Christophe Cassou

The year 2023 shattered numerous heat records globally and regionally. We here focus on the origins of the unprecedented and persistent warm sea surface temperature (SST) anomalies in the North Atlantic Ocean. Using a combination of multiple observational datasets and climate model large ensemble outputs, we show that the 2023 North Atlantic SST event is a manifestation of anthropogenically-forced warming, exacerbated by an extreme phase of internal climate variability and associated regional surface flux anomalies. The long-term stratification increase due to anthropogenically-driven ocean warming amplified the impacts of internal variability. At current global warming level, the 2023 event is assessed as a decadal-type occurrence for SST anomalies averaged across the entire North Atlantic basin, but it is estimated as a centennial-type event for the subtropics and the eastern basin. The distinctive horseshoe-shaped regional distribution of these anomalies is crucial to consider for correct communication and risk assessment in a warming climate.

The study of Decadal Climate Variability (DCV) and Predictability is the interdisciplinary endeavor to characterize, understand, attribute, simulate, and predict the slow, multiyear variations of climate at global (e.g., the recent slowdown of global mean temperature rise in the early 2000s) and regional (e.g., decadal modulation of hurricane activity in the Atlantic, ongoing drought in California or in the Sahel in the 1970s–80s, etc.) scales. This study remains very challenging despite decades of research, extensive progress in climate system modeling, and improvements in the availability and coverage of a wide variety of observations. Considerable obstacles in applying this knowledge to actual predictions remain. This short article is a succint review paper about DCV and predictability. Based on listed issues and priorities, it also proposes a unifying theme referred to as “drivers of teleconnectivity” as a backbone to address and structure the core DCV research challenge. This framework goes beyond a preoccupation with changes in the global mean temperature and directly addresses the regional impacts of external (natural and anthropogenic) climate forcing and internal climate interactions; it thus explicitly deals with the societal needs for region-specific climate information. Such a framework also enables the integration of efforts in a large international research community toward advancing the observation, characterization, understanding, and prediction of DCV. Recommendations to make progress are provided as part of the contribution of the CLIVAR “DCVP Research Focus” group.

Bridging the traditional gap between the spatio-temporal scales of weather and climate is a significant challenge facing the atmospheric community. In particular, progress in both medium-range and seasonal-to-interannual climate prediction relies on our understanding of recurrent weather patterns and the identification of specific causes responsible for their favoured occurrence, persistence or transition. Within this framework, I here present evidence that the main climate intra-seasonal oscillation in the tropics-the Madden-Julian Oscillation (MJO)-controls part of the distribution and sequences of the four daily weather regimes defined over the North Atlantic-European region in winter. North Atlantic Oscillation (NAO) regimes are the most affected, allowing for medium-range predictability of their phase far exceeding the limit of around one week that is usually quoted. The tropical-extratropical lagged relationship is asymmetrical. Positive NAO events mostly respond to a mid-latitude low-frequency wave train initiated by the MJO in the western-central tropical Pacific and propagating eastwards. Precursors for negative NAO events are found in the eastern tropical Pacific-western Atlantic, leading to changes along the North Atlantic storm track. Wave-breaking diagnostics tend to support the MJO preconditioning and the role of transient eddies in setting the phase of the NAO. I present a simple statistical model to quantitatively assess the potential predictability of the daily NAO index or the sign of the NAO regimes when they occur. Forecasts are successful in approximately 70 per cent of the cases based on the knowledge of the previous approximately 12-day MJO phase used as a predictor. This promising skill could be of importance considering the tight link between weather regimes and both mean conditions and the chances of extreme events occurring over Europe. These findings are useful for further stressing the need to better simulate and forecast the tropical coupled ocean-atmosphere dynamics, which is a source of medium-to-long range predictability and is the Achilles' heel of the current seamless prediction suites.

Extratropical SSTs can be influenced by the “reemergence mechanism,” whereby thermal anomalies in the deep winter mixed layer persist at depth through summer and are then reentrained into the mixed layer in the following winter. The impact of reemergence in the North Atlantic Ocean (NAO) upon the climate system is investigated using an atmospheric general circulation model coupled to a mixed layer ocean/thermodynamic sea ice model. The dominant pattern of thermal anomalies below the mixed layer in summer in a 150-yr control integration is associated with the North Atlantic SST tripole forced by the NAO in the previous winter as indicated by singular value decomposition (SVD). To isolate the reemerging signal, two additional 60-member ensemble experiments were conducted in which temperature anomalies below 40 m obtained from the SVD analysis are added to or subtracted from the control integration. The reemerging signal, given by the mean difference between the two 60-member ensembles, causes the SST anomaly tripole to recur, beginning in fall, amplifying through January, and persisting through the following spring. The atmospheric response to these SST anomalies resembles the circulation that created them the previous winter but with reduced amplitude (10–20 m at 500 mb per °C), modestly enhancing the winter-to-winter persistence of the NAO. Changes in the transient eddies and their interactions with the mean flow contribute to the large-scale equivalent barotropic response throughout the troposphere. The latter can also be attributed to the change in occurrence of intrinsic weather regimes.

Diagnostics combining atmospheric reanalysis and station-based temperature data for 1950–2003 indicate that European heat waves can be associated with the occurrence of two specific summertime atmospheric circulation regimes. Evidence is presented that during the record warm summer of 2003, the excitation of these two regimes was significantly favored by the anomalous tropical Atlantic heating related to wetter-than-average conditions in both the Caribbean basin and the Sahel. Given the persistence of tropical Atlantic climate anomalies, their seasonality, and their associated predictability, the suggested tropical–extratropical Atlantic connection is encouraging for the prospects of long-range forecasting of extreme weather in Europe.

The origin of the so-called summer North Atlantic “Horseshoe” (HS) sea surface temperature (SST) mode of variability, which is statistically linked to the next winter's North Atlantic Oscillation (NAO), is investigated from data and experiments with the CCM3 atmospheric general circulation model (AGCM). Lagged observational analyses reveal a linkage between HS and anomalous rainfall in the vicinity of the Atlantic intertropical convergence zone. Prescribing the observed anomalous convection in the model generates forced atmospheric Rossby waves that propagate into the North Atlantic sector. The accompanying perturbations in the surface turbulent and radiative fluxes are consistent with forcing the SST anomalies associated with HS. It is suggested that HS can therefore be interpreted as the remote footprint of tropical atmospheric changes. The ARPEGE AGCM is then used to test if the persistence of HS SST anomalies from summer to late fall can feed back to the atmosphere and have an impact on the n... Abstract The origin of the so-called summer North Atlantic “Horseshoe” (HS) sea surface temperature (SST) mode of variability, which is statistically linked to the next winter's North Atlantic Oscillation (NAO), is investigated from data and experiments with the CCM3 atmospheric general circulation model (AGCM). Lagged observational analyses reveal a linkage between HS and anomalous rainfall in the vicinity of the Atlantic intertropical convergence zone. Prescribing the observed anomalous convection in the model generates forced atmospheric Rossby waves that propagate into the North Atlantic sector. The accompanying perturbations in the surface turbulent and radiative fluxes are consistent with forcing the SST anomalies associated with HS. It is suggested that HS can therefore be interpreted as the remote footprint of tropical atmospheric changes. The ARPEGE AGCM is then used to test if the persistence of HS SST anomalies from summer to late fall can feed back to the atmosphere and have an impact on the n...

The relationship between global sea surface temperatures (SSTs) and the North Atlantic–Europe (NAE) atmospheric circulation is investigated using an ensemble of eight simulations with the ARPEGE atmospheric global circulation model forced with prescribed SSTs over the 1948–97 period. The model mean state is first validated against NCEP reanalyses. The interannual SST-forced variability is then compared to the internal one using analysis of variance (ANOVA) techniques. Both components are maximum in winter over the Northern Hemisphere and the associated potential predictability shows weak but significant values located over the Icelandic low (IL) and the Azores high (AH). The North Atlantic oscillation (NAO) is found to be the leading internal variability mode over the NAE sector as shown by principal component analysis of a control simulation with climatological SSTs. The noise imprint dominates the forced response estimated from the ensemble mean. The latter is related first to the El Niño–South... Abstract The relationship between global sea surface temperatures (SSTs) and the North Atlantic–Europe (NAE) atmospheric circulation is investigated using an ensemble of eight simulations with the ARPEGE atmospheric global circulation model forced with prescribed SSTs over the 1948–97 period. The model mean state is first validated against NCEP reanalyses. The interannual SST-forced variability is then compared to the internal one using analysis of variance (ANOVA) techniques. Both components are maximum in winter over the Northern Hemisphere and the associated potential predictability shows weak but significant values located over the Icelandic low (IL) and the Azores high (AH). The North Atlantic oscillation (NAO) is found to be the leading internal variability mode over the NAE sector as shown by principal component analysis of a control simulation with climatological SSTs. The noise imprint dominates the forced response estimated from the ensemble mean. The latter is related first to the El Niño–South...

This paper provides a detailed illustration that it is beneficial for ENSO forecasting to improve in priority the model parameterizations, instead of increasing only the consistency of the initial conditions with the coupled model. Moreover it is shown that the latter can lead to misleading results. Using sea level data in addition to wind to initialize the Cane and Zebiak model does not improve El Niño forecasts. Nudging the observed wind to the model one to initialize the forecasts as proposed by Chen et al. also fails to correct the model deficiencies and degrades the initial conditions of the ocean and atmosphere. These failures are explained by large model errors in the off-equatorial sea level and wind anomalies that play a key role in the coupled behavior. The use of data to estimate new model parameterizations allows for significantly improving both the initial conditions and the forecasts up to 6-month lead time. This success holds for all the various initialization procedures used in this study. Because of erroneous winds simulated by the atmospheric component in the eastern Pacific, errors grow fast though. Replacing the atmospheric model by a statistical one results in more reliable predictions over 1980–98. For lead times up to 1 yr, the model predicts well the observed anomalies between 1984 and 1993, including the sea level rises along the ITCZ after warm events and their subsequent equatorward migration. This success is attributed to the consistency between the observed anomalies over this period and the mechanisms involved in maintaining the oscillatory behavior of the model, including the off-equatorial meridional wind anomalies.