in rainfall. This provides a quantitative explanation for the varying trends in the past observational record of rainfall over India. We also quantify the likelihood of extreme trends and show that there is at least a 1% chance that monsoon rainfall could increase or decrease by one fifth over the next decade and that more extreme trends, though unlikely, are possible. We find that monsoon rainfall trends are influenced by trends in sea-surface temperatures over the Niño3.4 region and tropical Indian Ocean, and ∼1.5° cooling or warming of these regions can approximately double or negate the influence of climate change on rainfall over the next two decades. We also investigate the time-of-emergence of climate change signals in rainfall trends and find that it is unlikely for a climate change signal to emerge by the year 2050 due to the large internal variability of monsoon rainfall. The estimates of extreme rainfall change provided here could be useful for governments to prepare for worst-case scenarios and therefore aid disaster preparedness and decision-making.

In this study, the El Nino-Southern Oscillation (ENSO) phase-locking to the boreal winter in CMIP3 and CMIP5 models is examined. It is found that the models that are poor at simulating the winter ENSO peak tend to simulate colder seasonal-mean sea-surface temperature (SST) during the boreal summer and associated shallower thermocline depth over the eastern Pacific. These models tend to amplify zonal advection and thermocline depth feedback during boreal summer. In addition, the colder eastern Pacific SST in the model can reduce the summertime mean local convective activity, which tends to weaken the atmospheric response to the ENSO SST forcing. It is also revealed that these models have more serious climatological biases over the tropical Pacific, implying that a realistic simulation of the climatological fields may help to simulate winter ENSO peak better. The models that are poor at simulating ENSO peak in winter also show excessive anomalous SST warming over the western Pacific during boreal winter of the El Nino events, which leads to strong local convective anomalies. This prevents the southward shift of El Nino-related westerly during boreal winter season. Therefore, equatorial westerly is prevailed over the western Pacific to further development of ENSO-related SST during boreal winter. This bias in the SST anomaly is partly due to the climatological dry biases over the central Pacific, which confines ENSO-related precipitation and westerly responses over the western Pacific.

The phase-locking behavior of El Niño-Southern Oscillation (ENSO) in models from Coupled Model Intercomparison Project (CMIP) phase 5 to phase 6 is assessed in terms of the locking-month of ENSO peak and the sharpness of locking tendency. Overall, a robust improvement exists in CMIP6. Compared to CMIP5, more CMIP6 models truly reproduce the locking-month in November-January. Meanwhile, the sharpness of phase-locking in CMIP6 models also improves, though most of them are still far from the observations. The locking-month is verified to be highly corresponding to the phase of seasonal modulation of ENSO’s instabilities. The sharpness is mainly controlled by the intensity of this modulation and noise. Compared to CMIP5, CMIP6 models generally simulate these affecting factors better. Besides, models displaying an exaggerated semi-annual variation of ENSO’s instabilities simulate the ENSO phase-locking relative-poorly, and these models show no reduction from CMIP5 to CMIP6.