Non-linear loss of suitable wine regions over Europe in response to increasing global warming.

Evaluating the potential climatic suitability for premium wine production is crucial for adaptation planning in Europe. While new wine regions may emerge out of the traditional boundaries, most of the present-day renowned winemaking regions may be threatened by climate change. Here, we analyse the future evolution of the geography of wine production over Europe, through the definition of a novel climatic suitability indicator, which is calculated over the projected grapevine phenological phases to account for their possible contractions under global warming. Our approach consists in coupling six different de-biased downscaled climate projections under two different scenarios of global warming with four phenological models for different grapevine varieties. The resulting suitability indicator is based on fuzzy logic and is calculated over three main components measuring (i) the timing of the fruit physiological maturity, (ii) the risk of water stress and (iii) the risk of pests and diseases. The results demonstrate that the level of global warming largely determines the distribution of future wine regions. For a global temperature increase limited to 2°C above the pre-industrial level, the suitable areas over the traditional regions are reduced by about 4%/°C rise, while for higher levels of global warming, the rate of this loss increases up to 17%/°C. This is compensated by a gradual emergence of new wine regions out of the traditional boundaries. Moreover, we show that reallocating better-suited grapevine varieties to warmer conditions may be a viable adaptation measure to cope with the projected suitability loss over the traditional regions. However, the effectiveness of this strategy appears to decrease as the level of global warming increases. Overall, these findings suggest the existence of a safe limit below 2°C of global warming for the European winemaking sector, while adaptation might become far more challenging beyond this threshold.

A regional scale impact and uncertainty assessment of climate change in the Western Ghats in India.

The general circulation models (GCMs) and emission scenarios (RCP 4.5 and 8.5) have proven to be significantly functional in evaluating the impacts of climate change (CC) on hydrology, although their performance and accuracy varies on a regional scale. The objective of the present study is to evaluate the performance of five CMIP5 GCMs (CanESM2, BNU-ESM, CNRM-CM5, MPI-ESM-LR and MPI-ESM-MR) on a regional scale in the West Flowing River Basins-2 (WFRB-2) in India to model the impact of CC and its scenario uncertainty using reliability ensemble average (REA) method. For quantifying the results, the upper, middle and lower regions of WFRB-2 are separately analysed. The MPIMR and MPILR GCM model shows highest reliability factor range (0.3-0.6) in predicting the annual mean and annual maximum rainfall for most of the grids in the region. The GCM-simulated runoff using VIC (variable infiltration capacity) model is evaluated using statistical parameters such as root mean square error (RMSE), percentage bias (Pbias) and standard deviation (Std). The annual mean (maximum) runoff obtained using REA ensemble shows least RMSE, Pbias and Std values, i.e. 21.08%, 9.10 mm and 8.9 mm (6%, 39.1 mm, 39.1 mm), respectively for the middle region, which demonstrates higher reliability of GCM outputs in the flood-prone regions of WFRB-2. Furthermore, the future projection of annual maximum rainfall/runoff shows an increase of 50 mm/15 mm in the near future (2011-2040) for lower and 20 mm/6 mm for middle regions, which may cause flooding activities in the lower and middle region of WFRB-2.

How climate scenarios alter future predictions of field-scale water and nitrogen dynamics and crop yields.

Climate change scenarios are widely used for exploring future changes in environmental systems. However, many aspects of the uncertainties associated with the use of climate change scenarios in environmental systems modeling have not yet been studied sufficiently. We explore how the way that baseline scenarios are defined and general circulation model (GCM) outputs are used affects climate change impact assessments of agricultural systems. Our study builds on a previously validated agricultural systems model, the Root Zone Water Quality Model (RZWQM), coupled with the Decision Support System for Agrotechnology Transfer (DSSAT), which models a tiled-drained field in central Illinois of the United States and uses nine GCM outputs to investigate the effects. Our model simulations demonstrated the following three results. Firstly, the evaluation of climate change impacts presented a significant difference between the types of baseline used. The baseline scenario should be defined using the bias-corrected retrospective GCM outputs. Secondly, once GCM outputs are bias-corrected, the selective use of GCM outputs did not add significant value over using all available GCM outputs to provide more plausible future descriptions of agricultural systems' responses. Notably, however, selective use may have impacts comparable to carbon dioxide (CO2) emission scenarios in the field-scale agricultural climate change impact assessments. Thirdly, raw GCM outputs should be avoided for the predictions of field-scale agricultural systems' responses to climate change. Our findings can help provide a clearer picture of how GCM outputs should be used in agricultural systems modeling and might enable us to have more plausible descriptions of how future agricultural systems might unfold.

Satellite-based ensemble intelligent approach for predicting forest fire: a case of the Hyrcanian forest in Iran.

A machine learning-based approach is applied to simulate and forecast forest fires in the Golestan province in Iran. A dataset for no-fire, medium confidence (MC) fire events, and high confidence (HC) fire events is constructed from MODIS-MOD14A2. Nine climate variables from NASA's FLDAS are used as input variables, and 12 dates and 915 study points are considered. Three machine learning ensemble multi-label classifiers, gradient boosting (GBC), random forest (RFC), and extremely randomized tree (ETC), are used for forest fire simulation for the period 2000 to 2021, and ETC is found to be the most accurate classifier. Future fire projection for the near-future period of 2030 to 2050 is carried out with the ETC model, using CMIP6 EC-Earth3-SSP245 General Circulation Model (GCM) data. It is projected that MC forest fire occurrences will decrease, while HC forest fire occurrences will increase, and that the summer months, especially September, will be the most affected by fire.

Simulated inventory and distribution of 137Cs released from multiple sources in the global ocean.

Radioactive cesium (137Cs) is distributed in the world's oceans as a result of global fallout from atmospheric nuclear weapons tests, releases from fuel reprocessing plants, and inputs from nuclear power plant accident. In order to detect future radionuclide contamination, it is necessary to establish a baseline global distribution of radionuclides such as 137Cs and to understand the ocean transport processes that lead to that distribution. In order to aid in the interpretation of the observed database, we have conducted a suite of simulations of the distribution of 137Cs using a global ocean general circulation model (OGCM). Simulated 137Cs radioactivity concentrations agree well with observations, and the results were used to estimate the changes in inventories for each ocean basin. 137Cs activity concentration from atmospheric nuclear weapons tests are expected to be detectable in the world ocean until at least 2030.

Projection of temperature extremes of Egypt using CMIP6 GCMs under multiple shared socioeconomic pathways.

Global warming has amplified the frequency of temperature extremes, especially in hot dry countries, which could have serious consequences for the natural and built environments. Egypt is one of the hot desert climate regions that are more susceptible to climate change and associated hazards. This study attempted to project the changes in temperature extremes for three Shared Socioeconomic Pathways (SSPs), namely, SSP1-2.6, SSP2-4.5, and SSP5-8.5 and two future periods (early future: 2020-2059 and late future: 2060-2099) by using daily maximum (Tmax) and minimum temperature (Tmin) of general circulation model (GCMs) of Coupled Model Inter-comparison Project phase 6 (CMIP6). The findings showed that most temperature extreme indices would increase especially by the end of the century. In the late future, the change in the mean Tmin (4.3 °C) was projected to be higher than the mean Tmax (3.7 °C). Annual maximum Tmax, temperature above 95th percentile of Tmax, and the number of hot days above 40 °C and 45 °C were projected to increase in the range 3.0‒5.4 °C, 1.5‒4.8 °C, 20‒95 days, and 10‒52 days, respectively. In contrast, the annual minimum of Tmin, temperature below the 5th percentile, and the annual percentage of cold nights were projected to change in the range of 2.95‒5.0 °C, 1.4‒3.6 °C, and - 0.1‒0.1%, respectively. In all the cases, the lowest changes would be for SSP1-2.6 in the early period and the greatest changes for SSP5-8.5 in the late period. The study indicates that the country is likely to experience a rise in hot extremes and a decline in cold extremes. Therefore, Egypt should take long-term adaptation plans to build social resiliency to rising hot extremes.

Evaluation of the simulated aerosol optical properties over India: COALESCE model inter-comparison of three GCMs with ground and satellite observations.

Within the framework of COALESCE project (Carbonaceous aerosol emissions, source apportionment, and climate impacts) initiative, spatio-temporal distribution of aerosol optical properties from three general circulation models are evaluated against aerosol data from satellite observations (MODIS and CALIPSO) and ground-based measurements (AERONET) for the period 2005-2014. The GCMs, NICAM-SPRINTARS (N-S), ECHAM6.3-HAM2.3 (E-H), CAM5.3 (CAM), input with identical emissions from the SMoG-India-v1 emission inventory over India nested in the CEDS global inventory, including all emission sectors except sea salt and soil dust. The annual mean total aerosol optical depth (AOD) averaged over the Indian land region is 0.38, 0.27, and 0.17 from the N-S, CAM, and E-H models respectively, while the annual mean value from the MODIS observational dataset is 0.43. Single scattering albedo predicted by E-H is lower compared to CAM and N-S while model predictions of Angstrom exponent are closer to MERRA2 dataset. However, the average total aerosol column burden over Indian landmass simulated by the models is very close and comparable to the reanalysis results. Statistical analysis of AOD between model and AERONET measurements at nine sites shows that the root mean square error varies from 0.1 to 0.4 and the index of agreement (average value) is ∼0.4. The aerosol emission and transport models, methodology for calculation of aerosol optical properties and their mixing states contributes to the diversity in the results from various models. The present study provides an analysis of limitations and uncertainties contributing to the differences between the simulations and observations, and the inter-model diversity.

Volcanic hazard exacerbated by future global warming-driven increase in heavy rainfall.

Heavy rainfall drives a range of eruptive and non-eruptive volcanic hazards. Over the Holocene, the incidence of many such hazards has increased due to rapid climate change. Here, we show that extreme heavy rainfall is projected to increase with continued global warming throughout the twenty-first century in most subaerial volcanic regions, increasing the potential for rainfall-induced volcanic hazards. This result is based on a comparative analysis of nine general circulation models, and is prevalent across a wide range of spatial scales, from countries and volcanic arcs down to individual volcanic systems. Our results suggest that if global warming continues unchecked, the incidence of primary and secondary rainfall-related volcanic activity-such as dome explosions or flank collapse-will increase at more than 700 volcanoes around the globe. Improved coupling between scientific observations-in particular, of local and regional precipitation-and policy decisions may go some way towards mitigating the increased risk throughout the next 80 years.

A generalized methodology for ranking climate models based on climate indices for sector-specific studies: An application to the Mekong sub-basin.

This study proposes a methodological framework to evaluate and rank climate models based on extreme climate indices of precipitation and temperature for impact studies in seven sectors: Cryosphere, Energy, Forestry/GHGs, Health, Agriculture & Food Security, Disaster Risk Reduction (flood and drought), and Water Resources & Hydrology. The ranking of the climate models is based on their performance in sector-relevant extreme climate indices. Extreme climate indices for observed and climate models' datasets for a historical period and overall performance statistics were used to create a payoff matrix. The payoff matrix then served as an input to a multi-criteria decision-making process to rank the climate models for each of the climate indices. The final sector-specific ranking was achieved by averaging the ranks obtained in the sector-relevant indices. The developed methodology is demonstrated with an application to the Songkhram River Basin (Thailand), a sub-basin of the Mekong. Eighteen CMIP6 GCMs are used for the proposed evaluation and ranking processes and four performance statistics were used. Weights to each of the four performance statistics were determined using the entropy method. Compromise programming was applied to rank the GCMs based on the distance technique. The results indicate that the six best performing models are different for different sectors, with the GFDL_CM4 model common in all the seven sectors considered in the study. KACE1_0_G, GFDL_ESM4, GFDL_CM4, MRI_ESM2_0, and ACCESS_ESM1_5 models are the five top (ranked 1 to 5 respectively) performing models for the Water Resources & Hydrology sector. The developed framework is generic and can be applied to any region or basin; at the same time, it can also provide researchers and policymakers with specific information on best-performing models for particular sectors.

Dataset of Phanerozoic continental climate and Köppen-Geiger climate classes.

This article describes a suite of global climate model output files that provide continental climatic conditions (monthly temperatures, precipitation, evaporation, precipitation minus evaporation balance, runoff) together with the calculated Köppen-Geiger climate classes and topography, for 28 evenly spaced time slices through the Phanerozoic (Cambrian to Quaternary, 540 Ma to 0 Ma). Climatic variables were simulated with the Fast Ocean Atmosphere Model (FOAM), using a recent set of open-access continental reconstructions with paleotopography and recent atmospheric CO2 and solar luminosity estimates. FOAM is a general circulation model frequently used in paleoclimate studies, especially in the Palaeozoic. Köppen-Geiger climate classes were calculated based on simulated temperature and precipitation fields using Wong Hearing et al.'s [1] implementation of Peel et al.'s [2] updated classification. This dataset provides a unique window onto changing continental climate throughout the Phanerozoic that accounts for the simultaneous evolution of paleogeography (continental configuration and topography), atmospheric composition and greenhouse gas forcing, and solar luminosity.

Assimilation of Both Column- and Layer-Integrated Dust Opacity Observations in the Martian Atmosphere.

A new dust data assimilation scheme has been developed for the UK version of the Laboratoire de Météorologie Dynamique Martian General Circulation Model. The Analysis Correction scheme (adapted from the UK Met Office) is applied with active dust lifting and transport to analyze measurements of temperature, and both column-integrated dust optical depth (CIDO), τ ref (rescaled to a reference level), and layer-integrated dust opacity (LIDO). The results are shown to converge to the assimilated observations, but assimilating either of the dust observation types separately does not produce the best analysis. The most effective dust assimilation is found to require both CIDO (from Mars Odyssey/THEMIS) and LIDO observations, especially for Mars Climate Sounder data that does not access levels close to the surface. The resulting full reanalysis improves the agreement with both in-sample assimilated CIDO and LIDO data and independent observations from outside the assimilated data set. It is thus able to capture previously elusive details of the dust vertical distribution, including elevated detached dust layers that have not been captured in previous reanalyzes. Verification of this reanalysis has been carried out under both clear and dusty atmospheric conditions during Mars Years 28 and 29, using both in-sample and out of sample observations from orbital remote sensing and contemporaneous surface measurements of dust opacity from the Spirit and Opportunity landers. The reanalysis was also compared with a recent version of the Mars Climate Database (MCD v5), demonstrating generally good agreement though with some systematic differences in both time mean fields and day-to-day variability.

Assessment and mitigation of tangible flood damages driven by climate change in a tropical city: Hat Yai Municipality, southern Thailand.

Climate change-induced floods in tropical urban areas have presented a serious global challenge because of failed conventional stormwater management practices. This research aims to develop a comprehensive methodological framework for flood damage estimation and mitigation, particularly in a tropical urban city. In this study, interdisciplinary fields were integrated through statistical downscaling, hydrologic-hydraulic modeling, and the development of flood damage curves. Relationships between tangible flood damage and flood-borne outbreak with flood depths were elucidated to predict future damage. Various flood mitigation strategies were evaluated. Herein, Hat Yai Municipality in Southern Thailand was selected as the study area. The flood simulation was conducted for 2010 and the highest flood damage sensitivity was exhibited by non-commercial buildings due to significant commercial stock damage, which was followed by that observed for detached houses. There was a strong linear relationship between the number of patients infected with leptospirosis and flood depth (R2 = 0.85). For climate change studies, flood maps for storms with 20-, 50-, and 100-year return periods under the A2/RCP8.5 scenario were generated using hydrological-hydraulic 1D/2D model; these maps were applied with the developed flood damage curves for damage estimation. It was found that reducing flood damage by implementing agroforestry and expanding the main bypass channel provides comparable damage reductions of -25.5% and - 27.5%, respectively, under the worst-case scenario of a 100-year return period in 2040-2059. Therefore, to deal with uncertain climate change situations, the incorporation of structural and non-structural measures is recommended. Such a combination when coupled with an eight-hour flood awareness time can result in a damage reduction of -59.9%. A flood warning system was in high demand by residents in the area; however, damage reduction from this measure alone was not high (approximately -17.0%) when compared to that obtained with other measures; consequently, additional measures were needed.

GISS-E2.1: Configurations and Climatology.

This paper describes the GISS-E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS-E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden-Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7-3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks.

Projecting the effects of agricultural conservation practices on stream fish communities in a changing climate.

How anticipated climate change might affect long-term outcomes of present-day agricultural conservation practices remains a key uncertainty that could benefit water quality and biodiversity conservation planning. To explore this issue, we forecasted how the stream fish communities in the Western Lake Erie Basin (WLEB) would respond to increasing amounts of agricultural conservation practice (ACP) implementation under two IPCC future greenhouse gas emission scenarios (RCP4.5: moderate reductions; RCP8.5: business-as-usual conditions) during 2020-2065. We used output from 19 General Circulation Models to drive linked agricultural land use (APEX), watershed hydrology (SWAT), and stream fish distribution (boosted regression tree) models, subsequently analyzing how projected changes in habitat would influence fish community composition and functional trait diversity. Our models predicted both positive and negative effects of climate change and ACP implementation on WLEB stream fishes. For most species, climate and ACPs influenced species in the same direction, with climate effects outweighing those of ACP implementation. Functional trait analysis helped clarify the varied responses among species, indicating that more extreme climate change would reduce available habitat for large-bodied, cool-water species with equilibrium life-histories, many of which also are of importance to recreational fishing (e.g., northern pike, smallmouth bass). By contrast, available habitat for warm-water, benthic species with more periodic or opportunistic life-histories (e.g., northern hogsucker, greater redhorse, greenside darter) was predicted to increase. Further, ACP implementation was projected to hasten these shifts, suggesting that efforts to improve water quality could come with costs to other ecosystem services (e.g., recreational fishing opportunities). Collectively, our findings demonstrate the need to consider biological outcomes when developing strategies to mitigate water quality impairment and highlight the value of physical-biological modeling approaches to agricultural and biological conservation planning in a changing climate.

Habitable Climate Scenarios for Proxima Centauri b with a Dynamic Ocean.

The nearby exoplanet Proxima Centauri b will be a prime future target for characterization, despite questions about its retention of water. Climate models with static oceans suggest that Proxima b could harbor a small dayside surface ocean despite its weak instellation. We present the first climate simulations of Proxima b with a dynamic ocean. We find that an ocean-covered Proxima b could have a much broader area of surface liquid water but at much colder temperatures than previously suggested, due to ocean heat transport and/or depression of the freezing point by salinity. Elevated greenhouse gas concentrations do not necessarily produce more open ocean because of dynamical regime transitions between a state with an equatorial Rossby-Kelvin wave pattern and a state with a day-night circulation. For an evolutionary path leading to a highly saline ocean, Proxima b could be an inhabited, mostly open ocean planet with halophilic life. A freshwater ocean produces a smaller liquid region than does an Earth salinity ocean. An ocean planet in 3:2 spin-orbit resonance has a permanent tropical waterbelt for moderate eccentricity. A larger versus smaller area of surface liquid water for similar equilibrium temperature may be distinguishable by using the amplitude of the thermal phase curve. Simulations of Proxima Centauri b may be a model for the habitability of weakly irradiated planets orbiting slightly cooler or warmer stars, for example, in the TRAPPIST-1, LHS 1140, GJ 273, and GJ 3293 systems.

Investigation of Intense Precipitation from Tropical Cyclones during the 21st Century by Dynamical Downscaling of CCSM4 RCP 4.5.

In this article, a dynamical downscaling (DD) procedure is proposed to downscale tropical cyclones (TCs) from a general circulation model, with the goal of investigating inland intense precipitation from these storms in the future. This DD procedure is sequential as it is performed from the large scale to the small scale within a one-way nesting modeling framework with the Weather Research and Forecasting (WRF) model. Furthermore, it involves a two-step validation process to ensure that the model produces realistic TCs, both in terms of their general properties and in terms of their intense precipitation statistics. In addition, this procedure makes use of several algorithms such as for the detection and tracking of TCs, with the objective of automatizing the DD process as much as possible so that this approach could be used to downscale massively many climate projections with several sets of model options. The DD approach was applied to the Community Climate System Model (CCSM) version 4 using Representative Concentration Pathway (RCP) 4.5 during the period 2005⁻2100, and the resulting TCs and their intense precipitation were examined.

Projection of invertebrate populations in the headwater streams of a temperate catchment under a changing climate.

Climate change places considerable stress on riverine ecosystems by altering flow regimes and increasing water temperature. This study evaluated how water temperature increases under climate change scenarios will affect stream invertebrates in pristine headwater streams. The studied headwater-stream sites were distributed within a temperate catchment of Japan and had similar hydraulic-geographical conditions, but were subject to varying temperature conditions due to altitudinal differences (100 to 850 m). We adopted eight general circulation models (GCMs) to project air temperature under conservative (RCP2.6), intermediate (RCP4.5), and extreme climate scenarios (RCP8.5) during the near (2031-2050) and far (2081-2100) future. Using the water temperature of headwater streams computed by a distributed hydrological-thermal model as a predictor variable, we projected the population density of stream invertebrates in the future scenarios based on generalized linear models. The mean decrease in the temporally averaged population density of Plecoptera was 61.3% among the GCMs, even under RCP2.6 in the near future, whereas density deteriorated even further (90.7%) under RCP8.5 in the far future. Trichoptera density was also projected to greatly deteriorate under RCP8.5 in the far future. We defined taxa that exhibited temperature-sensitive declines under climate change as cold stenotherms and found that most Plecoptera taxa were cold stenotherms in comparison to other orders. Specifically, the taxonomic families that only distribute in Palearctic realm (e.g., Megarcys ochracea and Scopura longa) were selectively assigned, suggesting that Plecoptera family with its restricted distribution in the Palearctic might be a sensitive indicator of climate change. Plecoptera and Trichoptera populations in the headwaters are expected/anticipated to decrease over the considerable geographical range of the catchment, even under the RCP2.6 in the near future. Given headwater invertebrates play important roles in streams, such as contributing to watershed productivity, our results provide useful information for managing streams at the catchment-level.

Modelling explicit tides in the Indonesian seas: An important process for surface sea water properties.

Very intense internal tides take place in Indonesian seas. They dissipate and affect the vertical distribution of temperature and currents, which in turn influence the survival rates and transports of most planktonic organisms at the base of the whole marine ecosystem. This study uses the INDESO physical model to characterize the internal tides spatio-temporal patterns in the Indonesian Seas. The model reproduced internal tide dissipation in agreement with previous fine structure and microstructure observed in-situ in the sites of generation. The model also produced similar water mass transformation as the previous parameterization of Koch-Larrouy et al. (2007), and show good agreement with observations. The resulting cooling at the surface is 0.3°C, with maxima of 0.8°C at the location of internal tides energy, with stronger cooling in austral winter. The cycle of spring tides and neap tides modulates this impact by 0.1°C to 0.3°C. These results suggest that mixing due to internal tides might also upwell nutrients at the surface at a frequency similar to the tidal frequencies. Implications for biogeochemical modelling are important.

Climate Change and Simulation of Cardiovascular Disease Mortality: A Case Study of Mashhad, Iran.

BACKGROUND: Weather and climate play a significant role in human health. We are accustomed to affects the weather conditions. By increasing or decreasing the environment temperature or change of seasons, some diseases become prevalent or remove. This study investigated the role of temperature in cardiovascular disease mortality of city of Mashhad in the current decade and its simulation in the future decades under conditions of climate change. METHODS: Cardiovascular disease mortality data and the daily temperatures data were used during (2004-2013) period. First, the correlation between cardiovascular disease mortality and maximum and minimum temperatures were calculated then by using General Circulation Model, Emissions Scenarios, and temperature data were extracted for the next five decades and finally, mortality was simulated. RESULTS: There is a strong positive association between maximum temperature and mortality (r= 0.83, P-value<0.01), also observed a negative and weak but significant association between minimum temperatures and mortality. The results obtained from simulation show increased temperature in the next decades in Mashhad and a 1 °C increase in maximum temperature is associated with a 4.27% (95%CI: 0.91, 7.00) increase in Cardiovascular disease mortality. CONCLUSION: By increasing temperature and the number of hot days the cardiovascular disease mortality increases and these increases will be intensified in the future decades. Therefore, necessary preventive measures are required to mitigate temperature effects with greater attention to vulnerable group.

Global assessment of coral bleaching and required rates of adaptation under climate change.

Elevated ocean temperatures can cause coral bleaching, the loss of colour from reef-building corals because of a breakdown of the symbiosis with the dinoflagellate Symbiodinium. Recent studies have warned that global climate change could increase the frequency of coral bleaching and threaten the long-term viability of coral reefs. These assertions are based on projecting the coarse output from atmosphere-ocean general circulation models (GCMs) to the local conditions around representative coral reefs. Here, we conduct the first comprehensive global assessment of coral bleaching under climate change by adapting the NOAA Coral Reef Watch bleaching prediction method to the output of a low- and high-climate sensitivity GCM. First, we develop and test algorithms for predicting mass coral bleaching with GCM-resolution sea surface temperatures for thousands of coral reefs, using a global coral reef map and 1985-2002 bleaching prediction data. We then use the algorithms to determine the frequency of coral bleaching and required thermal adaptation by corals and their endosymbionts under two different emissions scenarios. The results indicate that bleaching could become an annual or biannual event for the vast majority of the world's coral reefs in the next 30-50 years without an increase in thermal tolerance of 0.2-1.0°C per decade. The geographic variability in required thermal adaptation found in each model and emissions scenario suggests that coral reefs in some regions, like Micronesia and western Polynesia, may be particularly vulnerable to climate change. Advances in modelling and monitoring will refine the forecast for individual reefs, but this assessment concludes that the global prognosis is unlikely to change without an accelerated effort to stabilize atmospheric greenhouse gas concentrations.