Climate Models Research Articles

A Forensic Investigation of Climate Model Biases in Teleconnections: The Case of the Relationship Between ENSO and the Northern Stratospheric Polar Vortex

AbstractTeleconnections are crucial in shaping climate variability and regional climate change. The fidelity of teleconnections in climate models is important for reliable climate projections. As the observed sample size is limited, scientific judgment is required when models disagree with observed teleconnections. We illustrate this using the example of the relationship between El Niño‐Southern Oscillation (ENSO) and the northern stratospheric polar vortex (SPV), where the MIROC6 large ensemble exhibits an ENSO‐SPV correlation opposite in sign to observations. Yet the model well captures the upward planetary‐wave propagation pathway through which ENSO is known to affect the SPV. We show that the discrepancy arises from the model showing an additional linkage related to horizontal stratospheric wave propagation. Observations do not provide strong statistical evidence for or against the existence of this linkage. Thus, depending on the research purpose, a choice has to be made in how to use the model simulations. Under the assumption that the additional linkage is spurious, a physically‐based bias adjustment is applied to the SPV, which effectively aligns the modeled ENSO‐SPV relationship with the observations, and thereby removes the model‐observations discrepancy in the surface air temperature response. However, if one believed that the additional linkage was genuine and was undersampled in the observations, a different approach could be taken. Our study emphasizes that caution is needed when concluding that a model is not suitable for studying teleconnections. We propose a forensic approach and argue that it helps to better understand model performance and utilize climate model data more effectively.

Bayesian estimates for changes of the Russian river runoff in the 21st century as based on the CMIP6 model ensemble simulations

Based on ensemble calculations with the CMIP6 (Coupled Model Intercomparison Project, phase 6) climate models and using Bayesian averaging, an analysis was conducted on the changes in the 21st century runoff of several Russian rivers – the Volga, Ob, Yenisei, Lena, Amur, and Selenga. Bayesian weights considered the quality of models’ reproduction of runoff (long-term average runoff, linear runoff trend over the time interval with available runoff observations, interannual and interdecadal variability). The quality of runoff characteristics reproduction by individual models in the CMIP6 ensemble varies most significantly for the long-term average runoff, runoff trend, and, to a lesser extent, for interannual variability. In the 21st century, the ensemble average runoff increases for most of the analyzed rivers, except for the Volga. This increase is more pronounced under scenarios with larger anthropogenic impacts. It is especially significant for the SSP5-8.5 scenario (Shared Socioeconomic Pathways, 5-8.5), under which the runoff increase trend from 2015 to 2100 relative to its current long-term average is (10 ± 4)% for the Ob, (16 ± 3)% for the Yenisei, (39 ± 7)% for the Lena, (36 ± 7)% for the Amur, and (18 ± 6)% for the Selenga. The primary reason for the change in ensemble average runoff in the 21st century in models under all SSP scenarios is the change in precipitation. Accounting for differences in model quality in reproducing river runoff on average for 2015–2100 reduces inter-model deviations relative to the corresponding values with uniform weighting of model results by 6–26%, depending on the SSP scenario and river basin.

Microwave scattering properties of ice crystal particles during the melting process

Ice crystal particles play an important role in the study of cloud resolution, climate models, and radiative forcing. During the melting process, significant changes occur in the microphysical properties of ice crystal particles, such as the ice phase state, morphology, and mixing state. This process further affects the scattering and radiation characteristics properties of ice crystal particles. In this study, we constructed a non-spherical and inhomogeneous particle model based on the melting process of ice crystal particles. The scattering properties of melting ice crystal particles under four selected microwave frequency bands (92 GHz, 220 GHz, 280 GHz, and 340 GHz) are investigated by using discrete dipole approximation (DDA) method. The influence of ice crystal content (ICC) and particle aspect ratio on the scattering properties of ice crystal particles under thin coating and medium coating conditions are emphasized. The results show that the melting process significantly affects the scattering properties of melting ice crystal particles in a frequency dependent manner. Additionally, even slight melting of ice crystal particles leads to drastic changes in their scattering properties. Furthermore, we found that the morphology of ice crystal nuclei has a significant impact on their scattering characteristics even at medium levels of melting degree. In summary, this study confirms that it is essential to consider morphology and inhomogeneous characteristics during the melting process for microwave detection of ice crystal particles. This research may have significant implications for studies related to detection and inversion techniques for ice crystal particles.

Manifold increase in the spatial extent of heatwaves in the terrestrial Arctic

It is widely acknowledged that the intensity, frequency and duration of heatwaves are increasing worldwide, including the Arctic. However, less attention has been paid to the land area affected by heatwaves. Here, using atmospheric reanalysis and global climate models, we show that the area covered by heatwaves is substantially expanding in the terrestrial Arctic. Compared to the mid-20th century, the total land area affected by severe heatwaves in the Arctic has doubled, the area of extreme heatwaves has tripled, and the area of very extreme heatwaves has quadrupled. Furthermore, climate model projections suggest that the extent of heatwaves will continue to increase in the 21st century, but with large regional differences in heatwave magnitudes due to summer intraseasonal temperature variability. Our findings underscore the growing vulnerability of the Arctic region to extreme heat, potentially leading to severe impacts on both ecosystems and societies.

Contrasting Rainfall Anomaly Patterns Over South America Related to Central and Eastern Atlantic Niño Modes

ABSTRACTThe present study examines the effects of the central Atlantic Niño (CAN) and eastern Atlantic Niño (EAN) events on the seasonal precipitation in South America (SA) during the 1951–2020 period. For the CAN during the summer and autumn, an interhemispheric sea surface temperature (SST) dipole mode induces an anomalous thermally direct circulation in the 10° N–10° S band and is the main factor causing precipitation anomaly patterns with a dipole structure between northern (negative) and northeastern (positive) SA. For winter and spring, the SST pattern featuring a South Atlantic dipole induces meridional and zonal anomalous circulations, which are the mechanisms causing positive precipitation anomalies in tropical SA to the north of 20° S. In contrast, for the EAN, the precipitation anomaly patterns show large areas with anomalous dryness, particularly during summer, autumn, and spring. For summer and autumn, the east–west SST anomaly gradient in the equatorial Atlantic and the associated sea level pressure (SLP) anomalies induce equatorial westerlies and a regional Walker cell with descending motions in most tropical SA, where large areas with anomalous dryness are noted. During spring, a northward SST gradient in the tropical Atlantic induces a meridional cell with descending motions in the 0°–10° S band; meanwhile, the westward SST gradient in the equatorial Atlantic and tropical South Atlantic induces a zonal circulation with descending motions over northeastern and eastern Brazil. These descending motions extend the anomalous dryness over a large area. For the EAN events, the east–west SST gradient and the associated east–west circulation in the South American/Atlantic region are crucial elements to modulate precipitation variability in SA. Therefore, the CAN and EAN events induce distinct precipitation anomaly patterns in SA due to distinct associated regional circulation patterns. The results presented here have not been discussed before and might have relevant implications for climate monitoring and modelling studies.

Spiralling Inverse Method: A new inverse method to estimate ocean mixing

Abstract Here we introduce the Spiralling Inverse Method (SIM) that provides estimates of the small-scale and mesoscale mixing strength. The SIM uses a vertical integral over a balance between the watermass transformation equation and the thermal wind equation. The result is an equation where all terms, except for the mixing strengths, can be obtained from hydrographic data of temperature and salinity. As an advantage, the SIM estimates the mixing strengths without the need of further knowledge of a reference velocity or streamfunction. Here we apply the SIM to a small region in the North Atlantic. We find that the estimates obtained by the SIM compare well to observations and other (inverse) estimates of the mixing strength. The SIM therefore has potential to improve and constrain parameterizations used for climate and ecosystem modelling using readily available hydrographic data.

Evaluation and projection of changes in temperature and precipitation over Northwest China based on CMIP6 models

AbstractNorthwest China is much more sensitive to climate warming, and the climate has varied rapidly from warm and drought to warm and humid conditions. In addition, due to the complex terrain of Northwest China, the methods and parameterization schemes of different CMIP6 models, these models are mostly applied to arid areas in Northwest China or Central Asia, lacking climate data for plateau areas and eastern Lanzhou, specifically in filtering CMIP6 models and evaluating applicable models. In this paper, 34 CMIP6 climate models are used to evaluate and forecast future trends in Northwest China under the SSP126, SSP245 and SSP585 scenarios in the short, medium and long term. CMIP6 models of temperature and precipitation are identified by applying the interannual variability skill score (IVS) between CN05.1 datasets and historical CMIP6 models, which are suitable for Northwest China. Then, we assess the characteristics, warming and wetting deviations, and uncertainties in the prediction of climatic change according to CMIP6 models over Northwest China. The results show that CMIP6 models in precipitation and temperature applicable to Northwest China are AWI‐CM‐1‐1‐MR, BCC‐CSM2‐MR, FGOALS‐g3, INM‐CM4‐8, INM‐CM5‐0 and MRI‐ESM2‐0. The multi‐model ensemble mean (MMEM) has better capability than individual CMIP6 models in precipitation and temperature prediction. Spatiotemporal climatic change over Northwest China shows overall warming and wetting trends. The IVS provides the ability to estimate CMIP6 model simulation performance both temporally and spatially. The temperature simulation is quite good in the Tarim Basin and Hexi Corridor region, and the precipitation simulation is quite good in the plateau region, Altai Mountains, Tianshan Mountains and Hexi Corridor region. Cold and wet deviations occur in Northwest China due to the topography and few stations, which are common reasons. The main sources of uncertainties in temperature prediction during this century are model uncertainty (before the 2090s) and scenario variability (after the 2090s), and model uncertainty in precipitation for CMIP6 becomes the main source of uncertainty.

Natural sinks and sources of CO<sub>2</sub> and CH<sub>4</sub> in the atmosphere of Russian regions and their contribution to climate change in the 21st century evaluated with CMIP6 model ensemble

The natural fluxes of CO2 and CH4 into the atmosphere from the territory of Russia in the 21st century have been analyzed using the results of calculations with the ensemble of global climate models of the international project CMIP6. Estimates of natural CO2 fluxes in Russian regions differ greatly for different models. Their values for the beginning of the 21st century range from –1 to 1 GtC/yr. In the 21st century the differences in model estimates of fluxes grow and at the end of the 21st century in the scenario with the largest anthropogenic impacts SSP5-8.5 range from –2.5 to 2.5 GtC/year. Estimates of natural methane emissions to the atmosphere from the territory of Russia also differ greatly for different models. Modern methane emissions are estimated in the range from 10 to 35 MtCH4/yr, with an increase in the 21st century of up to 300%. Ensemble model calculations show general trends for changes in natural greenhouse gas fluxes. Most CMIP6 ensemble models are characterized by a maximum of CO2 uptake by terrestrial ecosystems and its further reduction by the end of the 21st century, while natural methane emissions to the atmosphere for all models and scenarios of anthropogenic impacts grow throughout the 21st century. The cumulative temperature potential of natural CO2 fluxes on the territory of Russia in the 21st century is estimated, depending on the scenario of anthropogenic impacts, from –0.3 to 0.1 K, and the warming-accelerating impact of natural CH4 emissions is estimated in the range of 0.03-0.09 K.

Tropical cyclone landfalls in the Northwest Pacific under global warming

AbstractThis study projects the changes in tropical cyclone (TC) landfalls in the western North Pacific under shared socioeconomic pathway (SSPs) scenarios during the TC peak season by using low‐resolution global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). Projections are based on the relationship between mid‐ and lower‐level atmospheric circulation and TC landfall frequency during the historical period from 1985 to 2014 and the future climate period from 2015 to 2100. The landfall areas for TCs are divided into northern East Asia (NEA), middle East Asia (MEA) and southern East Asia (SEA); the TC peak seasons are July–September for NEA and MEA, and July–November for SEA. To evaluate reproducibility, both ensemble and individual model outputs for mid‐ and lower‐level atmospheric circulations associated with TC landfall in each East Asian subregion are compared to the reanalysis. An ensemble of seven models with stable results for all three regions is more reasonable in simulating atmospheric circulation patterns than an ensemble of all CMIP6 models. The findings suggest that TC landfall is projected to increase by about 12% and 32% in NEA and MEA, respectively, in the late 21st century under the SSP5‐8.5 scenario compared to the historical period, while decreasing by 13% in SEA. These changes are consistent under both warming scenarios, and are more pronounced in the SSP5‐8.5 scenario compared to SSP1‐2.6, particularly in the later period of this century. An analysis of future atmospheric circulations suggests that global warming will weaken the western North Pacific subtropical high and cause its boundary to retreat eastward. This will lead to changes in the steering flow, which is closely related to TC tracks, resulting in TC landfalls to increase or decrease depending on the East Asian subregion.

Efficient Estimation of Climate State and Its Uncertainty Using Kalman Filtering with Application to Policy Thresholds and Volcanism

Abstract We present the Energy Balance Model – Kalman Filter (EBM-KF), a hybrid model projecting and assimilating the global mean surface temperature (GMST) and ocean heat content anomaly (OHCA). It combines an annual energy balance model (difference equations) with 17 parameters drawn from the literature and a statistical Extended Kalman Filter assimilating GMST and OHCA, either observed timeseries or simulated by earth system models. Our motivation is to create an efficient and natural estimator of the climate state and its uncertainty, which we believe to be Gaussian at a global scale. We illustrate four applications: 1) EBM-KF generates a similar estimate to the 30-year time-averaged climate state 15 years sooner, or a model-simulated hindcasts’ annual ensemble average, depending on whether volcanic forcing is filtered or not. 2) EBM-KF conveniently assesses annually likelihoods of crossing a policy threshold. For example, based on temperature records up to the end of 2023, p=0.0017 that the climate state was 1.5°C over preindustrial, but there is a 16% likelihood that the GMST in 2023 itself could have been over that threshold. 3) A variant of the EBM-KF also approximates the spread of an entire climate model large ensemble using only one or a few ensemble members. 4) All variants of the EBM-KF are sufficiently fast to allow thorough sampling from non-Gaussian probabilistic futures, e.g., the impact of rare but significant volcanic eruptions. This sampling with the EBM-KF better determines how future volcanism may affect when policy thresholds will be crossed and what an ensemble with thousands of members exploring future intermittent volcanism reveals.

The Increase in Urban Heat Due to Global Warming Can be Significantly Affected by the Structure of the Land Use and Land Cover

ABSTRACTUrban populations are increasingly exposed to excessive heat. Heat distribution in the urban environment can be affected by several factors, including the spatial arrangement of land use/land cover (LULC) that is specific to a given city. This study applies a climate model with urban canopy parameterisation to downscale future climate projections and simulate the spatio‐temporal pattern of heat in the urban environment to better understand the effect of LULC structure on its distribution. Heat conditions are characterised by climate indices that are well representative in two mid‐sized Central European cities of Brno and Ostrava (Czech Republic). Our results show that the annual number of hot days (HOT), summer days (SUD), tropical nights (TRN) and warm nights (WAN) will increase significantly (p < 0.01) in the 21st century in both cities. The model also simulates a more intensive increase and a higher spatio‐temporal variability in all indices in Brno compared to Ostrava. In Brno, the annual number of HOT and TRN is projected to be more than 500% of the 1981–2010 reference period's value by the end of the 21st century under the RCP 8.5 scenario. To determine the causes of the differences in heat distribution, we applied LULC configuration metrics and correlation analysis using various geographical factors. The higher risk of urban heat in Brno compared to Ostrava can be attributed to a more homogenised and less fragmented LULC structure and to the more substantial role of altitude in the complex terrain of Brno. Other factors, such as the presence of impervious surfaces and vegetation, have a similar effect on the variability of the studied indices in both cities. Urban planners should consider the role of the LULC structure and the changes that can be made in a city when designing adaptation measures to mitigate the effects of urban heat.

Climate Change and Building Renovation: The Impact of Historical, Current, and Future Climatic Files on a School in Central Italy

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%.

A slower North Equatorial Countercurrent but faster Equatorial Undercurrent in a warming climate

Abstract We analyze century-end projections for the tropical Pacific upper-ocean currents simulated within the Climate Model Intercomparison Project Phase 6 (CMIP6) under global warming. We find that while the intensity of precipitation within the Intertropical Convergence Zone (ITCZ) increases, the ITCZ also shifts towards the equator and broadens, which reduces wind stress curl north of the equator. Consequently, the North Equatorial Countercurrent (NECC) shifts equatorward, following the ITCZ, and weakens, despite the more intense ITCZ. The strength of the North Equatorial Current (NEC) and the South Equatorial Current (SEC) also decreases due to the weakening of the Walker circulation and the corresponding wind stress. However, despite the weaker winds, the Equatorial Undercurrent (EUC) intensifies as it shoals due to stronger vertical stratification induced by surface warming. Furthermore, we find a slightly stronger zonal pressure gradient along the core of the EUC, instead of a weaker one expected from weaker wind stress and sea surface height gradient along the equator. Ultimately, we argue that it is reduced vertical friction theory due to increased ocean stratification and hence larger Richardson number that explains the faster EUC. These intricate balances control future changes in equatorial currents, and the uncertainties of projected changes need to be further examined.

Sea ice feedbacks cause more greenhouse cooling than greenhouse warming at high northern latitudes on multi-century timescales

Abstract In contrast to surface greenhouse warming, surface greenhouse cooling has been less explored, especially on multi-century timescales. Here, we assess the processes controlling the pacing and magnitude of the multi-century surface temperature response to instantaneously doubling and halving atmospheric carbon dioxide concentrations in a modern global coupled climate model. Over the first decades, surface greenhouse warming is larger and faster than surface greenhouse cooling both globally and at high northern latitudes (45–90° N). Yet, this initial multi-decadal response difference does not persist. After year 150, additional surface warming is negligible, but surface cooling and sea ice expansion continues. Notably, the equilibration timescale for high northern latitude surface cooling (∼437 years) is more than double the equivalent timescale for warming. The high northern latitude responses differ most at the sea ice edge. Under greenhouse cooling, the sea ice edge slowly creeps southward into the mid-latitude oceans amplified by positive lapse rate and surface albedo feedbacks. While greenhouse warming and sea ice loss at high northern latitudes occurs on multi-decadal timescales, greenhouse cooling and sea ice expansion occurs on multi-century timescales. Overall, this work shows the importance of multi-century timescales and sea ice processes for understanding high northern latitude climate responses.

Strong contribution from sensible heat to global precipitation increase in climate models is not supported by observational based data

It has previously been shown that trends in sensible heat from climate models have had a substantial contribution to global precipitation changes. We illustrate that this is the case also in the most recent Coupled Model Intercomparison Project Phase 6 (CMIP6). However, we find that over the period since 1980 reanalyses do not support the reduction in sensible heat from the CMIP6 models and rather estimate a global increase in sensible heat which would contribute to a precipitation reduction. Satellite data over a period of two decades over global ocean generally show an opposite sign of the sensible heat trend to the CMIP6 models, similarly to the reanalyses.

Uncertainty of climate models and policy implications: a European perspective

AbstractIn this paper we show that both climate models and economic models studying the effects of climate change are characterized by high uncertainty. Hence, far reaching policy implications such as the net zero goal lack a definite scientific foundation. Nevertheless, it cannot be excluded that the continued global warming will go along with high damages in the future. Therefore, decreasing greenhouse gas emissions could be justified due to the precautionary motif. However, there are strong signals from non-European economic regions that they definitely put a higher weight on economic growth rather than on greenhouse gas mitigation. The reduction of greenhouse gases in the European Union cause tremendous costs without influencing the climate on earth. Further, these investments do not raise the aggregate stock of productive capital nor do they lead to factor augmenting technical progress. Therefore, the net zero goal of the Green Deal of the European Union is to be seen sceptical.

The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models

AbstractFor a number of years research has been carried out in several centres which has demonstrated the potential benefits of 100‐m scale models for a range of meteorological phenomena. More recently, some meteorological services have started to consider seriously the operational implementation of practical hectometric models. Many, but by no means all, of the applications are likely to relate to urban areas, where the enhanced resolution has obvious benefits. This article is concerned with the issues that need to be addressed to bridge the gap between research at 100‐m scales and practical models. We highlight a number of key issues that need to be addressed, with suggestions of important avenues for future development. An overarching issue is the high computational cost of these models. Although some ideas to reduce this are presented, it will always be a serious constraint. This means that the benefits of these models over lower resolution ones, or other techniques for generating high‐resolution forecasts, will need to be clearly understood, as will the trade‐offs with resolution. We discuss issues with model dynamical cores and physics–dynamics coupling. There are a number of challenges around model parameterisations, where some of the traditional problems (e.g., convection) become easier but a number of new challenges (e.g., around surface parameterisations) appear. Observational data at these scales present a challenge and novel types of observations will need to be considered. Data assimilation will be needed for short‐range forecasts, but there is currently little knowledge of this, although some of the likely issues are clear. An ensemble approach will be essential in many cases (e.g., convection), but research is needed into ensembles at these scales and significant work on post‐processing systems is required to make the best use of models at these grid lengths.

Comparison of indicators to evaluate the performance of climate models

AbstractThe evaluation of climate models is a crucial step in climate studies. It consists of quantifying the resemblance of model outputs to reference data to identify models with superior capacity to replicate specific climate variables. Clearly, the choice of the evaluation indicator significantly impacts the results, underscoring the importance of selecting an indicator that properly captures the characteristics of a “good model”. This study examines the behaviour of six indicators, considering spatial correlation, distribution mean, variance and shape. Monthly data for precipitation, temperature and teleconnection patterns in Central America were utilized in the analysis. A new multicomponent measure was selected based on these criteria to assess the performance of 32 CMIP6 models in reproducing the annual seasonal cycle of these variables. The top six models were determined using multicriteria methods. It was found that even the best model reproduces one derived climatic variable poorly in this region. The proposed measure and selection method can contribute to enhancing the accuracy of climatological research based on climate models.

Impact of stochastic physics on the representation of atmospheric blocking in EC-Earth3

Abstract. Atmospheric blocking is a synoptic-scale phenomenon that consists in an obstruction of the normal easterly progression of weather patterns in the midlatitudes, leading to persistent atmospheric conditions sometimes associated with extreme weather. State-of-the-art climate models systematically underestimate winter atmospheric-blocking frequency, especially over Europe. This is often attributed to a poor representation of small-scale processes that are fundamental for the onset and maintenance of blocking events. Here, we explore how the implementation of two stochastic parameterizations, namely the stochastically perturbed parameterization tendencies (SPPTs) and the stochastic kinetic energy backscatter (SKEB) schemes, influences the representation of Northern Hemisphere winter blocking in EC-Earth3. We show that the activation of the two stochastic schemes has moderate detrimental effects on blocking representation, when assessed through a gradient reversal index. Using a zonal–blocked flow linear decomposition, we attribute such modification to changes in the mean winter atmospheric circulation, primarily manifested in a strengthening of the midlatitude jet stream and an intensification of the Hadley cell. Ultimately, an analysis of the meridional transport of zonal momentum by stationary and transient eddies reveals that these circulation differences arise from changes in tropical stationary-eddy activity. Our findings reconnect with earlier literature on similar experiments and suggest that the activation of stochastic parameterizations may require a retuning of the model to account for the resulting significant changes in the mean atmospheric circulation.

Climate-driven global redistribution of an ocean giant predicts increased threat from shipping

AbstractClimate change is shifting animal distributions. However, the extent to which future global habitats of threatened marine megafauna will overlap existing human threats remains unresolved. Here we use global climate models and habitat suitability estimated from long-term satellite-tracking data of the world’s largest fish, the whale shark, to show that redistributions of present-day habitats are projected to increase the species’ co-occurrence with global shipping. Our model projects core habitat area losses of >50% within some national waters by 2100, with geographic shifts of over 1,000 km (∼12 km yr−1). Greater habitat suitability is predicted in current range-edge areas, increasing the co-occurrence of sharks with large ships. This future increase was ∼15,000 times greater under high emissions compared with a sustainable development scenario. Results demonstrate that climate-induced global species redistributions that increase exposure to direct sources of mortality are possible, emphasizing the need for quantitative climate-threat predictions in conservation assessments of endangered marine megafauna.