The CNRM-Cerfacs Climate Prediction System (C3PS) is a new research modeling tool for performing climate reanalyses and seasonal-to-multiannual predictions for a wide array of earth system variables. C3PS is based on the CNRM-ESM2-1 model including interactive aerosols and stratospheric chemistry schemes as well as terrestrial and marine biogeochemistry enabling a comprehensive representation of the global carbon cycle. C3PS operates through a seamless coupled initialization for the atmosphere, land, ocean, sea ice and biogeochemistry components that allows a continuum of predictions across seasonal to interannual time-scales. C3PS has also contributed to the Decadal Climate Prediction Project (DCPP-A) as part of the sixth Coupled Model Intercomparison Project (CMIP6). Here we describe the main characteristics of this novel earth system-based prediction platform, including the methodological steps for obtaining initial states to produce forecasts. We evaluate the entire C3PS initialisation procedure with the most up-to-date observations and reanalysis over 1960-2021, and we discuss the overall performance of the system in the light of the lessons learnt from previous and actual prediction platforms. Regarding the forecast skill, C3PS exhibits comparable seasonal predictive skill to other systems. At the decadal scale, C3PS shows significant predictive skill in surface temperature during the first two years after initialisation in several regions of the world. C3PS also exhibits potential predictive skill in net primary production and carbon fluxes several years in advance. This expands the possibility of applications of forecasting systems, such as the possibility of performing multi-annual predictions of marine ecosystems and carbon cycle.

Wind renewable energy (WRE) is an essential component of the global sustainable energy portfolio. Recently, there has been increasing discussion on the potential supplementation of this conventional mitigation portfolio with Solar Radiation Modification (SRM). However, the impact of SRM on conventional mitigation measures has received limited attention to date. In this study, we explore one part of this impact, the potential effect of one type of SRM, Stratospheric Aerosol Injections (SAI), on WRE. Using hourly output from the Earth System Model CNRM-ESM2-1, we compare WRE potential under a medium emission scenario (SSP245) and a high emission scenario (SSP585) with an SRM scenario that has SSP585 baseline conditions and uses SAI to offset warming to approximately SSP245 global warming levels. Our results suggest that SAI may affect surface wind resources by modifying large-scale circulation patterns, such as a significant poleward jet-shift in the Southern Hemisphere. The modeled total global WRE potential is negligibly reduced under SAI compared to the SSP-scenarios. However, regional trends are highly variable, with large increases and decreases in WRE potential frequently reaching up to 16 % across the globe with SAI. This study highlights potential downstream effects of SRM on climatic elements, such as wind patterns, and offers perspectives on its implications for our mitigation efforts.

Clear-Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather-related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different regions in the Northern Hemisphere over the period 1980-2021. The signal-to-noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to global warming. In contrast, over the North Atlantic and North Pacific the internal climate variability is too strong to detect a response to anthropogenic forcing in the observed trends. Future climate projections show that over several regions in the Northern Hemisphere, CAT is projected to increase with a high model agreement and independently of the CAT diagnostic used. The largest increase in CAT is projected to occur over East Asia. In the North Atlantic, large uncertainty remains due to lack of model agreement and differences among the various CAT diagnostics.

Northwestern North America has experienced an exceptional heatwave in late June 2021 with many new temperature records across western Canada, Oregon and Washington states. Here we use a recent atmospheric reanalysis and a conditional approach based on dynamical adjustment to assess and quantify the influence of atmospheric circulation and other driving factors to the heatwave magnitude during the June 28–30 period. A blocking anticyclone, enhanced low-level moisture and clear-sky downward long-wave radiation are shown to be the main factors of the heatwave persistence and magnitude. The heatwave magnitude is mainly attributable to internal variability with climate change being an additional factor (10%). Consequences of a similar atmospheric circulation anomaly in different phases of the Atlantic Multidecadal and Pacific Decadal Oscillations and in a warmer world at different global warming levels (1, 2, 3 and 4°C) are explored based on a single model initial-condition large ensemble.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and mid-latitude countries. In this study we assess the performance of a multi-model ensemble of climate models, at resolutions ranging from 250km to 25km. 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 10m wind speeds by 2050.