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Frankignoul, Claude
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Frankignoul, Claude
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- PublicationOpen AccessImpacts of Arctic Sea Ice on Cold Season Atmospheric Variability and Trends Estimated from Observations and a Multi-model Large Ensemble(2021-10-01)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ;To examine the atmospheric responses to Arctic sea ice variability in the Northern Hemisphere cold season (from October to the following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily varying sea ice, sea surface temperature, and radiative forcings prescribed during the 1979–2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multimodel ensemble mean (MMEM) shows decreasing sea level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drive a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual covariability between sea ice extent in the Barents–Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the covariability in MMEMs. The interannual sea ice decline followed by a negative North Atlantic Oscillation–like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship.56 15 - PublicationOpen AccessForcing and impact of the Northern Hemisphere continental snow cover in 1979–2014(2023)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ; ; ; ;The main drivers of the continental Northern Hemisphere snow cover are investigated in the 1979–2014 period. Four observational datasets are used as are two large multi-model ensembles of atmosphere-only simulations with prescribed sea surface temperature (SST) and sea ice concentration (SIC). A first ensemble uses observed interannually varying SST and SIC conditions for 1979–2014, while a second ensemble is identical except for SIC with a repeated climatological cycle used. SST and external forcing typically explain 10 % to 25 % of the snow cover variance in model simulations, with a dominant forcing from the tropical and North Pacific SST during this period. In terms of the climate influence of the snow cover anomalies, both observations and models show no robust links between the November and April snow cover variability and the atmospheric circulation 1 month later. On the other hand, the first mode of Eurasian snow cover variability in January, with more extended snow over western Eurasia, is found to precede an atmospheric circulation pattern by 1 month, similar to a negative Arctic oscillation (AO). A decomposition of the variability in the model simulations shows that this relationship is mainly due to internal climate variability. Detailed outputs from one of the models indicate that the western Eurasia snow cover anomalies are preceded by a negative AO phase accompanied by a Ural blocking pattern and a stratospheric polar vortex weakening. The link between the AO and the snow cover variability is strongly related to the concomitant role of the stratospheric polar vortex, with the Eurasian snow cover acting as a positive feedback for the AO variability in winter. No robust influence of the SIC variability is found, as the sea ice loss in these simulations only drives an insignificant fraction of the snow cover anomalies, with few agreements among models.29 3 - PublicationOpen AccessInfluence of Atlantic SST anomalies on the atmospheric circulation in the Atlantic-European sector(2003)
; ; ; ;Frankignoul, C.; Laboratoire d Océanographie Dynamique et de Climatologie, Unité Mixte de Recherche CNRS-IRD-UPMC,Université Pierre et Marie Curie, Paris, France ;Friederichs, P.; Laboratoire d Océanographie Dynamique et de Climatologie, Unité Mixte de Recherche CNRS-IRD-UPMC,Université Pierre et Marie Curie, Paris, France ;Kestenare, E.; Laboratoire d Océanographie Dynamique et de Climatologie, Unité Mixte de Recherche CNRS-IRD-UPMC,Université Pierre et Marie Curie, Paris, France; ; Recent studies of observational data suggest that Sea Surface Temperature (SST) anomalies in the Atlantic Ocean have a significant influence on the atmospheric circulation in the Atlantic-European sector in early winter and in spring. After reviewing this work and showing that the spring signal is part of a global air-sea interaction, we analyze for comparison an ensemble of simulations with the ECHAM4 atmospheric general circulation model in T42 resolution forced by the observed distribution of SST and sea ice, and a simulation with the ECHAM4/OPA8 coupled model in T30 resolution. In the two cases, a significant influence of the Atlantic on the atmosphere is detected in the Atlantic-European sector. In the forced mode, ECHAM4 responds to SST anomalies from early spring to late summer, and also in early winter. The forcing involves SST anomalies not only in the tropical Atlantic, but also in the whole tropical band, suggesting a strong ENSO influence. The modeled signal resembles that seen in the observations in spring, but not in early winter. In the coupled mode, the Atlantic SST only has a significant influence on the atmosphere in summer. Although the SST anomaly is confined to the Atlantic, the summer signal shows some similarity with that seen in the forced simulations. However, there is no counterpart in the observations.194 2012 - PublicationOpen AccessQuantification of the Arctic Sea Ice‐Driven Atmospheric Circulation Variability in Coordinated Large Ensemble Simulations(2020)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ; ; ; ;A coordinated set of large ensemble atmosphere‐only simulations is used to investigatethe impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability andvariability driven by other forcings including sea surface temperature and greenhouse gases. The geographicpattern of SIDV is consistent across seven participating models, but its magnitude strongly depends onensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2for Arctic‐averaged sea level pressure(~1.5% of the total variance), and ~0.35 K2for surface air temperature (~21%) at interannual and longertimescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV fromother components for dynamical (thermodynamical) variables, and insufficient ensemble size always leadsto overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by otherforcings over northern Eurasia and Arctic.66 28 - PublicationRestrictedGulf Stream Variability in Five Oceanic General Circulation Models(2006-11)
; ; ; ; ; ; ; ;De Cetlogon, G.; Centre d’Etude Terrestre et Planétaire, IUT de Vélizy, Vélizy, France ;Frankignoul, C.; Laboratoire d’Océanographie Dynamique et de Climatologie, Université Pierre et Marie Curie, Paris, France ;Bentsen, M.; Nansen Environmental and Remote Sensing Center, Bergen, Norway ;Delon, C.; Laboratoire d’Aérologie, Observatoire Midi Pyrénées, Toulouse, France ;Haak, H.; Max Planck Institute for Meteorology, Hamburg, Germany ;Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Pardaens, A.; Hadley Centre for Climate Prediction and Research, Met Office, Exeter, United Kingdom; ; ; ; ; ; Five non-eddy-resolving oceanic general circulation models driven by atmospheric fluxes derived from the NCEP reanalysis are used to investigate the link between the Gulf Stream (GS) variability, the atmospheric circulation, and the Atlantic meridional overturning circulation (AMOC). Despite the limited model resolution, the temperature at the 200-m depth along the mean GS axis behaves similarly in most models to that observed, and it is also well correlated with the North Atlantic Oscillation (NAO), indicating that a northward (southward) GS shift lags a positive (negative) NAO phase by 0–2 yr. The northward shift is accompanied by an increase in the GS transport, and conversely the southward shift with a decrease in the GS transport. Two dominant time scales appear in the response of the GS transport to the NAO forcing: a fast time scale (less than 1 month) for the barotropic component, and a slower one (about 2 yr) for the baroclinic component. In addition, the two components are weakly coupled. The GS response seems broadly consistent with a linear adjustment to the changes in the wind stress curl, and evidence for baroclinic Rossby wave propagation is found in the southern part of the subtropical gyre. However, the GS shifts are also affected by basin-scale changes in the oceanic conditions, and they are well correlated in most models with the changes in the AMOC. A larger AMOC is found when the GS is stronger and displaced northward, and a higher correlation is found when the observed changes of the GS position are used in the comparison. The relation between the GS and the AMOC could be explained by the inherent coupling between the thermohaline and the wind-driven circulation, or by the NAO variability driving them on similar time scales in the models.150 21