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Satellite-derived sea-ice concentration (SIC) and re-analysed atmospheric data are used to analyse the potential feedback of the North Atlantic Oscillation (NAO)-driven sea-ice anomalies in winter onto the atmosphere during 1979–2013. A maximum covariance analysis shows that this feedback can be detected with monthly data. When SIC leads, the covariability between Atlantic SIC and the Euro-Atlantic atmospheric circulation in February is statistically significant, but shows intraseasonal differences: the December SIC influence is dominated by anomalies east of Greenland, with maximum amplitude in the Greenland Sea (GS); while the January SIC influence is dominated by anomalies west of Greenland, in the Davis Strait-Labrador Sea (DL) region. The lagged atmospheric anomalies are likewise different. A reduction of SIC over GS in December is followed in February by a negative NAO-like pattern near the surface and a hemispheric signature in the upper-troposphere, thus acting as a negative feedback. On the other hand, a reduction of SIC over DL in January is followed by an atmospheric anomaly over the North Atlantic that projects on the positive phase of the East Atlantic pattern. The dynamics associated with these atmospheric anomalies is described, indicating that transient-eddy activity is likely at work in settling the large-scale patterns. The role of concomitant North Atlantic sea surface temperature anomalies is discussed. ; The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement n.308299 (NACLIM – www.naclim.eu). JG-S was partially supported by the H2020-funded MSCA-IF-EF DPETNA project. The authors thank Francis Codron (LOCEAN-IPSL) for discussions and two anonymous reviewers for their comments on the manuscript. ; Peer Reviewed ; Postprint (author's final draft)

Satellite-derived sea-ice concentration (SIC) and re-analysed atmospheric data are used to analyse the potential feedback of the North Atlantic Oscillation (NAO)-driven sea-ice anomalies in winter onto the atmosphere during 1979–2013. A maximum covariance analysis shows that this feedback can be detected with monthly data. When SIC leads, the covariability between Atlantic SIC and the Euro-Atlantic atmospheric circulation in February is statistically significant, but shows intraseasonal differences: the December SIC influence is dominated by anomalies east of Greenland, with maximum amplitude in the Greenland Sea (GS); while the January SIC influence is dominated by anomalies west of Greenland, in the Davis Strait-Labrador Sea (DL) region. The lagged atmospheric anomalies are likewise different. A reduction of SIC over GS in December is followed in February by a negative NAO-like pattern near the surface and a hemispheric signature in the upper-troposphere, thus acting as a negative feedback. On the other hand, a reduction of SIC over DL in January is followed by an atmospheric anomaly over the North Atlantic that projects on the positive phase of the East Atlantic pattern. The dynamics associated with these atmospheric anomalies is described, indicating that transient-eddy activity is likely at work in settling the large-scale patterns. The role of concomitant North Atlantic sea surface temperature anomalies is discussed. ; The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement n.308299 (NACLIM – www.naclim.eu). JG-S was partially supported by the H2020-funded MSCA-IF-EF DPETNA project. The authors thank Francis Codron (LOCEAN-IPSL) for discussions and two anonymous reviewers for their comments on the manuscript. ; Peer Reviewed ; Postprint (author's final draft)

Many recent studies have revealed the importance of the climatic state in November on the seasonal climate of the subsequent winter. In particular, it has been shown that interannual variability of sea ice concentration (SIC) over the Barents-Kara (BK) seas in November is linked to winter atmospheric circulation anomaly that projects on the North Atlantic Oscillation. Understanding the lead lag processes involving the different components of the climate system from autumn to winter is therefore important. This note presents dynamical interpretation for the ice-oceanatmosphere relationships that can affect the BK SIC anomaly in late autumn. It is found that cyclonic (anticyclonic) wind anomaly over the Arctic in October, by Ekman drift, can be responsible for positive (negative) SIC in theBKseas in November. The results also suggest that ocean heat transport via the Barents Sea Opening in September and October can contribute to BK SIC anomaly in November. ; JG-S has been supported by the European Union's FP7-funded NACLIM project (ENV-308299) and H2020-funded DPETNA grant (MSCA-IF-EF 655339). MPK acknowledges the Severo Ochoa Visiting Fellowship at the Barcelona Supercomputing Center and the Nordforsk GREENICE project (61841). Mehmet Ilicak and MariusA˚ rthun provided suggestions related to ocean heat transport. Suggestions from the reviewer had also led to improvement in the analyses. ; Peer Reviewed ; Postprint (published version)

Many recent studies have revealed the importance of the climatic state in November on the seasonal climate of the subsequent winter. In particular, it has been shown that interannual variability of sea ice concentration (SIC) over the Barents-Kara (BK) seas in November is linked to winter atmospheric circulation anomaly that projects on the North Atlantic Oscillation. Understanding the lead lag processes involving the different components of the climate system from autumn to winter is therefore important. This note presents dynamical interpretation for the ice-oceanatmosphere relationships that can affect the BK SIC anomaly in late autumn. It is found that cyclonic (anticyclonic) wind anomaly over the Arctic in October, by Ekman drift, can be responsible for positive (negative) SIC in theBKseas in November. The results also suggest that ocean heat transport via the Barents Sea Opening in September and October can contribute to BK SIC anomaly in November. ; JG-S has been supported by the European Union's FP7-funded NACLIM project (ENV-308299) and H2020-funded DPETNA grant (MSCA-IF-EF 655339). MPK acknowledges the Severo Ochoa Visiting Fellowship at the Barcelona Supercomputing Center and the Nordforsk GREENICE project (61841). Mehmet Ilicak and MariusA˚ rthun provided suggestions related to ocean heat transport. Suggestions from the reviewer had also led to improvement in the analyses. ; Peer Reviewed ; Postprint (published version)

The relationship between Eurasian snow cover extent (SCE) and Northern Hemisphere atmospheric circulation is studied in reanalysis during 1979–2014 and in CMIP5 preindustrial control runs. In observations, dipolar SCE anomalies in November, with negative anomalies over eastern Europe and positive anomalies over eastern Siberia, are followed by a negative phase of the Arctic Oscillation (AO) one and two months later. In models, this effect is largely underestimated, but four models simulate such a relationship. In observations and these models, the SCE influence is primarily due to the eastern Siberian pole, which is itself driven by the Scandinavian pattern (SCA), with a large anticyclonic anomaly over the Urals. The SCA is also responsible for a link between Eurasian SCE anomalies and sea ice concentration (SIC) anomalies in the Barents–Kara Sea. Increasing SCE over Siberia leads to a local cooling of the lower troposphere and is associated with warm conditions over the eastern Arctic. This is followed by a polar vortex weakening in December and January, which has an AO-like signature. In observations, the association between November SCE and the winter AO is amplified by SIC anomalies in the Barents–Kara Sea, where large diabatic heating of the lower troposphere occurs, but results suggest that the SCE is the main driver of the AO. Conversely, the sea ice anomalies have little influence in most models, which is consistent with the different SCA variability, the colder mean state, and the underestimation of troposphere–stratosphere coupling simulated in these models. ; The research leading to these results has received funding from the European Union 7th Framework Programme under grant agreement #308299 (NACLIM). Javier García- Serrano also received funding from H2020-funded DPETNA grant (MSCA-IF-EF655339). We thank the European Center for Medium Range Weather Forecast for providing the ERA-Interim reanalysis, the Rutgers University for providing the observed snow cover fields, the National Snow and Ice Data Center for providing the sea ice extent. For their role in producing, coordinating, and making available CMIP5 model outputs, we acknowledge the climate modeling groups, the World Climate Research Programme's Working Group on Coupled Modelling and the Global Organization for Earth System Science Portals. This study benefited from the IPSL mesocenter facility which is supported by CNRS, UPMC, Labex L-IPSL, which is funded by the ANR (Grant #ANR-10-LABX-0018), and by the European FP7 IS-ENES2 project (Grant #312979). ; Peer Reviewed ; Postprint (author's final draft)

The relationship between Eurasian snow cover extent (SCE) and Northern Hemisphere atmospheric circulation is studied in reanalysis during 1979–2014 and in CMIP5 preindustrial control runs. In observations, dipolar SCE anomalies in November, with negative anomalies over eastern Europe and positive anomalies over eastern Siberia, are followed by a negative phase of the Arctic Oscillation (AO) one and two months later. In models, this effect is largely underestimated, but four models simulate such a relationship. In observations and these models, the SCE influence is primarily due to the eastern Siberian pole, which is itself driven by the Scandinavian pattern (SCA), with a large anticyclonic anomaly over the Urals. The SCA is also responsible for a link between Eurasian SCE anomalies and sea ice concentration (SIC) anomalies in the Barents–Kara Sea. Increasing SCE over Siberia leads to a local cooling of the lower troposphere and is associated with warm conditions over the eastern Arctic. This is followed by a polar vortex weakening in December and January, which has an AO-like signature. In observations, the association between November SCE and the winter AO is amplified by SIC anomalies in the Barents–Kara Sea, where large diabatic heating of the lower troposphere occurs, but results suggest that the SCE is the main driver of the AO. Conversely, the sea ice anomalies have little influence in most models, which is consistent with the different SCA variability, the colder mean state, and the underestimation of troposphere–stratosphere coupling simulated in these models. ; The research leading to these results has received funding from the European Union 7th Framework Programme under grant agreement #308299 (NACLIM). Javier García- Serrano also received funding from H2020-funded DPETNA grant (MSCA-IF-EF655339). We thank the European Center for Medium Range Weather Forecast for providing the ERA-Interim reanalysis, the Rutgers University for providing the observed snow cover fields, the National Snow and Ice Data Center for providing the sea ice extent. For their role in producing, coordinating, and making available CMIP5 model outputs, we acknowledge the climate modeling groups, the World Climate Research Programme's Working Group on Coupled Modelling and the Global Organization for Earth System Science Portals. This study benefited from the IPSL mesocenter facility which is supported by CNRS, UPMC, Labex L-IPSL, which is funded by the ANR (Grant #ANR-10-LABX-0018), and by the European FP7 IS-ENES2 project (Grant #312979). ; Peer Reviewed ; Postprint (author's final draft)

Prediction skill of continental climate in the Northern Hemisphere (NH) midlatitudes is generally limited throughout the year in dynamical seasonal forecast systems. Such limitations narrow the range of possible applications by different stakeholders. Improving the predictive capacity in these regions has been a challenging task. Sea ice is a central component of the Arctic climate system and a local source of climate predictability, yet its state is often not fully constrained in dynamical forecast systems. Using the EC-Earth3 climate model, we study the added value of assimilating observed Arctic sea ice concentration on the NH extratropical climate in retrospective forecasts of summer and fall, initialized every spring over 1992–2019. Predictions in the North Atlantic and Eurasia benefit from better initialization of sea ice in the Atlantic sector of the Arctic in a two-step mechanism. Initially, sea ice influences the central North Atlantic Ocean through an atmospheric bridge that develops in the first forecast weeks, subsequently leading to preserved skill in the sea surface temperatures (SSTs) throughout summer and early fall. Secondly, these long-lasting SST improvements provide better surface boundary conditions for the atmosphere and lead to more skillful predictions of circulation and surface climate in the Euro-Atlantic and Asian regions. In addition, our findings suggest that fully coupled ocean-atmosphere-sea ice models are likely necessary to study linkages between Arctic sea ice and midlatitudes, by better representing the interactions and feedbacks between the different components of the climate system. ; The data that support the findings of this study are available upon reasonable request from the authors. This work was funded by the European Union projects APPLICATE (Grant 727862), INTAROS (Grant 727890), and ESA/CMUG-CCI3. J C A N received financial support from the Spanish Ministerio de Ciencia, Innovación y Universidades through a Juan de la Cierva personal grant (FJCI-2017-34027). J G-S ...

The impact of El Niño-Southern Oscillation (ENSO) on the late-winter extra-tropical stratosphere (January–March) is assessed in a multi-model framework. Three state-of-the-art atmospheric models are run with prescribed SST anomalies representative of a strong ENSO event, with symmetric patterns for El Niño and La Niña. The well-known temperature perturbation in the lower stratosphere during El Niño is captured by two models, in which the anomalous warming at polar latitudes is accompanied by a positive geopotential height anomaly that extends over the polar cap. In the third model, which shows a lack of temperature anomalies over the pole, the anomalous anticyclone is confined over Canada and does not expand to the polar cap. This anomalous center of action emerges from the large-scale tropospheric Rossby wave train forced by ENSO, and shrinking/stretching around the polar vortex is invoked to link it to the temperature response. No disagreement across models is found in the lower stratosphere for La Niña, whose teleconnection is opposite in sign but weaker. In the middle-upper stratosphere (above 50 hPa) the geopotential height anomalies project on a wavenumber-1 (WN1) pattern for both El Niño and, more weakly, La Niña, and show a westward tilt with height up to the stratopause. It is suggested that this WN1 pattern arises from the high-latitude lower-stratospheric anomalies, and that the ENSO teleconnection to the polar stratosphere can be interpreted in terms of upward propagation of the stationary Rossby wave train and quasi-geostrophic balance, instead of wave breaking. ; This work was supported by the MEDSCOPE project. MEDSCOPE is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by AEMET (ES), ANR (FR), BSC (ES), CMCC (IT), CNR (IT), IMR (BE) and Météo-France (FR), with co-funding by the European Union (Grant 690462). B.M. and J.G.-S. were supported by the "Contratos Predoctorales para la Formación de Doctores" (BES-2016-076431) and "Ramón y Cajal" (RYC-2016-21181) programmes, respectively. F.M.P. was partially supported by the Spanish DANAE (CGL2015-68342-R) and GRAVITOCAST (ERC2018-092835) projects. Technical support at BSC (Computational Earth Sciences group) is sincerely acknowledged. We also thank the two anonymous reviewers for their helpful feedback. ; Peer Reviewed ; Postprint (published version)

Under the influence of global warming, heatwaves are becoming a major threat in many parts of the world, affecting human health and mortality, food security, forest fires, biodiversity, energy consumption, as well as the production and transportation networks. Seasonal forecasting is a promising tool to help mitigate these impacts on society. Previous studies have highlighted some predictive capacity of seasonal forecast systems for specific strong heatwaves such as those of 2003 and 2010. To our knowledge, this study is thus the first of its kind to systematically assess the prediction skill of heatwaves over Europe in a state-of-the-art seasonal forecast system. One major prerequisite to do so is to appropriately define heatwaves. Existing heatwave indices, built to measure heatwave duration and severity, are often designed for specific impacts and thus have limited robustness for an analysis of heatwave variability. In this study, we investigate the seasonal prediction skill of European summer heatwaves in the ECMWF System 5 operational forecast system by means of several dedicated metrics, as well as its added-value compared to a simple statistical model based on the linear trend. We are able to show, for the first time, that seasonal forecasts initialized in early May can provide potentially useful information of summer heatwave propensity, which is the tendency of a season to be predisposed to the occurrence of heatwaves. ; This work is a contribution to the HyMeX program through the project ERA4CS-MEDSCOPE, co-funded by the Horizon 2020 Framework Program of the European Union (Grant agreement 690462). Chloe Prodhomme and Javier García-Serrano were supported by the Spanish Juan de la Cierva (IJCI-2016-30802) and Ramon y Cajal (RYC-2016-21181) programs, respectively. Rachel H. White received funding from the European Unions Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement 797961. ; Peer Reviewed ; Postprint (published version)

El Niño-Southern Oscillation (ENSO) is known to affect the Northern Hemisphere tropospheric circulation in late-winter (January–March), but whether El Niño and La Niña lead to symmetric impacts and with the same underlying dynamics remains unclear, particularly in the North Atlantic. Three state-of-the-art atmospheric models forced by symmetric anomalous sea surface temperature (SST) patterns, mimicking strong ENSO events, are used to robustly diagnose symmetries and asymmetries in the extra-tropical ENSO response. Asymmetries arise in the sea-level pressure (SLP) response over the North Pacific and North Atlantic, as the response to La Niña tends to be weaker and shifted westward with respect to that of El Niño. The difference in amplitude can be traced back to the distinct energy available for the two ENSO phases associated with the non-linear diabatic heating response to the total SST field. The longitudinal shift is embedded into the large-scale Rossby wave train triggered from the tropical Pacific, as its anomalies in the upper troposphere show a similar westward displacement in La Niña compared to El Niño. To fully explain this shift, the response in tropical convection and the related anomalous upper-level divergence have to be considered together with the climatological vorticity gradient of the subtropical jet, i.e. diagnosing the tropical Rossby wave source. In the North Atlantic, the ENSO-forced SLP signal is a well-known dipole between middle and high latitudes, different from the North Atlantic Oscillation, whose asymmetry is not indicative of distinct mechanisms driving the teleconnection for El Niño and La Niña. ; This work was supported by the MEDSCOPE project. MEDSCOPE is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by AEMET (ES), ANR (FR), BSC (ES), CMCC (IT), CNR (IT), IMR (BE) and Météo-France (FR), with co-funding by the European Union (Grant 690462). B.M. and J.G.-S. were supported by the "Contratos Predoctorales para la Formación de Doctores" (BES-2016-076431) and "Ramón y Cajal" (RYC-2016-21181) programmes, respectively. F.M.P. was partially supported by the Spanish DANAE (CGL2015-68342-R) and GRAVITOCAST (ERC2018-092835) projects. Technical support at BSC (Computational Earth Sciences group) is sincerely acknowledged. We also thank four anonymous reviewers for their valuable insights. ; Peer Reviewed ; Postprint (published version)

El Niño Southern Oscillation (ENSO) represents the major driver of interannual climate variability at global scale. Observational and model-based studies have fostered a long-standing debate on the shape and intensity of the ENSO influence over the Euro-Mediterranean sector. Indeed, the detection of this signal is strongly affected by the large internal variability that characterizes the atmospheric circulation in the North Atlantic–European (NAE) region. This study explores if and how the low-frequency variability of North Pacific sea surface temperature (SST) may impact the El Niño-NAE teleconnection in late winter, which consists of a dipolar pattern between middle and high latitudes. A set of idealized atmosphere-only experiments, prescribing different phases of the anomalous SST linked to the Pacific Decadal Oscillation (PDO) superimposed onto an El Niño-like forcing in the tropical Pacific, has been performed in a multi-model framework, in order to assess the potential modulation of the positive ENSO signal. The modelling results suggest, in agreement with observational estimates, that the PDO negative phase (PDO−) may enhance the amplitude of the El Niño-NAE teleconnection, while the dynamics involved appear to be unaltered. On the other hand, the modulating role of the PDO positive phase (PDO+) is not reliable across models. This finding is consistent with the atmospheric response to the PDO itself, which is robust and statistically significant only for PDO−. Its modulation seems to rely on the enhanced meridional SST gradient and the related turbulent heat-flux released along the Kuroshio–Oyashio extension. PDO− weakens the North Pacific jet, whereby favoring more poleward propagation of wave activity, strengthening the El Niño-forced Rossby wave-train. These results imply that there might be conditional predictability for the interannual Euro-Mediterranean climate variability depending on the background state. ; This work has been performed in the framework of the MEDSCOPE (MEDiterranean Services Chain based on climate PrEdictions) ERA4CS project (grant agreement no. 690462) funded by the European Union. J.G.-S. was supported by the "Ramón y Cajal" programme (RYC-2016-21181). F.M.P. was partially supported by the Spanish DANAE (CGL2015-68342-R) and GRAVITOCAST (ERC2018-092835) projects. We greatly thank the two anonymous reviewers for the insightful and constructive comments and suggestions. ; Postprint (published version)

A set of ensemble integrations from the Coupled Model Intercomparison Project phase 5, with historical forcing plus RCP4.5 scenario, are used to explore if state-of-the-art climate models are able to simulate previously reported linkages between sea-ice concentration (SIC) anomalies over the eastern Arctic, namely in the Greenland–Barents–Kara Seas, and lagged atmospheric circulation that projects on the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO). The study is focused on variability around the long-term trends, so that all anomalies are detrended prior to analysis; the period of study is 1979–2013. The model linkages are detected by applying maximum covariance analysis. As also found in observational data, all the models considered here show a statistically significant link with sea-ice reduction over the eastern Arctic followed by a negative NAO/AO-like pattern. If the simulated relationship is found at a lag of one month, the results suggest that a stratospheric pathway could be at play as the driving mechanism; in observations this is preferentially shown for SIC in November. The interference of a wave-like anomaly over Eurasia, accompanying SIC changes, with the climatological wave pattern appears to be key in setting the mediating role of the stratosphere. On the other hand, if the simulated relationship is found at a lag of two months, the results suggest that tropospheric dynamics are dominant, presumably due to transient eddy feedback; in observations this is preferentially shown for SIC in December. The results shown here and previous evidence from atmosphere-only experiments emphasize that there could be a detectable influence of eastern Arctic SIC variability on mid-latitude atmospheric circulation anomalies. Even if the mechanisms are robust among the models, the timing of the simulated linkages strongly depends on the model and does not generally mimic the observational ones. This implies that the atmospheric sensitivity to sea-ice changes largely depends on the mean-flow and parameterizations, which could lead to misleading conclusions elsewhere if a multi-model ensemble-mean approach is adopted. It might also represent an important source of uncertainty in climate prediction and projection. Modelling efforts are hence further required to improve representation of the background atmospheric circulation and reduce biases, in order to attain more accurate covariability. ; The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement No. 308299 (NACLIM—www.naclim.eu). JG-S was partially supported by the H2020-funded MSCA-IF-EF DPETNA project (GA No. 655339). This work was also supported by the BMBF project CLIMPRE Inter-Dec (FKZ:01LP1609A; DM) and the RCN project KLIMAFORSK InterDec (260393; YG) within the framework of JPI CLIM Belmont-Forum InterDec consortial project. JG-S and MPK thank the 6th Severo Ochoa mobility programme for funding the visit of the latter to BSC-CNS in October 2015. The authors thank Ileana Bladé (UB, Spain) and Lantao Sun (CIRES-NOAA/ESRL, USA) for useful discussions, and Neven S. Fuckar (BSC-CNS) for his help during the review process. Technical support at BSC-CNS (Computational Earth Sciences group) is sincerely acknowledged. The authors are also grateful to the anonymous reviewers for their comments, which helped to improve the clarity of the manuscript. ; Peer Reviewed ; Postprint (author's final draft)

A set of ensemble integrations from the Coupled Model Intercomparison Project phase 5, with historical forcing plus RCP4.5 scenario, are used to explore if state-of-the-art climate models are able to simulate previously reported linkages between sea-ice concentration (SIC) anomalies over the eastern Arctic, namely in the Greenland–Barents–Kara Seas, and lagged atmospheric circulation that projects on the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO). The study is focused on variability around the long-term trends, so that all anomalies are detrended prior to analysis; the period of study is 1979–2013. The model linkages are detected by applying maximum covariance analysis. As also found in observational data, all the models considered here show a statistically significant link with sea-ice reduction over the eastern Arctic followed by a negative NAO/AO-like pattern. If the simulated relationship is found at a lag of one month, the results suggest that a stratospheric pathway could be at play as the driving mechanism; in observations this is preferentially shown for SIC in November. The interference of a wave-like anomaly over Eurasia, accompanying SIC changes, with the climatological wave pattern appears to be key in setting the mediating role of the stratosphere. On the other hand, if the simulated relationship is found at a lag of two months, the results suggest that tropospheric dynamics are dominant, presumably due to transient eddy feedback; in observations this is preferentially shown for SIC in December. The results shown here and previous evidence from atmosphere-only experiments emphasize that there could be a detectable influence of eastern Arctic SIC variability on mid-latitude atmospheric circulation anomalies. Even if the mechanisms are robust among the models, the timing of the simulated linkages strongly depends on the model and does not generally mimic the observational ones. This implies that the atmospheric sensitivity to sea-ice changes largely depends on the mean-flow and parameterizations, which could lead to misleading conclusions elsewhere if a multi-model ensemble-mean approach is adopted. It might also represent an important source of uncertainty in climate prediction and projection. Modelling efforts are hence further required to improve representation of the background atmospheric circulation and reduce biases, in order to attain more accurate covariability. ; The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement No. 308299 (NACLIM—www.naclim.eu). JG-S was partially supported by the H2020-funded MSCA-IF-EF DPETNA project (GA No. 655339). This work was also supported by the BMBF project CLIMPRE Inter-Dec (FKZ:01LP1609A; DM) and the RCN project KLIMAFORSK InterDec (260393; YG) within the framework of JPI CLIM Belmont-Forum InterDec consortial project. JG-S and MPK thank the 6th Severo Ochoa mobility programme for funding the visit of the latter to BSC-CNS in October 2015. The authors thank Ileana Bladé (UB, Spain) and Lantao Sun (CIRES-NOAA/ESRL, USA) for useful discussions, and Neven S. Fuckar (BSC-CNS) for his help during the review process. Technical support at BSC-CNS (Computational Earth Sciences group) is sincerely acknowledged. The authors are also grateful to the anonymous reviewers for their comments, which helped to improve the clarity of the manuscript. ; Peer Reviewed ; Postprint (author's final draft)