Abstract. Future climate change will affect marine productivity, as well as other many components of Earth system. We have investigated the response of marine productivity to global warming with two different ocean biogeochemical schemes and two different atmosphere-ocean coupled general circulation models (GCM). Both coupled GCMs were used without flux correction to simulate climate response to increased greenhouse gases (+1% CO2/yr for 80 years). At 2xCO2, increased stratification leads to both reduced nutrient supply and increased light efficiency. Both effects drive a reduction in marine export production (-6%), although regionally changes can be both negative and positive (from-15% zonal average in the tropics to +10% in the Southern Ocean). Both coupled models and both biogeochemical schemes simulate a poleward shift of marine production due mainly to a longer growing season at high latitudes. At low latitudes, the effect of reduced upwelling prevails. The resulting reduction in marine productivity, and other marine resources, could become detectable in the near future, if appropriate long-term observing systems are implemented.

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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.

This paper describes the main characteristics of CNRM-CM6-1, the fully coupled atmosphere-ocean general circulation model of sixth generation jointly developed by Centre National de Recherches Météorologiques (CNRM) and Cerfacs for the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6). The paper provides a description of each component of CNRM-CM6-1, including the coupling method and the new online output software. We emphasize where model's components have been updated with respect to the former model version, CNRM-CM5.1. In particular, we highlight major improvements in the representation of atmospheric and land processes. A particular attention has also been devoted to mass and energy conservation in the simulated climate system to limit long-term drifts. The climate simulated by CNRM-CM6-1 is then evaluated using CMIP6 historical and Diagnostic, Evaluation and Characterization of Klima (DECK) experiments in comparison with CMIP5 CNRM-CM5.1 equivalent experiments. Overall, the mean surface biases are of similar magnitude but with different spatial patterns. Deep ocean biases are generally reduced, whereas sea ice is too thin in the Arctic. Although the simulated climate variability remains roughly consistent with CNRM-CM5.1, its sensitivity to rising CO 2 has increased: the equilibrium climate sensitivity is 4.9 K, which is now close to the upper bound of the range estimated from CMIP5 models.

Abstract:Two downscaling methods designed for the study of the hydrological impact of climate change on the Seine basin in France are tested for present climate. First, a multivariate statistical downscaling (SD) methodology based on weather typing and conditional resampling is described. Then, a bias correction technique for dynamical downscaling based on quantile-quantile mapping is introduced. To evaluate the end-to-end SD methodology, the atmospheric forcing derived from the large-scale circulation (LSC) of the ERA40 reanalysis by SD is used to force a hydrological model. Simulated discharges reproduce historical values reasonably well. Next, the dynamical and statistical approaches are compared using the Météo-France ARPEGE general circulation model in a variable resolution configuration (resolution around 60 km over France). The ARPEGE simulation is downscaled using the two methodologies, and hydrological simulations are performed. Regarding downscaled temperature and precipitation, the statistical approach is more efficient in reproducing the temporal and spatial autocorrelation properties. The simulated river discharges from the two approaches are nevertheless very similar: the two methods reproduce well the seasonal cycle and the daily distribution of streamflows. Finally, the results of the study are discussed from a practical impact study perspective.

A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ~0.5 to ~0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

The observed low-frequency winter atmospheric variability of the North Atlantic-European region and its relationship with global surface oceanic conditions is investigated based on the climate and weather regimes paradigm. Asymmetries between the two phases of the North Atlantic Oscillation (NAO) are found in the position of the Azores high and, to a weaker extent, the Icelandic low. There is a significant eastward displacement or expansion toward Europe for the NAOϩ climate regime compared to the NAOϪ regime. This barotropic signal is found in different datasets and for two quasi-independent periods of record (1900-60 and 1950-2001); hence, it appears to be intrinsic to the NAOϩ phase. Strong spatial similarities between weather and climate regimes suggest that the latter, representing long time scale variability, can be interpreted as the time-averaging signature of much shorter time scale processes. Model results from the ARPEGE atmospheric general circulation model are used to validate observed findings. They confirm in particular the eastward shift of the Atlantic centers of action for the NAOϩ phase and strongly suggest a synoptic origin as it can be extracted from daily analyses. These results bring together present-day climate variability and scenario studies where such an NAO shift was suggested, as it is shown that the last three decades are clearly dominated by the occurrence of NAOϩ regimes when concentrations of greenhouse gases are rapidly increasing. These findings highlight that the displacement of the North Atlantic centers of action should be treated as a dynamical property of the North Atlantic atmosphere and not as a mean longitudinal shift of climatological entities in response to anthropogenic forcings. The nonstationarity with time of the atmospheric variability is documented. Late-century decades differ from early ones by the predominance of NAO climate regimes versus others. In such a context, comments on the relevance of the station-based NAO index is provided. Both tropical and extratropical sea surface temperature (SST) anomalies alter the frequency distribution of the North Atlantic regimes. Evidence is presented that the so-called ridge regime is preferably excited during La Niña events, while the NAO regimes are associated with the North Atlantic SST tripole. The ARPEGE model results indicate that the tropical branch of the SST tripole affects the NAO regimes occurrence. Warm tropical SST anomalies are more efficient at exciting NAOϪ regimes than cold anomalies are at forcing NAOϩ regimes. The extratropical portion of the North Atlantic SST tripole also seems to play a significant role in the model, tending to counteract the dominant influence of the tropical Atlantic basin on NAO regimes.

This study elucidates the physical mechanisms underlying internal and forced components of winter surface air temperature (SAT) trends over North America during the past 50 years (1963–2012) using a combined observational and modeling framework. The modeling framework consists of 30 simulations with the Community Earth System Model (CESM) at 1° latitude–longitude resolution, each of which is subject to an identical scenario of historical radiative forcing but starts from a slightly different atmospheric state. Hence, any spread within the ensemble results from unpredictable internal variability superimposed upon the forced climate change signal. Constructed atmospheric circulation analogs are used to estimate the dynamical contribution to forced and internal components of SAT trends: thermodynamic contributions are obtained as a residual. Internal circulation trends are estimated to account for approximately one-third of the observed wintertime warming trend over North America and more than half locally over parts of Canada and the United States. Removing the effects of internal atmospheric circulation variability narrows the spread of SAT trends within the CESM ensemble and brings the observed trends closer to the model’s radiatively forced response. In addition, removing internal dynamics approximately doubles the signal-to-noise ratio of the simulated SAT trends and substantially advances the “time of emergence” of the forced component of SAT anomalies. The methodological framework proposed here provides a general template for improving physical understanding and interpretation of observed and simulated climate trends worldwide and may help to reconcile the diversity of SAT trends across the models from phase 5 of the Coupled Model Intercomparison Project (CMIP5).