Nitrous oxide (N2O) is a greenhouse gas and an ozone-depleting agent with large and growing anthropogenic emissions. Previous studies identified the influx of N2O-depleted air from the stratosphere to partly cause the seasonality in tropospheric N2O (aN2O), but other contributions remain unclear. Here we combine surface fluxes from eight land and four ocean models from phase 2 of the Nitrogen/N2O Model Intercomparison Project with tropospheric transport modeling to simulate aN2O at the air sampling sites: Alert, Barrow, Ragged Point, Samoa, Ascension Island, and Cape Grim for the modern and preindustrial periods. Models show general agreement on the seasonal phasing of zonal-average N2O fluxes for most sites, but, seasonal peak-to-peak amplitudes differ severalfold across models. After transport, the seasonal amplitude of surface aN2O ranges from 0.25 to 0.80 ppb (interquartile ranges 21-52% of median) for land, 0.14 to 0.25 ppb (19-42%) for ocean, and 0.13 to 0.76 ppb (26-52%) for combined flux contributions. The observed range is 0.53 to 1.08 ppb. The stratospheric contributions to aN2O, inferred by the difference between surface-troposphere model and observations, show 36-126% larger amplitudes and minima delayed by ~1 month compared to Northern Hemisphere site observations. Our results demonstrate an increasing importance of land fluxes for aN2O seasonality, with land fluxes and their seasonal amplitude increasing since the preindustrial era and are projected to grow under anthropogenic activities. In situ aN2O observations and atmospheric transport-chemistry models will provide opportunities for constraining terrestrial and oceanic biosphere models, critical for projecting surface N2O sources under ongoing global warming.

The ocean is a major carbon sink and takes up 25-30% of the anthropogenically emitted CO2. A state-of-the-art method to quantify this sink are global ocean biogeochemistry models (GOBMs) but their simulated CO2 uptake differs between models and is systematically lower than estimates based on statistical methods using surface ocean pCO2 and interior ocean measurements. Here, we provide an in-depth evaluation of ocean carbon sink estimates from 1980 to 2018 from a GOBM ensemble. As sources of inter-model differences and ensemble-mean biases our study identifies the (i) model set-up, such as the length of the spin-up, the starting date of the simulation, and carbon fluxes from rivers and into sediments, (ii) the ocean circulation, such as Atlantic Meridional Overturning Circulation and Southern Ocean mode and intermediate water formation, and (iii) the oceanic buffer capacity. Our analysis suggests that the late starting date and biases in the ocean circulation cause a too low anthropogenic CO2 uptake across the GOBM ensemble. Surface ocean biogeochemistry biases might also cause simulated anthropogenic fluxes to be too low but the current set-up prevents a robust assessment. For simulations of the ocean carbon sink, we recommend in the short-term to (1) start simulations in 1765, when atmospheric CO2 started to increase, (2) conduct a sufficiently long spin-up such that the GOBMs reach steady-state, and (3) provide key metrics for circulation, biogeochemistry, and the land-ocean interface. In the long-term, we recommend improving the representation of these metrics in the GOBMs.

Mesoscale eddies regulate the ocean heat and carbon budgets. However, how and where the kinetic energy flows out from the mesoscale reservoir remains uncertain. In this study, a simplified equation of the mesoscale energy budget is used to obtain a global estimation of the eddy dissipation rate. This framework is first validated in a global ocean model and then applied to a density climatology and a global reconstruction of the eddy kinetic energy field. We find a global disipation rate of 0.66±0.19 TW for the mesoscale kinetic energy, in agreement with recent independent estimates. The results also show an intense dissipation near western boundary currents and in the Antarctic Circumpolar Current, where both large levels of energy and baroclinic conversion occur. The resulting geographical distribution of the dissipation rate brings new insights for closing the ocean kinetic energy budget, as well as constraining future mesoscale parameterizations and associated mixing processes.

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.

Climate change is anticipated to considerably reduce global marine fish biomass, driving marine ecosystems into unprecedented states with no historical analogues. The Time of Emergence (ToE) marks the pivotal moment when climate conditions (i.e. signal) deviate from pre-industrial norms (i.e. noise). Leveraging ensemble climate-to-fish simulations, this study examines the ToE of epipelagic, migratory and mesopelagic fish biomass, alongside their main environmental drivers, for two contrasted climate-change scenarios. Globally-averaged biomass signals emerge over the historical period. Epipelagic biomass decline emerges earlier (1950) than mesozooplankton decline (2000) due to a stronger signal in the early 20th century, possibly related to trophic amplification induced by an early-emerging surface warming (1915). Trophic amplification is delayed for mesopelagic biomass due to postponed warming in the mesopelagic zone, resulting in a later emergence (2000). ToE displays strong size class dependence, with medium sizes (20 cm) experiencing delays compared to the largest (1 m) and smallest (1 cm) categories. Regional signal emergence lags behind the global average, with median ToE estimates of 2029, 2034 and 2033 for epipelagic, mesopelagic and migrant communities, respectively, due to systematically larger local noise compared to global one. These ToEs are also spatially heterogeneous, driven predominantly by the signal pattern, akin to mesozooplankton. Additionally, our findings underscore that mitigation efforts (i.e. transitioning from SSP5-8.5 to SSP1-2.6 scenario) have a potential to curtail emerging ocean surface signals by 40%.

The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). Major advances have improved our understanding of the coastal air-sea exchanges of these three gasses since the first phase of the Regional Carbon Cycle Assessment and Processes (RECCAP in 2013), but a comprehensive view that integrates the three gasses at the global scale is still lacking. In this second phase (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ~60% larger in models (-0.72 vs. -0.44 PgC/yr, 1998-2018, coastal ocean area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e /yr in observational product and +0.54 PgCO2-e /yr in model median) and of CH4 (+0.21 PgCO2-e /yr in observational product), which offsets a substantial proportion of the net radiative effect of coastal \co uptake (35-58% in CO2-equivalents). Data products and models need improvement to better resolve the spatio-temporal variability and long term trends in CO2, N2O and CH4 in the global coastal ocean.

Inter-annual to decadal variability in the strength of the land and ocean carbon sinks impede accurate predictions of year-to-year atmospheric carbon dioxide (CO2) growth rate. Such information is crucial to verify the effectiveness of fossil fuel emissions reduction measures. Using a multi-model framework comprising prediction systems based on Earth system models, we find a predictive skill for the global ocean carbon sink of up to 6 years. Longer regional predictability horizons and robust spatial patterns are found across single models. On land, a predictive skill of up to 2 years is primarily maintained in the tropics and extra-tropics enabled by the initialization of the physical climate variables towards observations. We further show that anomalies of atmospheric CO2 growth rate inferred from natural variations of the land and ocean carbon sinks are predictable at lead time of 2 years and the skill is limited by the land carbon sink predictability horizon.