Coupled Model Intercomparison Project Phase Research Articles

Optimal reliability ensemble averaging approach for robust climate projections over China

AbstractAccurate simulation and reliable projection of temperature and precipitation over China under climate change is important for proposing adaptation measures for future natural ecosystems. This study proposes a novel method to construct an optimal reliability ensemble averaging (REA) subset from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on their historical performance in simulating temperature and precipitation across different subregions. The optimal REA ensemble outperforms the multi‐model ensemble mean (MMEM) and single optimal model in reproducing the spatial patterns of historical annual mean temperature and precipitation over China from 1985 to 2014. Under the examined Shared Socioeconomic Pathway scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), the REA projects persistent warming and increased precipitation towards the end of the 21st century, intensifying under higher emissions. Nationwide mean temperature rises of 1.39, 2.69 and 5.05°C, and precipitation increases of 9%, 10% and 20% are projected in the long‐term (2081–2100) relative to 1995–2014 under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 scenarios, respectively. Northwestern China and the Tibetan Plateau are expected to experience amplified warming and precipitation increases, respectively. Compared to the MMEM, the REA generally indicates reduced warming but larger precipitation increases, especially over the Tibetan Plateau under higher‐emissions scenarios. The REA exhibits lower projection uncertainty than the MMEM for both temperature and precipitation, primarily attributed to reduced internal variability. The novel optimal framework for REA shows the potential for extracting robust regional climate information applicable to different subregions of China. This study may contribute to new comprehension of future climate change over China.

Changes in the North Atlantic Oscillation over the 20th century

Abstract. The North Atlantic Oscillation explains a large fraction of the climate variability across the North Atlantic from the eastern seaboard of North America across the whole of Europe. Many studies have linked the North Atlantic Oscillation to climate extremes in this region, especially in winter, which has motivated considerable study of this pattern of variability. However, one overlooked feature of how the North Atlantic Oscillation has changed over time is the explained variance of the pattern. Here we show that there has been a considerable increase in the percentage of variability explained by the North Atlantic Oscillation (NAO) over the 20th century from 32 % in 1930 to 53 % by the end of the 20th century. Whether this change is due to natural variability, a forced response to climate change, or some combination remains unclear. However, we found no evidence for a forced response from an ensemble of 50 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. These models did all show substantial internal variability in the strength of the North Atlantic Oscillation, but it was biased towards being too high compared to the reanalysis and with too little variation over time. Since there is a direct connection between the North Atlantic Oscillation and climate extremes over the region, this has direct consequences for both the long-term projection and near-term prediction of changes to climate extremes in the region.

Modeling the impact of measured and projected climate and management systems on agricultural fields: Surface runoff, soil moisture, and soil erosion.

As global climate change poses a challenge to crop production, it is imperative to prioritize effective adaptation of agricultural systems based on a scientific understanding of likely impacts. In this study, we applied an integrated watershed modeling framework to examine the impacts of projected climate on runoff, soil moisture, and soil erosion under different management systems in Central Oklahoma. The proposed model uses measured climate data and three downscaled ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) at the water resources and erosion watershed to understand the impact of climate change and various climate conditions under three management systems: (1) continuous winter wheat (Triticum aestivum) under conventional tillage (WW-CT; baseline system), (2) continuous winter wheat under no-till (WW-NT), and (3) cool and warm season forage cover crop mixes under no-till (CC-NT). The study indicates that the occurrence of agricultural drought is projected to increase while erosion rates will remain unchanged under the WW-CT. In contrast, climate simulations imposed on the WW-NT and CC-NT systems significantly reduce runoff and sediment while preserving soil moisture levels. Especially, implementing the CC-NT system can bolster food security and foster sustainable farming practices in Central Oklahoma in the face of a changing climate.

Historical and Future global warming under different RCP emission scenarios

Understanding the relationship between carbon emissions and climate change has become increasingly urgent amidst the universal endorsement of sustainable development and the establishment of net-zero carbon emission target (The Paris Agreement). In this study, model projections based on Coupled Model Intercomparison Project Phase 5 (CMIP5) are used to examine future climate change under different representative concentration pathway (RCP) emission scenarios till 2300. Besides analysis of future global average temperature change under the emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP 8.5, historical data is first collected during the past three decades (1990-2021). The results show that the simulated global warming ranges from 0.9 to 1.3 between 1990 and 2021, consistent with the observations (0.93). Carbon emissions in China arose mostly from manufacturing and construction, electricity and heat and transport. Emissions from electricity, heat and transport increase by a high ratio of 7.7 and 3.5 times due to industry development. Under different RCP scenarios, the global surface temperature anomaly will increase by 0.2-1.0, 1.2-2.0, 3.5-4.3 and 3.0-8.5 , respectively. The surface temperature anomaly values under RCP8.5 are much higher than those under other emission scenarios. Only in the RCP2.6 scenario (sustainability), the surface warming in all simulations stays below a 2 threshold at the end of the 21st century. To attain net zero emissions, it is highly demanded to develop strict emission policies, chart a course toward decarbonization, and institute effective measures aimed at realizing net zero emissions within the short to medium term. Concurrently striving for economic objectives, managing the equilibrium between economic growth and environmental sustainability emerges as a critical imperative.

A warming-induced glacier reduction causes lower streamflow in the upper Tarim River Basin

Study areaThree headwater basins of the Tarim River Study focusThis study built upon existing knowledge by incorporating threshold melting temperatures into the Spatial Processes in Hydrology (SPHY) model and decomposing the streamflow changes into individual runoff components. Additional glacier retreat rate data were used to calibrate the improved SPHY, which provides better constrained estimates of glacier response to climate change. We employed bias-corrected simulations from Coupled Model Intercomparison Project Phase 6 (CMIP6) models to drive the improved SPHY under four future scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5). New hydrological insights for the regionModeling results show accelerated glacier melt in the future, with glacier volume at the end of this century projected to be less than 20% of the current level under SSP5–8.5. Furthermore, future streamflow is expected to decrease, most notably in the Karakash River basin under the SSP1–2.6 scenario. The reduction in streamflow, mainly during the summer months, results from decreased glacier melt runoff, which cannot be offset by increased rainfall runoff. Additionally, the implementation of climate change mitigation measures could delay glacier loss, but the dominant component of runoff would still shift from current glacier melt to future rainfall. Plain language summaryGlobal warming accelerates the hydrological cycle, altering the temporal and spatial patterns of streamflow, especially in cold regions, such as the Tarim River Basin. Understanding future streamflow changes is important for the economic development and ecological protection of this region, which will help to manage the risk of water shortages and to plan engineering works to mitigate water shortage crises. We therefore used state-of-the-art climate simulation to project future streamflow changes over three basins of the Upper Tarim River. We found that under all future scenarios, runoff will decrease in these basins. This decrease is mainly due to glacier retreat and cannot be mitigated by anticipated increases in rainfall in the future.

Enhanced performance of CMIP6 climate models in simulating historical precipitation in the Florida Peninsula

AbstractAssessing the performance of General Circulation Models (GCMs) in simulating historical regional precipitation is essential for climate assessments. This study analysed 18 GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and 27 GCMs from Phase 6 (CMIP6) for the Florida Peninsula. Naïve combinations formed the CMIP5‐Ensemble and CMIP6‐Ensemble. The reference dataset consisted of global gridded precipitation data from National Oceanic and Atmospheric Administration. GCM‐simulated precipitation data were compared to the reference dataset across multiple time scales between 1951 and 2005. Most CMIP5 and CMIP6 GCMs exhibited a negative bias at the daily time scale, with an absolute value ranging between 0 and 2 mm day−1 at the median level, except for INM‐CM4 and MRI‐CGCM3 (CMIP5) and CNRM‐ESM2‐1 (CMIP6). Two performance metrics, that is, Pearson correlation and mean absolute error (MAE), were used to evaluate the GCMs. A correlation value above 0.3 is statistically significant at the significance level (α = 0.05). For the Pearson correlation between simulated and observed monthly precipitation, only 15% of CMIP5 GCMs (3 out of 19) had a median value above 0.3, whilst this increased to approximately 39% (11 out of 28) for CMIP6 GCMs. For monthly climatological precipitation, only 21% (4 out of 21) of GCMs in CMIP5 showed a correlation with a median value of 0.8 or higher. This percentage rose to 50% (14 out of 28) for CMIP6. A notable difference was observed in the MAE between CMIP5 and CMIP6 climate models. Lastly, GCM raw outputs were evaluated based on rainy season characteristics (onset, demise and duration). Significant improvements from the CMIP5 to the CMIP6 models were observed in capturing the rainy season in the Florida Peninsula. This study thoroughly compares CMIP5 and CMIP6 climate models in simulating historical precipitation at various time scales for the study region. Although the results are specific to the study area, the methods can be applied more broadly.

Evaluation and projection of circulation conditions tied to summertime compound drought and heatwave frequency over the Yangtze River Delta, China, for the carbon neutrality period based on CMIP6 GCMs

AbstractFrequent occurrences of compound droughts and heatwaves (CDHWs) may have considerable adverse impacts on human health and socioeconomic development. To project future summertime CDHWs over the Yangtze River Delta (YRD) of China under carbon neutrality (CN) for policymakers, we used nine global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated and projected circulation conditions tied to the summer YRD CDHW frequency in the boreal summer. The results show that a marked mid‐tropospheric regional‐scale anticyclonic anomaly centred over the East China Sea can be deemed the dominant system linking the more frequent occurrence of YRD CDHWs. Our selected nine CMIP6 GCMs better captured the observed climatological and anomalous spatial circulation patterns connected to the summer YRD CDHW frequency. Moreover, the nine models' multi‐model ensemble mean (9MME) was better than most of the individual models regarding the related climatological circulation simulations. The 9MME‐projected changes in circulation conditions tied to summer YRD CDHWs during the carbon neutrality period (2050–2060) under SSP119 favour the comparable occurrence of the YRD with that for the same period under the medium greenhouse gas (GHG) warming scenario (SSP245), but the intensities of the CDHWs are the least severe. However, the highest number of YRD CDHWs is driven by the high GHG warming scenario (SSP585), and these CDHWs feature the most severe intensity. Our research identified a new paradigm regarding the frequency and intensity of the summer YRD CDHW under SSP119, highlighting the potential role of the newly accessible CN‐oriented sustainable development pathway in alleviating compound extremes.

Unstable interdecadal relationship between the Pacific Decadal Oscillation and eastern China summer precipitation in simulated warm interglacial epochs and twenty-first century

The modern connection between the Pacific Decadal Oscillation (PDO) and eastern China summer precipitation (ECSP) at the decadal scale has been extensively studied. However, whether this correlation is stable during the warmer backgrounds in the past and future remains unclear. Clarifying this issue may yield meaningful insights into past PDO reconstruction and decadal climate projection in eastern China (EC). Based on the FGOALS-f3-L, which performs best in reproducing the observed PDO pattern and the decadal PDO–ECSP relationship among 10 models under the framework of the coupled Model Intercomparison Project phase 6 (CMIP6), we find an unstable relationship between the PDO and ECSP at the decadal scale during the last Interglacial (LIG), mid-Holocene, and the twenty-first century under the Shared Socioeconomic Pathway (SSP) SSP5–8.5 scenario. The PDO-related ECSP roughly shows a west–east dipole pattern with excessive precipitation in the east during the LIG, whereas the mid-Holocene witnesses a generally decreased ECSP, except for South and Northeast China. Under the SSP5–8.5 scenario, the PDO-related decadal ECSP exhibits excessive precipitation in the west but a deficit in the east, especially in South and Northeast China. This instability is ascribed to changes in the vertical motions and moisture divergence associated with various configurations of large-scale atmospheric circulations from the lower to upper troposphere. Furthermore, these diverse atmospheric circulation patterns relate to the variations in the convective heating over the western North Pacific and the propagation of extratropical Rossby waves, which are connected with the different PDO patterns and the mean state differences in the westerly jet stream locations during the past and future warm periods

Compound successive dry-hot and wet extremes in China with global warming and urbanization

Global warming has accelerated the interregional hydrological cycle, resulting in a significant increase in the frequency and intensity of extreme events worldwide. These events often involve a combination of spatial and temporal factors, giving rise to compound events. Among them are rapid transitions from dry and hot conditions to wet (DHW) events, which can have more severe impacts on human societies and ecosystems than individual extreme events. Urbanization not only heightens the likelihood of disasters but also exacerbates the exposure of affected populations. However, there has been insufficient attention given to understanding the connections between these successive compound events and the heightened risks posed by the increasing urbanization. In this study, we used bias-corrected daily precipitation and maximum temperature data simulated by the Coupled Model Intercomparison Project Phase 6 (CMIP6) model, along with historical and future daily runoff data simulated by the Variable Infiltration Capacity (VIC) model. We systematically investigated the spatiotemporal changes (i.e., frequency, duration, intensity, and compound probability) in DHW events in China during the upper historical period (1979–2014) and under two medium and high emission scenarios (2015–2100) − Shared Socioeconomic Pathways (SSP245 and SSP585). Furthermore, we examined how extreme runoff responds to variations in maximum temperature and daily precipitation during DHW events. We also evaluated the potential population and urban exposure to DHW events using dynamic future population and urban expansion data to assess the potential risks. Our results indicate that the multi-model ensemble predicts varying spatial patterns of future DHW events under SSP245 and SSP585 scenarios. The frequency and duration of these events are expected to decrease by approximately 20–25% in the Northwest region under both scenarios. At the same time, the middle and lower plains of the Yangtze and Yellow River Basins experience increased occurrence, broader geographical impact, and higher DHW event intensity alongside urban expansion and population growth in these regions. Specifically, event intensity is anticipated to increase by a factor of approximately 7–11. Temporally, we expect short-duration, high-intensity DHW events to occur in the Yangtze and Yellow River basins around 2023, 2038, and 2058, respectively. The primary driver for the future rise in population exposure to DHW events is the expected increase in event frequency in the middle and lower plains of the Yangtze and Yellow River basins, concurrent with population growth in these regions. Under the medium emission scenario, the total exposed population to DHW events in China is predicted to be 1.61 times higher than the historical baseline. In contrast, the high-emission scenario estimates a total population of 2.41 times higher than the historical baseline period. Most of the DHW events occurred in regions that exhibit a positive dependence between high temperature and high runoff events, serving as the primary driver of DHW events. Urbanization has a positive impact on DHW events, with the effect under high emissions being approximately 30% higher than during the historical base period. Additionally, it is indicated that future DHW events will exhibit higher sensitivity to global warming, with intensity projected to increase approximately fourfold and the exposed population to rise by about 1.5 times for every 1 °C of global warming. This research enhances our understanding of forecasting future compound hydrometeorological extreme events under different scenarios and provides insight into the role of climate change and urbanization in shaping these events in China.

Changes in the Typhoon Intensity under a Warming Climate: A Numerical Study of Typhoon Mangkhut

Abstract Accurately assessing cyclone intensity changes due to global warming is crucial for predicting and mitigating sequential hazards. This study develops a high-resolution, fully coupled air-sea model to investigate the impact of global warming on Super Typhoon Mangkhut (2018). A numerical sensitivity analysis is conducted using the Pseudo-Global Warming (PGW) technique based on multiple global climate models (GCMs) from the Coupled Model Intercomparison Project Phases 6 (CMIP6). Under ocean warming scenarios, the increasing average sea surface temperature (SST) by 2.26 °C, 2.44 °C, 3.45 °C, and 4.53 °C result in reductions in minimum sea-level pressure by 9.2 hPa, 10.6 hPa, 15.7 hPa, and 19.4 hPa, respectively, compared to the original state of Typhoon Mangkhut. Rising SST increases turbulent heat flux, to be specific, an average SST increase of 2.26-4.53 °C changes the turbulent heat flux into 177% to 272% of the original value. Besides, stronger winds enhance SST cooling, including upwelling and entrainment, leading to an increase in the mixed layer depth (MLD). Tropical cyclone heat potential (TCHP) tends to be enhanced under the combined influences as the SST rises. An average increase in SST of 2.26 °C, 2.44 °C, 3.45 °C, and 4.53 °C leads to increase in TCHP of 9.94%, 9.85%, 14.67%, and 15.30%, respectively. However, future changes in atmospheric temperature and humidity will moderate typhoon intensification induced by ocean warming. Considering atmospheric conditions, the maximum wind speed decreases by approximately 10% compared to only considering ocean warming. Nevertheless, typhoon intensity is projected to strengthen under future climate change.

Assessment of precipitation and near-surface temperature simulation by CMIP6 models in South America

This study evaluated the performance of 50 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the statistical features of precipitation and air temperature in five subdomains of South America during the historical period (1995–2014). Monthly precipitation and temperature simulations were validated with data from the Climate Prediction Center Merged Analysis of Precipitation, the Global Precipitation Climatology Project, and the ERA5 reanalysis. The models’ performance was evaluated using a ranking analysis with statistical metrics such as mean, standard deviation, Pearson’s spatial correlation, annual cycle amplitude, and linear trend. The analyses considered the representation of precipitation and air temperature separately for each subdomain, the representation for all five regions together, and the joint representation of precipitation and air temperature for all five subdomains. In the Brazilian Amazon, the best-performing models were EC-Earth3-Veg, INM-CM4-8, and INMCM5-0 (precipitation), and IPSL-CM6A-LR, MPI-ESM2-0, and IITM-ESM (temperature). In the La Plata Basin, KACE-1-0-G, ACCESS-CM2, and IPSL-CM6A-LR (precipitation), and GFDL-ESM4, TaiESM1, and EC-Earth3-Veg (temperature) yielded the best simulations. In Northeast Brazil, SAM0-UNICON, CESM2, and MCM-UA-1-0 (precipitation), BCC-CSM2-MR, KACE-1-0-G, and CESM2 (temperature) showed the best results. In Argentine Patagonia, the GCMs ACCESS-CM2, ACCESS-ESM1-5 and EC-Earth3-Veg-LR (precipitation), and CAMS-CSM1-0, CMCC-CM2-HR4, and GFDL-ESM4 (temperature) outperformed. Finally, for Southeast Brazil, the models ACCESS-CM2, ACCESS-ESM1-5, and EC-Earth3-Veg-LR (precipitation), and CAMS-CSM1-0, CMCC-CM2-HR4, and GFDL-ESM4 (temperature) yielded the best simulations. The joint evaluation of the regions and variables indicated that the best models are CESM2, TaiESM1, CMCC-CM2-HR4, FIO-ESM-2-0, and MRI-ESM2-0.

Variation and attribution of probable maximum precipitation of China using a high-resolution dataset in a changing climate

Abstract. Accurate assessment of the probable maximum precipitation (PMP) is crucial in assessing the resilience of high-risk water infrastructures, water resource management, and hydrological hazard mitigation. Conventionally, PMP is estimated based on a static climate assumption and is constrained by the insufficient spatial resolution of ground observations, thus neglecting the spatial heterogeneity and temporal variability of climate systems. Such assumptions are critical, especially for China, which is highly vulnerable to global warming in ∼ 100 000 existing reservoirs. Here, we use the finest-spatiotemporal-resolution (1 d and 1 km) precipitation dataset from an ensemble of machine learning algorithms to present the spatial distribution of 1 d PMP based on the improved Hershfield method. Current reservoir design values, a quasi-global satellite-based PMP database, and in situ precipitation are used to benchmark against our results. The 35-year running trend from 1961–1995 to 1980–2014 is quantified and partitioned, followed by future projections using the Coupled Model Inter-comparison Project Phase 6 simulations under two scenarios. We find that the national PMP generally decreases from southeast to northwest and is typically dominated by the high variability of precipitation extremes in northern China and high intensity in southern China. Though consistent with previous project design values, our PMP calculations present underestimations by comparing them with satellite and in situ results due to differences in spatial scales and computation methods. Interannual variability, instead of the intensification of precipitation extremes, dominates the PMP running trends on a national scale. Climate change, mainly attributed to land–atmosphere coupling effects, leads to a widespread increase (> 20 %) in PMP across the country under the SSP126 scenario, which is projected to be higher along with the intensification of CO2 emissions. Our observation- and modeling-based results can provide valuable implications for water managers under a changing climate.

Historical Soil Moisture Variability in High‐Latitude Humid Regions: Insights From a Paleoclimate Data‐Model Comparison

AbstractUnderstanding historical soil moisture (SM) variations and their relationship with temperature in high‐latitude humid regions is essential for predicting hot droughts under widespread warming. This paper presents the first‐ever annual‐resolution summer surface SM reconstruction (1736–2006 CE) in Sweden, located in northern Europe (NE). The reconstruction utilizes the paleoclimate proxy, tree‐ring δ18O, which exhibits a strong correlation with reanalysis SM data during 1948–2007 CE (r = −0.67, p < 0.001). In contrast to an unprecedented trend suggested by previous studies, our reconstruction exhibits a wetting trend in NE since the 1960s falling within the historical spectrum of trends. Both reanalysis SM data and our reconstruction show significant negative correlations with temperature at interannual timescales. However, Coupled Model Intercomparison Project Phase 6 climate models failed to capture the significant SM‐temperature relationship during the historical (1850–1947 CE) and observation periods (1948–2006 CE). This proxy‐model comparison represents a critical step toward enhancing our understanding of SM dynamics and the reliability of SM projections in high‐latitude humid regions.

Impact of volcanic eruptions on CMIP6 decadal predictions: a multi-model analysis

Abstract. In recent decades, three major volcanic eruptions of different intensity have occurred (Mount Agung in 1963, El Chichón in 1982 and Mount Pinatubo in 1991), with reported climate impacts on seasonal to decadal timescales that could have been potentially predicted with accurate and timely estimates of the associated stratospheric aerosol loads. The Decadal Climate Prediction Project component C (DCPP-C) includes a protocol to investigate the impact of volcanic aerosols on the climate experienced during the years that followed those eruptions through the use of decadal predictions. The interest of conducting this exercise with climate predictions is that, thanks to the initialisation, they start from the observed climate conditions at the time of the eruptions, which helps to disentangle the climatic changes due to the initial conditions and internal variability from the volcanic forcing. The protocol consists of repeating the retrospective predictions that are initialised just before the last three major volcanic eruptions but without the inclusion of their volcanic forcing, which are then compared with the baseline predictions to disentangle the simulated volcanic effects upon climate. We present the results from six Coupled Model Intercomparison Project Phase 6 (CMIP6) decadal prediction systems. These systems show strong agreement in predicting the well-known post-volcanic radiative effects following the three eruptions, which induce a long-lasting cooling in the ocean. Furthermore, the multi-model multi-eruption composite is consistent with previous work reporting an acceleration of the Northern Hemisphere polar vortex and the development of El Niño conditions the first year after the eruption, followed by a strengthening of the Atlantic Meridional Overturning Circulation the subsequent years. Our analysis reveals that all these dynamical responses are both model- and eruption-dependent. A novel aspect of this study is that we also assess whether the volcanic forcing improves the realism of the predictions. Comparing the predicted surface temperature anomalies in the two sets of hindcasts (with and without volcanic forcing) with observations we show that, overall, including the volcanic forcing results in better predictions. The volcanic forcing is found to be particularly relevant for reproducing the observed sea surface temperature (SST) variability in the North Atlantic Ocean following the 1991 eruption of Pinatubo.

Projected changes in compound hot-dry events depend on the dry indicator considered

The intensification of compound hot-dry events due to climate change is a pressing concern, underscoring the need for precise analysis. However, the impact of different dry indicators on projections of these events has not been quantitatively evaluated, nor has its importance been compared with other sources of uncertainty. Here we examine the sensitivity of projected changes in compound hot-dry events to different dry indicators. We use data from 22 Coupled Model Intercomparison Project Phase 6 (CMIP6) models to characterize global dry conditions based on precipitation, runoff, soil moisture, and a multivariate index combining these variables through trivariate copulas. Our findings reveal large differences in projected changes in the likelihood of compound hot-dry events across different dry indicators. While model uncertainty remains the primary source of uncertainty for compound hot-dry event projections, the uncertainty associated with dry indicators is also substantial, surpassing scenario uncertainty in specific regions.

Warming climate is helping human beings run faster, jump higher and throw farther through less dense air

Understanding both positive and negative impacts of climate change is essential for comprehensively assessing and well adapting to the impacts of changing climate. Conventionally, climate warming is revealed to negatively impact human activities. Here, we reveal that human beings’ performance in anaerobic sports may benefit from climate warming. Using global weather observation and athletes’ performance datasets, we show that world-top athletes’ performances in nearly all athletics anaerobic events (i.e., sprints, jumps and throws) substantially improve as ambient temperature rises. For example, 100 m performance monotonically improves by 0.26 s as ambient temperature rises from 11.8° to 36.4 °C. Using Coupled Model Intercomparison Project Phase 6 datasets, we further show that global warming can substantially improve world-top athletes’ performance in eleven of the thirteen Olympics athletics anaerobic events by 0.27%–0.88% and 0.14–0.48% under high-emission and medium-emission scenarios, respectively, during 1979–2100. Among them, the improvements for 100 m are 0.59% (0.063 s) and 0.32% (0.034 s), respectively. Mechanism analysis shows that the warmed ambient atmosphere can improve competitors’ performance through expanding the air and thus reducing the air resistance to the competitors and throwing implements for hummer throw and all the sprints, hurdling and jumps. Quantitative analysis estimates that this thermodynamic process is essential for the impacts of warmed ambient atmosphere on the performances in these events as physiological processes are.

Interannual synchronization of the North American summer monsoon and the North Atlantic tropical cyclone genesis frequency

Variations of the North American summer monsoon (NASM) and North Atlantic tropical cyclone (NATC) activities strongly influence climate anomalies in North America, with serious potential risk to life and property. Despite the scientific importance of this topic, the possible linkage between the NASM and the NATC genesis frequency remains unexplored. Here, we aim to examine the relationship between interannual variations of the NASM intensity and the NATC genesis frequency based on observations and Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Our results show a strong association between the NASM intensity and the NATC genesis frequency during the extended boreal summer, with a good synchronization between their interannual variations. In years with stronger (weaker) NASM intensity, the NATC genesis frequency tends to be higher (lower). The observed NASM–NATC synchronization may be explained by two pathways: tropical-ocean-driven pathway and monsoon-heating-driven pathway. In the tropical-ocean-driven pathway, the tropical Pacific and Atlantic interbasin sea surface temperature (SST) anomalies play a critical role in bridging the NASM and NATC, by modulating the cross-Central American wind. Simulations of the tropical Pacific–Atlantic interbasin SST anomalies are critical for CMIP6 models to capture the observed linkage between the NASM and the vertical wind shear over the NATC main development region (MDR). In the monsoon-heating-driven pathway, the heating source due to the rainfall anomalies associated with the NASM can trigger atmospheric circulation anomalies through the Gill-type response, thereby affecting the NATC by changing the vertical wind shear over the MDR. This study demonstrates a connection between interannual variations of the NASM and the NATC genesis frequency, results of which can be used to advance our understanding of the monsoon–TC relationship and increase research focus on the interannual NASM–NATC synchronization in climate prediction.

Probabilistic projections of temperature and rainfall for climate risk assessment in Vietnam

ABSTRACT In this study, we developed a probabilistic model using the surrogate mixed model ensemble (SMME) method to project temperature and rainfall in Vietnam under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The SMME model combines patterns from 31 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their weighted model surrogates. Testing for the period of 2006–2018 demonstrated the SMME's ability to encompass observed temperature and rainfall changes. By the end of the 21st century, there is a 5% probability of average temperature increase exceeding 6.29 °C, and a 95% probability of minimum temperature increasing by more than 2.21 °C during 2080–2099 under RCP8.5 compared to 1986–2005. Meanwhile, rainfall is projected to slightly increase, with an average rise of 6.12% at the 5% probability level. The study also quantified the contributions of uncertainty sources – unforced, forced, and scenario-related – to the projection results, revealing that unforced uncertainty dominates the total signal at the beginning of the 21st century and gradually decreases, while forced uncertainty remains relatively moderate but increases gradually over time. As we approach the end of the century, scenario uncertainty dominates, accounting for 75–80% of the total signal.

Predicting the Spatial Distribution of the Mangshan Pit Viper (Protobothrops mangshanensis) under Climate Change Scenarios Using MaxEnt Modeling

This study explores the critical issue of understanding the potential impacts of climate change on the habitat suitability of the highly endangered forest-dwelling Mangshan pit viper (Protobothrops mangshanensis) in China. Through the application of the MaxEnt model, high-resolution bioclimatic datasets, and species occurrence data, the research aims to elucidate the spatial and temporal dynamics of P. mangshanensis distribution from the present to the years 2050 and 2070. Through the integration of three climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and exploring different shared socioeconomic pathway (SSP) scenarios (SSP126, SSP370, and SSP585), the study seeks to provide comprehensive insights into the potential variations in habitat suitability under diverse future climate conditions. The methodology employed involves the construction of the MaxEnt model utilizing the BioClim dataset and 83 species occurrence points. The SSP scenarios mentioned above represent future climate change scenarios, and the accuracy of the model is evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Key findings reveal that the MaxEnt model exhibits high accuracy (AUC = 0.998), pinpointing the current suitable habitat for P. mangshanensis to be confined to the Mangshan area within the Nanling Mountains, covering an approximate area of 1023.12 km2. However, projections based on future climate scenarios suggest notable shifts in habitat suitability dynamics. While potential suitable habitats may emerge in the northwest of the current range, the existing suitable habitats are anticipated to undergo significant reduction or even complete disappearance. Notably, precipitation during the driest month emerges as a critical determinant influencing the distribution of the species. In conclusion, the study underscores the exacerbating impact of climate change on habitat deterioration and survival risks for P. mangshanensis, emphasizing the urgent need for conservation measures to safeguard the remaining suitable habitats for this endangered species. The implications of these findings are far-reaching, with the anticipated contraction of the snake’s range potentially leading to its disappearance and increased habitat fragmentation. By shedding light on the potential distributional changes of P. mangshanensis in Mangshan, the research provides valuable insights for informing targeted conservation strategies and policy interventions aimed at mitigating the adverse effects of climate change on endangered species.

Assessing groundwater drought vulnerability through baseflow separation and index-based analysis under climate change projections

Groundwater is an essential resource, providing drinking water to millions of people globally and supporting agriculture, industry, and ecosystems. It acts as a drought buffer and provides a stable source of water during dry periods. However, groundwater is often underestimated and overexploited, leading to aquifer depletion and other negative impacts. Groundwater is invisible and difficult to measure, which makes it challenging for sustainable management. This study employed the Soil & Water Assessment Tool (SWAT) hydrological model to simulate streamflow in an eastern Afghan watershed using satellite-based and reanalysis data. Variables from five Coupled model intercomparison project phase 6 (CMIP6) general circulation models (GCMs), including minimum and maximum temperature and precipitation, were bias-corrected (downscaled) using Quantile Mapping (QM). The results from these five GCMs were then compared based on statistical criteria to determine the most reliable model, and the selected model was used to derive future data (i.e., 2021 to 2050) under different climate scenarios after applying QM. Using the future climate data and the developed SWAT model, streamflow values were projected for future periods. Considering that there are various methods to estimate groundwater recharge and the most commonly used technique involves baseflow separation procedures, this study used seven baseflow separation methods to estimate groundwater recharge values based on streamflow time series from the baseline period and different climate scenarios. To evaluate the groundwater drought characteristics, a recently proposed index called the Groundwater Recharge Drought Index (GRDI) and the run theory method were used. Results indicated that the SWAT model performed well in simulating and predicting streamflow. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC6) provided the highest accuracy compared to other climate models. Moreover, it was observed that the baseflow separation methods significantly affected the estimation of groundwater recharge, thus the obtained results from all developed methods were considered. The log-normal function was found to provide the best correlation for estimating GRDI. The findings revealed a gradual decrease in drought duration in the coming years. However, the magnitude and severity of droughts are projected to increase, especially under pessimistic climate scenarios.