Coupled Model Intercomparison Project Phase Research Articles

Future shifts in climatic conditions promoting northward expansion of the Mediterranean climate in the circum-Mediterranean region.

In the upcoming decades, precipitation and temperature patterns are expected to shift in the Mediterranean basin due to global warming, potentially having an influence on the environment and the economy in the area. Using monthly precipitation and temperature data from 15 global climate models (GCMs) developed as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Mediterranean Climate Envelop (MCE), as defined by Daget's (1977) criteria, is projected under two climate change scenarios: SSP2-4.5 and SSP5-8.5, and for two future periods: 2050s and 2070s. According to the findings, the MCE is expected to expand by 3.51 and 4.93% in the 2050s under the SSP2-4.5 and SSP5-8.5 scenarios, respectively, in comparison to the current state. This expansion is expected to reach 5.28 and 9.87% for SSP2-4.5 and SSP5-8.5, respectively, in 2070s. For both situations and durations, MCE contraction would be minor, however, at less than 1%. More than 99% of the present MCE would stay stable proportionately. The northern Mediterranean region is mostly concerned by the MCE's expansion. The SSP2-4.5 scenario predicts that by the 2070s, expansion zones will occupy 674,183 km2, with 64% of the area located in Southern Europe and 36% in Western Asia. In SSP5-8.5 scenario, this area is expected to be significantly larger, estimated to be approximately 1,256,881 km2; 67% in Southern Europe and 33% in Western Asia.

Influence of SST‐Precipitation Relationship Over the Equatorial Western Pacific on Simulation of the Madden‐Julian Oscillation

AbstractCapabilities of 43 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the Madden‐Julian Oscillation (MJO) were compared in this study. Models with higher MJO simulation skills reproduce organized large‐scale convection more frequently over the equatorial western Pacific (EWP), suggesting that MJO simulations are tightly connected to organization of large‐scale precipitation over the EWP. MJO simulation skills are not significantly correlated with the mean sea surface temperature (SST) over the EWP, but tightly connected to SST threshold for convection there. The top simulations exhibit lower SST threshold and more realistic SST‐precipitation relationship over the EWP, suggesting that convection can be organized more efficiently and intensified more rapidly with the increasing SST in these simulations. Our results emphasize that reproducing the relationship between SST and large‐scale precipitation over the EWP is critical to MJO simulations.

Projected Changes of the Warm Arctic‐Cold North American Pattern

AbstractThe Warm Arctic‐Cold North American (WACNA) pattern features opposing surface temperature anomalies, with centers over the Chukchi‐Bering Seas (CBS) and the North American Great Plains. The pattern is mainly driven by meridional heat transport and damped by the generation of available potential energy through diabatic heating. The Canadian Earth System Model CanESM5, part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), reasonably reproduces this pattern and its formation mechanisms. Future projections under the Shared Socioeconomic Pathway 8.5 (SSP5‐8.5) suggest a significant weakening of WACNA with global warming. Notable changes in pattern intensity and spatial structure are anticipated, particularly a decrease in intensity over the CBS. WACNA changes are also found in 31 CMIP6 multi‐model ensemble simulations. These changes are attributed to Arctic amplification associated with global warming, which diminishes the equator‐to‐pole temperature gradient and consequently reduces meridional heat transport, particularly over the CBS region.

Integrated modeling of surface water and groundwater interactions in the Eastern Mitidja Plain, North Algeria: investigating the impact of human activities and climate change

ABSTRACT The study aims to investigate surface water (SW)–groundwater (GW) interactions in the Mitidja Plain (northern Algeria), taking into account the impacts of human activity and climate change emphasizing the alignment with Sustainable Development Goals, Clean Water and Sanitation, and Climate Action. The dynamic interactions between the El Hamiz River and the alluvial aquifer were studied using MODFLOW 6. A typical scenario analysis approach was employed, considering historical and projected climate conditions based on Coupled Model Intercomparison Project version 5 and Coupled Model Intercomparison Project phase 6 models, as well as current and projected GW abstraction rates. The findings reveal substantial changes in flow dynamics over time. In 1982, the aquifer refilled the river at a rate of 2.59 m3/s. In 2019, a new state was observed where the opposite occurred the river recharged the aquifer at a rate of 0.73 m3/s. This reduction in the flow rate can be attributed to over-pumping and declining recharge rates, and this pattern is anticipated to persist in the future. Furthermore, future forecasts indicate that GW overuse has a greater impact on GW dynamics compared to climate change. However, the adoption of saltwater desalination and enhanced irrigation methods could make a significant contribution to the sustainable development of GW resources, with an increase of up to approximately 14 m.

HiCPC: A new 10-km CMIP6 downscaled daily climate projections over China

Accurate climate projections are critical for various applications and impact assessments in environmental science and management. This study presents HiCPC (High-resolution CMIP6 downscaled daily Climate Projections over China), a novel dataset tailored to China’s specific needs. HiCPC leverages outputs from 22 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). To address inherent biases in daily GCM simulations, an advanced Bias Correction and Spatial Disaggregation (BCSD) method is employed, using the China Meteorological Forcing Dataset (CMFD) as a reference. HiCPC offers detailed daily precipitation and temperature data across China at an enhanced spatial resolution of 0.1° × 0.1°. It covers both the historical period (1979–2014) and future projections (2015–2100) based on four CMIP6 Shared Socioeconomic Pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Upon validation, HiCPC demonstrates good performance, surpassing CMIP6 GCMs across the historical period. This reinforces its significance for essential research in climate change evaluation and its associated implications within China.

Early emergence and determinants of human-induced Walker circulation weakening

The Walker circulation is projected to slow down in response to greenhouse gas warming. However, detecting the impact of human activities on changes in the Walker circulation is challenging due to the significant influence of internal variability. Here, based on ensembles of multiple climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we show evidence that the emergence of the human-induced weakening of Walker circulation tends to occur earlier in the middle-upper troposphere than at the surface. This earlier emergence is attributed to a more pronounced initial weakening response of the middle-upper tropospheric Walker circulation to atmospheric CO2 radiative forcing. We further reveal that the emergence time of a weaker Walker circulation varies across models. This intermodel spread is governed by an ocean thermostat that operates by modulating the zonal sea surface temperature gradient over the tropical Indo-Pacific region. Our findings address the key question of whether and how to detect human-induced large-scale atmospheric circulation changes and provide valuable insights for assessing the associated risks.

Strong Linkage Between Observed Daily Precipitation Extremes and Anthropogenic Emissions Across the Contiguous United States

AbstractThe results of probabilistic event attribution studies depend on the choice of the extreme value statistics used in the analysis, particularly with the arbitrariness in the selection of appropriate thresholds to define extremes. We bypass this issue by using the Extended Generalized Pareto Distribution (ExtGPD), which jointly models low precipitation with a generalized Pareto distribution and extremes with a different Pareto tail, to conduct daily precipitation attribution across the contiguous United States (CONUS). We apply the ExtGPD to 12 general circulation models from the Coupled Model Intercomparison Project Phase 6 and compare counterfactual scenarios with and without anthropogenic emissions. Observed precipitation by the Climate Prediction Center is used for evaluating the GCMs. We find that greenhouse gases rather than natural variability can explain the observed magnitude of extreme daily precipitation, especially in the temperate regions. Our results highlight an unambiguous linkage of anthropogenic emissions to daily precipitation extremes across CONUS.

Concurrent Inter‐Model Spread of Boreal Winter Westerly Jet Meridional Positions Between the Northern and Southern Hemispheres in CMIP6 Models

ABSTRACTThis study investigates the inter‐model spread of climatological extratropical westerly jets in boreal winter, using the historical simulation of 52 Coupled Model Intercomparison Project phase 6 (CMIP6) models from 1851 to 2014. The results show that there is a substantial spread in the latitude of the upper‐tropospheric westerly jet across models, characterised by large inter‐model standard deviations to both the poleward and equatorward sides of the jet axis, although the multi‐model ensemble mean (MME) performs well in simulating meridional position of westerly jets. Furthermore, we detect the consistency of inter‐model jet position spread between the Northern and Southern Hemispheres, based on the inter‐model empirical orthogonal function (EOF) decomposition and correlation of regional‐averaged zonal winds. Specifically, the models that simulate the westerly jets poleward/equatorward relative to the MME position in one hemisphere also tend to simulate the jets poleward/equatorward in the other hemisphere. Accordingly, we define a global jet spread index to depict the concurrence of jet shift in the two hemispheres. The results of inter‐model regression analyses based on this index indicate that the models positioning the jets poleward than the MME tend to simulate a wider Hadley Cell, a poleward‐shifted Ferrel Cell in the Southern Hemisphere, enhanced precipitation in the subtropics and suppressed precipitation in the tropics, and warmer sea surface temperatures in the subtropics and mid‐latitudes. The present results suggest that improving the simulation of jet positions in climate models requires a comprehensive consideration of thermal states in the tropics and subtropics/mid latitudes.

Assessing the stability of terrestrial water storage to drought based on CMIP6 forcing scenarios

Assessing the stability of terrestrial water storage (TWS) under drought conditions is critical for the sustainable development of water resources. In this study, we integrated surface temperature (ST), leaf area index (LAI), and precipitation (P) data from five different scenarios (History, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to develop a standardized temperature vegetation precipitation index (STVPI). The index was then utilized to monitor global drought conditions and investigate the stability of TWS to drought disaster. The results showed that STVPI can not only monitor meteorological drought, but also has a remarkable sensitivity and applicability to drought caused by sparse vegetation. Notably, 21.16% of the global land area will have a drought trend under the SSP1-2.6 scenario, while it will rise to 35.81% under the SSP5-8.5 scenario, which underscored the potential for an expansion of drought-affected regions worldwide as a result of ongoing global warming and escalating emissions. In addition, the results also found that the warm temperate and tropical regions at lower elevations have an advantage in maintaining the stability of TWS. Unfortunately, the stability of TWS to drought will decline in the western Sahara Desert, central China and northern United States in the future, where will face a serious water crisis. The research framework provides an important reference for deeply evaluating and scientifically allocating water resources under climate change.

A scenario–neutral approach to climate change in glacier mass balance modeling

Abstract Scenario–neutral methods are commonly used to rapidly compare system responses to changes in climate. Using glacier mass balance as a system response, we present a bottom-up, scenario–neutral method as an effective tool for preliminary and overview studies on glacier sensitivity and a complementary approach to traditional top–down methods. The method's main characteristic is its visual result: two–dimensional response surfaces depicting glacier mass balance. Their axes represent perturbations in temperature and precipitation relative to a baseline. The simplicity of our approach makes it applicable to all global glaciers. As a proof–of–concept, the Open Global Glacier Model (OGGM) is used to perform a scenario–neutral glacier sensitivity analysis for four glaciers. In addition, the integration with a top–down approach is demonstrated by overlaying temperature and precipitation from four Coupled Model Intercomparison Project Phase 6 (CMIP6) models, under four Shared Socioeconomic Pathways (SSP). Finally, the benefits of the method are discussed for decision–making and science communication. Assessing results shows that overall, this scenario–neutral method can provide useful information for the research of climate change impact on glacier mass, from aiding study design to science communication.

Light Precipitation rather than Total Precipitation Determines Aerosol Wet Removal.

Precipitation scavenging is an important sink for both organic and inorganic pollutants in the atmosphere. However, there has been controversy over the relative importance of different precipitation characteristics (i.e., the precipitation amount, intensity, frequency, and duration) in the removal of air pollutants. It is critical to reach a consensus on which precipitation characteristics are most significant for aerosol wet removal. In this study, the analysis of multisource in situ observations of aerosol wet deposition worldwide indicates that the precipitation frequency plays a first-order role in scavenging aerosols. This is because large amounts of air pollutants are efficiently removed at precipitation initiation. As the duration and amount of precipitation increase, the scavenging efficiency decreases sharply. Consequently, it is featured that light precipitation, due to its high frequency of occurrence, rather than total precipitation, determines climatological aerosol wet deposition. To further confirm this, a state-of-the-art global climate model with convection resolved is modified to reduce the light precipitation frequency in both stratiform and convective cloud regimes. Results show widespread increases in aerosol optical depth (AOD) due to the reduced wet deposition. The spatial distribution of aerosol wet deposition changes resembles that of changes in the light precipitation frequency rather than that of total precipitation changes. These findings are consistent with those from the Coupled Model Intercomparison Project Phase 6 multimodel simulations, which show that the intermodel uncertainty in simulated AOD correlates more strongly with the uncertainty in light precipitation frequency than with that in total precipitation.

Drivers of summer Arctic sea-ice extent at interannual time scale in CMIP6 large ensembles revealed by information flow

Arctic sea-ice extent has strongly decreased since the beginning of satellite observations in the late 1970s. While several drivers are known to be implicated, their respective contribution is not fully understood. Here, we apply the Liang-Kleeman information flow method to five different large ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over the 1970-2060 period to investigate the extent to which fluctuations in winter sea-ice volume, air temperature and ocean heat transport drive changes in subsequent summer Arctic sea-ice extent. This allows us to go beyond classical correlation analyses. Results show that air temperature is the most important controlling factor of summer sea-ice extent at interannual time scale, and that winter sea-ice volume and Atlantic Ocean heat transport play a secondary role. If we replace air temperature by net shortwave and downward longwave radiations, we find that the sum of influences from both radiations is almost similar to the air temperature influence, with the longwave radiation being dominant in driving changes in summer sea-ice extent. Finally, we find that the influence of air temperature is more prominent during periods of large sea-ice reduction and that this temperature influence has overall increased since 1970.

Interannual Covariation of the North American and African Summer Monsoons

ABSTRACTThe North American summer monsoon (NASM) and the North African summer monsoon (NAFSM) are two vital subsystems of the global monsoon. To date, the potential inter‐monsoon relationship between the NASM and NAFSM has not been fully understood. To fill this gap, we investigate the NASM–NAFSM relationship on the interannual timescale during the period of 1979–2022. Based on statistical methods (including correlation, empirical orthogonal function and cross wavelet analyses), we identify a noteworthy interannual covariation of the NASM and NAFSM. This observed NASM–NAFSM covariation can be explained by atmospheric circulation anomalies associated with sea surface temperature (SST) anomalies in the tropical central‐eastern Pacific and tropical Atlantic, suggesting the critical roles of tropical Pacific–Atlantic SST anomalies in shaping the NASM–NAFSM covariation. The results of Coupled Model Intercomparison Project Phase 6 (CMIP6) models indicate that a model's ability to simulate the NASM–NAFSM covariation tends to be related to its ability to reproduce the modulating effects of the tropical Pacific–Atlantic SST anomalies. These results have potential implications for seasonal forecasts of the NASM and NAFSM variations, suggesting that the NASM and NAFSM can be considered simultaneously in climate predictions.

Projection of climate change impact on main climate variables and assessment of the future of Köppen–Geiger climate classification in Iran

AbstractHuman society and the environment are facing significant challenges due to climate change. Climate change is projected to impact main climate variables, such as temperature and precipitation. Changes in main climate variables affect climate classification and alter climate zone maps. In this research, first, the projection of temperature and precipitation in 30 main stations of Iran under the Shared Socioeconomic Pathways scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from Coupled Model Intercomparison Project Phase Six (CMIP6) for the end of the twenty-first century (2071–2099) was carried out. Then, the future of climate zone maps was assessed in Iran by Köppen-Geiger climate classification. The evaluation of the model data based on observation data for the period of 1991–2020 showed an acceptable correlation, with R-square and RMSE values in the ranges of 0.67–0.96 and 2.44–8.38, respectively. Results showed that the temperature in the future period (2071–2099) will increase by 1–4.7 °C under all scenarios compared to the historical study period (1991–2020), while the precipitation will either increase or decrease depending on the season and the specific climate change scenario. Assessment of future climate classifications revealed that the BW (arid desert) and BS (semi-arid steppe) categories will increase, as classified by Köppen-Geiger, will increase. At the same time, Ds and Cs (dry summer) classifications will decrease in during the study period over Iran. These findings provide policymakers with some insights into how to deal with the impacts of climate change in the future and implement some measures now.

Projected North Equatorial Current/Countercurrent Towards an El Niño-Like Condition in the Western Pacific under Moderate and Worst-case CO2 Emission Scenarios

Abstract Validating the mean state and historical trends of the North Equatorial Current and Countercurrent (NEC and NECC) in 36 Coupled Model Intercomparison Project (CMIP) phase 5 models and 32 CMIP phase 6 models with those in ocean reanalysis products, this study extracts the most qualified 17 model outputs to explore the projected changes in NEC and NECC in the western Pacific Ocean under scenarios of moderate and worst-case CO2 emissions. NEC and NECC are robustly predicted to have an El Niño-like change, in which the NEC (NECC) tends to intensify with a poleward (equatorward) movement, during the 21st century under both scenarios. Meanwhile, the Kuroshio and Mindanao Current are projected to become weaker. Change in meridional gradient of basin-scale wind stress curl in the tropical Pacific Ocean is the major contributor to the centennial changes in NEC and NECC; however, anomalous wind stress curl dipole on the two sides of NEC off the eastern Philippines is the major factor in controlling the western boundary currents. This study not only represents a step forward in understanding the impact of global warming on the western tropical Pacific surface circulation, but also serves as a reference for downscaled modeling, which can better resolve regional circulation and western boundary currents, for selecting suitable inputs from a large number of CMIP models.

Assessment of CMIP6 models and multi-model averaging for temperature and precipitation over Iran

In this study, the performances of 40 Coupled Model Intercomparison Project Phase 6 are evaluated against observational data at synoptic stations in Iran using various evaluation criteria. The results reveal diverse model accuracy across different climate conditions and criteria, emphasizing particularly notable disparities in the nonstationarity R criterion compared to others. Although according to the ranking of the raw and bias-corrected outputs of CMIP6 GCMs for Iran, the NorESM2-MM, AWI-ESM-1-1-LR, and MPI-ESM1-2-LR models are consistently among the top six ranked models for precipitation in both raw and corrected outputs. For temperature, MPI-ESM1-2-LR, TaiESM1, INM-CM4-8, and IITM-ESM are consistently among the top six models for both the raw and bias-corrected outputs of CMIP6 GCMs. The Bias correction methods, including quantile mapping and linear scaling, integrated with Bayesian model averaging, were applied. While quantile mapping demonstrates superior performance and less disparity than linear scaling, it proves ineffective for correcting biases at stations with bias nonstationarity over time. The RMSE for monthly precipitation ranges from almost 0 to 200 mm, with a large RMSE value related to the high precipitation stations, and the monthly temperature exhibits a range of 0 to 4 °C. The use of a multi-model ensemble improves accuracy compared to individual models, resulting in a reduction in the differences between the minimum and maximum RMSE values from 178.6 to 91.0. Additionally, the range for mean absolute error decreases from 126.9 to 93.3, and the difference in the correlation coefficient narrows from 0.9 to 0.42. Averaging models after bias correction prevents significant fluctuations while maintaining higher accuracy, in contrast to the second method, which involves bias-correcting models after averaging.

Uncertainty-informed selection of CMIP6 Earth system model subsets for use in multisectoral and impact models

Abstract. Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.

How Climate Change Will Shape Pesticide Application in Quebec’s Golf Courses: Insights with Deep Learning Based on Assessing CMIP5 and CMIP6

The accelerating impact of climate change on golf course conditions has led to a significant increase in pesticide dependency, underscoring the importance of innovative management strategies. The shift from Coupled Model Intercomparison Project Phase 5 (CMIP5) to the latest CMIP6 phase has drawn the attention of professionals, including engineers, decision makers, and golf course managers. This study evaluates how climate projections from CMIP6, using Canadian Earth System Models (CanESM2 and CanESM5), impact pesticide application trends on Quebec’s golf courses. Through the comparison of temperature and precipitation projections, it was found that a more substantial decline in precipitation is exhibited by CanESM2 compared to CanESM5, while the latter projects higher temperature increases. A comparison between historical and projected pesticide use revealed that, in most scenarios and projected periods, the projected pesticide use was substantially higher, surpassing past usage levels. Additionally, in comparing the two climate change models, CanESM2 consistently projected higher pesticide use across various scenarios and projected periods, except for RCP2.6, which was 27% lower than SSP1-2.6 in the second projected period (PP2). For all commonly used pesticides, the projected usage levels in every projected period, according to climate change models, surpass historical levels. When comparing the two climate models, CanESM5 consistently forecasted greater pesticide use for fungicides, with a difference ranging from 65% to 222%, and for herbicides, with a difference ranging from 114% to 247%, across all projected periods. In contrast, insecticides, growth regulators, and rodenticides displayed higher AAIR values in CanESM2 during PP1 and PP3, showing a difference of 28% to 35.6%. However, CanESM5 again projected higher values in PP2, with a difference of 1.5% to 14%.

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.

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.