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The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to +3.5∘C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥1.7∘C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

In this paper we study the influence of atmospheric and oceanic resolutions on the sea surface temperature (SST) under climate change and the related mechanisms. To this end, a set of historical period and future simulations in which two different atmospheric resolutions are combined with two different oceanic resolutions, one of them eddy-permitting, are used. We found that the magnitude of the warming is more dependent on atmospheric resolution, while the influence of oceanic resolution is stronger on the spatial pattern of SST changes, leading to the enhancement of the climate change signal in coastal regions in the higher resolution configuration. The mechanisms related to these changes involve both the atmosphere and the ocean, with the latter playing the main role. We found that changes in upwelling are the primary drivers of SST changes in regions close to the coast, and these changes in SST exhibit a clear seasonal pattern, precisely associated with the marked seasonality of the Benguela upwelling system. The radiative and turbulent fluxes adjust to the increase of greenhouse gases and are also influenced by the resolution and SST patterns. Additionally, the net longwave fluxes into the ocean increase, while the shortwave fluxes decrease due to the formation of low clouds. [ABSTRACT FROM AUTHOR]

The study provides a detailed analysis of the climate change projections in mean and extreme precipitation across the Dinaric Alps and the Adriatic coastal area until the end of the 21st century. It uses simulations from the extensive EURO-CORDEX regional climate model ensemble to study precipitation changes considering three greenhouse gas concentration scenarios. Additionally, the performance and systematic errors of historical simulations are evaluated. The ensemble demonstrates good skill in representing spatial variability and seasonal variations of mean and extreme precipitation. However, biases are evident and substantial across the Dinaric Alps, predominantly wet in winter and autumn, with the exceptions of dry biases in summer. The ensemble overestimates the frequency of heavy and extreme events. Regardless of these inconsistencies, projections clearly suggest a change in precipitation character with an overall intensification and a decrease in wet-day frequency, resulting in a mean precipitation winter increase over northern lowlands, summer decrease across southern parts, and spring and autumn zero-change zone across the Dinaric Alps. Extreme precipitation events are expected to intensify and become more frequent during winter and autumn with robust signals over the lowlands. During summer, the ensemble shows substantial uncertainties, but an intensification nonetheless within a smaller number of extreme events. Overall, the study identifies more consistency in the direction of change than magnitude in individual simulations, with the strongest consensus on precipitation intensification. Limitations include low station density in the observational dataset and an incomplete ensemble size, however, findings align with previous research and observed trends. [ABSTRACT FROM AUTHOR]

Monsoons are a vital part of the agriculture and economy of India which most of its population rely on for their livelihoods. It still is not clear how climate change will impact precipitation events over India due to the complexity of accurately modelling precipitation. Using twelve Coupled Model Intercomparison Project Six (CMIP6) models, we compared their performance to observed data taken from CRU as well as looking at the future changes in precipitation until the end of the twenty first century for the six precipitation homogenous regions over India. The individual models showed varying degrees of wet and dry biases and the ensemble mean of these models showed relatively lesser bias and improved spatial correlation. Out of 12 models, NorESM and MIROC6 models outperform other models in terms of capturing the spatial variability of precipitation over the Indian region. It is also found that due to lesser moisture transport from the adjoining seas represented through vertically integrated moisture transport (VIMT) analysis, there is consistent dry bias across the models. Further a comprehensive analysis of model performance across six homogeneous precipitation regions indicates that NorESM demonstrates better performance in the CNE and HR regions, EC-Earth excels in the PR, WC, and NE regions, while CMCC shows better performance specifically in the NW region compared to other models. Shared Socioeconomic Pathways (SSPs) were used for future projections and a slight increase in June, July, August, and September (JJAS) precipitation until the end of the century with SSP5-8.5 showing the largest increase. We found an increase in precipitation of 0.49, 0.74 and 1.4 mm/day under SSP1-2.6, SSP2-4.5 and SSP5-8.5 in the far future. The northeast region was shown to receive the largest increase in precipitation (2.9 mm/day) compared to other precipitation homogenous regions and northwest will experience largest shift in precipitation. Interestingly, the number of wet days is expected to increase in the northwest region implying more VIMT towards the region. Our results indicate that monsoon precipitation extremes across all the homogenous regions will increase into the future with a higher severity under fossil-fuelled development, although the models still show large biases lowering confidence in our results. [ABSTRACT FROM AUTHOR]

In the context of rapidly rising sea levels over the north Indian Ocean, the decadal variations play significant role and predicting them is of utmost important to the society. The present study evaluates the quality of all the available retrospective decadal sea level predictions from the state-of-the-art climate models of the Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6). The models are skilful in predicting the sea level over the tropical Indo-Pacific for the lead year 1 and thereafter the skill persists mainly over the western Indian Ocean regions. Most of the models exhibit significant skill in the Arabian Sea region at higher leads including 2–5 years and 6–9 years. Half of the models display higher sea level prediction skill over the Arabian Sea at lead year 2–5, compared to lead year 1. Taking into account of the close association between the Indian Ocean decadal sea level variations and the decadal climate variability in the Pacific and Atlantic, the skill of models in predicting the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) up to a decade is also assessed in this study. The AMO is better predicted in most of the models up to lead year 9, whereas only few models display skill in predicting the PDO. Skilful representations of strong cross equatorial flow and convergence of southerly winds towards the Arabian Sea region are noted in the CMIP6 predictions, which are responsible for better sea level prediction skill over the Arabian Sea. This study highlights that the better representation of AMO in the models has primarily contributed to the skilful sea level predictions over the Arabian Sea region. [ABSTRACT FROM AUTHOR]

A significant fraction of multidecadal fluctuations in the reanalysis-based gridded estimates of the observed climate variability over the past century and a half lie outside of the envelope generated by ensembles of climate-model historical simulations. Several pattern-recognition methods have been previously used to map out a truly global reach of the observed vs. simulated climate-data differences; in our own work we dubbed these global discrepancies the stadium wave to highlight their most striking spatiotemporal characteristic. Here we used a novel combination of such methods in conjunction with a large multi-model ensemble and two popular twentieth-century reanalysis products to: (i) succinctly describe the geographical evolution of the observed stadium wave in the annually sampled near-surface atmospheric temperature and mean sea-level pressure fields in terms of three basic patterns; (ii) show the robustness of this identification with respect to methodological details, including the demonstration of the truly global character of the stadium wave; and (iii) provide essential clues to its dynamical origin. Part I of this study decomposed all input time series into the forced signal and the residual internal variability; multi-model forced-signal estimates were also decomposed into their common-evolution part and the individual-model residuals. Analysis of the latter residuals suggests a contribution to the stadium-wave dynamics from a delayed climate response to variable external forcing despite the observed stadium-wave patterns' exhibiting the magnitudes and the level of global teleconnectivity unmatched by the forced-signal residuals. Part III of this paper will compare the observed stadium wave with the model simulated internal patterns. [ABSTRACT FROM AUTHOR]

Under global warming, extreme events have been increasing in the last decade and are projected to increase in the future with every increment of global warming. The potential increase in compound drought and hot events may induce a complex web of impacts on societies, ecosystems, and economies, including crop failure, wildfires, and water scarcity. This is particularly concerning for Brazil, where it has been demonstrated to be vulnerable to recent extreme climate events. Using an ensemble of CORDEX-CORE simulations over Tropical Brazil, we investigate changes in compound events in response to changes in radiative forcing and their impact on climate extreme events, including drought and extreme heat. The simulations are conducted at a 25 km horizontal grid spacing using lateral and lower boundary forcing from three Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. Each model covers the period from 1980 to 2100 under two Radiative Concentration Pathways (RCP2.6 and RCP8.5) in the 21st-century projection period. We used observed data from the Brazilian Daily Weather Gridded Data (BR-DWGD) to evaluate the simulations and perform a quantitative assessment of areas affected by these compound events during the present day. The study finds a generally good agreement between RCM simulations and observed data, with moderate to high correlation coefficients for precipitation, though the strength of these correlations varies across different regions and seasons. The analysis emphasizes the prevalence of compound climate events during the Austral summer season and projects a significant increase in both extreme heat and drought events in the coming decades. These findings underscore Brazil's vulnerability to compound climate events, highlighting the need for adaptive strategies and policy interventions to mitigate the socio-economic and environmental impacts across various sectors. [ABSTRACT FROM AUTHOR]

The north and central coast of Chile is influenced by El Niño-Southern Oscillation (ENSO) through oceanic and atmospheric teleconnections. However, it also experiences episodic oceanic warmings off central Chile (30°S) lasting a few months that are not necessarily associated with ENSO. These episodes, called "Chile Niño" events, besides their ecological and socio-economical impacts, have also the potential to influence tropical Pacific variability. Here, we investigate how realistically the models in the Coupled Model Intercomparison Project (CMIP, Phases 5 and 6) simulate Chile Niño/Niña (CN) events, and quantify their changes under anthropogenic forcing. Despite limitations of the global models in simulating realistically coastal upwelling dynamics, we show that they simulate reasonably well the observed spatial pattern, amplitude and seasonal evolution of CN events. They however fail to properly represent the positive skewness from observations. The analysis of a sub-group of models (36) that simulate ENSO realistically reveals that CN events increase in amplitude and variance in the future climate with no changes in their frequency of occurence. This is interpreted as resulting from compensating effects amongst changes in remote drivers and local feedbacks. In particular, ENSO variance increases while that of the South Pacific Oscillation decreases. Conversely, we found that while the Wind-Evaporation-SST feedback tends to increase and the coupling between mixed-layer depth and SST weakens, favoring the development of CN events, the thermocline and wind-SST feedbacks decrease. However, only the change in the thermocline feedback is correlated to changes in CN variance amongst the models, suggesting a dominant role of local oceanic stratification changes in constraining the sensitivity of CN to global warming. [ABSTRACT FROM AUTHOR]

High clouds play an important role in climate variations by shading the sun and contributing to the greenhouse effect. It has been suggested that these variations are strongly controlled by atmospheric circulations; however, the relationship between high clouds and circulations in global simulations has been confirmed only for a limited number of general circulation models (GCMs). Increasing our understanding of this relationship requires a more complete dataset of state-of-the-art GCMs. This study quantifies the relationship between high clouds and circulations by spatial and temporal correlation using data from 28 atmospheric GCMs along with a global nonhydrostatic model, a new-type of GCM, and reveals a robust and strong relationship in most models. This study also finds that the sensitivity, which is defined as the slope of the relationship between high clouds and mass fluxes of circulations, is highly model-dependent. This suggests that a similar change of circulations does not guarantee that of high clouds, which could be one reason for the complexity in projecting high-cloud changes due to warming. Moreover, this study confirms in both observation and models that the relationship with circulations is stronger for medium-thickness and thick high clouds than for thin clouds. Furthermore, the relationship between high clouds and circulations is more convincing in near-equatorial regions between 15°S–15°N, the ascending branch of the Hadley circulation, where deep convection is especially active. [ABSTRACT FROM AUTHOR]

The Himalayas are undergoing significant changes in temperature and moisture availability due to global climate change. Understanding how these changes affect tree growth is critical for conserving and managing this biodiverse region. To investigate the growth-limiting climatic factors, we collected tree-ring data from Abies pindrow old-growth mountain forests across 3190 to 3700 m a.s.l. in the inner valleys of the Garhwal Himalayas. This area faces significant temperature increases, reduced summer monsoon activity, and decreased winter precipitation. We found that over the past century, tree growth suffered from warm and dry springs and benefited from cool and moist springs, particularly at lower elevations (< 3400 m a.s.l.). Conversely, summer climate dynamics had minimal impact on radial growth. The sensitivity of Abies growth to spring climate can be attributed to the inner valleys' continental climate, marked by spring water deficit. Additionally, higher elevation trees (> 3400 m a.s.l.) showed positive correlations with dormant period temperatures in prior October and January, with the positive effect of October warmth strengthening over time. A dynamic analysis of the impact of spring (March–May) temperature, precipitation and Standardized Precipitation-Evapotranspiration Index revealed a recent unification (the 1980–2010s) of the climate–growth relationship across elevations. Specifically, the low-elevation trees have become less sensitive to warm springs, while the high-elevation trees have only recently become sensitive to warm and dry springs. The varying growth responses along the elevation gradient highlight the necessity of site-dependent differentiation when assessing the impacts of global climate change on species performance and geographic range shifts. [ABSTRACT FROM AUTHOR]

The Atlantic Meridional Overturning Circulation (AMOC) is a crucial system influencing regional and even global climate changes, with the Subpolar North Atlantic (SPNA) being a key region affecting this system. In the context of global climate change, the impact and mechanisms of aerosols on the AMOC remain unclear. This study, based on state-of-the-art ensemble model simulations paired with latest observations, reveals that aerosols in the SPNA region significantly influence sea surface temperature anomalies by affecting cloud cover, which in turn affects ocean stratification, thus impacting the strength of the AMOC. Based on this, we present the trends and spatiotemporal characteristics of future AMOC under different forcings. Our research contributes to a deeper understanding and prediction of the AMOC. [ABSTRACT FROM AUTHOR]

The increase in vegetation coverage resulting from the implementation of the Grain for Green Project (GFGP) on the Loess Plateau (LP) in China has sparked debates on how the GFGP affects the water cycle, due to the limited understanding of the interaction between land cover and the atmosphere. This study investigated spatiotemporal changes in atmospheric water vapor (WV) from 1979 to 2022 using ERA5 dataset and quantified the impacts of the GFGP on the WV budget on the LP through numerical simulations with the Community Earth System Model. The analysis of ERA5 data revealed an increase in WV content (WVC) after the implementation of the GFGP (2000–2022) compared to the pre-program period (1979–1999). This increase was primarily attributed to a greater reduction in WV outflow at the eastern boundary than the reduction in inflow at the western boundary, resulting in greater WV retention. Our sensitivity simulation experiments indicated that the GFGP had positive effects on WVC, with evident increases in the lower atmosphere (700–1000 hPa). The GFGP increased WV inflows at the southern and western boundaries by 3.84 × 104 kg·s-1·m-1, while WV outflows at the eastern and northern boundaries also increased by 1.40 × 104 kg·s-1·m-1, leading to a net WV input in the low atmospheric layer due to higher inflows than outflows. These findings suggested that although the GFGP positively impacted WV, the observed post-2000 WV increase cannot be solely attributed to the GFGP, indicating that changes in atmospheric circulation patterns under climate change also play an important role. [ABSTRACT FROM AUTHOR]

The effective radius of cloud droplets ( r eff ), representing the ratio of the third to the second moment of the droplet size distribution, is a pivotal factor in inferring the cloud optical properties, such as cloud optical thickness, and single scattering albedo, and consequently plays a vital role in the calculation of radiative properties. Effective radius holds significance not only in assessing the global radiation budget but also in incorporating the aerosol indirect effect within climate models. Hence, refining the parameterization of cloud droplet’s effective radius in earth system models (ESMs) has emerged as a critical endeavor for assessing climate change. Understanding the relationship between the gradient (k) or effective radius ratio (β ), a dimensionless parameter, and mean diameter and relative dispersion (ϵ ) is essential for the parameterization of effective radius. Fundamental theoretical studies using the Eulerian–Lagrangian particle-based model, guided by airborne observations, yield a spectrum of effective radius ratios (β ) aimed at improving the parameterization of r eff . Notably, β or the gradient (k) exhibit significant variations across shallow and convective clouds, with k ranging from 0.61 to 0.84 (mean of 0.72 at a relative dispersion of 0.35). The analysis of CMIP6 models indicate that adopting appropriate β value in the effective radius parameterization is crucial to mitigate the bias in r eff . Thus, better parameterization of the cloud effective radius remains essential for elucidating the radiative impacts in ESMs. [ABSTRACT FROM AUTHOR]

Hypoxia is a major environmental threat for coastal seas, including the strongly-stratified Baltic Sea in northern Europe. There, a pronounced increase in nutrient loads since the 1950s led to the development of one of the largest hypoxic areas worldwide. So far, other drives of hypoxia, like the increase in water temperatures due to global warming, have been considered minor compared to eutrophication. We show, by analyzing 159-years long hindcast simulations of three different Baltic Sea models, that exceptional warming trends in deep water layers of the western Baltic Sea deteriorated the local oxygen conditions. The above-average warming is only to a small extent attributed directly to global warming, but mainly to a shift in the seasonality of saltwater inflows from the North Sea towards more warm summer and early autumn inflows. Hence, we identify a so far unknown driver of oxygen depletion in the western Baltic Sea with potentially serious ecological consequences. [ABSTRACT FROM AUTHOR]

The climate of western Europe and northwest Africa strongly depends on the Azores anticyclone strength, location, and shape and, locally, also on the characteristics of the Iberia and Sahara summer thermal lows. EC-EARTH3 global simulations are here used to assess the predicted behaviour of these two relevant surface pressure systems and associated surface wind, by the end of XXI century (2071–2100), considering two climate change scenarios. Additionally, a high-resolution Weather Research and Forecasting (WRF) simulation centred on Madeira Island is used to assess the influence of climate change on the surface wind at smaller scales, in a region well known for its perturbed flows. Results indicate a general mean wind speed decrease over a sector of the North-Atlantic, associated with a flatter Azores anticyclone. However, the predicted intensification of the Iberia and Sahara thermal lows imposes an increasing surface wind speed near west Iberia and northwest Africa, in summer. Southwest of Iberia, Madeira Island is also predicted to experience a summer intensification of its tip-jets. The projected changes in low-level wind speed and variability will impact on different sectors of activity, either directly as are the cases of aeronautical operation and offshore renewable energy, or indirectly through changes in the ocean circulation. [ABSTRACT FROM AUTHOR]

Observational evidence has shown that precipitation extremes are expected to increase over Southeast Asia (SEA) under climate change. The physical mechanism of the future changes in precipitation extremes has remained largely unclear, which is a great challenge to project the future hydrologic cycle. In this study, the changes in precipitation extremes over SEA by the end of the 21st century (2071–2100) were estimated based on simulations from CMIP6 (Phase 6 of the Coupled Model Intercomparison Project) models. Results showed that the spatiotemporal intensity of precipitation extremes is expected to increase significantly over SEA, as compared to the historical period of 1985–2014. The frequency and intensity of precipitation extremes in Kalimantan is projected to increase markedly in 2071–2100. Moreover, the wet and dry periods will be intensified in SEA, which is consistent with the "wet-get-wetter, dry-get-drier" mechanism. We further investigated the thermodynamic and dynamic contributions to the enhanced precipitation extremes using a physical scaling diagnostic method, and results showed thermodynamic factors accounting for approximately 77% (75%) of the total scaling change under the SSP2-4.5 (SSP5-8.5) scenario, but dynamic components constituting around 18% (15%). Alterations in thermodynamic scaling prevail as the primary contributor to amplified precipitation extremes. Furthermore, it was verified that the change in saturation specific humidity of thermodynamic scaling is intensified, and the model simulation consistency of thermodynamic scaling is better than that of dynamic scaling, revealing the effects of atmospheric thermodynamics and dynamics in the change of precipitation extremes over SEA. [ABSTRACT FROM AUTHOR]

The present study analyzes zonal mean cloud and radiation trends over the global oceans for the past 35 years from a suite of satellite datasets covering two periods. In the longer period (1984–2018) cloud properties come from the ISCCP-H, CLARA-A3, and PATMOS-x datasets and radiative properties from the ISCCP-FH dataset, while for the shorter period (2000–2018) cloud data from MODIS and CloudSat/CALIPSO and radiative fluxes from CERES-EBAF are added. Zonal mean total cloud cover (TCC) trend plots show an expansion of the subtropical dry zone, a poleward displacement of the midlatitude storm zone and a narrowing of the tropical intertropical convergence zone (ITCZ) region over the 1984–2018 period. This expansion of the 'low cloud cover curtain' and the contraction of the ITCZ rearrange the boundaries and extents of all major climate zones, producing a more poleward and narrower midlatitude storm zone and a wider subtropical zone. Zonal mean oceanic cloud cover trends are examined for three latitude zones, two poleward of 50 ° and one bounded within 50oS and 50oN, and show upward or near-zero cloud cover trends in the high latitude zones and consistent downward trends in the low latitude zone. The latter dominate in the global average resulting in TCC decreases that range from 0.72% per decade to 0.17% per decade depending on dataset and period. These contrasting cloud cover changes between the high and low latitude zones produce contrasting low latitude cloud radiative warming and high latitude cloud radiative cooling effects, present in both the ISCCP-FH and CERES-EBAF datasets. The global ocean mean trend of the short wave cloud radiative effect (SWCRE) depends on the balance between these contrasting trends, which in the CERES dataset materializes as a SW cloud radiative warming trend of 0.12 W/m2/decade coming from the dominance of the low-latitude positive SWCRE trends while in the ISCCP-FH dataset it manifests as a 0.3 W/m2/decade SW cloud radiative cooling trend coming from the dominance of the high latitude negative SWCRE trends. The CERES cloud radiative warming trend doubles in magnitude to 0.24 W/m2/decade when the period is extended from 2016 to 2022, implying a strong cloud radiative heating in the past 6 years coming from the low latitude zone. [ABSTRACT FROM AUTHOR]

Data from the EURO-CORDEX ensemble of regional climate model simulations and the CORDEX-Adjust dataset were evaluated over the European Alps using multiple gridded observational datasets. Biases, which are here defined as the difference between models and observations, were assessed as a function of the elevation for different climate indices that span average and extreme conditions. Moreover, we assessed the impact of different observational datasets on the evaluation, including E-OBS, APGD, and high-resolution national datasets. Furthermore, we assessed the bi-variate dependency of temperature and precipitation biases, their temporal evolution, and the impact of different bias adjustment methods and bias adjustment reference datasets. Biases in seasonal temperature, seasonal precipitation, and wet-day frequency were found to increase with elevation. Differences in temporal trends between RCMs and observations caused a temporal dependency of biases, which could be removed by detrending both observations and RCMs. The choice of the reference observation datasets used for bias adjustment turned out to be more relevant than the choice of the bias adjustment method itself. Consequently, climate change assessments in mountain regions need to pay particular attention to the choice of observational dataset and, furthermore, to the elevation dependence of biases and the increasing observational uncertainty with elevation in order to provide robust information on future climate. [ABSTRACT FROM AUTHOR]

Assessing the impacts of anthropogenic land use and land cover change (LULCC) on climate extremes is crucial for the public. This necessitates the utilization of state-of-the-art experiments and datasets to enhance our understanding. Here, we used CMIP6-LUMIP experimental results to show the biogeophysical effects of LULCC on extreme temperature and precipitation during the historical period. Three regions with intense LULCC in the Northern Hemisphere experienced cooling effects caused by LULCC. In contrast, only the highest maximum temperature (TXx) showed slight warming effects in three regions with intense LULCC in the Southern Hemisphere near the tropics. The maximum changes in intensity were an ∼ 0.8 °C decrease in the TXx and nearly a 2 °C decrease in the 90th percentile in the lowest minimum temperature (TNn) in North America. South Asia experienced ∼ 4% and 10-day decreases in warm days (TX90p) and warm spell duration (WSDI), respectively, in the 90th percentile. The precipitation response to LULCC displayed a clear difference between the Northern Hemisphere (wetter) and the Southern Hemisphere (drier), especially in terms of mean precipitation and wet days (R1mm). Previous studies support our findings that the impacts of LULCC on temperature extremes are greater in regions with intense LULCC than in remote areas. Seasonal results showed that March-April-May (MAM) and June-July-August (JJA) contributed more to the maximum temperature changes, while the minimum temperature experienced greater responses in MAM and December-January-February (DJF). LULCC tended to induce a shift toward either warmer and drier conditions or wetter and colder conditions in approximately two-thirds of season–region pairs. [ABSTRACT FROM AUTHOR]

Accurately delineating and predicting changes in climate zones, which serve as a comprehensive reflection of various climatic factors, is of utmost importance for food production, biodiversity conservation, and the sustainable development of society. This study used the K-means clustering method to analyze the distribution characteristics of China's climate zones during the historical-term (HT, 1981–2014). Additionally, it examined the spatial distribution trends of these zones during the mid-term (MT, 2015–2050) and long-term (LT, 2051–2100) under different socioeconomic development pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results highlight the alignment of the seven climate zones identified by K-means with the distribution characteristics of climate zones in China. The future annual average temperature and precipitation in China are expected to significantly increase, leading potentially to a transformation of vulnerable climate zones into adjacent high-temperature and high-humidity climate zone types. The MT period demonstrated the most pronounced changes, characterized by continuous and significant spatial distribution trends in most climate zones. Notably, these changes appear relatively unaffected by the chosen socioeconomic development pathways. During the LT period, the intensity of climate zone area changes was comparatively lower than during the MT period. Under the SSP1-2.6 development pathway, the trend of climate zone changes could potentially decelerate in the future. Therefore, the early formulation of policies to address the impacts of climate change becomes imperative for navigating the future trajectory of climate zones. [ABSTRACT FROM AUTHOR]

This study uses experiments from the Energy Exascale Earth System Model (E3SM) to compare the influence on tropical cyclone (TC) activity of: (i) the atmospheric effect of aerosols under specified sea-surface temperatures (SSTs); and (ii) the net effect of greenhouse gases (GhGs) (including changes in SSTs). The experiments were performed using the CMIP6 Shared Socioeconomic Pathway SSP5-8.5 emissions scenario with GhG-induced SST warming specified and atmospheric aerosol effects simulated but without explicit ocean coupling. Insignificant changes in global TC frequency are found in response to the atmospheric effect of future aerosols and GhGs, as significant regional responses in TC frequency counteract each other. Future GhGs contribute to more frequent TCs in the North Atlantic, and reductions over the Northwestern Pacific and Southern Indian Ocean. The atmospheric effect of future aerosols drives more frequent TCs over the Northwestern Pacific and reductions over the Northeast Pacific and North Atlantic. Along with increases in TC intensity, global TC precipitation (TCP) is projected to increase by 52.8% (14.1%/K) due to the combined effect of future aerosols and GhGs. Although both forcings contribute to TCP increases (14.7–19.3% from reduced aerosols alone and 28.1–33.3% from increased GhGs alone), they lead to different responses in the spatial structure of TCP. TCP increases preferentially in the inner-core due to increased GhGs, whereas TCP decreases in the inner-core and increases in the outer-bands in response to the atmospheric effects of decreased aerosols. These changes are distinct from those caused by aerosol-induced SST changes, which have been considered in other studies. [ABSTRACT FROM AUTHOR]

This study reveals the simulation results of a regional ocean-atmosphere coupled model (Coupled Ocean-Atmosphere-Wave Sediment Transport Modeling System, COAWST) for the Coordinated Regional Climate Downscaling Experiment (CORDEX) East Asia Phase II, which covers a period of 21 years (1989–2009) at a horizontal resolution of 25 km. The coupled simulation (CPL) and the uncoupled atmospheric simulation (UNCPL) are compared with observations to assess their capability of capturing the climatology characteristics over East Asia. The simulated sea surface temperature (SST) in CPL is generally overestimated (underestimated) in summer (winter) over most CORDEX-EA-II regions. Both CPL and UNCPL can capture the spatial patterns of seasonal air temperature over East Asia well. However, they both simulate cold biases of the winter temperature over most regions of China. CPL can reduce the cold biases over certain regions, which may be related to the increased cloud cover reflecting more longwave radiation to the ground. Additionally, CPL improves the simulation results of summer precipitation, diminishing the dry biases over northern Bay of Bengal and South China Sea. This improvement may be related to the better description of moisture transportation and precipitable water. Furthermore, The CPL experiment can better simulate the inter-annual variability of summer precipitation and the relationship between SST and precipitation, especially over the South China Sea and Philippines Sea. CPL also captures the northward propagation and amplitude of boreal summer intra-seasonal oscillation precipitation anomalies more accurately. These findings highlight the importance of ocean-atmosphere coupling processes to simulate multiscale climate changes in the CORDEX-EA-II regions. Key Points: • The COAWST regional coupled model enhances the simulation of surface air temperature and precipitation climatology over CORDEX East Asia. • The coupled model effectively represents the inter-annual variability of summer precipitation over most western Northern Pacific regions. • The coupled model provides a more accurate depiction of the northward propagation and amplitude of BSISO precipitation anomalies. [ABSTRACT FROM AUTHOR]

The Arabian Sea, notably the Sea of Oman, has exhibited a gradual warming trend since the twentieth century, expected to persist in the future, necessitating a climatological assessment for potential environmental disaster mitigation. This study conducts a comprehensive analysis using satellite-derived data on sea surface temperature (SST), Chlorophyll-a (Chl-a), sea level anomaly (SLA), and wind stress curl (WSC) to understand the region's climate dynamics. Phytoplankton (Chlorophyll-a) in the Sea of Oman plays a vital role in the ocean ecosystem, serving as primary producers and oxygen suppliers by fixing atmospheric carbon dioxide. Over the past four decade, the average Chl-a in the Sea of Oman was 3.06 mg/m3, with elevated levels (> 5.5 mg/m3) observed along coastal regions, peaking in summer and declining in winter. Over four decades, SST has risen by 0.658 °C on average, with the highest gradient magnitude observed along the coast. SLA has steadily increased exceeding 0.722 cm over the entire period (1993–2021). WSC shows seasonal variations, with high values (> 1 N/m2) in July and August and slightly lower values in winter. Furthermore, significant correlations between ocean variables and major climatic oscillations such as the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), El Nino-3.4 (Nino3.4), and the Dipole Mode Index (DMI) are identified, highlighting the intricate interplay shaping the Arabian Sea's ecosystem and providing critical insights for effective environmental management strategies. Implement integrated monitoring and adaptive management strategies to mitigate the impacts of climate variability on the Sea of Oman marine ecosystem. [ABSTRACT FROM AUTHOR]

This study conducted and evaluated 44 experiments using the non-hydrostatic version of the regional climate model RegCM4 (RegCM4-NH) and an additional three experiments with RegCM version 5 (RegCM5) over Southeast Asia for the period 2010–2015. The initiative was part of the coordinated regional climate downscaling experiment—Southeast Asia (CORDEX-SEA) project, in preparation for downscaling the latest coupled model intercomparison project Phase 6 (CMIP6) global climate models (GCMs). The RegCM4-NH experiments, forced by the ERA5 reanalysis, were configured using combinations of four cumulus, three planetary boundary layer (PBL), and three explicit moisture schemes. The spatiotemporal variability of simulated 2 m-temperature and rainfall for 2010–2015 was evaluated against observational datasets. The best experiments demonstrated reasonable reproduction of observed annual cycles and spatial distribution, while many exhibited unrealistic biases. A score ranking system was implemented to objectively compare the performance of experiments, enabling the identification of top-ranked experiments for Southeast Asia. The ensemble mean of the 44 RegCM4-NH experiments exhibited commendable performance, ranking 11th overall. Furthermore, the three additional RegCM5 experiments did not yield improved results compared to RegCM4-NH under the same physical configuration, suggesting that opting for RegCM4-NH would be a prudent choice for the CORDEX-SEA community in the forthcoming CMIP6 downscaling cycle for Southeast Asia. [ABSTRACT FROM AUTHOR]

The compound extremes have received a widespread attention. A quantile delta-mapped spatial disaggregation (QDMSD) method has been developed to analyze summertime compound dry-warm (CDDW) and wet-warm (CDWW) extremes in historical (1980–2014) and future (2030–2099). The evaluation results show that QDMSD has an improvement in reproducing precipitation relative to the bias correction and spatial disaggregation (BCSD) model. QDMSD could also reasonably reproduce the mean temperature and precipitation in sub-regions of China at monthly and interannual scales. The downscaled results indicate that the projected changes in two parameters (i.e., occurrence frequency and averaged duration) would increase under SSP5-8.5. CDDW is projected to occur in northwest and central China under SSP2-4.5, while it would expand to eastern China under SSP5-8.5. Projected CDWW events will occur frequently in southwestern, northeastern, central, and eastern China under SSP5-8.5. Under SSP5-8.5, the annual increase in the averaged duration of CDDW could reach 4 days/event, with an annual increment of 1.2 event in frequency. For CDWW, the annual increment in averaged duration could reach 0.4 day/event, with an annual increment of 0.1 event in frequency. The factorial analysis results imply that GCMs are the primary source for the uncertainty of projections in the 2050s (i.e., 2030–2064). In the 2080s (i.e., 2065–2099), the emission scenarios are the major uncertain factor for CDDW. For CDWW, the GCMs are the dominant factor. These findings could support policy-making to address potential risks from compound extremes across multiple sectors (e.g., agriculture, industry and food security). [ABSTRACT FROM AUTHOR]

The increasing use of climate projections in adaptation necessitates a consistent method for producing estimates of likely future conditions from available climate model data. Many climate projections are produced using high emission scenarios and an evenly weighted ensemble of all available climate models despite substantial evidence that the continuously rising emissions in high emission scenarios are unrealistic, and that some models are more reliable than others. While high emission scenarios can be used to generate a more significant climate change signal and are often not intended to be interpreted as projections, a reader who is a non-expert on climate scenarios may not understand this nuance. As a result, unlikely climate projections could be inadvertently used to plan crucial adaptation efforts for future warming. Here, we present a simple and easy to use framework for creating projections of our likely future climate by combining existing methods. The framework involves three measures: selecting the most likely emission scenario, choosing the most reliable models, and debiasing against observational or reanalysis data. Each of these steps allows for a range of methods with varying complexity, precision, and utility. To demonstrate our framework and its components, we use the simplest applicable methods to estimate future changes in tropical width, a hydrologically important climate feature. Our projections show that the likely tropical expansion by the end of this century is roughly half of some previously reported estimates, largely due to the selected emission scenario. This simple framework can be easily applied to other climate features, allowing for better estimates of likely future conditions. [ABSTRACT FROM AUTHOR]

Since 2000, Clouds and the Earth's Radiant Energy System (CERES) instruments on Aqua and Terra satellites have recorded top-of-atmosphere (TOA) clear-sky outgoing radiation fluxes. Over northwest India, analysis of these two decades of data revealed significant negative trends in reflected shortwave radiation, indicating positive shortwave radiative forcing. To understand the drivers of this trend, we investigate changes in the surface reflectance, aerosol optical depth (AOD), Normalized Difference Vegetation Index (NDVI), and land surface temperature from MODIS observations during the same period. We find decreasing trends in surface reflectance and AOD, while NDVI shows a pronounced increase. Notably, despite positive shortwave radiative forcing, daytime land surface temperature exhibits a significant decrease, with only a slight nighttime increase. Sensitivity analysis using a radiative transfer model identifies decrease in the surface reflectance as the primary contributor to the decrease in TOA shortwave fluxes. This suggests that the observed greening, potentially linked to expanded irrigation projects, has played a crucial role by reducing both surface reflectance and aerosol production. Our findings highlight the potential for increasing vegetation as a locally effective strategy to mitigate the effects of global warming through enhanced evapotranspiration process, even in the presence of positive shortwave radiative forcing. Investigating regional climate trends is vital for understanding and quantifying climate change; these results highlight the need for future climate change impact studies to consider interplay between vegetation dynamics and regional climate. [ABSTRACT FROM AUTHOR]

Due to its high influence on agriculture, infrastructure, water management, and other areas, precipitation is one of the most important climate factors. However, it is still challenging for climate models to realistically reproduce regional patterns, temporal variability, and precipitation intensity. This is especially true for extreme conditions and terrains with heterogeneous orography, like the Carpathian region. For the sake of quantifying the uncertainty and improving the accuracy of the precipitation simulations of the RegCM4.7 regional climate model over the Carpathian region, we evaluate the performance of different options at 10 km horizontal resolution, using ERA-Interim reanalysis data as initial and boundary conditions. Altogether 24 simulations were carried out by using various combinations of the physical schemes (2 land surface, 2 microphysics, 3 cumulus convection and 2 planetary boundary layer (PBL) schemes) for the year 2010, which was the wettest year in the Carpathian region (especially in Hungary) since 1901. Different parameterization combinations lead to different simulated climates, so their variance can serve as an estimate of model uncertainty due to the representation of unresolved phenomena. The results show that RegCM is sensitive to the choice of scheme combinations. The analysis of the RegCM4.7 ensemble indicates systematic precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Based on the results, RegCM4.7 is the most sensitive to the applied convection scheme, but the interactions with the other schemes (e.g., land surface and microphysics) affect the convective and large-scale precipitation in addition to the total precipitation. [ABSTRACT FROM AUTHOR]

Mountain regions are recognised as hot-spots of climate change. Although the existence of an Elevation-Dependent Warming has been extensively confirmed in several mountain areas of the globe, fewer studies have analysed the elevational stratification of temporal trends of other climate variables, and particularly for precipitation. This study analyses changes in mean precipitation and its extremes in ERA5 global reanalysis data in key mountain areas of the globe, along with their elevational dependence, from 1951 to 2020. These include the Tibetan Plateau, the US Rocky Mountains, the Greater Alpine Region, and the Andes, as representative of different latitudes and climatic influences. Our analysis reveals common patterns of elevational dependent change in precipitation and its extremes in most of the mountainous areas, which emerge beyond their geographical differences. A positive elevational gradient of trends of extreme precipitation indices is found in the Tibetan Plateau, the Greater Alpine Region, and the subtropical Andes, highlighting a wetting effect (positive trends) at very high elevations. In contrast, the Rocky Mountains exhibit a negative elevational gradient, with a drying effect (negative trends) increasing with the elevation. Notably, a simple linear regression proved to be effective to describe the stratification of change in the Greater Alpine Region and the Rocky Mountains, whereas more complex vertical patterns need to be considered for the Andes and the Tibetan Plateau. Mean precipitation, heavy (≥ 10 mm) precipitation and the length of consecutive wet days show a consistent elevation-dependent stratification within each of the study areas, suggesting possible common driving mechanisms. [ABSTRACT FROM AUTHOR]

IPCC reports and climate change impact studies generally exploit ensembles of climate projections based on different socio-economic pathways and climate models, which provide the temporal evolution of plausible future climates. However, The Paris Agreement and many national and international commitments consider adaptation and mitigation plans targeting future global warming levels. Model uncertainty and scenario uncertainty typically affect both the crossing-time of future warming levels and the climate features at a given global warming level. In this study, we assess the uncertainties in a multi-model multi-member CMIP6 ensemble (MME) of seasonal and regional temperature and precipitation projections. In particular, we show that the uncertainties of regional temperature projections are considerably reduced if considered at a specific global warming level, with a limited effect of the emission scenarios and a reduced influence of GCM sensitivity. We also describe in detail the large uncertainties related to the different behavior of the GCMs in some regions. [ABSTRACT FROM AUTHOR]

Future changes in streamflow and sediment, influenced by anthropogenic activities and climate change, have a crucial role in watershed management. This study aimed to quantify the effects of anthropogenic and natural drivers on future streamflow and sediment changes in the tropical Sai Gon Dong Nai River basin using the Soil and Water Assessment Tool (SWAT) model. Specifically, the model incorporated thirty-six reservoirs and analyzed twenty future climate projected scenarios from four Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) for 2023–2100. These models include BCC-CSM2-MR (China), CanESM5 (Canada), MIROC6 (Japan), and MRI-ESM2-0 (Japan). Our findings indicate that (1) dam operation and diversion lead to a 0.5% decrease in streamflow during the dry season and a 4.1% increase during the rainy season compared to those in scenarios without dams; (2) there is a 37.4% decrease in annual sediment across the entire basin under same climate conditions; and (3) rainfall is projected to decrease (24.6% – 6.2%), resulting in a decrease in streamflow (0.2 – 32.2%) and sediment (39.3 – 56.0%) compared to historical records. Streamflow is expected to decrease during the rainy season (16.7 – 23.1%) and increase during the dry season (14.5 – 25.4%). Further potential degradation of the environmental conditions and water mismanagement are caused by the synergies between too much and too little rainfall conditions. The anticipated reductions in future streamflow and sediment could adversely affect ecological streamflow, water security, and sediment dynamics in the Sai Gon Dong Nai River basin. Our approach effectively identifies future changes in streamflow and sediment due to the combined effects of climate change and reservoir operations, providing valuable insights for integrated water resource management in tropical regions. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems are experiencing notable changes due to global change, making it crucial to determine their future responses under different climate scenarios. In previous theories, it has been proposed that resilience, which reflects the ability of ecosystems to withstand disturbances such as drought and wildfires, can serve as an indicator of the ecosystem structure and function. In this study, we applied ecosystem resilience as a metric to assess the state of terrestrial ecosystems. Our analysis revealed a positive trend in vegetation growth across different climate scenarios. Additionally, SSP5-8.5 having the least masked areas exhibits the smallest uncertainties among the considered scenarios. We further examined the theoretical recovery rates based on variance and lag-1 auto-correlation (AC1) to quantify resilience, considering three future periods (near-term, mid-term, and long-term). The theoretical recovery rates decrease from the near-term to the long-term, while larger uncertainties are observed in the long-term compared to the near-term. Notably, equatorial regions experience a significant degradation in resilience, despite the anticipated increase in vegetation growth. Our study highlights the complex dynamics between vegetation growth and ecosystem resilience, disentangling the resilience change of terrestrial ecosystems in the face of global change. [ABSTRACT FROM AUTHOR]

The study presents a simulation of climate change across Northern Eurasia during the 20th and 21st centuries using two different versions of the Earth system model developed by the Marchuk Institute of Numerical Mathematics at the Russian Academy of Sciences (INMCM). Model version INMCM5 participates in Coupled Model Intercomparison Project Phase 6 (CMIP6) and has the lowest equilibrium climate sensitivity (ECS) among the CMIP6 models. In the next model version, INMCM6, changes in the physical parameterisations lead to an increase in ECS by a factor of 2. Changes in near-surface temperature, precipitation, snow cover area and sea ice extent simulated by both model versions are compared with available observational and reanalysis data. Climate change predictions for the middle and end of the twenty-first century are provided by two model versions. Both model versions simulate similar climate changes for the upcoming two decades. After the middle of twenty-first century, the model version with high equilibrium climate sensitivity simulates stronger climate changes over Northern Eurasia than the model version with low sensitivity. But, in general, the ratio of predicted warming is much less than the ratio of ECS. [ABSTRACT FROM AUTHOR]

The Earth System is warming due to anthropogenic greenhouse gas emissions which increases the risk of passing a tipping point in the Earth System, such as a collapse of the Atlantic Meridional Overturning Circulation (AMOC). An AMOC weakening can have large climate impacts which influences the marine and terrestrial carbon cycle and hence atmospheric pCO 2 . However, the sign and mechanism of this response are subject to uncertainty. Here, we use a state-of-the-art Earth System Model, the Community Earth System Model v2 (CESM2), to study the atmospheric pCO 2 response to an AMOC weakening under low (SSP1-2.6) and high (SSP5-8.5) emission scenarios over the years 2015–2100. A freshwater flux anomaly in the North Atlantic strongly weakens the AMOC, and we simulate a weak positive pCO 2 response of 0.45 and 1.3 ppm increase per AMOC decrease in Sv for SSP1-2.6 and SSP5-8.5, respectively. For SSP1-2.6 this response is driven by both the oceanic and terrestrial carbon cycles, whereas in SSP5-8.5 it is solely the ocean that drives the response. However, the spatial patterns of both the climate and carbon cycle response are similar in both emission scenarios over the course of the simulation period (2015–2100), showing that the response pattern is not dependent on cumulative CO 2 emissions up to 2100. Though the global atmospheric pCO 2 response might be small, locally large changes in both the carbon cycle and the climate system occur due to the AMOC weakening, which can have large detrimental effects on ecosystems and society. [ABSTRACT FROM AUTHOR]

Small Caribbean islands are on the frontline of climate change because of sea level rise, extreme rainfall and temperature events, and heavy hurricanes. The Archipelago of San Andrés, Providencia, and Santa Catalina (SAI), are Caribbean islands belonging to Colombia and declared a Biosphere Reserve by UNESCO. SAI is highly vulnerable to climate change impacts but no hydroclimatological study quantified the extreme climatic changes yet. This study analyzes historical (1960s-2020, 7 stations) and future (2071–2100, CMIP6 multi-model ensemble, for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) trends in mean and extreme precipitation and temperature duration, frequency, and intensity. We find that heatwaves have more than tripled in frequency and doubled their maximum duration since the end of the '80 s. Precipitation is historically reduced by 5%, with a reduction recorded in 5 stations and an increase in 2, while extreme rainfall events significantly increased in frequency and intensity in most stations. The hotter-and-drier climate is amplified in the future for all scenarios, with much drier extremes (e.g., -0.5─-17% wet days, +8%─30% consecutive dry days, and +60%─89% in hot days). Although we show that hurricanes Categories IV and V near SAI (< 600 km) more than doubled since the'60 s, only a small fraction of extreme rainfall in the archipelago is associated with hurricanes or tropical storms. La Niña events also have no substantial influence on extreme precipitation. Interestingly, opposite and heterogeneous historical extreme rainfall trends are found across such small territory (< 30 km2). Thus, downscaled hydrometeorological data and model simulations are essential to investigate future extreme climatic events and strengthen small Caribbean islands' climate change adaptation efforts. [ABSTRACT FROM AUTHOR]

The study investigates variabilities and trends in the onset, peak, and retreat of Intertropical Discontinuity (ITD) annual migrations over West Africa between 1979 and 2020, using reanalysis data of the daily mean surface location of ITD of longitudes 15°W to 15°E. The ITD migration peaks are determined from its migration pentad graphs, while its migration onsets and retreats are detected using the ogive. ITD attains peak from August 4 to 28 at latitudes 17°N to 23°N. The percentage cumulative migrations of ITD perfectly exhibit the ogive/sigmoid curve that reflects changes in ITD's migration speed and direction. A new precision method is developed for the determination of the onsets and retreats on the ogive. The ITD periods of onset are between April 26 and May 5 in the west and April 21 and 25 in the east while their corresponding periods of retreats are between October 27 and November 1 and October 18 and 22. The locations of ITD at the onset and retreat periods increase from approximately 11°N and 12°N to 17°N and 20°N in the east and west, respectively. The peak period exhibits the highest variability (5.5–8.6% Coefficient of Variation (CV) and 45–85 days ranges), followed by the onset (4.9–7.2% CV and 20–35 days ranges) and the retreat (1.8–2.9% CV and 20–40 days ranges). However, the latitudinal location of the onset shows the highest variability (9.4–19.7% CV and 8.3–13° latitudinal ranges), followed by the retreat (9.0-15.3% CV and 4.7–11.8° latitudinal ranges) and lastly, the peak (1.6–7.8% CV and 1.4–7.9° latitudinal ranges). There are significant upward trends in the ITD's latitudinal location at the onset, peak and retreat along longitudes 5°E, 0°-15°E, and 10°E, respectively. The trends are attributed to the deepening of the Sahara Heat Low, which in turn is due to its enhanced heating in association with climate change. Direct relationships are observed between the pairs of ITD onset, peak and retreat periods. The ITD migration speed increases from the beginning of the year to the end and displays a gradual advance but rapid retreat. [ABSTRACT FROM AUTHOR]

Extreme precipitation events are frequent under global warming, leading to severe social, economic, and environmental damages. Therefore, a coupled stepwise clustered copula downscaling (SCCD) method is developed to explore the spatial and temporal variability of extreme precipitation in Eastern China under two shared socioeconomic pathways (SSPs). The performance of SCCD in reproducing historical climatology is assessed by comparing its simulated values with the observed data. The result demonstrates that SCCD performs well in modeling climate variables. In addition, the seasonal variations, probability distributions, and absolute changes of nine extreme precipitation indices in the future periods (i.e., 2024—2060 and 2061—2100) are compared with their performance in the historical period (i.e., 1981—2020). The results show that the precipitation in Eastern China shows an increasing trend over time. For example, compared to the historical period, the mean annual precipitation increases by 9.4% and 13.6% for the periods 20424–2060 and 2060–2100 under SSP585, respectively. The spatial variability and age trends suggest that future precipitation extremes also show significant regional differences. By the end of the twenty-first century, both frequencies and intensities of extreme precipitation at high latitudes have changed significantly. Under both SSP scenarios, all nine indices (except Consecutive Dry Days) increase by more than 10% in the future period at the high latitudes, especially for Very heavy precipitation days (R20), where the increase is more than 50% in most areas. In addition, the impacts of different emission scenarios on precipitation in autumn and winter are significantly greater than those in spring and summer. The results can provide a scientific basis for decision-makers to develop mitigation and adaptation policies to minimize the risks caused by climate change. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) exhibit greater potential than global models (GCMs) in capturing geographical details of climate change arising from orography and land–water distribution, but dynamical downscalings are only available for a limited number of GCMs. The full GCM ensembles are much more representative. Furthermore, the current EURO-CORDEX RCM runs most likely underestimate future warming. Thus, neither GCMs nor RCMs as such constitute an ideal tool for preparing reliable spatially detailed climate projections. This study introduces an easy-to-use GCM-RCM hybrid method that takes advantage of the best properties of both model categories. The large-scale response is adopted from GCM simulations, but the pattern is enriched with RCM-simulated details. For temperature projections, the procedure resembles the conventional pattern-scaling technique. However, the spatial averages of temperature change used for scaling are calculated over an area surrounding each grid point, either by giving an equal weight to the entire area or by taking into account the land–sea distribution. For precipitation, a linearised version of the method has been formulated. The method is demonstrated by integrating spatial details from 12 EURO-CORDEX RCM simulations with the CMIP6 multi-GCM mean projection. The resulting temperature responses include RCM-generated spatial details of up to ∼ 1 ∘ C while effectively correcting the general tendency of RCMs to underestimate warming in Europe. For precipitation, geographical details originating from the different CORDEX runs tend to diverge, resulting in a low signal-to-noise ratio. This probably reflects the substantial impact of internal variability on small-scale changes in precipitation. [ABSTRACT FROM AUTHOR]

In this model study, we address the probability of rapid reorganization of thermohaline structure and circulation in the Arctic (AO) and North Atlantic (NA) oceans under the prolonged unidirectional atmospheric forcing over the AO. The relevance of such investigation is dictated by the presence of huge volume of surplus fresh water accumulated in the Beaufort Gyre (BG) of the Canada Basin for the past 30 years due to extremal sea ice melting and increased river runoff. In hypothetical case of rapid release to the NA, this fresh water volume may at least cause strong salinity anomaly similar to the Great Salinity Anomaly in the 1970s. Taking into account that the subpolar NA is the key locus of the deep water formation feeding the southward branch of the Atlantic Meridional Overturning Circulation (AMOC), the excess freshening at the ocean surface may negatively affect the AMOC intensity. To check up the validity of this hypothesis, we carried out the two idealized model experiments with opposite atmospheric forcings over the AO: the so-called "cyclonic" one, which favors intensive NA–AO water exchange, and the "anticyclonic" one, which impedes such an exchange. We chose the two actual years with extremal forcings (1989 as a cyclonic one, and 2004 as an anticyclonic one) and artificially applied them for the 10-year period assuming that such a duration is at the margin of physical realism. Our major finding, within the limitations of numerical experiments on the OGCM (Ocean General Circulation Model) INMOM (Institute of Numerical Mathematics Ocean Model), shows that anomalously long preservation of "cyclonic" forcing over the AO is able to substantially rearrange salinity in the upper ocean layer. However, it may not trigger massive "instant" outflow of freshwater through the Fram and Denmark Straits, since a large portion of accumulated in the BG freshwater spreads around the AO following the surface circulation pattern without reaching the Fram Strait. However, the tendency of the upper ocean layer freshening in the subpolar NA due to freshwater flushing from the AO is confirmed. [ABSTRACT FROM AUTHOR]

The simulation of tropical precipitation has been a challenge to climate models. The multi-model ensemble mean of CMIP6 models only show limited improvement relative to the CMIP3 and CMIP5 models. However, a simple ensemble mean may mask the improvement of individual models. Here we evaluated 20 CMIP6 models and their corresponding earlier version in CMIP5. The results show that the CMIP6 models is significantly improved in the tropical precipitation compared to their counterparts in CMIP5, and the alleviation of bias mainly happened in the top ten model pairs with largest RMSE reduction (TOP10). For the mean of TOP10, the antisymmetric (symmetric) bias mode in CMIP5 is significantly reduced by 55% (78%). Further energetics evaluation shows that, the CMIP5-to-CMIP6 decrease of antisymmetric bias in the bulk of TOP10 models is accompanied by more realistic southward cross-equatorial atmospheric energy transport ( AET EQ ), which is mainly contributed by the better representation of the extra-tropical surface turbulent flux ( STF ). On the other hand, the decrease in the symmetric bias of TOP10 models is associated with the enlargement of the negative bias in the seasonal contrast of AET EQ , which is caused by the alleviation of the biases in the seasonal contrast of extra-tropical STF . Our analysis revealed the improvement in the simulation of tropical precipitation in CMIP6, and we pointed out that the improvement is associated with the model-generational changes in the simulated atmospheric energy balances. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the hydrologic cycle through precipitation and evapotranspiration. The hydrologic intensity is more complex under climate change in high mountainous regions. The spatial and temporal patterns of hydrological intensity were analyzed. The results showed that the degree of annual variations of hydrological intensity increased between 2001 and 2015 compared to 1980 and 2000. The slope of hydrological intensification showed a significant downward trend along the elevation gradient from 1980 to 2000, but no significant elevation-dependent pattern existed from 2001 to 2015. The variation of hydrologic intensity in spring before 2000 and after 2000 was most significant, while the change of hydrologic intensity in summer was not significant. Precipitation, air temperature, net radiation, and vapor pressure deficit (VPD) were significantly correlated with the hydrological intensity before 2000, while only precipitation and air temperature were significantly correlated with hydrological intensity after 2000. The spatial correlation coefficient between hydrological intensity and vertically integrated moisture flux at different altitudes was distributed more homogeneity after 2000. Local meteorological factors and large-scale circulation can influence the elevation-dependent precipitation variation. Under climate change, more attention should be paid to no elevation-dependent changes in hydrological intensity and societal decision-making in mountainous regions. [ABSTRACT FROM AUTHOR]

Global climate change has led to more frequent and intense dry and wet extremes, causing considerable socio-economic losses, but whether these extremes in distant regions are linked and what mechanisms are driving their changes remain unclear. Based on the standardized precipitation-evapotranspiration index and ERA5 reanalysis data, this study reveals a dry-wet teleconnection between southwestern China (SWC) and northeastern China (NEC) from January to April: when SWC was extremely dry, NEC tended to be anomalously wet, and vice versa. Although the seesawing teleconnection is most significant on interannual time scales, it also experienced interdecadal changes, with wet SWC and dry NEC in 1979–1998 and 2019-present and dry SWC and wet NEC in 1999–2018. Further investigations suggest that the pattern of dry SWC and wet NEC is related to anomalous anticyclones (cyclones) over SWC (NEC), which lead to significant changes in surface temperature and total precipitation in the respective regions. The dryness in western (eastern) SWC is mainly influenced by the changes in temperature (precipitation), while the NEC wetness is affected mainly by the changes in temperature. Observational and modeling studies further suggest that the pressure anomalies over SWC and NEC are caused by zonally and meridionally propagating Rossby wave trains, triggered by the North Atlantic Oscillation and the enhanced Indo-Pacific convection, respectively. These wave trains further lead to hydroclimatic extremes in North America, southern Europe, and the Middle East by regulating the atmospheric circulation anomalies over these regions. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) and sea surface air temperature (SSAT) are commonly used as proxies for investigating the impact of climate change on oceans. These variables have been warming since pre-industrial times and are expected to continue to warm in the future under all Shared Socioeconomic Pathways (SSPs). However, they are warming in a spatially heterogeneous way, even with some cooling spots. In this work, we provide a general overview on the regional scaling of SST and SSAT with global warming, based on a 26-member CMIP6 ensemble. We utilize the global warming level (GWL) as a climate change dimension to analyze scaling patterns between sea temperature anomalies and the corresponding GWLs during the 21st century. This analysis is conducted globally, regionally, and on grid-point basis. The results show that SST and SSAT scale linearly with GWL at global scale, with scaling factors β = 0.71 ± 0.001 K/K and β = 0.86 ± 0.001 K/K, respectively. These results are robust, showing only minor differences between seasons, SSPs, and horizontal model resolutions. However, large differences emerge at regional scale, and the scaling of the two temperatures are strongly influenced by sea-ice. The lowest values are obtained for the Southern Ocean region, β = 0.54 ± 0.005 K/K, projecting that the mean SST will increase only half as fast as the global mean temperature. These results provide valuable insight for refining the ocean IPCC reference regions, considering spatial homogeneity in terms of the regional response to global warming. A refinement of six ocean reference regions has been proposed. [ABSTRACT FROM AUTHOR]

Global climate models (GCMs) are essential for studying the climate system and climate change projections. Due to their coarse spatial resolution, downscaling is necessary on the regional scale. Regional climate models (RCMs) represent a standard solution for this issue. Nevertheless, the boundary conditions provided by GCMs unavoidably influence the outputs of RCMs. This study evaluates CMIP6 GCMs regarding the variables relevant to RCM boundary conditions. Particular focus is on the simulation of CNRM-ESM2-1, which is being used as a driving model for convection-permitting ALARO-Climate RCM, used as one source feeding new Czech climate change scenarios. The analysis is conducted over the boundaries and inside the RCM integration domain. Firstly, an evaluation of CFSR and ERA5 reanalyses against radiosondes is performed to choose an appropriate reference dataset for upper air variables. A high correlation between the two studied reanalysis and radiosondes was revealed, and it slightly decreases at the upper tropospheric levels. ERA5 is then chosen as the reference for the boundary analysis. Over the inner region, the simulated mean annual cycle of impact-relevant variables is validated against E-OBS. The CNRM-ESM2-1 performs well regarding near-surface variables over the Czech Republic, but it exhibits larger errors along the boundaries, especially for air temperature and specific humidity. The GCM performance in simulating the upper air atmospheric variables used as RCM boundary conditions relates rather weakly to the GCM performance in simulating the near-surface parameters in the inner region in terms of parameters relevant for impact studies. [ABSTRACT FROM AUTHOR]

The amount of winter precipitation in Japan is increasing only in the Kanto-Koshin region, which includes the Tokyo metropolitan area located on the Pacific Ocean side of Japan. This study investigated long-term historical changes in winter precipitation in Japan using a large ensemble of regional climate simulations that capture the observed increases in precipitation in the Kanto-Koshin region. In addition, self-organizing maps (SOMs) were applied to the atmospheric pressure to explore historical changes in weather pattern (WP) leading to precipitation. The results suggest that long-term changes in precipitation/snowfall could be due to differences in the WP frequency of southern-coastal cyclones and WP-related precipitation due to altered background states during the winter. The former and latter can be interpreted as dynamic and thermodynamic impacts of historical climate change. As for the Kanto-Koshin region, atmospheric circulation analogs revealed that thermodynamic and dynamic effects account for ~ 2/3 and ~ 1/3 of the precipitation changes, respectively, while dynamic effects (increases in south coast cyclone occurrence) dominantly account for snowfall changes. These changes could be attributed to the large-scale historical increases in air temperature and water vapor content. [ABSTRACT FROM AUTHOR]

Under global warming, compound event arises increasing attract as it can lead to a growing impact on water resources management, human society, and ecosystem, especially for the compound heatwave and humidity extremes (CHHE), which can exert harmful influence on human health. However, the understanding of changes in CHHE both in the historical and future, and attribution of global population exposure to CHHE are far from enough. In this study, we selected the wet-bulb temperature (Tw) to define the CHHE, and used the Coupled Model Intercomparison Project Phase 6 (CMIP6) data to investigate future changes in global CHHE. Furthermore, we quantified the relative contributions of population, climate change and their interaction effect to the change in population exposure to CHHE. We found that all scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) show an increasing trend of CHHE. For SSP5-8.5, the global mean Tw will increase by 7 °C, and the northern North America and central Africa experience warming approaching 10 °C by the end of twenty-first century. Under SSP3-7.0 and SSP5-8.5, large equatorial regions will witness Tw exceeding 35 °C resulting in an exposure of 105 million person-days. All the scenarios presented an increase in population exposure to CHHE, which is mainly contributed by climate change (50%-90%) rather than population under different scenarios. We also found that the contribution of population-climate interaction is significantly higher in Africa than in other regions, which mainly due to high population growth rates in the future. Our study provides scientific basis and useful information for the development of adaptation strategies to reduce disaster risks caused by CHHE. [ABSTRACT FROM AUTHOR]

Europe experienced severe heat waves during the last decade, which impacted ecological and societal systems and are likely to increase under projected global warming. A better understanding of pre-industrial warm-season changes is needed to contextualize these recent trends and extremes. Here, we introduce a network of 352 living and relict larch trees (Larix decidua Mill.) from the Matter and Simplon valleys in the Swiss Alps to develop a maximum latewood density (MXD) chronology calibrating at r = 0.8 (p > 0.05, 1901–2017 CE) against May–August temperatures over Western Europe. Machine learning is applied to identify historical wood samples aligning with growth characteristics of sites from elevations above 1900 m asl to extend the modern part of the chronology back to 881 CE. The new Alpine record reveals warmer conditions in the tenth century, followed by an extended cold period during the late Medieval times, a less-pronounced Little Ice Age culminating in the 1810s, and prolonged anthropogenic warming until present. The Samalas eruption likely triggered the coldest reconstructed summer in Western Europe in 1258 CE (-2.32 °C), which is in line with a recently published MXD-based reconstruction from the Spanish Pyrenees. Whereas the new Alpine reconstruction is potentially constrained in the lowest frequency, centennial timescale domain, it overcomes variance biases in existing state-of-the-art reconstructions and sets a new standard in site-control of historical samples and calibration/ verification statistics. [ABSTRACT FROM AUTHOR]

Convective-permitting ensemble simulations are used to understand the roles of thermodynamic and dynamic processes in changing intense storms over the West African Sahel due to increases in atmospheric greenhouse gas concentrations. Ensemble simulations with 16 members represent recent August conditions during the height of the boreal summer monsoon season over the Sahel. They are compared with 5 Future-Warming ensemble simulations with increased greenhouse gas concentrations under the late-21st -century high-emission SSP5-8.5 scenario and initial/boundary conditions from the Current-Climate data plus the multi-model mean anomalies derived from CMIP6 experiments. The Current-Climate simulations reproduce observed precipitation and environmental conditions over the Sahel well. The frequency of heavy rainfall events with 24-hr rainfall > 77 mm (the 99.9th percentile) increases by 38.2% in the Future-Warming simulations. While the low- to mid-level vertical wind shear increases in the Future-Warming simulations, we find no significant correlations between the environmental shear strength and peak storm rain rates. In contrast, lower (middle) tropospheric moisture and temperature are correlated (anticorrelated) with peak rain rates and/or the maximum updraft velocity of intense events, consistent with significant correlations between the increased atmospheric instability and storm intensity. Thus, thermodynamic processes and not dynamical (shear-related) processes dominate the rainfall intensification over the Sahel in the simulations. Nevertheless, the enhanced shear strength is associated with larger rain-shield areas and propagation speeds of intense storms in Future-Warming. Wind shear strength is also correlated with pre-storm atmospheric instability, which grows less/more under strong/weak shear with greenhouse gas increases and is relevant for sub/super Clausius-Clapeyron scaling of precipitation. [ABSTRACT FROM AUTHOR]

In the transitional zone between a monsoon and an arid climate, isotopic composition of precipitation is sensitive to climatic changes. Isotopic compositions of cloud base raindrops (CBR) are directly related to water vapor transport and in-cloud processes, but have been seldom studied. In this study, we examined precipitation-event samples from a ten-year period in Taiyuan, a climatic transition region, and developed a simple method to determine the isotopic composition of CBR. We analyzed and compared the relationship between the isotopic composition of meteoric water and various climatic factors and processes. Results indicate that the alteration of moisture sources plays a crucial role in determining the intra-annual isotopic pattern of precipitation and CBR. During the humid summer monsoon periods, the rainfall amount effect dominates the isotopic variation of precipitation, while the temperature effect controls the isotopic variation under the impact of the winter continental air mass. The isotopic effects are specific to precipitation originating from the same moisture source. The below-cloud evaporation (BCEV) is particularly strong in autumn and causes a great difference in d-excess between precipitation and CBR, which limits applications of d-excess of precipitation as an indicator of hydrometeorological and hydroclimatic processes. The d-excess of CBR can more effectively characterize the oceanic sources of water vapor than that of precipitation. In addition, the fraction of recycled moisture derived from d-excess of precipitation could be underestimated compared to the estimates based on d-excess of CBR. The BCEV process can be divided into an initial moderate evaporation stage and a subsequent deep evaporation stage. We report for the first time that the rates of change for δ18O, δD and d-excess of falling raindrops are significantly accelerated during the deep evaporation stage. [ABSTRACT FROM AUTHOR]

Modeling studies which abruptly increase atmospheric CO2 concentration evidence a rapid reduction or collapse of the Atlantic Meridional Overturning Circulation (AMOC) from its present state of strong overturning circulation into one characterized by a nearly absent deep ocean overturning in the Atlantic and a reduced northward heat transport. Similar transitions are frequently discussed in the context of both present and past global climate changes. Far less discussed, however, is the eventual recovery of the circulation and the establishment of a new equilibrium state, which may occur, or not, many millennia following the initial collapse. Here, we use the Community Earth System Model (CESM1) and a range of abrupt CO2 forcing scenarios (0.5xCO2, and 2xCO2 up to 16xCO2) to evaluate the timescales, and the factors influencing these timescales, in the AMOC's slow evolution to equilibrium. This takes ~ 2000 years for 2xCO2, but over 10,000 years for 8xCO2 in the model. We focus on the interplay between upper- and deep-ocean temperature and salinity, and Arctic sea ice, to diagnose the mechanisms of AMOC recovery and its transition towards equilibrium. We show that the freshening of the Arctic and Subpolar region can delay or possibly halt AMOC recovery. Critically, even after radiative balance is reached at the top of the atmosphere, ocean temperature and salinity keep evolving for thousands of years, affecting the AMOC. These results highlight the long timescales needed for ocean adjustment to radiative forcing, and also shed light on AMOC characteristics in past climates with atmospheric CO2 concentrations markedly different from the present day. [ABSTRACT FROM AUTHOR]