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Quantifying how and where climate change will alter meteorological drought properties is a priority to inform adaptation policies. Here we use the standardized precipitation index to portray future changes in the climatological properties of moderate drought events projected by the latest generation of Earth system models. Beyond the assessment of their mean frequency and intensity, other metrics are explored including length of drought intervals, drought duration, starting date and severity. Two extended 6‐month seasons are distinguished starting in October and April, respectively. Consistent changes in drought properties are projected across timescales and seasons. Regional “dry spots” are identified, such as northern South America and the Caribbean Islands, where the median model response shows the largest increase in drought severity, mostly as a result of prolonged duration. Yet, there are many regions where the inter‐model spread remains substantial and cannot be reduced by the application of global and regional observational constraints.

Efforts to predict long‐term changes in continental runoff at both global and basin scales generally remain ambiguous. Here we use a global runoff reconstruction and a Bayesian statistical method to narrow uncertainties in runoff projections from the latest generation of global climate models. Three representative tropical river basins are used to illustrate the application and showcase the potential for substantial reduction in modeling uncertainty. Yet, results are fairly sensitive to the selected reconstruction thus highlighting the need for reliable and homogeneized gridded runoff data sets or river discharge measurements. Moreover, climate models do not account for water withdrawals, whose effect on observed runoff should also be removed in order to detect and attribute the hydrological effect of climate change. Finally, and more importantly, most models fail at capturing the observed recent decrease in runoff ratio, which may highlight either model deficiencies or increasing water derivation over the selected river basins. Plain Language Summary The response of river discharge under the effect of climate change generally remains very uncertain. Bayesian statistical tools and global runoff reconstructions, constrained by flow observations, can nevertheless be used to evaluate the capacity of climate models to simulate the historical runoff and, thus, constrain its future changes at the basin scale. Three representative tropical river basins help illustrate the method. The results are nevertheless sensitive to the choice of the runoff reconstruction, thus emphasizing the need to have good quality flow data, if possible corrected for the direct effects of water withdrawals from the rivers or the aquifers which supply them. Worryingly, the latest generation of global climate models show a systematic underestimation of the downward evolution of the ratio between runoff and precipitation, which could reflect the increasing importance of these withdrawals or the inability of models to capture the rapidly increasing land surface evapotranspiration under climate change. Key Points Global 21st century projections of basin‐scale runoff remain highly model‐dependent within the latest generation of Earth System Models Gridded runoff reconstructions and precipitation observations can however be used to constrain the projections through Bayesian statistics A model‐observation mismatch is underlined regarding recent changes in the annual runoff to precipitation ratio over specific river basins

Efforts to detect long‐term changes in global mean evaporation minus precipitation over the ocean remain ambiguous. Here we define an ad hoc sea surface salinity index to assess the observed and simulated intensification of the freshwater flux pattern over the global ocean and, thus, of the overall water cycle. A recent salinity reconstruction shows a long‐term amplification of the climatological patterns, thereby supporting the popular “fresh gets fresher, salty gets saltier” paradigm. Unlike in a previous study, no systematic underestimation of this amplification is found in the latest generation of global climate models. Yet, the “fresh gets fresher” paradigm is much more robust than its “salty gets saltier” counterpart and the proposed salinity index does not yet provide a strong constraint on the model‐dependent projected intensification of the global water cycle intensification along the 21st century. Plain Language Summary Recent changes in continental mean precipitation and evaporation remain poorly observed and thus poorly constrained in both atmospheric reanalyzes and global climate models. Here we propose a new index based on global sea surface salinity contrasts as a surrogate of changes in metric of the water cycle intensity. Overall, both observed and simulated indices support the “fresh gets fresher, salty gets saltier” paradigm, widely used to depict the overall intensification of the water cycle. Unlike in a previous study, no systematic underestimation of the observed amplification in salinity patterns is found in the latest generation of global climate models. The “salty gets saltier” response is however less robust than the “fresh gets fresher” and the proposed salinity index is not yet very useful to constrain the future intensity of the global water cycle. Key Points Both observations and climate models evidence an amplification of the global ocean climatological contrasts in sea surface salinity (SSS) Yet, the “fresh gets fresher” paradigm is more robust than its salty counterpart, which is more sensitive to the ocean domain's definition Global SSS observations do not yet provide a strong constraint on the projected intensification of the global water cycle

Given the low skill of seasonal forecasts in the Northern Hemisphere, it is important to look for extra sources of long‐range predictability in addition to the global distribution of sea surface temperature (SST). Former studies have suggested the potential contribution of the stratosphere but have never really quantified this influence and compared it to the SST forcing. In the present study, two ensembles of global atmospheric simulations driven by observed SST and radiative forcings have been performed over the 1971–2000 period. In the perturbed experiment, the stratospheric dynamics and temperature is nudged towards the ERA40 reanalyses north of 25°N in order to mimic a “perfect” polar vortex. The comparison with the control experiment reveals a strong improvement in the simulation of the Arctic and North Atlantic Oscillation, with obvious positive impacts on the interannual variability of winter surface air temperature and precipitation, especially over 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 CO2 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. Key Points Description of CNRM‐CM6‐1 model components, their coupling, and tuning procedures are described Historical simulations and DECK experiments are assessed Preindustrial simulation is stable and mean climate and variability in historical runs is realistic

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.

Persistent precipitation deficits are among the most impactful consequences of global warming. Here we focus on changes in the annual number of dry days (NDD) and in the annual maximum length of dry spells due to a quadrupling of atmospheric CO2. We use atmosphere‐only simulations to decompose the projected changes into additive contributions. A fast adjustment leads to a global increase in NDD despite notable regional exceptions (e.g., South Asia and Sahel). The effect of the uniform component of the surface ocean warming is model‐dependent but shapes the regional distribution of the NDD response in each model. Finally, the ocean warming pattern also contributes to large uncertainties, likely through contrasting changes in large‐scale circulation. Our results thus highlight the complexity of the NDD response, with policy‐relevant practical implications for mitigation and adaptation strategies. Plain Language Summary Global warming is expected to intensify the global water cycle, including the intensity and frequency of precipitation extremes. Yet, the response of the dry side of the daily precipitation distribution to increased atmospheric CO2 has received so far less attention. Here we show that this response remains highly model‐dependent across the latest generation of global climate models. Furthermore, we use atmosphere‐only simulations to isolate different drivers of the precipitation response. A fast radiative and vegetation adjustment to increased CO2 leads to an overall increase in the mean annual number of dry days (NDD) despite some regional exceptions. The effect of the ocean surface warming is highly model‐dependent, only partly due to the diversity of the simulated patterns of sea surface temperature anomalies. The regional response of NDD and of the maximum length of dry spells thus does not simply scale with global warming across the different models. Key Points AGCM simulations are used to split the dry day response to increased CO2 into fast adjustment versus slower uniform and patterned SST effects None of the three components consistently dominates the global land response of dry days across the selected CMIP6 models The uniform SST warming dominates the regional anomalies, which however do not scale with global warming across the multi‐model ensemble

Understanding the response of evapotranspiration to global warming should help to predict surface climate, including heatwaves and droughts. This study shows that increasing atmospheric concentrations of greenhouse gases and decreasing loadings of anthropogenic (and volcanic) aerosols have led to enhanced evapotranspiration in mid and high latitudes over recent decades. Global warming is expected to intensify the global hydrological cycle 1 , with an increase of both evapotranspiration (EVT) and precipitation. Yet, the magnitude and spatial distribution of this global and annual mean response remains highly uncertain 2 . Better constraining land EVT in twenty-first-century climate scenarios is critical for predicting changes in surface climate, including heatwaves 3 and droughts 4 , evaluating impacts on ecosystems and water resources 5 , and designing adaptation policies. Continental scale EVT changes may already be underway 6 , 7 , but have never been attributed to anthropogenic emissions of greenhouse gases and sulphate aerosols. Here we provide global gridded estimates of annual EVT and demonstrate that the latitudinal and decadal differentiation of recent EVT variations cannot be understood without invoking the anthropogenic radiative forcings. In the mid-latitudes, the emerging picture of enhanced EVT confirms the end of the dimming decades 8 and highlights the possible threat posed by increasing drought frequency to managing water resources and achieving food security in a changing climate.

The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.

The present study examines the correspondence between short- and long-term systematic errors in five atmospheric models by comparing the 16 five-day hindcast ensembles from the Transpose Atmospheric Model Intercomparison Project II (Transpose-AMIP II) for July–August 2009 (short term) to the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and AMIP for the June–August mean conditions of the years of 1979–2008 (long term). Because the short-term hindcasts were conducted with identical climate models used in the CMIP5/AMIP simulations, one can diagnose over what time scale systematic errors in these climate simulations develop, thus yielding insights into their origin through a seamless modeling approach. The analysis suggests that most systematic errors of precipitation, clouds, and radiation processes in the long-term climate runs are present by day 5 in ensemble average hindcasts in all models. Errors typically saturate after few days of hindcasts with amplitudes comparable to the climate errors, and the impacts of initial conditions on the simulated ensemble mean errors are relatively small. This robust bias correspondence suggests that these systematic errors across different models likely are initiated by model parameterizations since the atmospheric large-scale states remain close to observations in the first 2–3 days. However, biases associated with model physics can have impacts on the large-scale states by day 5, such as zonal winds, 2-m temperature, and sea level pressure, and the analysis further indicates a good correspondence between short- and long-term biases for these large-scale states. Therefore, improving individual model parameterizations in the hindcast mode could lead to the improvement of most climate models in simulating their climate mean state and potentially their future projections.