Centre National de Recherches Météorologiques

Abstract. Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.

A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. The first set of simulations with a horizontal resolution of 12.5 km was completed for the new emission scenarios RCP4.5 and RCP8.5 with more simulations expected to follow. The aim of this paper is to present this data set to the different communities active in regional climate modelling, impact assessment and adaptation. The EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The large-scale patterns of changes in mean temperature and precipitation are similar in all three scenarios, but they differ in regional details, which can partly be related to the higher resolution in EURO-CORDEX. The results strengthen those obtained in ENSEMBLES, but need further investigations. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate – the “global carbon budget” – is important tobetter understand the global carbon cycle, support the development ofclimate policies, and project future climate change. Here we describe andsynthesize data sets and methodology to quantify the five major componentsof the global carbon budget and their uncertainties. Fossil CO2emissions (EFOS) are based on energy statistics and cement productiondata, while emissions from land-use change (ELUC), mainlydeforestation, are based on land use and land-use change data andbookkeeping models. Atmospheric CO2 concentration is measured directlyand its growth rate (GATM) is computed from the annual changes inconcentration. The ocean CO2 sink (SOCEAN) and terrestrialCO2 sink (SLAND) are estimated with global process modelsconstrained by observations. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the lastdecade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), andELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ± 0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budgetimbalance BIM of −0.1 GtC yr−1 indicating a near balance betweenestimated sources and sinks over the last decade. For the year 2019 alone, thegrowth in EFOS was only about 0.1 % with fossil emissions increasingto 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEANwas 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminarydata for 2020, accounting for the COVID-19-induced changes in emissions,suggest a decrease in EFOS relative to 2019 of about −7 % (medianestimate) based on individual estimates from four studies of −6 %, −7 %,−7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in thecomponents of the global carbon budget are consistently estimated over theperiod 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for therepresentation of semi-decadal variability in CO2 fluxes. Comparison ofestimates from diverse approaches and observations shows (1) no consensusin the mean and trend in land-use change emissions over the last decade, (2)a persistent low agreement between the different methods on the magnitude ofthe land CO2 flux in the northern extra-tropics, and (3) an apparentdiscrepancy between the different methods for the ocean sink outside thetropics, particularly in the Southern Ocean. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set (Friedlingstein et al.,2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014,2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

A parameterization of land surface processes to be included in mesoscale and large-scale meteorological models is presented. The number of parameters has been reduced as much as possible, while attempting to preserve the representation of the physics which controls the energy and water budgets. We distinguish two main classes of parameters. The spatial distribution of primary parameters, i.e., the dominant types of soil and vegetation within each grid cell, can be specified from existing global datasets. The secondary parameters, describing the physical properties of each type of soil and vegetation, can be inferred from measurements or derived from numerical experiments. A single surface temperature is used to represent the surface energy balance of the land/cover system. The soil heat flux is linearly interpolated between its value over bare ground and a value of zero for complete shielding by the vegetation. The ground surface moisture equation includes the effect of gravity and the thermo-hydric coefficients of the equations have been either calculated or calibrated using textural dependent formulations. The calibration has been made using the results of a detailed soil model forced by prescribed atmospheric mean conditions. The results show that the coefficients of the surface soil moisture equation are greatly dependent upon the textural class of the soil, as well as upon its moisture content. The new scheme has been included in a one-dimensional model which allows a complete interaction between the surface and the atmosphere. Several simulations have been performed using data collected during HAPEX-MOBILHY. These first results show the ability of the parameterization to reproduce the components of the surface energy balance over a wide variety of surface conditions.

The Mediterranean Sea is a marine biodiversity hot spot. Here we combined an extensive literature analysis with expert opinions to update publicly available estimates of major taxa in this marine ecosystem and to revise and update several species lists. We also assessed overall spatial and temporal patterns of species diversity and identified major changes and threats. Our results listed approximately 17,000 marine species occurring in the Mediterranean Sea. However, our estimates of marine diversity are still incomplete as yet-undescribed species will be added in the future. Diversity for microbes is substantially underestimated, and the deep-sea areas and portions of the southern and eastern region are still poorly known. In addition, the invasion of alien species is a crucial factor that will continue to change the biodiversity of the Mediterranean, mainly in its eastern basin that can spread rapidly northwards and westwards due to the warming of the Mediterranean Sea. Spatial patterns showed a general decrease in biodiversity from northwestern to southeastern regions following a gradient of production, with some exceptions and caution due to gaps in our knowledge of the biota along the southern and eastern rims. Biodiversity was also generally higher in coastal areas and continental shelves, and decreases with depth. Temporal trends indicated that overexploitation and habitat loss have been the main human drivers of historical changes in biodiversity. At present, habitat loss and degradation, followed by fishing impacts, pollution, climate change, eutrophication, and the establishment of alien species are the most important threats and affect the greatest number of taxonomic groups. All these impacts are expected to grow in importance in the future, especially climate change and habitat degradation. The spatial identification of hot spots highlighted the ecological importance of most of the western Mediterranean shelves (and in particular, the Strait of Gibraltar and the adjacent Alboran Sea), western African coast, the Adriatic, and the Aegean Sea, which show high concentrations of endangered, threatened, or vulnerable species. The Levantine Basin, severely impacted by the invasion of species, is endangered as well. This abstract has been translated to other languages (File S1).

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate is critical to better understand the global carboncycle, support the development of climate policies, and project futureclimate change. Here we describe and synthesize data sets and methodologies toquantify the five major components of the global carbon budget and theiruncertainties. Fossil CO2 emissions (EFOS) are based on energystatistics and cement production data, while emissions from land-use change(ELUC), mainly deforestation, are based on land use and land-use changedata and bookkeeping models. Atmospheric CO2 concentration is measureddirectly, and its growth rate (GATM) is computed from the annualchanges in concentration. The ocean CO2 sink (SOCEAN) is estimatedwith global ocean biogeochemistry models and observation-baseddata products. The terrestrial CO2 sink (SLAND) is estimated withdynamic global vegetation models. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, withfossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission(including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1(40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with aBIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low orsinks were too high). The global atmospheric CO2 concentration averaged over2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest anincrease in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %)globally and atmospheric CO2 concentration reaching 417.2 ppm, morethan 50 % above pre-industrial levels (around 278 ppm). Overall, the meanand trend in the components of the global carbon budget are consistentlyestimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadalvariability in CO2 fluxes. Comparison of estimates from multipleapproaches and observations shows (1) a persistent large uncertainty in theestimate of land-use change emissions, (2) a low agreement between thedifferent methods on the magnitude of the land CO2 flux in the northernextratropics, and (3) a discrepancy between the different methods on thestrength of the ocean sink over the last decade. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set. The data presented inthis work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

Abstract This study presents the global climate model IPSL‐CM6A‐LR developed at Institut Pierre‐Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone [ITCZ], frequency of midlatitude wintertime blockings, and El Niño–Southern Oscillation [ENSO] dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850–2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biosphere– the “global carbon budget” – is important to better understand theglobal carbon cycle, support the development of climate policies, andproject future climate change. Here we describe data sets and methodology toquantify the five major components of the global carbon budget and theiruncertainties. Fossil CO2 emissions (EFF) are based on energystatistics and cement production data, while emissions from land use change(ELUC), mainly deforestation, are based on land use and land use changedata and bookkeeping models. Atmospheric CO2 concentration is measureddirectly and its growth rate (GATM) is computed from the annual changesin concentration. The ocean CO2 sink (SOCEAN) and terrestrialCO2 sink (SLAND) are estimated with global process modelsconstrained by observations. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the lastdecade available (2009–2018), EFF was 9.5±0.5 GtC yr−1,ELUC 1.5±0.7 GtC yr−1, GATM 4.9±0.02 GtC yr−1 (2.3±0.01 ppm yr−1), SOCEAN 2.5±0.6 GtC yr−1, and SLAND 3.2±0.6 GtC yr−1, with a budgetimbalance BIM of 0.4 GtC yr−1 indicating overestimated emissionsand/or underestimated sinks. For the year 2018 alone, the growth in EFF wasabout 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr−1, reaching 10 GtC yr−1 for the first time in history,ELUC was 1.5±0.7 GtC yr−1, for total anthropogenicCO2 emissions of 11.5±0.9 GtC yr−1 (42.5±3.3 GtCO2). Also for 2018, GATM was 5.1±0.2 GtC yr−1 (2.4±0.1 ppm yr−1), SOCEAN was 2.6±0.6 GtC yr−1, and SLAND was 3.5±0.7 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of−0.2 % to 1.5 %) based on national emissions projections for China, theUSA, the EU, and India and projections of gross domestic product correctedfor recent changes in the carbon intensity of the economy for the rest ofthe world. Overall, the mean and trend in the five components of the globalcarbon budget are consistently estimated over the period 1959–2018, butdiscrepancies of up to 1 GtC yr−1 persist for the representation ofsemi-decadal variability in CO2 fluxes. A detailed comparison amongindividual estimates and the introduction of a broad range of observationsshows (1) no consensus in the mean and trend in land use change emissionsover the last decade, (2) a persistent low agreement between the differentmethods on the magnitude of the land CO2 flux in the northernextra-tropics, and (3) an apparent underestimation of the CO2variability by ocean models outside the tropics. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set (Le Quéré etal., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated bythis work are available at https://doi.org/10.18160/gcp-2019 (Friedlingsteinet al., 2019).

Abstract. Ocean ecosystems are increasingly stressed by human-induced changes of their physical, chemical and biological environment. Among these changes, warming, acidification, deoxygenation and changes in primary productivity by marine phytoplankton can be considered as four of the major stressors of open ocean ecosystems. Due to rising atmospheric CO2 in the coming decades, these changes will be amplified. Here, we use the most recent simulations performed in the framework of the Coupled Model Intercomparison Project 5 to assess how these stressors may evolve over the course of the 21st century. The 10 Earth system models used here project similar trends in ocean warming, acidification, deoxygenation and reduced primary productivity for each of the IPCC's representative concentration pathways (RCPs) over the 21st century. For the "business-as-usual" scenario RCP8.5, the model-mean changes in the 2090s (compared to the 1990s) for sea surface temperature, sea surface pH, global O2 content and integrated primary productivity amount to +2.73 (±0.72) °C, −0.33 (±0.003) pH unit, −3.45 (±0.44)% and −8.6 (±7.9)%, respectively. For the high mitigation scenario RCP2.6, corresponding changes are +0.71 (±0.45) °C, −0.07 (±0.001) pH unit, −1.81 (±0.31)% and −2.0 (±4.1)%, respectively, illustrating the effectiveness of extreme mitigation strategies. Although these stressors operate globally, they display distinct regional patterns and thus do not change coincidentally. Large decreases in O2 and in pH are simulated in global ocean intermediate and mode waters, whereas large reductions in primary production are simulated in the tropics and in the North Atlantic. Although temperature and pH projections are robust across models, the same does not hold for projections of subsurface O2 concentrations in the tropics and global and regional changes in net primary productivity. These high uncertainties in projections of primary productivity and subsurface oxygen prompt us to continue inter-model comparisons to understand these model differences, while calling for caution when using the CMIP5 models to force regional impact models.

Abstract. Accurate assessment of anthropogenic carbon dioxide(CO2) emissions and their redistribution among the atmosphere,ocean, and terrestrial biosphere – the “global carbon budget” – isimportant to better understand the global carbon cycle, support thedevelopment of climate policies, and project future climate change. Here wedescribe data sets and methodology to quantify the five major components ofthe global carbon budget and their uncertainties. Fossil CO2emissions (EFF) are based on energy statistics and cementproduction data, while emissions from land use and land-use change (ELUC),mainly deforestation, are based on land use and land-use change data andbookkeeping models. Atmospheric CO2 concentration is measureddirectly and its growth rate (GATM) is computed from the annualchanges in concentration. The ocean CO2 sink (SOCEAN)and terrestrial CO2 sink (SLAND) are estimated withglobal process models constrained by observations. The resulting carbonbudget imbalance (BIM), the difference between the estimatedtotal emissions and the estimated changes in the atmosphere, ocean, andterrestrial biosphere, is a measure of imperfect data and understanding ofthe contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1,SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of0.5 GtC yr−1 indicating overestimated emissions and/or underestimatedsinks. For the year 2017 alone, the growth in EFF was about 1.6 %and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017,ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1,with a BIM of 0.3 GtC. The global atmosphericCO2 concentration reached 405.0±0.1 ppm averaged over 2017.For 2018, preliminary data for the first 6–9 months indicate a renewedgrowth in EFF of +2.7 % (range of 1.8 % to 3.7 %) basedon national emission projections for China, the US, the EU, and India andprojections of gross domestic product corrected for recent changes in thecarbon intensity of the economy for the rest of the world. The analysispresented here shows that the mean and trend in the five components of theglobal carbon budget are consistently estimated over the period of 1959–2017,but discrepancies of up to 1 GtC yr−1 persist for the representationof semi-decadal variability in CO2 fluxes. A detailed comparisonamong individual estimates and the introduction of a broad range ofobservations show (1) no consensus in the mean and trend in land-use changeemissions, (2) a persistent low agreement among the different methods onthe magnitude of the land CO2 flux in the northern extra-tropics,and (3) an apparent underestimation of the CO2 variability by oceanmodels, originating outside the tropics. This living data update documentschanges in the methods and data sets used in this new global carbon budgetand the progress in understanding the global carbon cycle compared withprevious publications of this data set (Le Quéré et al., 2018, 2016,2015a, b, 2014, 2013). All results presented here can be downloaded fromhttps://doi.org/10.18160/GCP-2018.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate is critical to better understand the global carboncycle, support the development of climate policies, and project futureclimate change. Here we describe and synthesize datasets and methodology toquantify the five major components of the global carbon budget and theiruncertainties. Fossil CO2 emissions (EFOS) are based on energystatistics and cement production data, while emissions from land-use change(ELUC), mainly deforestation, are based on land use and land-use changedata and bookkeeping models. Atmospheric CO2 concentration is measureddirectly, and its growth rate (GATM) is computed from the annualchanges in concentration. The ocean CO2 sink (SOCEAN) is estimatedwith global ocean biogeochemistry models and observation-baseddata products. The terrestrial CO2 sink (SLAND) is estimated withdynamic global vegetation models. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the firsttime, an approach is shown to reconcile the difference in our ELUCestimate with the one from national greenhouse gas inventories, supportingthe assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, withfossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1, and SLANDwas 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. Theglobal atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOSrelative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budgetare consistently estimated over the period 1959–2020, but discrepancies ofup to 1 GtC yr−1 persist for the representation of annual tosemi-decadal variability in CO2 fluxes. Comparison of estimates frommultiple approaches and observations shows (1) a persistent largeuncertainty in the estimate of land-use changes emissions, (2) a lowagreement between the different methods on the magnitude of the landCO2 flux in the northern extra-tropics, and (3) a discrepancy betweenthe different methods on the strength of the ocean sink over the lastdecade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understandingof the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; LeQuéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). Thedata presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

A new version of the general circulation model CNRM-CM has been developed jointly by CNRM-GAME (Centre National de Recherches Météorologiques—Groupe d’études de l’Atmosphère Météorologique) and Cerfacs (Centre Européen de Recherche et de Formation Avancée) in order to contribute to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The purpose of the study is to describe its main features and to provide a preliminary assessment of its mean climatology. CNRM-CM5.1 includes the atmospheric model ARPEGE-Climat (v5.2), the ocean model NEMO (v3.2), the land surface scheme ISBA and the sea ice model GELATO (v5) coupled through the OASIS (v3) system. The main improvements since CMIP3 are the following. Horizontal resolution has been increased both in the atmosphere (from 2.8° to 1.4°) and in the ocean (from 2° to 1°). The dynamical core of the atmospheric component has been revised. A new radiation scheme has been introduced and the treatments of tropospheric and stratospheric aerosols have been improved. Particular care has been devoted to ensure mass/water conservation in the atmospheric component. The land surface scheme ISBA has been externalised from the atmospheric model through the SURFEX platform and includes new developments such as a parameterization of sub-grid hydrology, a new freezing scheme and a new bulk parameterisation for ocean surface fluxes. The ocean model is based on the state-of-the-art version of NEMO, which has greatly progressed since the OPA8.0 version used in the CMIP3 version of CNRM-CM. Finally, the coupling between the different components through OASIS has also received a particular attention to avoid energy loss and spurious drifts. These developments generally lead to a more realistic representation of the mean recent climate and to a reduction of drifts in a preindustrial integration. The large-scale dynamics is generally improved both in the atmosphere and in the ocean, and the bias in mean surface temperature is clearly reduced. However, some flaws remain such as significant precipitation and radiative biases in many regions, or a pronounced drift in three dimensional salinity.

The possibility of extending existing techniques for turbulence parameterization in the planetary boundary layer to attitude, orography-induced turbulence events is examined. Starting from a well-tested scheme, we show that it is possible to generalize the specification method of the length scales, with no deterioration of the scheme performance in the boundary layer. The new scheme is implemented in a two-dimensional version of a limited-area, numerical model used for the simulation of mesobeta-scale atmospheric flows. Three well-known cases of orographically induced turbulence are studied. The comparison with observations and former studies shows a satisfactory behavior of the new scheme.

Abstract 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. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the global carbon budget – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).

Abstract Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been considered for a long time as a “desert of predictability.” In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of subseasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models significantly underestimate the amplitude of the Madden–Julian oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database also represents an important tool for case studies of extreme events. For instance, a multimodel combination of S2S models displays higher probability of a landfall over the islands of Vanuatu 2–3 weeks before Tropical Cyclone Pam devastated the islands in March 2015.

Abstract Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.