Search

Exchanges of mass, momentum and energy between the ocean and atmosphere are of large importance in regulating the climate system. Here, we apply for the first time a relatively novel approach, the rate of information transfer, to quantify interactions between the ocean surface and the lower atmosphere over the period 1988–2017 at a monthly timescale. More specifically, we investigate dynamical dependencies between sea surface temperature (SST), SST tendency and turbulent heat flux in satellite observations. We find a strong two-way influence between SST and/or SST tendency and turbulent heat flux in many regions of the world, with the largest values in the eastern tropical Pacific and Atlantic oceans, as well as in western boundary currents. The total number of regions with a significant influence by turbulent heat flux on SST and on SST tendency is reduced when considering the three variables (this case should be privileged, as it provides additional sources of information), while it remains large for the information transfer from SST and SST tendency to turbulent heat flux, suggesting an overall stronger ocean influence compared to the atmosphere. We also find a relatively strong influence by turbulent heat flux taken 1 month before on SST. Additionally, an increase in the magnitude of the rate of information transfer and in the number of regions with significant influence is observed when looking at interannual and decadal timescales compared to monthly timescales.

Modelling rainfall extremes and dry periods over the Southeast Asia (SEA) region is challenging due to the characteristics of the region, which consists of the Maritime Continent and a mountainous region; it also experiences monsoonal conditions, as it is located between the Asian summer monsoon and the Australian summer monsoon. Representing rainfall extremes is important for flood and drought assessments in the region. This paper evaluates extreme rainfall climatic indices from regional climate models from CORDEX Southeast Asia and compares them with the results of high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. Observations indicate a high intensity of rainfall over areas affected by tropical cyclones and long consecutive dry day periods over some areas in Indochina and the southern end of Indonesia. In the model simulations, we find that both coupled and sea surface temperature-forced HighResMIP model experiments are more similar to the observations than CORDEX model results. However, the models produce a poorer simulation of precipitation intensity-related indices due to model biases in the rainfall intensity. This bias is higher in CORDEX than in HighResMIP and is evident in both the low- and high-resolution HighResMIP model versions. The comparable performances of HighResSST (atmosphere-only runs) and Hist-1950 (coupled ocean–atmosphere runs) demonstrate the accuracy of the ocean model. Comparable performances were also found for the two different resolutions of HighResMIP, suggesting that there is no improvement in the performance of the high-resolution HighResMIP model compared to the low-resolution HighResMIP model. © 2022 The Authors. International Journal of Climatology published by John Wiley Sons Ltd on behalf of Royal Meteorological Society.

The recent advancements in climate modeling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC-CM2) model used here adopt the highest horizontal resolutions available within the last family of the global coupled climate models developed at CMCC to participate in the Coupled Model Intercomparison Projects, Phase 6 (CMIP6) effort. The main aim of this study is to document the ability of the CMCC-CM2 models to represent the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), multi-source weighted-ensemble precipitation (MSWEP) and Climate Hazards Group infrared precipitation with station data (CHIRPS) observations. For a more detailed evaluation we use both 6-hourly and daily time series, to compute indices representative of intense and extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The high resolution version (1/4∘ horizontal resolution) of the atmospheric model provides better results than the standard resolution one (1°), not only in terms of means but also in terms of intense and extreme events of temperature defined at daily and 6-hourly frequencies. This is also the case of average and intense precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

Starting to resolve the oceanic mesoscale in climate models is a step change in model fidelity. This study examines how certain obstinate biases in the midlatitude North Atlantic respond to increasing resolution (from 1° to 0.25° in the ocean) and how such biases in sea surface temperature (SST) affect the atmosphere. Using a multimodel ensemble of historical climate simulations run at different horizontal resolutions, it is shown that a severe cold SST bias in the central North Atlantic, common to many ocean models, is significantly reduced with increasing resolution. The associated bias in the time-mean meridional SST gradient is shown to relate to a positive bias in low-level baroclinicity, while the cold SST bias causes biases also in static stability and diabatic heating in the interior of the atmosphere. The changes in baroclinicity and diabatic heating brought by increasing resolution lead to improvements in European blocking and eddy-driven jet variability. Across the multimodel ensemble a clear relationship is found between the climatological meridional SST gradients in the broader Gulf Stream Extension area and two aspects of the atmospheric circulation: the frequency of high-latitude blocking and the southern-jet regime. This relationship is thought to reflect the two-way interaction (with a positive feedback) between the respective oceanic and atmospheric anomalies. These North Atlantic SST anomalies are shown to be important in forcing significant responses in the midlatitude atmospheric circulation, including jet variability and the storm track. Further increases in oceanic and atmospheric resolution are expected to lead to additional improvements in the representation of Euro-Atlantic climate.

Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of near-term climate change and are a useful tool to inform decision-makers on future climate-related risks. Here we present results from the CMIP6 (Coupled Model Intercomparison Project Phase 6) Decadal Climate Prediction Project (DCPP) decadal hindcasts produced with the operational CMCC (Euro-Mediterranean Center on Climate Change) decadal prediction system (DPS), based on the fully coupled CMCC-CM2-SR5 dynamical model. A 20-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2020, is performed using a full-field initialization strategy. The predictive skill for key variables is assessed and compared with the skill of an ensemble of non-initialized historical simulations so as to quantify the added value of the initialization. In particular, the CMCC DPS is able to skillfully reproduce past climate surface and subsurface temperature fluctuations over large parts of the globe. The North Atlantic Ocean is the region that benefits the most from initialization, with the largest skill enhancement occurring over the subpolar region compared to historical simulations. On the other hand, the predictive skill over the Pacific Ocean rapidly decays with forecast time, especially over the North Pacific. In terms of precipitation, the skill of the CMCC DPS is significantly higher than that of the historical simulations over a few specific regions, including the Sahel, northern Eurasia, and over western and central Europe. The Atlantic multidecadal variability is also skillfully predicted, and this likely contributes to the skill found over remote areas through downstream influence, circulation changes, and teleconnections. Considering the relatively small ensemble size, a remarkable prediction skill is also found for the North Atlantic Oscillation, with maximum correlations obtained in the 1–9 lead year range. Systematic errors also affect the forecast quality of the CMCC DPS, featuring a prominent cold bias over the Northern Hemisphere, which is not found in the historical runs, suggesting that, in some areas, the adopted full-field initialization strategy likely perturbs the equilibrium state of the model climate quite significantly. The encouraging results obtained in this study indicate that climate variability over land can be predictable over a multiyear range, and they demonstrate that the CMCC DPS is a valuable addition to the current generation of DPSs. This stresses the need to further explore the potential of the near-term predictions, further improving future decadal systems and initialization methods, with the aim to provide a reliable tool to inform decision-makers on how regional climate will evolve in the next decade.

The connection between the Atlantic meridional overturning circulation (AMOC) and the Atlantic multidecadal variability (AMV) is inspected in a suite of pre-industrial integrations from the 6th phase of the Coupled Model Inter-comparison Project (CMIP6), using a change-point detection method to identify different AMOC-AMV co-variability regimes. A key finding of this study is that models robustly simulate multi-decadal windows where the AMV and the AMOC are essentially uncorrelated. These regimes coexist with longer periods with relatively high correlation. Drops and recoveries of correlation are found to be often abrupt and confined in a temporal window of the order of 10 years. Phenomenological evidence suggests that the no-correlation regimes may be explained by drops in the variance of the AMOC: a less variable meridional heat transport leads to a suppressed co-variability of the AMV, leaving a larger role for non-AMOC drivers, consistent with a non-stationary AMOC-stationary noise interpretative framework.

Understanding long-term committed climate change due to anthropogenic forcing is key to inform climate policies, yet these timescales are still under-explored. We present here a set of 1000-year long abrupt stabilization simulations performed with EC-Earth3. Each simulation follows a sudden stabilization of the external forcing at the level specified by CMIP6 for historical (1990) or SSP5-8.5 scenario (2025, 2050, 2065, 2080, 2100) conditions, with a final temperature increase ranging between 1.4 and 9.6 K with respect to the pre-industrial baseline. Remarkably, the simulation stabilized at a level of greenhouse gases (GHGs) close to present-day (2025) well exceeds in the long term the Paris agreement goals of 1.5 and 2 degrees warming above pre-industrial, and only the 1990 simulation leads to a stabilized climate below 1.5 degrees warming. We first focus on the evolution of the climate response at multi-centennial timescales and its dependence on the level of forcing. Surface warming patterns evolve during the course of the simulations, with the most striking feature being a drastic acceleration of the warming in the Southern Ocean. The patterns of precipitation change also evolve during the stabilization runs: the drying trends found in the sub-tropical oceans and in Mediterranean-like hotspots in the SSP5-8.5 scenario tend to reduce, or even to reverse. We finally focus on the rate of heat storage in the global ocean, which is the main driver of the climate response at multi-centennial timescales. We find that the rate of warming of the deep ocean is almost independent from the amplitude of the forcing, so that most of the additional heat remains in the upper layers at high forcing. We hypothesize that this is due – at least partly – to a decreased ventilation of the deep ocean, caused by changes in the meridional overturning circulation (MOC). The results highlight the importance of studying multi-centennial timescales of climate change to better understand the response of the deep ocean, which will play a crucial role in determining the final state of the climate system once GHGs concentrations are stabilized.

The Liang-Kleeman rate of information transfer is used to quantify interactions between the different terms of the ocean heat budget at monthly time scale over the period 1988–2017 in three coupled global climate models participating in the High Resolution Model Intercomparison Project (HighResMIP), as well as in the Ocean Reanalysis System 5 (ORAS5). In particular, we focus on the influences of ocean heat transport convergence (dynamical influence) and net surface heat flux (thermodynamical influence) on ocean heat content tendency. At least two different configurations are used for each model, allowing to investigate the impact of ocean resolution on these causal relationships. A very small number of regions with a dynamical influence is found at high ocean resolution (≤ 0.25°) and ORAS5 reanalysis when considering the upper 50 m, while a thermodynamical influence is present in a large number of regions. The number of regions with a dynamical influence increases when taking into account the upper 300 m and becomes comparable to the thermodynamical influence. Interestingly, low-resolution model configurations (1° in the ocean) show a much larger number of regions with a significant dynamical influence for both depth integrations (upper 50 m and 300 m) compared to high-resolution model configurations. The reason for the large difference in dynamical influence between low and high resolutions partly comes from the spatial distribution of ocean velocity field, which is highly variable at high resolution, leading to a smaller dynamical influence. High resolution is therefore key in representing realistically the causal interactions between the ocean and atmosphere.

Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of climate change in the near-term range and a useful tool to inform decision-makers on future climate-related risks. Here we present results from the CMIP6 DCPP-A decadal hindcasts produced with the operational CMCC decadal prediction system (CMCC DPS), based on the fully-coupled CMCC-CM2-SR5 dynamical model. A 15-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2020, is performed using a full-field initialization strategy. The predictive skill for key variables is assessed and compared with the skill of an ensemble of non-initialized historical simulations so as to quantify the added value of initialization. In particular, the CMCC DPS is able to skilfully reproduce past-climate surface temperature fluctuations over large parts of the globe. The North Atlantic Ocean is the region that benefits the most from initialization, with the largest skill enhancement occurring over the subpolar region compared to historical simulations. On the other hand, the predictive skill over the Pacific Ocean rapidly decays with forecast time, especially over the North Pacific. In terms of precipitation, the CMCC DPS skill is significantly higher than that of the historical simulations over a few specific regions, including Sahel, Northern Eurasia and over the Western and Central Europe. The Atlantic Multidecadal Variability is also skilfully predicted, and this likely contributes to the skill found over remote areas through downstream influence, circulation changes and teleconnections. Considering the relatively small ensemble size, a remarkable prediction skill is also found for the North Atlantic Oscillation, with maximum correlations obtained in the 1–9 lead-year range. Model systematic errors also affect the forecast quality of the CMCC DPS, featuring a prominent cold bias over the Northern Hemisphere, which is not found in the historical runs. This lack of agreement suggests that in some areas the adopted full-value initialization strategy likely perturbs the equilibrium state of the model climate quite significantly.

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF–platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage.

We study the impact of horizontal resolution in setting the North Atlantic gyre circulation and representing the ocean–atmosphere interactions that modulate the low-frequency variability in the region. Simulations from five state-of-the-art climate models performed at standard and high-resolution as part of the High-Resolution Model Inter-comparison Project (HighResMIP) were analysed. In some models, the resolution is enhanced in the atmospheric and oceanic components whereas, in some other models, the resolution is increased only in the atmosphere. Enhancing the horizontal resolution from non-eddy to eddy-permitting ocean produces stronger barotropic mass transports inside the subpolar and subtropical gyres. The first mode of inter-annual variability is associated with the North Atlantic Oscillation (NAO) in all the cases. The rapid ocean response to it consists of a shift in the position of the inter-gyre zone and it is better captured by the non-eddy models. The delayed ocean response consists of an intensification of the subpolar gyre (SPG) after around 3 years of a positive phase of NAO and it is better represented by the eddy-permitting oceans. A lagged relationship between the intensity of the SPG and the Atlantic Meridional Overturning Circulation (AMOC) is stronger in the cases of the non-eddy ocean. Then, the SPG is more tightly coupled to the AMOC in low-resolution models.

The Kuroshio Extension (KE) shifts between elongated and convoluted states on interannual to decadal time scales. The nature of this low frequency variability (LFV) is still under debate since it is known to be driven by intrinsic oceanic mechanisms, but it is also synchronized with the Pacific Decadal Oscillation (PDO). In this analysis we present the results from two present-climate coupled simulations performed with the CMCC-CM2 model under the CMIP6 HighResMIP protocol and differing only by their atmospheric component resolution. The impact of increased atmospheric resolution on the KE LFV is assessed inspecting several aspects: the KE bimodality, the large-scale variability and the air–sea interactions. The KE LFV and the teleconnection mechanism that connects the KE and the PDO are well captured by both configurations. However, higher atmospheric resolution favors the occurrence of the elongated state and leads to a more realistic PDO representation. Moreover, both simulations qualitatively capture the signatures of atmosphere-driven and ocean-driven regimes over the North Pacific Ocean, even if the higher resolution induces an excessively strong ocean–atmosphere coupling that leads to an overestimation of the air–sea feedbacks. This work highlights that the small scale atmospheric variability (resolution lower than 1°) does not substantially contribute to improve the realism of the KE LFV, but causes significant differences in the air–sea interaction over the KE region likely related to the strengthening of the coupling. The eddy-permitting ocean resolution shared by both configurations is likely responsible for the degree of realism exhibited by the simulated KE LFV in the two analyzed simulations.

Sea surface temperature (SST) has been thought to be linked with air-sea surface heat fluxes (SHF). General knowledge is that the high frequency variating atmosphere properties modify oceanic quantities due to their slower response. However, recent studies show how in regions where SST gradients and heat losses are stronger – in the Western Boundary Currents region (WBC) – variabilities in SST and SHF are due to internal ocean processes and water dynamic effects. Theoretical models suggest that the correlation between SST and SHF and between SST tendency (namely the time derivative) and THF can be used to retrieve the sources of variations of these two quantities distinguishing to influences due to ocean or atmosphere dynamics (ocean or atmosphere driven regimes). In this study, We use observational data and numerical model outputs with different resolutions to distinguish different regimes of variability and to investigate spatial resolution effects over the Agulhas Current region and the Eastern South Atlantic. In these regions waters flowing southward from the Indian Ocean along the eastern coasts of Africa interact with bathymetry and cold waters of the Antarctic Circumpolar Current (ACC) and the SubTropical Front and generate turbulence and eddies that propagates into the South Atlantic carrying warm and salty waters (Agulhas Leakage). Hence this methodology is particularly effective due to the mesoscale length scale of the physical phenomena that occur here. Observations are retrieved from OAFlux dataset and J-OFURO3. Model data come from the Coupled Model Intercomparison Project (CMIP6). The increase of ocean resolution leads to a better representation of the cross-covariance patterns and cross-correlation forms, indicating an improvement of the eddy-permitting from the eddy-parametrized models’ capability. Covariance maps have been calculated to highlight qualitative patterns for the lead-lag symmetry. We concluded that, while high resolution model data have similar covariance patterns and correlation values to the observations, their low-resolution counterpart, in two cases, fails to reconstruct the signal caused by the ocean dynamics. The stronger impact on the capability of reproduce this interaction phenomenon belongs to the ocean part of the coupled model: the higher, the better is the symmetric properties of the correlation functions (symmetry index) and the greater the transition scale is, implying the needs of a wider filtering window to cancel out the ocean driven regime signal.

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1,2,3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7,8,9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models10, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade. DMS, AAS, NJD, LH and RE were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP project (GA 776613). FJDR, LPC, SW and RB also acknowledge the support from the EUCP project (GA 776613) and from the Ministerio de Econom´ıa y Competitividad (MINECO) as part of the CLINSA project (Grant No. CGL2017-85791-R). SW received funding from the innovation programme under the Marie Sk´lodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433 and PO from the Ramon y Cajal senior tenure programme of MINECO. The EC-Earth simulations were performed on Marenostrum 4 (hosted by the Barcelona Supercomputing Center, Spain) using Auto-Submit through computing hours provided by PRACE.WAM, HP, KMand KP were supported by the German FederalMinistry for Education and Research (BMBF) project MiKlip (grant 01LP1519A). NK, IB, FC and YW were supported by the Norwegian Research Council projects SFE (grant 270733) the Nordic Center of excellent ARCPATH (grant 76654) and the Trond Mohn Foundation, under the project number : BFS2018TMT01 and received grants for computer time from the Norwegian Program for supercomputing (NOTUR2, NN9039K) and storage grants (NORSTORE, NS9039K). JM, LFB and DS are supported by Blue-Action (European Union Horizon 2020 research and innovation program, Grant Number: 727852) and EUCP (European Union Horizon 2020 research and innovation programme under grant agreement no 776613) projects. The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the US National Science Foundation (NSF) under Cooperative Agreement No. 1852977. NCAR contribution was partially supported by the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under Climate Variability and Predictability Program Grant NA13OAR4310138 and by the US NSF Collaborative Research EaSM2 Grant OCE-1243015.

Significance Much work has been done to quantify tropical cyclone (TC)-induced precipitation and its role in determining flood events. We identify the role of tropical cyclones in reducing precipitation over particular areas of the tropical domain. The significant reduction in the precipitation over the Maritime Continent when the TC season is particularly active is in line with the net reduction in westward water flow into the Maritime Continent atmosphere, induced by TC-associated circulation over the region., The Maritime Continent plays a role in the global circulation pattern, due to the energy released by convective condensation over the region which influences the global atmospheric circulation. We demonstrate that tropical cyclones contribute to drying the Maritime Continent atmosphere, influencing the definition of the onset of the dry season. The process was investigated using observational data and reanalysis. Our findings were confirmed by numerical experiments using low- and high-resolution versions of the CMCC-CM2 General Circulation Model contributing to the HighResMIP CMIP6 effort.

The decadal time scale (∼1–10 years) bridges the gap between seasonal predictions and longer-term climate projections. It is a key planning time scale for users in many sectors as they seek to adapt to our rapidly changing climate. While significant advances in using initialized climate models to make skillful decadal predictions have been made in the last decades, including coordinated international experiments and multimodel forecast exchanges, few user-focused decadal climate services have been developed. Here we highlight the potential of decadal climate services using four case studies from a project led by four institutions that produce real-time decadal climate predictions. Working in co-development with users in agriculture, energy, infrastructure, and insurance sectors, four prototype climate service products were developed. This study describes the challenge of trying to match user needs with the current scientific capability. For example, the use of large ensembles (achieved via a multisystem approach) and skillfully predicted large-scale environmental conditions, are found to improve regional predictions, particularly in midlatitudes. For each climate service, a two-page “product sheet” template was developed that provides users with both a concise probabilistic forecast and information on retrospective performance. We describe the development cycle, where valuable feedback was obtained from a “showcase event” where a wider group of sector users were engaged. We conclude that for society to take full and rapid advantage of useful decadal climate services, easier and more timely access to decadal climate prediction data are required, along with building wider community expertise in their use. This study received support from the C3S_34c contract (ECMWF/COPERNICUS/2019/C3S_34c_DWD) of the Copernicus Climate Change Service (C3S) operated by ECMWF. DS, AS, and HT were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. AP, KP, and BF were funded by the Deutscher Wetterdienst. Peer Reviewed "Article signat per 22 autors/es: Nick Dunstone, Julia Lockwood, Balakrishnan Solaraju-Murali, Katja Reinhardt, Eirini E. Tsartsali, Panos J. Athanasiadis, Alessio Bellucci, Anca Brookshaw, Louis-Philippe Caron, Francisco J. Doblas-Reyes, Barbara Früh, Nube González-Reviriego, Silvio Gualdi, Leon Hermanson, Stefano Materia, Andria Nicodemou, Dario Nicolì, Klaus Pankatz, Andreas Paxian, Adam Scaife, Doug Smith, and Hazel E. Thornton"

The Gulf Stream (GS) plays a key role in shaping the North Atlantic climate. Moreover, the associated sea surface temperature (SST) front undergoes interannual-to-decadal variability that is thought to force significant atmospheric circulation anomalies. However, general circulation models do not accurately reproduce the atmospheric response to SST front variability as estimated from observations. In this work we analyze the atmospheric response to the GS SST front (GSF) shifts in a multimodel ensemble of atmosphere-only simulations forced with observed SSTs (1950–2014). The atmospheric response is found to be resolution dependent. Only the high-resolution simulations produce a wintertime response similar to observed anomalies. More specifically, (i) analysis of the atmospheric thermodynamic balance close to the GSF showed that the anomalous diabatic heating associated to the GSF displacement is mainly balanced by vertical motion and by meridional transient eddy heat transport (not the case for low-resolution models), while (ii) the large-scale response includes a meridional shift of the North Atlantic eddy-driven jet and storm track homodirectional to the GSF displacement. This atmospheric response is accompanied by changes in low-level baroclinicity close to and north of the GSF, resulting from the oceanic forcing and the zonal atmospheric circulation anomalies respectively. The low-level baroclinicity anomalies lead to changes in baroclinic eddy activity and, ultimately, in the jet via eddy–mean flow interaction. Considering the two-way nature of air–sea interactions, using historical atmosphere-only simulations is a powerful way to isolate the impact of realistic oceanic variability on the atmosphere. Our results suggest that interannual-to-decadal predictability may be higher than what low-resolution models currently indicate.

11 pages, 6 figures, supplementary information https://doi.org/10.1038/s41612-021-00188-5.-- Data availability; The data generated and analyzed during the current study are available from the corresponding author YRR on reasonable request, Atlantic multidecadal variability (AMV) has been linked to the observed slowdown of global warming over 1998–2012 through its impact on the tropical Pacific. Given the global importance of tropical Pacific variability, better understanding this Atlantic–Pacific teleconnection is key for improving climate predictions, but the robustness and strength of this link are uncertain. Analyzing a multi-model set of sensitivity experiments, we find that models differ by a factor of 10 in simulating the amplitude of the Equatorial Pacific cooling response to observed AMV warming. The inter-model spread is mainly driven by different amounts of moist static energy injection from the tropical Atlantic surface into the upper troposphere. We reduce this inter-model uncertainty by analytically correcting models for their mean precipitation biases and we quantify that, following an observed 0.26 °C AMV warming, the equatorial Pacific cools by 0.11 °C with an inter-model standard deviation of 0.03 °C, Y.R.-R. was founded by the European Union’s Horizon 2020 Research and Innovation Program in the framework of the Marie Skłodowska-Curie grant INADEC (Grant agreement 800154). E.M.-C. acknowledges funding from the European Commission’s Horizon 2020 projects PRIMAVERA (Grant Agreement 641727). X.L. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433. A.B. and D.N. acknowledge funding from the European Commission’s Horizon 2020 project EUCP (Grant agreement 776613). F.C. and G.D. were supported by the US National Science Foundation (NSF) under the Collaborative Research EaSM2 Grant OCE-1243015 to NCAR and by the US National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under the Climate Variability and Predictability Program Grant NA13OAR4310138. NCAR is a major facility sponsored by the US NSF under Cooperative Agreement 1852977. [...] R.E., N.D., L.H., and D.S. were supported by the Met Office Hadley Center 522 Climate Program funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP 523 project (GA 776613). J.L.-P. was funded by the European Union’s Horizon 2020 Research and Innovation Program in the framework of the PRIMAVERA project (Grant Agreement 641727). J.R. and D.H. were funded by NERC via NCAS and the ACSIS project (NE/N018001/1), and JR was also funded by the NERC SMURPHS project (NE/N006054/1). M.M.-R. was funded by the European Union’s Horizon 2020 Research and Innovation Program in the framework of the Marie Skłodowska-Curie grant FESTIVAL (Grant agreement 797236). E.T. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 748750 (SPFireSD project), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

The recent advancements in climate modelling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the CMCC-CM2 model used here, adopt the highest horizontal resolutions available within the last family of the global coupled climate models de¬veloped at CMCC to participate in the CMIP6 effort. The main aim of this study is to document the ability of the CMCC-CM2 models in representing the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations (ERA5 Reanalysis and CHIRPS observations). For a more detailed evaluation we investigate both 6 hourly and daily time series for the definition of the extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The very-high resolution version (¼ degree horizontal resolution) of the atmospheric model provides better results than the high resolution one (one degree), not only in terms of means but also in terms of extreme events of temperature defined at daily and 6-hourly frequency. This is also the case of average precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

After the early pioneering studies during the 2000s, and the first coordinated multi-model effort within the framework of the 5th Coupled Model Inter-comparison Project (CMIP5) in early 2010s, decadal climate predictions are now entering a more mature phase of their historical development. Near-term climate prediction activities have been recently endorsed by the World Climate Research Programme (WCRP) as one of the Grand Challenges in climate science research, and the Lead Centre for Annual-to-Decadal Climate Prediction, collecting hindcasts and forecasts from several contributing centres worldwide has been established by the WMO.Here we present results from the CMIP6 DCPP-A decadal hindcasts produced with the CMCC decadal prediction system (CMCC DPS), based on the fully-coupled CMCC-CM2-SR5 dynamical model. A 10-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2019, is performed using a full-field initialization strategy.The predictive skill for key quantities is assessed and compared with a non-initialized historical simulation, so as to verify the added value of initialization. In particular, the CMCC DPS is capable to skilfully reproduce past-climate surface temperature over the North Atlantic ocean, the Indian ocean and the Western Pacific ocean, as well as over most part of the continents. Beyond the contribution of the climate change, predictive skill emerges, among other regions, for the subpolar North Atlantic sea-surface temperatures, resembling the imprint of the extra-tropical part of the Atlantic Multidecadal Variability.In terms of precipitation, CMCC DPS is able to capture most of the decadal variability over the Northern part of the Eurasian continent. Indeed, a set of regional diagnostics is aimed to investigate the process at stake behind this high predictive skill.

Western boundary currents transport a large amount of heat from the Tropics toward higher latitudes; furthermore they are characterized by a strong sea surface temperature (SST) gradient. For such reasons they have been shown to be fundamental in influencing the climate of the Northern Hemisphere and its variability, and a potentially relevant source of atmospheric predictability. General circulation models show deficiencies in simulating the observed atmospheric response to SST front variability. The atmospheric horizontal resolution has been recently proposed as a key element in understanding such differences. However, a multi-model analysis to systematically investigate differences between low-resolution and high-resolution atmospheric response to oceanic forcing is still lacking. The present work has the objective to fill this gap, analysing the atmospheric response to Gulf Stream SST front (GSF) shifting using data from recent High Resolution Model Intercomparison Project (HighResMIP). Ensembles of historical simulations performed with three atmospheric general circulation models (AGCMs) have been analysed, each conducted with a low-resolution (LR, about 1°) and a high-resolution (HR, about 0.25°) configuration. AGCMs have been forced with observed SSTs (HadISST2 dataset), available at daily frequency on a 0.25° grid, during 1950–2014. Results show atmospheric responses to the SST-induced diabatic heating anomalies that are strongly resolution dependent. In LR simulations a low-pressure anomaly is present downstream of the SST anomaly, while the diabatic heating anomaly is mainly balanced by meridional advection of air coming from higher latitudes, as expected for an extra-tropical shallow heat source. In contrast, HR simulations generate a high-pressure anomaly downstream of the SST anomaly, thus driving positive temperature advection from lower latitudes (not balancing diabatic heating). Along the vertical direction, both in LR and HR simulation, the diabatic heating in the interior of the atmosphere is balanced by upward motion south of GS SST front and downward motion north and further south of the Gulf Stream. Finally, LR simulations show a reduction in storm-track activity over the North Atlantic, whereas HR simulations show a meridional displacement of the storm-track considerably larger (yet in the same direction) than that of the SST front. HR simulations reproduce the atmospheric response obtained from observations, albeit weaker. This is a hint for the existence of a positive feedback between ocean and atmosphere, as proposed in previous studies. These findings are qualitatively consistent with previous results in literature and, leveraging on recent coordinated modelling efforts, shed light on the effective role of atmospheric horizontal resolution in modelling the atmospheric response to extra-tropical oceanic forcing.

The Kuroshio Extension (KE) is the inertial meandering jet formed by the convergence of the Kuroshio and Oyashio currents in the Northern Pacific. It is widely mentioned in the literature that the KE variability is bimodal on interannual to decadal time scale. The nature of this low frequency variability (LFV) is still under debate; intrinsic oceanic mechanisms are known to play a fundamental role in the phenomenon but there is also evidence from observations that the KE LFV is connected with changes in broader patterns associated with the Pacific Decadal Oscillation, which is in its turn generated by the dominant decadal mode of the sea level pressure variability in the North Pacific. We investigate the respective contributions of oceanic and atmospheric drivers of the KE variability by taking advantage of the OCCIPUT 1/4° global model dataset: it consists in an ensemble of 50 ocean–sea ice hindcasts performed over the period 1960–2015 (hereafter OCCITENS), and in a one-member 330-year climatological simulation (hereafter OCCICLIM). In this context, OCCITENS simulates both the intrinsic and forced variability, while OCCICLIM simulates the "pure" intrinsic variability. We explore several features of the KE, finding analogies between the OCCICLIM and OCCITENS datasets with autonomous and non-autonomous dynamical systems respectively. This approach aims to apply concepts from the dynamical systems theory on complex and realistic ocean simulations. In this framework, the results suggest that both oceanic and atmospheric drivers control the KE LFV, and that the effect of the low-frequency atmospheric forcing reduces the phase space region explored by the system through synchronization mechanisms. The system’s intrinsic variability can be paced, and therefore clustered over the system’s pullback attractor under the effect of the time dependent forcing.

In this study we assess to what extent seven different dynamical prediction systems can retrospectively predict the winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic Seas in the time period 1970-2005. We focus in particular on the region where warm water flows poleward, i.e., the Atlantic water pathway, and on interannual-to-decadal time scales. To better understand why dynamical prediction systems have predictive skill or lack thereof, we confront them with a mechanism identified from observations – propagation of oceanic anomalies from low to high latitudes – on different forecast lead times. This observed mechanism shows that warm and cold anomalies propagate along the Atlantic water pathway within a certain time frame. A key result from this study is that most models have difficulty representing this mechanism, resulting in an overall poor prediction skill after 1-2 years lead times (after applying a band-pass filter to focus on interannual-to-decadal time scales). There is a link, although not very strong, between predictive skill and the representation of the SST propagation. Observational studies demonstrate predictability several years in advance in this region, thus suggesting a great potential for improvement of dynamical climate predictions by resolving the causes for the misrepresentation of the oceanic link. Inter model differences in simulating surface velocities along the Atlantic water pathway suggest that realistic velocities are important to better circulate anomalies poleward, and hence, increase predictive skill on interannual-to-decadal time scales in the oceanic gateway to the Arctic.

Representing the rainy season of the maritime continent is a challenge for global and regional climate models. Here, we compare regional climate models (RCMs) based on the coupled model intercomparison project phase 5 (CMIP5) model generation with high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. The onset and the total precipitation of the rainy season for both model experiments are compared against observational datasets for Southeast Asia. A realistic representation of the monsoon rainfall is essential for agriculture in Southeast Asia as a delayed onset jeopardizes the possibility of having three annual crops. In general, the coupled historical runs (Hist-1950) and the historical force atmosphere run (HighresSST) of the high-resolution model intercomparison project (HighResMIP) suite were consistently closer to the observations than the RCM of CMIP5 used in this study. We find that for the whole of Southeast Asia, the HighResMIP models simulate the onset date and the total precipitation of the rainy season over the region closer to the observations than the other model sets used in this study. High-resolution models in the HighresSST experiment showed a similar performance to their low-resolution equivalents in simulating the monsoon characteristics. The HighresSST experiment simulated the anomaly of the onset date and the total precipitation for different El Niño-southern oscillation conditions best, although the magnitude of the onset date anomaly was underestimated. Indonesia Endowment Fund for Education (LPDP), Grant/Award Number: S-353/LPDP.3/2019; H2020 Marie Skłodowska-Curie, Grant/Award Number: 748750; European Union's Horizon 2020 Research and Innovation Programme, Grant/Award Number: 641727

A dominant paradigm for mid-latitude air-sea interaction identifies the synoptic-scale atmospheric “noise” as the main driver for the observed ocean surface variability. While this conceptual model successfully holds over most of the mid-latitude ocean surface, its soundness over frontal zones (including western boundary currents; WBC) characterized by intense mesoscale activity, has been questioned in a number of studies suggesting a driving role for the small scale ocean dynamics (mesoscale oceanic eddies) in the modulation of air-sea interaction. In this context, climate models provide a powerful experimental device to inspect the emerging scale-dependent nature of mid-latitude air-sea interaction. This study assesses the impact of model resolution on the representation of air-sea interaction over the Gulf Stream region, in a multi-model ensemble of present-climate simulations performed using a common experimental design. Lead-lag correlation and covariance patterns between sea surface temperature (SST) and turbulent heat flux (THF) are diagnosed to identify the leading regimes of air-sea interaction in a region encompassing both the Gulf Stream system and the North Atlantic subtropical basin. Based on these statistical metrics it is found that coupled models based on “laminar” (eddy-parameterised) and eddy-permitting oceans are able to discriminate between an ocean-driven regime, dominating the region controlled by the Gulf Stream dynamics, and an atmosphere-driven regime, typical of the open ocean regions. However, the increase of model resolution leads to a better representation of SST and THF cross-covariance patterns and functional forms, and the major improvements can be largely ascribed to a refinement of the oceanic model component. The authors of this study wish to thank two reviewers for their many insightful comments. AB, PA, ES, RH, JG-S, DP, ESG, MJR, CR, JS, PV acknowledge PRIMAVERA funding received from the European Commission under Grant Agreement 641727 of the Horizon 2020 research programme. JG-S was additionally supported by the Spanish ‘Ramón y Cajal’ programme (RYC-2016-21181). The authors declare that they have no conflict of interest. The datasets used in this work are cited in this manuscript with appropriate doi’s in publicly available archives.

This article is part of the Topical Collection on Advances and Future Directions in Earth System Modelling Purpose of Review Assessment of the impact of ocean resolution in Earth System models on the mean state, variability, and future projections and discussion of prospects for improved parameterisations to represent the ocean mesoscale. Recent Findings The majority of centres participating in CMIP6 employ ocean components with resolutions of about 1 degree in their full Earth System models (eddy-parameterising models). In contrast, there are also models submitted to CMIP6 (both DECK and HighResMIP) that employ ocean components of approximately 1/4 degree and 1/10 degree (eddy-present and eddy-rich models). Evidence to date suggests that whether the ocean mesoscale is explicitly represented or parameterised affects not only the mean state of the ocean but also the climate variability and the future climate response, particularly in terms of the Atlantic meridional overturning circulation (AMOC) and the Southern Ocean. Recent developments in scale-aware parameterisations of the mesoscale are being developed and will be included in future Earth System models. Summary Although the choice of ocean resolution in Earth System models will always be limited by computational considerations, for the foreseeable future, this choice is likely to affect projections of climate variability and change as well as other aspects of the Earth System. Future Earth System models will be able to choose increased ocean resolution and/or improved parameterisation of processes to capture physical processes with greater fidelity. HTH, EB, PM, PH, MJR, and MB acknowledge the Met Office Hadley Centre Climate Programme. MJR, DP, and TA acknowledge PRIMAVERA funding received from the European Commission under Grant Agreement 641727 of the Horizon 2020 research programme. EP, TK, and AY were supported by the National Environmental Research Council (NERC) National Capability Science Multi-Centre funding for the UK Earth System Modelling project through grant NE/N018036/1 and the EU Horizon 2020 CRESCENDO project, grant number 641816. BFK is supported by ONR N00014-17-1-2963, NSF 1350795 and 1655221, and NOAA NA19OAR4310366. RB was supported by NSF’s Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under NSF Award PLR-1425989. DPM is supported by NERC NE/R000999/1. TA acknowledges PRACE for awarding us access to MN4 supercomputer, hosted by BSC, Spain. The CESM1.3 simulations are completed through the International Laboratory for High Resolution Earth System Prediction (iHESP)—a collaboration among QNLM, TAMU, and NCAR, from which QZ, BG, and FC acknowledge funding. LZ was supported by NSF‐GEO 1912357 and NOAA CVP NA19OAR4310364.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere‐only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050., Key Points Biases in tropical cyclone distribution, frequency, and intensity are generally reduced in models at 25 km resolutionNorthern Hemisphere basins show mixed responses to future forcing, while Southern Indian Ocean activity projected to declineFuture changes in 10 m wind speed in coupled models are mixed, and models with lower bias suggest small increases

Tropical cyclones (TCs) transport energy and moisture along their pathways interacting with the climate system and TCs activities are expected to extend further poleward during the 21st century.For this reason, it is important to assess the ability of state-of-the-art climate models in reproducing an accurate meridional distribution of TCs as well as a reasonable meridional portrait of moisture transport associated with TCs.Since high resolutions are required to reconstruct observed TCs activity, the present work is based on the simulations performed as part of HighResMIP in the framework of the community CMIP6 effort. To inspect this feature, two horizontal resolutions for each climate model are considered. Besides, the impact of boundary conditions, i.e. observed ocean surface state, is examined by considering both coupled and atmosphere-only configurations.In the present work, the north Atlantic region is analyzed as a sample region, while the same approach is applied on a multi-basin basis. In the sample area, climate models present a good ability in reproducing the TCs distribution, with a general underestimation at lower latitudes and a slight overestimation at high-latitudes compared to observed TCs tracks (e.g. IBTRACK).The meridional distribution of moisture transport associated with TCs is evaluated by considering the radial average of the integrated water vapor transport along the TC tracks. When compared to observation (IBTRACS and JRA-55 reanalysis), the simulated moisture transport associated with TCs displays reasonably good performance in atmosphere-only high-resolution models configuration. The interannual variability of water vapor associated with TCs, instead, is poorly represented in climate models.Climate models in high-resolution configuration can then be used in estimating future TCs meridional distribution and changes in meridional moisture transport associated with TCs.This effort is part of HighResMIP and it is developed in the framework of the EU-funded PRIMAVERA project.

The Kuroshio Extension (KE) is the inertial meandering jet formed by the convergence of the Kuroshio and Oyashio currents in the Northern Pacific. It is widely mentioned in the literature that the KE variability is bimodal on the decadal time scale. The nature of this low frequency variability (LFV) is still under debate; some authors suggest that internal oceanic mechanisms play a fundamental role in the phenomenon but there is also evidence from the observations that the KE LFV is connected with changes in broader patterns of variability such as the Pacific Decadal Oscillation.We first inspect the interplay between the ocean and the atmosphere in the KE by taking advantage of the OCCIPUT 1/4° model dataset: it consists in an ensemble of 50 global ocean–sea-ice hindcasts performed over the period 1960–2015 (hereafter OCCITENS), and in a one-member 330-yr climatological simulation (hereafter OCCICLIM). In this context, OCCITENS simulates both the intrinsic and forced variability and allows for their separation via ensemble statistics, while OCCICLIM simulates the "pure" intrinsic variability of the jet. We then explore some features of the KE dynamical system attractor in the quasi-autonomous (OCCICLIM) and nonautonomous (OCCITENS) regimes: we thus assess the KE predictability in the OCCIPUT dataset in order to better understand the ocean-atmosphere interactions and the source of the associated predictability.Our analyses show that both oceanic and atmospheric drivers control the KE LFV variability. In this framework, the results suggest that the jet oscillates between the two intrinsic oceanic modes with transitions triggered by the atmosphere.

Understanding processes and mechanisms which contribute to decadal climate variability is a crucial step in the development of a reliable prediction system, and as such it constitutes an important segment of the activities carried forward by the EU-funded Horizon 2020 EUCP project.Sea surface temperature (SST) variability in the North Atlantic is known to be a key source of decadal predictability for the Euro-Atlantic sector. However, the nature of the observed variability is at the core of a long-standing debate.In this work, we investigate the origins of North Atlantic SST variability, focusing on a specific event: the mid-20th century (1940-1975) “warm-to-cold” transition. This event is particularly interesting as it represents a well documented decadal-scale fluctuation of the observed climate record and can be used as a suitable test-bed to evaluate the relative skill of initialized versus non-initialized (historical) climate simulations.Several mechanisms and processes have been taken into account to explain the cooling in the middle of 20th century, ranging from a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) to an increase in anthropogenic aerosol. Here the 1940-1975 transition is examined firstly in the NCAR Large Ensemble (NCAR-LENS), aiming to further explore the role of the possible drivers. Despite the lack of a realistic model state initialization, the NCAR-LENS shows some skill in capturing the North Atlantic SST transition, suggesting a non-negligible influence of the external forcing. Some lag between observations and model results is found, with the ensemble mean SST leading the onset of the observed transition by about ten years. This is consistent with previous studies, where some evidence was found of the driving role of anthropogenic aerosol and greenhouse gas forcing. In contrast, the simultaneous ocean dynamic response (AMOC) exhibits a large intra-member spread. This finding corroborates the hypothesis of a non-oceanic driver for the decadal-scale SST fluctuation. The same episode is then analysed in the NCAR Decadal Prediction Large Ensemble (NCAR-DPLE), which shares the same model code, configuration details, component resolutions, and external forcing datasets as for the non-initialized LENS ensemble. This allows a rigorous attribution of the relative roles of initialization, (mainly constraining the ocean-driven internal variability) and external forcing conditions on the overall skill in reproducing the Atlantic decadal variability, with clear implications for decadal predictability and predictions.

The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the three-dimensional ocean circulation that transports warm and salty water northward, and exports cold and dense water from the Arctic southward.The simulated AMOC in Coupled Model Intercomparison Project models (both coupled and ocean-only) has been studied extensively. However, correctly simulating the AMOC with these models remains a challenge for the climate modelling community. One model aspect that can affect the AMOC representation is the model resolution (i.e. grid spacing).Here, we examine key aspects of the North Atlantic Ocean circulation using a multi-model, multi-resolution ensemble based on the CMIP6 HighResMIP coupled experiments. The AMOC and associated heat transport tend to become stronger as model resolution increases, particularly when the ocean resolution changes from non-eddying to eddy-present and eddy-rich. However, the circulation remains too shallow compared to observations for most models, and this, together with temperature biases, cause the northward heat transport to be too low for a given overturning strength.In the period 2015-2050, the overturning circulation tends to decline more rapidly in the higher resolution models by more than 20% compared to the control state, which is related to both themean state and to the subpolar gyre contribution to deep water formation. The main part of the decline comes from the Florida Current component of the circulation.

Previous research has extensively established that, during the last decades, the Trade Wind Charging (TWC) mechanism is a fundamental precursor of El Niño Southern Oscillation (ENSO). Moreover, recent results suggest that its relevance as an ENSO driver varies when a longer time interval is included the analysis. This article investigates whether TWC is isolated as a significant ENSO precursor; and how the internal variance of their coupling behaves, on a CMIP6 multi model ensemble. In particular, we consider the models participating to the CMIP6 HigResMIP, specifically designed to investigate the role that model resolution plays in simulating climate processes. For each model, we have included in the analysis 100-year long integrations of the present climate that are forced with constant radiative forcing representative of the 1950s at standard and enhanced resolutions.The analysis follows two steps for each experiment. First, through a combination of Empirical Orthogonal Function (EOF) and Canonical Correlation Analysis (CCA) it isolates ENSO and TWC. Then, in order to study their mutual relation, the combination of EOF and CCA is repeated over shifting time intervals.The analysis indicates TWC as a strong ENSO precursor for at least one model, and the coupling between the modes shows signs of internal variability. Also, the ways in which the models reconstruct the TWC, in its intensity and shape, and its coupling with ENSO appear to be affected by the changes in resolution. These results provide an insight over the different degrees at which HigResMIP model experiments are able to characterize the features of a fundamental process like ENSO. Moreover, they cast a light over the impacts that a change in oceanic or atmospheric resolution can have when simulating a coupled mode.

International audience; Finer grids in global climate models could lead to an improvement in the simulation of precipitation extremes. We assess the influence on model performance of increasing spatial resolution by evaluating pairs of high-and low-resolution forced atmospheric simulations from six global climate models (generally the latest CMIP6 version) on a common 1°× 1°grid. The differences in tuning between the lower and higher resolution versions are as limited as possible, which allows the influence of higher resolution to be assessed exclusively. We focus on the 1985-2014 climatology of annual extremes of daily precipitation over global land, and models are compared to observations from different sources (i.e., in situ-based and satellite-based) to enable consideration of observational uncertainty. Finally, we address regional features of model performance based on four indices characterizing different aspects of precipitation extremes. Our analysis highlights good agreement between models that precipitation extremes are more intense at higher resolution. We find that the spread among observations is substantial and can be as large as intermodel differences, which makes the quantitative evaluation of model performance difficult. However, consistently across the four precipitation extremes indices that we investigate, models often show lower skill at higher resolution compared to their corresponding lower resolution version. Our findings suggest that increasing spatial resolution alone is not sufficient to obtain a systematic improvement in the simulation of precipitation extremes, and other improvements (e.g., physics and tuning) may be required.

Middle East surface air temperature (ME−SAT), during boreal summer (June to August: JJA), shows robust multidecadal variations for the period 1948−2016. Here using observational and reanalysis datasets as well as coupled atmosphere−ocean model simulations, we linked the observed summer ME−SAT variability to the multidecadal variability of sea surface temperature (SST) in the North Atlantic Ocean (AMV). This Atlantic−ME connection during summer involves ocean−atmosphere interactions through multiple ocean basins, with an influence from the Indian Ocean and the Arabian Sea. The downstream response to Atlantic SST is a weakening of the subtropical westerly jet stream that impacts summer ME−SAT variability through a wave−like pattern in the upper tropospheric levels. The Atlantic SST response is further characterized by positive geopotential height anomalies in the upper levels over the Eurasian region and dipole−like pressure distribution over the ME lower levels. For positive Atlantic SST anomalies, this pressure gradient initiates anomalous low−level southerly flow, which transports moisture from the neighboring water bodies toward the extremely hot and dry ME landmass. The increase in atmospheric moisture reduces the longwave radiation damping of the SAT anomaly, increasing further ME−SAT. A suite of Atlantic Pacemaker experiments skillfully reproduces the North Atlantic−ME teleconnection. Our findings reveal that in observations and models the Atlantic Ocean acts as a critical pacemaker for summer ME−SAT multidecadal variability and that a positive AMV can lead to enhanced summer warming over the Middle East.

A multimodel, multiresolution ensemble using Coupled Model Intercomparison Project Phase 6 (CMIP6) High Resolution Model Intercomparison Project (HighResMIP) coupled experiments is used to assess the performance of key aspects of the North Atlantic circulation. The Atlantic Meridional Overturning Circulation (AMOC), and related heat transport, tends to become stronger as ocean model resolution is enhanced, better agreeing with observations at 26.5°N. However, for most models the circulation remains too shallow compared to observations and has a smaller temperature contrast between the northward and southward limbs of the AMOC. These biases cause the northward heat transport to be systematically too low for a given overturning strength. The higher‐resolution models also tend to have too much deep mixing in the subpolar gyre. In the period 2015–2050 the overturning circulation tends to decline more rapidly in the higher‐resolution models, which is related to both the mean state and to the subpolar gyre contribution to deep water formation. The main part of the decline comes from the Florida Current component of the circulation. Such large declines in AMOC are not seen in the models with resolutions more typically used for climate studies, suggesting an enhanced risk for Northern Hemisphere climate change. However, only a small number of different ocean models are included in the study. M. J. R., C. D. R., V. M., D. D., T. K., P. O., E. M.‐C., A. B., S. D., E. E., O. G., D. I., K. L., D. P., R. S., J. S., and L. T. acknowledge PRIMAVERA funding received from the European Commission under Grant Agreement 641727 of the Horizon 2020 research program. M. R., L. C. J., and H. H. were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra (GA01101). R. S. acknowledges funding from the National Environmental Research Council (NERC). A. C. acknowledges funding from the ACSIS project that is supported by the Natural Environment Research Council (Grant NE/N018044/1). XX acknowledges funding from the NOAA Climate Program Office MAPP Program (Award NA15OAR4310088). The CESM1.3 simulations are completed through the International Laboratory for High Resolution Earth System Prediction (iHESP)—a collaboration among QNLM, TAMU, and NCAR, from which Q. Z., P. C., S. G. Y., F. S. C., S. Z., and L. W. acknowledge funding and were performed on Frontera at the Texas Advanced Computing Center. NCAR is a major facility sponsored by the US National Science Foundation under Cooperative Agreement No. 1852977. Data from the RAPID‐MOCHA program are funded by the U.S. National Science Foundation and U.K. Natural Environment Research Council and are freely available at www.noc.soton.ac.uk/rapidmoc and https://mocha.rsmas.miami.edu/mocha/results/mocha-new/index.html websites. We acknowledge extensive use of the supercomputers at our institutes to complete the simulations and for the CEDA‐JASMIN platform to enable coordinated data storage and model analysis. The authors would like to thank all the teams involved in the EU H2020 PRIMAVERA project and iHESP for the hard work in configuring and executing model simulations and making the data available for analysis. They also thank two anonymous reviewers and the Editor for their helpful feedback to improve the manuscript.