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Interactions among species are likely to change geographically due to climate-driven species range shifts and in intensity due to physiological responses to increasing temperatures. Marine ectotherms experience temperatures closer to their upper thermal limits due to the paucity of temporary thermal refugia compared to those available to terrestrial organisms. Thermal limits of marine ectotherms also vary among species and trophic levels, making their trophic interactions more prone to changes as oceans warm. We assessed how temperature affects reef fish trophic interactions in the Western Atlantic and modeled projections of changes in fish occurrence, biomass, and feeding intensity across latitudes due to climate change. Under ocean warming, tropical reefs will experience diminished trophic interactions, particularly herbivory and invertivory, potentially reinforcing algal dominance in this region. Tropicalization events are more likely to occur in the northern hemisphere, where feeding by tropical herbivores is predicted to expand from the northern Caribbean to extratropical reefs. Conversely, feeding by omnivores is predicted to decrease in this area with minor increases in the Caribbean and southern Brazil. Feeding by invertivores declines across all latitudes in future predictions, jeopardizing a critical trophic link. Most changes are predicted to occur by 2050 and can significantly affect ecosystem functioning, causing dominance shifts and the rise of novel ecosystems., SI

M. Bermudez acknowledges funding from EU's Horizon 2020 Programme under Marie Skodowska-Curie Grant Agreement 754446 and UGR Research and Knowledge Transfer Fund-Athenea3i. Funding for open access charge: Universidad de Granada/CBUA., Flood assessment in coastal river areas is subject to complex dependencies and interactions between flood drivers. In addition, coastal areas are especially vulnerable to climate change, and thus its effects should be considered in the evaluation of future flood hazard. In the present study, we propose a methodology for a robust evaluation of historical and future flooding in coastal river areas. It follows a continuous simulation approach in which a hydrologic-hydraulic modeling cascade is run for several years, driven by a simultaneous series of flood drivers. The method differs from other existing methodologies in: (a) jointly considering the relevant flood drivers, both coastal and inland, together with their dependencies and interactions, to represent the simultaneous occurrence of extreme water levels correctly, and (b) obtaining local-scale physically consistent projections of flood drivers to account for future climate change effects on compound flood hazard. The methodology is tested for a coastal river reach in NW Spain. The results show that, although mean sea level rise is usually expected to be the main driver of increased flood hazard, climate change effects on river discharge can play a very significant role in regions with compound flooding potential., European Commission 754446, UGR Research and Knowledge Transfer Fund-Athenea3i, Universidad de Granada/CBUA

The Etesians are the dominant synoptically driven winds observed in the Eastern Mediterranean, usually from late spring to late summer. Due to the complex topography, the Etesians can be very strong and pose significant environmental hazards, especially over wildfire incidents. This study assesses the impacts of climate change on future Etesians by analyzing the response of the most recent EURO-CORDEX regional climate simulations at the 12-km grid resolution over the twenty-first century. The mean model ensemble projects a significant increase of the Etesians' frequency and intensity under the two emission scenarios RCP4.5 and RCP8.5. This response is connected to an increase in the zonal wind at 200 hPa, a reinforcement of the midlatitude westerly flow, and a decrease in the wave amplitude. These circulation changes accelerate the mid-to-high latitude eastward propagation of the large-scale circulation systems which can favor enhanced ridges over the Balkans. A strengthening and poleward shift of the subtropical jet stream is also projected, connected with stronger subsidence over the Eastern Mediterranean. The projected changes will have profound environmental and societal implications, including the lengthening of the wildfire season and increasing air pollution risk in the region. On the other hand, the current estimate of future wind power potential in the Aegean Sea will be significantly increased by the end of the century, which might have positive impact in the regional economy.

A framework for analyzing and benchmarking climate model outputs is built upon δ‐MAPS, a recently developed complex network analysis method. The framework allows for the possibility of highlighting quantifiable topological differences across data sets, capturing the magnitude of interactions including lagged relationships and quantifying the modeled internal variability, changes in domains properties and in their connections over space and time. A set of four metrics is proposed to assess and compare the modeled domains shapes, strengths, and connectivity patterns. δ‐MAPS is applied to investigate the topological properties of sea surface temperature from observational data sets and in a subset of the Community Earth System Model (CESM) Large Ensemble focusing on the past 35 years and over the 20th and 21st centuries. Model ensemble members are mapped in a reduced metric space to quantify internal variability and average model error. It is found that network properties are on average robust whenever individual member or ensemble trends are removed. The assessment identifies biases in the CESM representation of the connectivity patterns that stem from too strong autocorrelations of domains signals and from the overestimation of the El Niño–Southern Oscillation amplitude and its thermodynamic feedback onto the tropical band in most members.

The Mediterranean is recognized among the most responsive regions to climate change, with annual temperatures projected to increase by 1–5 °C until 2100. Large cities may experience an additional stress discomfort due to the Urban Heat Island (UHI) effect. In the present study, the WRF-ARW numerical weather prediction model was used to investigate the climate change impact on UHI for two Mediterranean cities, Rome and Thessaloniki. For this purpose, three 5-year time-slice simulations were conducted (2006–2010, 2046–2050, 2096–2100) under the Representative Concentration Pathway (RCP) 8.5 emission scenario, with a spatial resolution of 2 km. In order to comprehensively investigate the urban microclimate, we analyze future simulation data across sections crossing urban/non-urban areas, and after grouping them into three classes depending on the location of the grid cells. The urban areas of both cities present increased average minimum temperature (Tmin) in winter/summer compared to other rural areas, with an UHI of ~+1.5–3 °C on average at night/early morning. Considering UHI under future climate change, we found no significant variations (~±0.2 °C). Finally, we found that the numbers of days with Tmin ≥ 20 °C will mostly increase in urban coastal areas until 2100, while the largest increase of minimum Discomfort Index (DImin) is expected in urban low-ground areas.

To support the development of national adaptation policies and measures addressing climate change impacts over Italy, this work aims to analyze projected changes in mean temperatures and precipitations, and extreme events such as droughts and floods, highlighting some local trends in the different Italian regions that have been little considered to date. The investigations are made on the basis of a set of high-resolution Euro-CORDEX models (horizontal resolution 0.11°, about 12 km) to infer quantitative assessments about the danger of climate changes under three different Representative Concentration Pathways (RCPs): business as usual scenario, i.e., without a reduction in green-house gas emissions (RCP 8.5), medium stabilization scenario (RCP 4.5) and mitigation scenario (RCP 2.6). After filtering the models with limited performances in reconstructing the current climate, the multi-model climate change scenarios were characterized by comparing the ensemble mean values computed for the base-line period (1971–2000) with those elaborated for the short- (2021–2050), medium- (2041–2070) and long-term (2071–2100). Two WMO ETCCDI indices were considered to investigate climate extremes: Consecutive Dry Days and extreme precipitations. Despite some uncertainties (related to discrepancies among the models), drought conditions and extreme precipitations will likely exacerbate in the coming decades without mitigation (RCP 8.5). Such conditions will be less critical if partial mitigation actions will be undertaken (RCP 4.5) and are expected to be significantly reduced with decarbonization policies (RCP 2.6).

Shifts in winter temperature and precipitation patterns can profoundly affect snow accumulation and melt regimes. These shifts have varying impacts on local to large-scale hydro-ecological systems and freshwater distribution, especially in cold regions with high hydroclimatic heterogeneity. We evaluate winter climate changes in the six ecozones (Mountains, Foothills, Prairie, Parkland, Boreal, and Taiga) in Alberta, Canada, and identify regions of elevated susceptibility to change. Evaluation of historic trends and future changes in winter climate use high-resolution (~10 km) gridded data for 1950–2017 and projections for the 2050s (2041–2070) and 2080s (2071–2100) under medium (RCP 4.5) and high (RCP 8.5) emissions scenarios. Results indicate continued declines in winter duration and earlier onset of spring above-freezing temperatures from historic through future periods, with greater changes in Prairie and Mountain ecozones, and extremely short or nonexistent winter durations in future climatologies. Decreases in November–April precipitation and a shift from snow to rain dominate the historic period. Future scenarios suggest winter precipitation increases are expected to predominantly fall as rain. Additionally, shifts in precipitation distributions are likely to lead to historically-rare, high-precipitation extreme events becoming more common. This study increases our understanding of historic trends and projected future change effects on winter snowpack-related climate and can be used inform adaptive water resource management strategies.

Indian Ocean Dipole (IOD), a major climate variability in the tropics which drives the abiotic stress associated with heavy rainfalls and severe droughts, is not much understood in terms of its role in the carbon cycle, while El Nino-Southern Oscillation (ENSO)-related terrestrial carbon cycle variation has been intensively studied. Here, we investigate IOD's impact on land photosynthesis over the Indian ocean rim countries during austral spring using satellite-based gross primary productivity (GPP) and Earth System Model simulations produced in the Coupled Model Intercomparison Project Phase 6 (CMIP6). IOD independently affects GPP with significant positive partial correlation coefficients (urn:x-wiley:23284277:media:eft2795:eft2795-math-0001) over most of Africa and India, and negative urn:x-wiley:23284277:media:eft2795:eft2795-math-0002 over southern China, Indo-China peninsula, maritime continent, and Australia, mostly driven by precipitation variations; this obviously differs from the widespread significant negative urn:x-wiley:23284277:media:eft2795:eft2795-math-0003 pattern induced by ENSO. The recent extremely positive IOD in 2019 caused the canonical IOD-affected GPP patterns, however, with its extreme impacts. Furthermore, though large inter-model spreads exist, the CMIP6 multimodel median can basically capture the main characteristics of IOD-affected precipitation and GPP patterns. Importantly, IOD is predicted to occur more frequently in future warming scenarios. Model future projections suggest that it will exert larger impacts on GPP variations over central and eastern Africa, Sumatra, western and southeastern Australia with stronger urn:x-wiley:23284277:media:eft2795:eft2795-math-0004 and enhanced explained variance, but less impacts over southern Africa, east India, Indo-China peninsula, and northeastern Australia. Therefore, besides ENSO, understanding the IOD impacts can provide us new insights into regional and global carbon cycle interannual variability.

Dominant Euro-Atlantic climate modes such as the North Atlantic Oscillation (NAO), the Eastern Atlantic pattern (EA), the Eastern Atlantic Western Russian pattern (EAWR), and the Scandinavian pattern (SCA) significantly affect interannual-to-decadal Euro-Mediterranean climate fluctuations, especially in winter.In this contribution, we will present and discuss results from a CMIP6 multi-model analysis performed to investigate the robustness of historical and projected state and variability of such modes under the historical and ssp585 future scenario of anthropogenic forcing (fossil-fueled development with 8.5W/m2 forcing level) simulations, focusing on the winter season.Toward this goal, we first search for a reliable box-based index definition for each of the abovementioned observed climate modes and, then, we perform a comparative assessment of the temporal, spectral and distributional properties of the so-defined indices during the historical (1850-2014) and ssp585 future scenario (2015-2099) time periods, with a special focus on the two interdecadal periods 1960-1999 and 2060-2099.Results show overall good skills of the historical ensemble to reproduce the observed temporal, spectral and distributional properties of all considered modes. At the end of the 21st Century the ssp585 ensemble yields non-significant distributional changes for NAO, EAWR, and SCA indices and a transition to a stronger baroclinic structure for EA, with persistent positive anomalies in the mid-troposphere enhancing globally-driven warming over the Euro-Mediterranean region. The hemispheric spatial correlation patterns with temperature and precipitation significantly change for all modes, that is, we observe a significant modulation of the teleconnections associated with each index.

Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21st century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1 km and 2.5 km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database., Measurement(s) temperature of air • volume of hydrological precipitation Technology Type(s) digital curation • computational modeling technique Factor Type(s) monthly temperature measurement • monthly precipitation measurement Sample Characteristic - Environment climate system Sample Characteristic - Location Europe Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13190834

International audience; Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all forest landscape models currently applied in temperate European forests (LandClim, TreeMig, LANDIS-II, iLand). We examined the uncertainty of model projections under several future climate, disturbance, and dispersal scenarios, and quantified uncertainties by variance partitioning. While projections under past climate conditions were in good agreement with observations, uncertainty under future climate conditions was high, with between-model biomass differences of up to 200 t ha-1. Disturbances strongly influenced landscape dy-namics and contributed substantially to uncertainty in model projections (similar to 25-40% of observed variance). Overall, model differences were the main source of uncertainty, explaining at least 50% of observed variance. We advocate a more rigorous and systematic model evaluation and calibration, and a broader use of ensemble projections to quantify uncertainties in future landscape dynamics.

Special issue Oceanic biodiversity under climate change: shifts in natural and human systems.-- 11 pages, 5 figures, 2 tables, supplementary data https://doi.org/10.1016/j.dsr2.2019.104666.-- This research was conducted as part of the CLIOTOP program. This is a contribution 942 from AZTI Marine Research Division, Species shifts due to climate change are being recorded and reported worldwide. However, the accurate estimation and causal attribution of species shifts using spatial distribution indicators, such as the center of gravity, is challenging. This is particularly problematic for commercially exploited marine species with data from research surveys, commercial fisheries or other data collection methods that are not recorded homogeneously over time and space. Here, we propose a new framework to ascertain whether the changes in the spatial distribution of species are due to changes in habitat conditions, fishing activity or other factors. This approach is developed to help elucidate the main drivers of species shifts and it is based upon the comparison of historical trends in species distribution shifts among raw data and modeled: i) fishing effort, ii) population occurrence and abundance, iii) habitat, and iv) spatio-temporal reconstruction of the species distribution. We apply this new methodology to the case study of swordfish populations worldwide. On a global scale, 2 out of 6 stocks of swordfish shifted latitudinally during 1958–2004. Of those two, only the Mediterranean stock was associated with a linear trend change of its habitat. In two other stocks, the latitudinal center of gravity of populations occurrence varies following their habitats’ interannual variability; however, this shift is not linear. We further developed a worldwide habitat suitability model for swordfish and projected its distribution and abundance into the future under the RCP8.5 climate change scenario, the highest greenhouse gas concentration scenario, by the end of the century. Future projections estimate an overall swordfish decrease of 22% in CPUE (catch per unit of effort), with substantial decreases in most tropical areas, and a slight increase in its distribution range limits, both in the north and southern hemispheres, This research was funded by the Basque Government (Department Deputy of Agriculture, Fishing, and Food Policy). M. Erauskin-Extramiana has benefited from a Basque Government scholarship through Economic Development and Infrastructures Department. [...] A. Cabre is grateful for the ‘‘Beatriu de Pinos’’ fellowship and the program Marie Curie Actions COFUND of the 7th Framework Program for Research and Technological Development of the European Union. R. Coelho is supported by an Investigador-FCT contract (Ref: IF/00253/2014) from FCT, the Portuguese Foundation for Science and Technology. D. Rosa is supported by a Ph.D. grant from FCT (Ref: SFRH/BD/136074/2018), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

This study expands previous work on climate extremes in Australia by investigating the simulation of a large number of extremes indices in the CMIP5 multi-model dataset and comparing them to multiple observational datasets over a century of observed data using consistent methods. We calculate 24 indices representing extremes of temperature and precipitation from 1911 to 2010 over Australia and show that there have been significant observed trends in temperature extremes associated with warming while there have been few significant observed trends in precipitation extremes. We compare the observed indices calculated from two mostly independent datasets with 22 CMIP5 models to determine how well global climate models are able to simulate observed climatologies, variability and trends. We find that generally temperature extremes are reasonably well simulated (climatology, variability and trend patterns) although the models tend to overestimate minimum temperature extremes and underestimate maximum temperature extremes. Some models stand out as being outliers and we exclude one model (INMCM4) entirely from the multi-model analysis as it simulates unrealistic minimum temperature extremes over the historical period. There is more spread between models for precipitation than temperature extremes but in most cases the observations sit within the model spread. Exceptions are consecutive wet days (CWD) where nearly all models overestimate the actual number of annual wet days and simple daily intensity (SDII) and one day precipitation maxima (Rx1day) where the models tend to underestimate precipitation intensity. However, some of these differences likely lie in observational uncertainty. Most models including the multi-model mean indicate that precipitation intensity has increased over the last century but the two observational datasets analysed disagree on the sign of change of precipitation intensity, one of them indicating a significant decrease. We use the CMIP5 simulations for two future Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5) to project changes in temperature and precipitation extremes across Australia. By the end of the century the number of cold temperature extremes substantially reduces and the number of warm temperature extremes substantially increases; changes scaling relative to the strength of emissions scenario. Changes in temperature extremes are often greatest in the tropics. While the results for precipitation extremes are less marked, simulations for the end of the century compared to present day indicate more periods of dryness while the most intense precipitation extremes increase substantially, with a separation becoming clear between emissions scenarios.

(IF 3.14; Q2); International audience; Species Distribution Models (SDMs) are useful tools to project potential future species distributions under climate change scenarios. Despite the ability to run SDMs in recent and reliable tools, there are some misuses and proxies that are widely practiced and rarely addressed together, particularly when dealing with marine species.In this paper, we propose an open-source framework that includes (i) a procedure for homogenizing occurrence data to reduce the influence of sampling bias, (ii) a procedure for generating pseudo-absences, (iii) a hierarchical-filter approach, (iv) full incorporation of the third dimension by considering climatic variables at multiple depths and (v) building of maps that predict current and potential future ranges of marine species. This framework is available for non-modeller ecologists interested in investigating future species ranges with a user-friendly script. We investigated the robustness of the framework by applying it to marine species of the Eastern English Channel. Projections were built for the middle and the end of this century under RCP2.6 and RCP8.5 scenarios.

Key message We developed a climatic response function using 20-year tree height observed from 45Ginkgo bilobaplantations in China and used it to predict the growth and habitat responses to anticipated climate change. We projected northward and upward shifts in the species habitat and productive areas, but a dramatic contraction of the species distribution is unlikely to occur at least during the present century. Context Ginkgo biloba is the only living species in the division Ginkgophyta. The species exists in small natural populations in southeastern China but is cultivated across China and the world. The species’ future under climate change is of concern. Aims This study was initiated to model the species’ growth response to climate change and to predict its range of suitable habitat under future climates. Methods Using height data from 45 20 years old plantations growing under a wide range of climatic conditions across China, we developed univariate and bivariate climatic response functions to identify the climate requirements of the species. Results According to the amount of variance explained (> 70%) and the high level of agreement (> 99%) with independent species occurrence coordinates, the developed climate response function was highly accurate and credible. Projections for future periods (2011–2040, 2041–2070, and 2071–2100) under the Representative Concentration Pathway 4.5 (RCP4.5) scenario indicated that the areas of potential suitable habitat would increase (25–67 million hectares). It would also be associated with northward (0.21–0.62° in latitude) and elevational (24–75 m) shifts. Conclusion Global climate change is projected to increase the area of potential suitable habitats for Ginkgo and shift its spatial distributions northward and upward.

International audience; Renewable energy systems are promoted and developed notably due to their low environmental footprint. Fleet-wide robust environmental assessments are needed to drive the sustainable transition of energy systems worldwide. This study introduces a tailored comprehensive impact assessment methodology for fleets of renewable energy systems based on Life Cycle Analysis and its application to Danish wind turbines fleet through an online platform LCA_WIND_DK (viewer.webservice-energy.org/lca-wind-dk/). This platform enables to visualize environmental performances of wind turbines in Denmark and their temporal evolution. The fleet is known in detail from 1980 to 2016 and projected from 2017 to 2030 based on national objectives for onshore/offshore capacity and pre-approved offshore projects. Each turbine's future electricity production is estimated from its power curve and geo-localized wind time-series. More than 10,000 cradle-to-grave life cycle inventories are generated, considering the spatio-temporal context and technological characteristics. The comprehensive analysis of the Danish fleet over fifty years reveals long-term trends for several impact categories. Improvements in all categories follow similar trends as in climate change, which decreases from 40 to 13 g CO2-eq/kWh between 1980 and 2030. Improvements stem from combined economies of scale and higher load factors linked to increasingly large and powerful turbines. The interactive mapping tool LCA_WIND_DK may provide statistics to support renewable energy oriented policy scenarios and unique spatio-temporal environmental information to project developers. This novel approach designed for large territories, here applied to the Danish wind turbine fleet, is generic and can be applied to other renewable energy systems and/or to other territories.

Many studies have projected that as the climate changes, the magnitudes of extreme precipitation events in the Northeastern United States are likely to continue increasing, regardless of the emission scenario. To examine this issue, we analyzed observed and modeled daily precipitation frequency (PF) estimates in the Northeastern US on the rain gauge station scale based on both annual maximum series (AMS) and partial duration series (PDS) methods. We employed four Coupled Model Intercomparison Project Phase 5 (CMIP5) downscaled data sets, including a probabilistic statistically downscaled data set developed specifically for this study. The ability of these four data sets to reproduce the observed features of historical point PF estimates was compared, and the two with the best historical accuracy, including the newly developed probabilistic data set, were selected to produce projected PF estimates under two CMIP5-based emission scenarios, namely Representative Concentration Pathway 4.5 (RCP4.5) and Representative Concentration Pathway 8.5 (RCP8.5). These projections indeed demonstrate a likely increase in PF estimates in the Northeastern US with noted differences in magnitudes and spatial distributions between the two data sets and between the two scenarios. We also quantified how the exceedance probabilities of the historical PF estimate values are likely to increase under each scenario using the two best performing data sets. Notably, an event with a current exceedance probability of 0.01 (a 100-year event) may have an exceedance probability for the second half of the 21st century of &asymp, 0.04 (a 27-year event) under the RCP4.5 scenario and &asymp, 0.05 (a 19-year event) under RCP8.5. Knowledge about the projected changes to the magnitude and frequency of heavy precipitation in this region will be relevant for the socio-economic and environmental evaluation of future infrastructure projects and will allow for better management and planning decisions.

The objective of the present study is to show a comprehensive assessment of the wind resource dynamics along the Spanish coastal environment of the Iberian Peninsula. After studying the historical resources (reported at 100 m height) for the 20-year period from 1999 to 2018 by analyzing the ERA5 time series of wind speed data, the 10 locations with highest historical wind resources are considered. For these, the study of the future dynamics for the 30-year period from 2021 to 2050 under the climate change scenario RCP 4.5 is carried out. After further selection, mean and maximum values, as well as the seasonal and monthly variability of the wind power density, are obtained for six locations along the Spanish coasts. Furthermore, a performance and economic dynamics assessment is presented for four different wind turbine technologies with rated capacities ranging between 3 and 9.5 MW. A further comparison with other locations in the Baltic Sea and the Black Sea is presented to provide a critical image of the Spanish wind resources dynamics in the European framework. The results indicate a noticeable gain of wind resources in various locations of the Atlantic and Mediterranean coasts, with others presenting slight losses.

Many coastal seas worldwide are affected by human impacts such as eutrophicationcausing, inter alia, oxygen depletion, and extensive areas of hypoxia. Depending on theregion, global warming may reinforce these environmental changes by reducing air-seaoxygen fluxes, intensifying internal nutrient cycling, and increasing river-borne nutrientloads. The development of appropriate management plans to effectively protect themarine environment requires projections of future marine ecosystem states. However, projections with regional climate models commonly suffer from shortcomings in thedriving global General Circulation Models (GCMs). The differing sensitivities of GCMsto increased greenhouse gas concentrations affect regional projections considerably. In this study, we focused on one of the most threatened coastal seas, the BalticSea, and estimated uncertainties in projections due to climate model deficiencies anddue to unknown future greenhouse gas concentration, nutrient load and sea level rise scenarios. To address the latter, simulations of the period 1975–2098 were performedusing the initial conditions from an earlier reconstruction with the same Baltic Sea model(starting in 1850). To estimate the impacts of climate model uncertainties, dynamicaldownscaling experiments with four driving global models were carried out for twogreenhouse gas concentrationscenarios and for three nutrient load scenarios, coveringthe plausible range between low and high loads. The results suggest that changes innutrient supply, in particular phosphorus, control the long-term (centennial) responseof eutrophication, biogeochemical fluxes and oxygen conditions in the deep water.The analysis of simulated primary production, nitrogen fixation, and hypoxic areasshows that uncertainties caused by the various nutrient load scenarios are greaterthan the uncertainties due to climate model uncertainties and future greenhouse gasconcentrations. In all scenario simulations, a proposed nutrient load abatement strategy,i.e., the Baltic Sea Action Plan, will lead to a significant improvement in the overallenvironmental state. However, the projections cannot provide detailed information onthe timing and the reductions of future hypoxic areas, due to uncertainties in salinityprojections caused by uncertainties in projections of the regional water cycle and of themean sea level outside the model domain.&nbsp

18 pages, 5 figures, 3 tables, supporting information https://dx.doi.org/10.1111/gcb.14630, Tuna are globally distributed species of major commercial importance and some tuna species are a major source of protein in many countries. Tuna are characterized by dynamic distribution patterns that respond to climate variability and long-term change. Here, we investigated the effect of environmental conditions on the worldwide distribution and relative abundance of six tuna species between 1958 and 2004 and estimated the expected end-of-the-century changes based on a high-greenhouse gas concentration scenario (RCP8.5). We created species distribution models using a long-term Japanese longline fishery dataset and two-step generalized additive models. Over the historical period, suitable habitats shifted poleward for 20 out of 22 tuna stocks, based on their gravity centre (GC) and/or one of their distribution limits. On average, tuna habitat distribution limits have shifted poleward 6.5 km per decade in the northern hemisphere and 5.5 km per decade in the southern hemisphere. Larger tuna distribution shifts and changes in abundance are expected in the future, especially by the end-of-the-century (2080–2099). Temperate tunas (albacore, Atlantic bluefin, and southern bluefin) and the tropical bigeye tuna are expected to decline in the tropics and shift poleward. In contrast, skipjack and yellowfin tunas are projected to become more abundant in tropical areas as well as in most coastal countries' exclusive economic zones (EEZ). These results provide global information on the potential effects of climate change in tuna populations and can assist countries seeking to minimize these effects via adaptive management, This research was funded by the Basque Government (Department Deputy of Agriculture, Fishing, and Food Policy) and Fundación Biodiversidad (Spanish Ministry of Agriculture and Fishing, Food and Environment; CLIREMAR project). M. Erauskin has benefited from a Basque Government scholarship through Economic Development and Infrastructures Department. [...] A. Cabre is grateful for the “Beatriu de Pinos” fellowship and the program Marie Curie Actions COFUND of the 7th Framework Program for Research and Technological Development of the European Union

International audience This study introduces CNRM‐ESM2‐1, the Earth system (ES) model of second generation developed by CNRM‐CERFACS for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). CNRM‐ESM2‐1 offers a higher model complexity than the Atmosphere‐Ocean General Circulation Model CNRM‐CM6‐1 by adding interactive ES components such as carbon cycle, aerosols, and atmospheric chemistry. As both models share the same code, physical parameterizations, and grid resolution, they offer a fully traceable framework to investigate how far the represented ES processes impact the model performance over present‐day, response to external forcing and future climate projections. Using a large variety of CMIP6 experiments, we show that represented ES processes impact more prominently the model response to external forcing than the model performance over present‐day. Both models display comparable performance at replicating modern observations although the mean climate of CNRM‐ESM2‐1 is slightly warmer than that of CNRM‐CM6‐1. This difference arises from land cover‐aerosol interactions where the use of different soil vegetation distributions between both models impacts the rate of dust emissions. This interaction results in a smaller aerosol burden in CNRM‐ESM2‐1 than in CNRM‐CM6‐1, leading to a different surface radiative budget and climate. Greater differences are found when comparing the model response to external forcing and future climate projections. Represented ES processes damp future warming by up to 10% in CNRM‐ESM2‐1 with respect to CNRM‐CM6‐1. The representation of land vegetation and the CO2‐water‐stomatal feedback between both models explain about 60% of this difference. The remainder is driven by other ES feedbacks such as the natural aerosol feedback.

Following earlier regional assessment studies, such as the Assessment of Climate Change for the Baltic Sea Basin and the North Sea Region Climate Change Assessment, knowledge acquired from available literature about future scenario simulations of biogeochemical cycles in the Baltic Sea and their uncertainties is assessed. The identification and reduction of uncertainties of scenario simulations are issues for marine management. For instance, it is important to know whether nutrient load abatement will meet its objectives of restored water quality status in future climate or whether additional measures are required. However, uncertainties are large and their sources need to be understood to draw conclusions about the effectiveness of measures. The assessment of sources of uncertainties in projections of biogeochemical cycles based on authors\' own expert judgment suggests that the biggest uncertainties are caused by (1) unknown current and future bioavailable nutrient loads from land and atmosphere, (2) the experimental setup (including the spin up strategy), (3) differences between the projections of global and regional climate models, in particular, with respect to the global mean sea level rise and regional water cycle, (4) differing model-specific responses of the simulated biogeochemical cycles to long-term changes in external nutrient loads and climate of the Baltic Sea region, and (5) unknown future greenhouse gas emissions. Regular assessments of the models\' skill (or quality compared to observations) for the Baltic Sea region and the spread in scenario simulations (differences among projected changes) as well as improvement of dynamical downscaling methods are recommended.

The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow–climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR), and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs), participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX) and in the Fifth Coupled Model Intercomparison Project (CMIP5) respectively. We evaluate their reliability in reproducing the main drivers of snow processes – near-surface air temperature and precipitation – against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around the ensemble mean. We find that GCMs at spatial resolutions equal to or finer than 1.25° longitude are in closer agreement with the ensemble mean of satellite and reanalysis products in terms of root mean square error and standard deviation than lower-resolution GCMs. The set of regional climate models from the EURO-CORDEX ensemble provides estimates of snow water equivalent at 0.11° resolution that are locally much larger than those indicated by the gridded data sets, and only in a few cases are these differences smoothed out when snow water equivalent is spatially averaged over the entire Alpine domain. ERA-Interim-driven RCM simulations show an annual snow cycle that is comparable in amplitude to those provided by the reference data sets, while GCM-driven RCMs present a large positive bias. RCMs and higher-resolution GCM simulations are used to provide an estimate of the snow reduction expected by the mid-21st century (RCP 8.5 scenario) compared to the historical climatology, with the main purpose of highlighting the limits of our current knowledge and the need for developing more reliable snow simulations.

We analyze the past (1900–2015) temperature and precipitation changes in nine separate US climate regions. We find that the temperature increased in a statistically significant (95% confidence level equivalent to alpha level of 0.05) manner in all of these regions. However, the variability in the observed precipitation was much more complex. In the eastern US (east of Rocky Mountains), the precipitation increased in all five climate regions and the increase was statistically significant in three of them. In contract, in the western US, the precipitation increased in two regions and decreased in two with no statistical significance in any region. The CMIP5 climate models (an ensemble mean) were not able to capture properly either the large precipitation differences between the eastern and the western US, or the changes of precipitation between 1900 and 2015 in eastern US. The statistical regression model explains the differences between the eastern and western US precipitation as results of different significant predictors. The anthropogenic greenhouse gases and aerosol (GHGA) are the major forcing of the precipitation in the eastern part of US, while the Pacific Decadal Oscillation (PDO) has the major influence on precipitation in the western part of the US. Our analysis suggests that the precipitation over the eastern US increased at an approximate rate of 6.7%/K, in agreement with the Clausius-Clapeyron equation, while the precipitation of the western US was approximately constant, independent of the temperature. Future precipitation over the western part of the US will depend on the behavior of the PDO, and how it (PDO) may be affected by future warming. Low hydrological sensitivity (percent increase of precipitation per one K of warming) projected by the CMIP5 models for the eastern US suggests either an underestimate of future precipitation or an overestimate of future warming.

Cold air intrusions in three areas frequently affected by frosts of southeastern South America are analyzed based on GFDL-CM2.0 Coupled Atmospheric and Oceanic Global Circulation Model. The general objective is to investigate the model ability to simulate the frequency of intrusions in the present climate as well as the changes in the frequency of occurrence and atmospheric characteristics in a future climate scenario. The cold period (May to September) is analyzed for the control period 1961 to 1990 and for the period 2081 to 2100 from the CMIP3 A2 scenario, which reflects the extreme global warming. The coupled GFDL-CM2.0 overestimated the number of cold air intrusions for the present climate (control). This systematic error should be considered in the analyses of future climate results. Future projections indicated a reduction of these cases in GFDL results. As this model overestimated the number of cases, the reduction could be even greater. Composites of extreme cases for the present and future climate in the three areas indicated intensification of the temperature gradient which suggests more vigorous frontal systems, intensification of post-frontal highs and cold air extending to lower latitudes as compared to the present climate. Anomaly intensification was related to the climatological mean temperature, which is higher in the future than in the present. Therefore, even with less cold air intrusion over southeastern South America and a lower number of frost cases in the three areas, the occurrence of more intense systems would have an impact on the agriculture of these areas and such impact would extend to lower latitudes. Fil: Fonseca de Albuquerque Cavalcanti, Iracema. Centro de Previsao de Tempo e Estudos Climaticos; Brasil Fil: Muller, Gabriela Viviana. Provincia de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Universidad Autónoma de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; Argentina Fil: Andrade, Kelen M.. Centro de Previsao de Tempo e Estudos Climaticos; Brasil Fil: Fernández Long, María Elena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía; Argentina

This study analyzes the impact of climate change on several characteristics of rainfall in the Mekrou catchment for the twenty-first century. To this end, a multi-model ensemble based on regional climate model experiments considering two Representative Concentration Pathways (RCP4.5 and RCP8.5) is used. The results indicate a wider range of precipitation uncertainty (roughly between −10% and 10%), a decrease in the number of wet days (about 10%), an increase (about 10%) of the total intensity of precipitation for very wet days, and changes in the length of the dry spell period, as well as the onset and end of the rainy season. The maximum rainfall amounts of consecutive 24 h, 48 h and 72 h will experience increases of about 50% of the reference period. This change in rate compared to the reference period may cause an exacerbation of extreme events (droughts and floods) in the Mekrou basin, especially at the end of the century and under the RCP8.5 scenario. To cope with the challenges posed by the projected climate change for the Mekrou watershed, strong governmental policies are needed to help design response options.

In this work we developed projections for future fire regimes in the Iberian Peninsula using outputs from Regional Climate Model (RCM) from the ENSEMBLES project. Wildfires are the cause of major ecological and economic impacts in this region, and the increasing evidence of climate change consequences in this region raises concerns on the future impacts of fires in the Iberian forests ecosystems. Our results confirm that the inter-annual variability of total burnt area is mainly controlled by meteorological conditions, in spite of the current efforts for fire control and suppression. We also show that this meteorology dominance over fire activity is not only true during the fire season itself, but also that certain specific meteorological backgrounds (such as prolonged droughts) may enhance the risk for severe wildfire episodes in some areas. Based on a previous classification of the Iberian Peninsula into four distinct pyro-regions, we developed statistical models which reproduce about two thirds of the inter-annual variability of the burnt area, using meteorological variables as predictors (calibrated with data from the ERA-Interim reanalysis). Specific models were developed for each sub-domain, testing their robustness for extrapolation under climate-change conditions. Using an ensemble of state-of-the-art RCM future climate scenarios, we present future BA projections considering two alternative techniques of statistical correction of model data often used in climate change impact studies: (1) unbiasing method; (2) delta change method. Our results clearly project large increases in mean burnt areas for all the considered pyro-regions, despite some fluctuations regarding each considered technique. By 2075, mean burnt areas could be about two to three times larger than in the present, taking into account current climate projections for the next century, and non-significant changes in other external factors, such as human activity, fire suppression or land use., Pedro M. Sousa was supported by Fundação para a Ciência e a Tecnologia (FCT) through a doctoral grant (SFRH/BD/84395/2012). Mario Gonzalez Pereira was supported by national funds by FCT - Portuguese Foundation for Science and Technology, under the project PEst-OE/AGR/UI4033/2014.

Foram propostos dois cenários futuros para a Amazônia Ocidental, utilizando-se a saída do Modelo de circulação regional HadRM3 para radiação solar global (Rg), para o Estado do Acre. Os cenários A2 (pessimista) e B2 (otimista) são baseados no relatório do IPCC (Intergovernmental Panel on Climate Change). Foram definidas duas estações distintas para ambos os cenários: a estação seca, de abril a setembro, e a estação chuvosa, de outubro a março. O período de 1961 a 1990, "baselines", e para os cenários A2 e B2, a simulação ocorreu entre 2070 e 2100. A conversão da grade pontual do modelo HadRM3 foi baseada no método de Krigagem Ordinária. Os menores valores de R g abrangem a parte oeste do Estado do Acre, na estação seca, em ambos os cenários. Os valores intermediários de R g são na direção norte-sul, seguidos dos maiores valores de R g, que são na porção leste do Estado; houve um aumento significativo de Rg na estação chuvosa no período de 2080 a 2090, em ambos os cenários adotados no estudo. Com base na estatística descritiva e exploratória dos cenários otimista, pessimista e "baseline" mostrou-se que a forçante radiativa (positivo) tende a aquecer a superfície continental e, ao contrário, situação negativa tende a esfriar, sendo identificado tal quadro na formação do gradiente entre as direções leste-oeste do Estado do Acre, para ambas as estações no período de estudo. Two future climate scenarios have been proposed for the the Western Amazon region - state of Acre, Brazil - using the HadRM3 regional climate model for global solar radiation (Rg). The two climate scenarios, A2 (pessimistic) and B2 (optimistic), are based on findings of the IPCC (Intergovernmental Panel on Climate Change) report. Two distinct seasons were defined for both climate scenarios (dry and rainy): the dry season (from April to September) and the rainy season (from October to March). We chose the time period between 1961 and 1990 as baseline and carried out future simulation from 2070 to 2100 for the A2 and B2 settings. The grid point conversion of the HadRM3 model was based on the Ordinary Kriging method. The smallest values of Rg are found for the western part of Acre state during the dry season in both scenarios. Intermediate values of Rg are observed for the north to south direction, followed by the highest values of Rg for the east side of the state, with significant increase of Rg during the rainy season between 2080 and 2090 for both settings adopted in this study. Based on descriptive and exploratory statistics for the optimistic, pessimistic, and baseline settings, we conclude that the positive radiative forcing tends to warm the land surface, while the negative radiative forcing tends to cool it. This was observed in the formation of the gradient in the east to west direction of the state of Acre in both seasons during the study period.

Lakes (including reservoirs) are an important component of the global carbon (C) cycle, as acknowledged by the fifth assessment report of the IPCC. In the context of lakes, the boreal region is disproportionately important contributing to 27% of the worldwide lake area, despite representing just 14% of global land surface area. In this study, we used a statistical approach to derive a prediction equation for the partial pressure of CO2 (pCO2 ) in lakes as a function of lake area, terrestrial net primary productivity (NPP), and precipitation (r2 = .56), and to create the first high-resolution, circumboreal map (0.5°) of lake pCO2 . The map of pCO2 was combined with lake area from the recently published GLOWABO database and three different estimates of the gas transfer velocity k to produce a resulting map of CO2 evasion (FCO2 ). For the boreal region, we estimate an average, lake area weighted, pCO2 of 966 (678-1,325) μatm and a total FCO2 of 189 (74-347) Tg C year-1 , and evaluate the corresponding uncertainties based on Monte Carlo simulation. Our estimate of FCO2 is approximately twofold greater than previous estimates, as a result of methodological and data source differences. We use our results along with published estimates of the other C fluxes through inland waters to derive a C budget for the boreal region, and find that FCO2 from lakes is the most significant flux of the land-ocean aquatic continuum, and of a similar magnitude as emissions from forest fires. Using the model and applying it to spatially resolved projections of terrestrial NPP and precipitation while keeping everything else constant, we predict a 107% increase in boreal lake FCO2 under emission scenario RCP8.5 by 2100. Our projections are largely driven by increases in terrestrial NPP over the same period, showing the very close connection between the terrestrial and aquatic C cycle.