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Quantifying the extent of change in climatic and hydrological variables in the past and the future is essential for climate change-resilient development, especially in the climate change sensitive region of Nepal. This paper analyzed future climatic trends and extremes, historical hydrological extremes and their linkage with historical precipitation extremes, and discussed the impacts of climate change on various sectors in the less-studied Small and Medium-sized Eastern River Basins (SMERB) of Nepal. Applying an ensemble of five Coupled Model Intercomparison Project phase 6 (CMIP6) global climate models (GCMs), we evaluated 10 precipitation and 13 temperature extreme indices using Climpact2 for the historical (1979–2020), near-future (2021–2045), mid-future (2046–2070) and far-future (2071–2100) under two Shared Socioeconomic Pathway (SSP), SSP245 and SSP585. Hydrological extreme indices were assessed using Indicators of Hydrologic Alteration tool. Projected climate revealed significant increase (9–73%) in annual and seasonal rainfall except winter; frequent intense rainfall extremes but prolonged dry spells; significant increasing minimum and maximum temperature trends (0.4–5 °C); rise in extreme heat events; increasing minimum and maximum discharge extreme trends in most hydrological stations; as well as strong association between maximum 1 day precipitation (Rx1day) and 1 day max flow for all stations. Growing dry periods but intense rainfall in few wet days, coupled with warming pattern all-over SMERB with frequent extreme events indicate high risk for future climate-related disasters. The harsher climate will potentially have damaging implications, especially in climate-induced disasters, food security, and water and sanitation infrastructure. [ABSTRACT FROM AUTHOR]

Changing climate has altered the trends and variability of precipitation and temperature globally and thereby increasing the risk of natural and social disasters, especially in coastal climatic transitional zones such as the Huaihe river basin (HRB). This paper applies the Empirical Quantile Mapping (EQM) method for bias correction and systematically evaluates the performance of the 30 Global climate models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating precipitation and temperature over the Huaihe river basin (HRB) for 1979–2014. A suitable multi-model ensemble subset (BMME) is selected based on the Euclidean Distance (ED) synthetic metric. Results show that in comparison to the baseline period 1995–2014, precipitation (temperature) over HRB is projected to increase at the rate of around 15 mm/decade (0.1 °C/decade), 16 mm/decade (0.3 °C/decade), 20 mm/decade (0.5 °C/decade), and 15 mm/decade (0.6 °C/decade) for the period 2015–2100, under Shared Socioeconomic Pathways SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. In the long-term (2081–2100), the annual precipitation is projected to increase by 32%, 27%, 35%, and 26%, under the four scenarios, respectively. The temperature is projected to remain stable or slightly decrease under SSP1-2.6 (2 °C) and SSP2-4.5 (3 °C), while will keep rising and increasing by 6 °C under SSP5-8.5 and by 4 °C under SSP3-7.0 by 2100. The isotherm and isohyet are projected to shift northwest from southeastern coastal China to inland in the future, which is likely associated with the northwestward shift of the western Pacific anticyclone in summer. [ABSTRACT FROM AUTHOR]

Tropical cyclones have resulted in casualties and economic losses in the areas surrounding the Bay of Bengal (BoB). Thus, a comprehensive investigation of these tropical cyclones holds vital implications for disaster preparedness and mitigation. This paper compares the occurrence of storms in the last two decades, i.e., 2002–2011 and 2012–2021, and results reveal that such storms exhibited predominantly a northwesterly track towards the northwestern BoB, with a severer intensity but equal total storm frequencies. Over the past decade, a southeast-northwest pathway (SNP) was identified, demonstrating a higher incidence of severe tropical cyclones (STC, with lifetime maximum intensity ≥ 64 knots) over the BoB. Further analysis of the changes in the environmental conditions between these two decades indicates that a southeasterly anomaly in the steering flow contributed to the formation of the SNP. During the same period, the more favorable oceanic conditions during the last decade, including higher sea surface temperatures, a greater upper ocean heat content, a thicker warm water layer, and a thicker barrier layer beneath the SNP, favored the development of these storms by providing more heat energy to the storms. The atmospheric conditions, including increased air-sea heat fluxes, moisture, and instability within the lower troposphere, as well as reduced vertical wind shear, facilitated the development of convection within these storm systems. These favorable conditions improved the potential for storm development into STCs and elevated the risk of the northwestern BoB being impacted by more destructive storms. [ABSTRACT FROM AUTHOR]

This paper presents results from high-resolution climate change simulations that permit convection and resolve mesoscale orography at 3-km grid spacing over Fenno-Scandinavia using the HARMONIE-Climate (HCLIM) model. Two global climate models (GCMs) have been dynamically down-scaled for the RCP4.5 and RCP8.5 emission scenarios and for both near and far future periods in the 21st century. The warmer and moister climate conditions simulated in the GCMs lead to changes in precipitation characteristics. Higher precipitation amounts are simulated in fall, winter and spring, while in summer, precipitation increases in northern Fenno-Scandinavia and decreases in the southern parts of the domain. Both daily and sub-daily intense precipitation over Fenno-Scandinavia become more frequent at the expense of low-intensity events, with most pronounced shifts in summer. In the Scandinavian mountains, pronounced changes occur in the snow climate with a shift in precipitation falling as snow to rain, reduced snow cover and less days with a significant snow depth. HCLIM at 3-km grid spacing exhibits systematically different change responses in several aspects, e.g. a smaller shift from snow to rain in the western part of the Scandinavian mountains and a more consistent decrease in the urban heat island effect by the end of the 21st century. Most importantly, the high-resolution HCLIM shows a significantly stronger increase in summer hourly precipitation extremes compared to HCLIM at the intermediate 12-km grid spacing. In addition, an analysis of the statistical significance of precipitation changes indicates that simulated time periods of at least a couple of decades is recommended to achieve statistically robust results, a matter of important concern when running such high-resolution climate model experiments. The results presented here emphasizes the importance of using "convection-permitting" models to produce reliable climate change information over the Fenno-Scandinavian region. [ABSTRACT FROM AUTHOR]

Research into weather circulation changes over the UK for future climate has mainly focused on changes in the Summer and Winter seasons, with less analysis on seasonality and the transition seasons. Using the 30 Met Office weather patterns we examine the influence of climate change on seasonality through atmospheric circulation using a number of climate models. Changes in seasonality are important as they can have large impacts on many sectors including agriculture, energy and tourism. This paper finds a noticeable increase in Autumn over the UK in the frequency of drier summer-type regimes and a decrease in stormy winter types that emerge as early as the 2020s. The change in circulation signal once isolated from the overall signal is responsible for a 4–12% decrease in Autumn mean rainfall on average for England by the end of this century (where the values in the range are dependent on the emissions scenario). This change is projected over English regions that are already experiencing water stress, and with predictions of drier summers over the UK in future, this could further increase drought risk. The change in circulation in Autumn also moderates the large increase in the number of large-scale extreme daily rainfall events over the same regions predicted due to climate change. While this future circulation change is replicated across all the climate models used, large differences remain in the strength of the signal between models. The climate models used replicate the frequency of the 30 weather patterns well for all seasons. [ABSTRACT FROM AUTHOR]

Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we use output from global climate models in a perfect-data sense to develop a framework for conducting regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is lower than in other regions. Our unified approach can simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. Model output is used to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day), which ensures our D&A is insensitive to structural uncertainty. Our framework is developed using synthetic data in a Pearl-causal perspective wherein causality can be identified using intervention-based simulations. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming. [ABSTRACT FROM AUTHOR]

Projections of West African Monsoon (WAM) precipitation are uncertain. To address this, an improved understanding of the mechanisms driving WAM precipitation change is needed to shed light on inter-model differences and aid model development. The full forcing of increased CO2 can be decomposed into different components such as the impact of ocean warming, or the direct radiative effect of increased CO2. This paper investigates such a decomposition, analysing the effect of a uniform 4K ocean warming whilst keeping atmospheric CO2 concentrations constant. The analysis highlights several mechanisms acting to decrease WAM precipitation over a range of timescales, from days after the abrupt ocean warming, to the long-term equilibrium response. The initial decrease in WAM precipitation is caused by warming and enhanced convection over the ocean, stabilising the atmosphere inland and disrupting the monsoon inflow at low levels. Later in the response (after about 5 days), the WAM precipitation is reduced through a strengthening of the shallow circulation over West Africa, associated with changes in the large-scale temperature gradients and a local warming of the atmosphere related to a soil moisture feedback mechanism over the Sahel. Finally, from around 20 days after the SST increase, the WAM precipitation is also reduced through changes in specific humidity gradients that lead to increased potency of dry air advection into the monsoon rainband. The analysis concludes by demonstrating that the processes affecting precipitation in the early stages of the response are also relevant to the long-term equilibrium response. [ABSTRACT FROM AUTHOR]

Regional climate projections indicate that European summer precipitation may change considerably in the future. Southern Europe can expect substantial drying while Northern Europe could actually become wetter. Model spread and internal variability in these projections are large, however, and unravelling the processes that underlie the changes is essential to get more confidence in these projections. Large-scale circulation change is one of the contributors to model spread. In this paper we quantify the role of future large-scale circulation changes to summer precipitation change, using a 16-member single-model ensemble obtained with the regional climate model RACMO2, forced by the global climate model EC-Earth2.3 and the RCP8.5 emission scenario. Using the method of circulation analogues three contributions to the future precipitation change are distinguished. The first is the precipitation change occurring without circulation change (referred to as the thermodynamic term). This contribution is characterised by a marked drying-to-wetting gradient as one moves north from the Mediterranean. The second contribution measures the effects of changes in the mean circulation. It has a very different spatial pattern and is closely related to the development of a region of high pressure (attaining its maximum west of Ireland) and the associated anti-cyclonic circulation response. For a large area east of Ireland including parts of western Europe, it is the major contributor to the overall drying signal, locally explaining more than 90% of the ensemble-mean change. In regions where the patterns overlap, the signal-to-noise ratio of the total change is either enhanced or reduced depending on their relative signs. Although the second term is expected to be particularly model dependent, the high-pressure region west of Ireland also appears in CMIP5 and CMIP6 ensemble-mean projections. The third contribution records the effects of changes in the circulation variability. This term has the smallest net contribution, but a relatively large uncertainty. The analogues are very good in partitioning the ensemble-mean precipitation change, but describe only up to 40% of the ensemble-spread. This demonstrates that other precipitation-drivers (SST, spring soil moisture etc.) will generally strongly influence trends in single climate realisations. This also re-emphasises the need for large ensembles or using alternative methods like the Pseudo Global Warming approach where signal to noise ratios are higher. Nevertheless, identifying the change mechanisms helps to understand the future uncertainties and differences between models. [ABSTRACT FROM AUTHOR]

For those involved in planning for regional and local scale changes in future climate, there is a requirement for climate information to be available in a context more usually associated with meteorological timescales. Here we combine a tool used in numerical weather prediction, the 30 weather patterns produced by the Met Office, which are already applied operationally to numerical weather prediction models, to assess changes in the UK Climate Projections (UKCP) Global ensemble. Through assessing projected changes in the frequency of the weather patterns at the end of the 21st Century, we determine that future changes in large-scale circulation tend towards an increase in winter of weather patterns associated with cyclonic and westerly wind conditions at the expense of more anticyclonic, settled/blocked weather patterns. In summer, the results indicate a shift towards an increase in dry settled weather types with a corresponding reduction in the wet and windy weather types. Climatologically this suggests a shift towards warmer, wetter winters and warmer, drier summers; which is consistent with the headline findings from the UK Climate Projections 2018. This paper represents the first evaluation of weather patterns analysis within UKCP Global. It provides a detailed assessment of the changes in these weather patterns through the 21st Century and how uncertainty in emissions, structural and perturbed parameters affects these results. We show that the use of these weather patterns in tandem with the UKCP projections is useful for future work investigating changes in a range of weather-related climate features such as extreme precipitation. [ABSTRACT FROM AUTHOR]

Analysis of wind generated waves due to the prevailing climate change induced by global warming is vital for benefit to the coastal community. In the present paper, the hindcasting of decadal variation namely (i) 1979–1992, (ii) 1993–2006, and (iii) 2007–2019 of wind-wave climate over seasonal and annual scale through 41 years starting from 1979 is carried out using ERA5 reanalysis wind-forcing with a daily temporal and 0.5° × 0.5° spatial resolution. The numerical simulations are executed over the computational domains (i) Global—Indian Ocean and (ii) Regional—south Gujarat to north Goa for evaluating the variability analysis of annual and seasonal mean significant wave heights. The evaluation framework is validated over three in-situ measurement locations with good correlation as compared to the simulated results. The results indicate that at this site the wind and wave activity is noted to increase during transition from 1979–1992 to 1993–2006, then a declination of mean significant wave height is noted during the span 2007–2019. Further, along with the spatial variation estimation, 27 locations along 15 m bathymetric contour at 25 km interval are selected for trend line study. All the 27 locations exhibits a similar kind of trend by variation of decreasing trend from 1979–2019 with variations 0.07–0.22 cm/year. This study highlights the significance in simulating the prevailing wind-wave changes at a regional level considering the impact of the climatology and seasonality changes for effective coastal management, environmental impact assessments and sustainable development. [ABSTRACT FROM AUTHOR]

In a recent paper, Baño-Medina et al. (Configuration and Intercomparison of deep learning neural models for statistical downscaling. preprint, 2019) assessed the suitability of deep convolutional neural networks (CNNs) for downscaling of temperature and precipitation over Europe using large-scale 'perfect' reanalysis predictors. They compared the results provided by CNNs with those obtained from a set of standard methods which have been traditionally used for downscaling purposes (linear and generalized linear models), concluding that CNNs are well suited for continental-wide applications. That analysis is extended here by assessing the suitability of CNNs for downscaling future climate change projections using Global Climate Model (GCM) outputs as predictors. This is particularly relevant for this type of "black-box" models, whose results cannot be easily explained based on physical reasons and could potentially lead to implausible downscaled projections due to uncontrolled extrapolation artifacts. Based on this premise, we analyze in this work the two key assumptions that are made in perfect prognosis downscaling: (1) the predictors chosen to build the statistical model should be well reproduced by GCMs and (2) the statistical model should be able to reliably extrapolate out of sample (climate change) conditions. As a first step to test the suitability of these models, the latter assumption is assessed here by analyzing how the CNNs affect the raw GCM climate change signal (defined as the difference, or delta, between future and historical climate). Our results show that, as compared to well-established generalized linear models (GLMs), CNNs yield smaller departures from the raw GCM outputs for the end of century, resulting in more plausible downscaling results for climate change applications. Moreover, as a consequence of the automatic treatment of spatial features, CNNs are also found to provide more spatially homogeneous downscaled patterns than GLMs. [ABSTRACT FROM AUTHOR]

10.1007/s00382-020-0539-w 21 Jacob D, Elizalde A, Haensler A, Hagemann S, Kumar P. Assessing the transferability of the regional climate model REMO to different coordinated regional climate downscaling experiment (CORDEX) regions. All these issue are currently under discussion within the CORDEX community, so that the CORDEX-CORE initiative can remain a central resource for the climate modeling and climate service communities. The CORDEX-CORE EXP-I dataset is indeed intended to be a community resource for the study of regional climate phenomena in a climate change context and for application to vulnerability-impacts-adaptation (VIA) assessment studies and climate service activities. The Coordinated Regional Downscaling Experiment (CORDEX, Giorgi et al. [15]; Jones et al. [24]) is the main reference program for the climate downscaling community. [Extracted from the article]

Regional Climate Models (RCMs) provide climate information required for evaluating vulnerability, impacts, and adaptation at finer scales than their global driving models. As they explicitly resolve the basic conservation and state equations, they solve physics with more detail, conserving teleconnection of larger scales provided by Global Climate Models (GCMs). In South America (SA), the regional simulations have been historically evaluated principally on climatological aspects, but the representativeness of extremes still needs a more profound assessment. This study aims to analyze three RCMs (RegCM4-7, REMO2015, and Eta) driven by different GCMs in SA, focusing on their capacity to reproduce extreme historical indices of daily precipitation and temperature. The indices of maximum consecutive 5 days precipitation (Rx5day), Consecutive Dry Days (CDD), daily maximum and minimum annual temperature (TXx and TNn, respectively) were evaluated regarding the historical spatio-temporal variability and trends. Furthermore, their projections for the 2071–2099 period, under the Representative Concentration Pathway 8.5 scenario, were analyzed. The historical behavior of RCMs (1981–2005) was compared with two gridded products: Climate Prediction Center (CPC) and agrometeorological indicators derived from the fifth generation of global reanalysis produced by the ECMWF (AgERA5), previously compared with records from meteorological stations to evaluate them. The results show that the highest differences within the gridded products and stations were observed in the regions with more scarce surface stations (North and West of SA) and with complex topography (The Andes Cordillera), being more pronounced in the precipitation-based indices. We found that RCMs generally show more agreement in the spatial variability than in the inter-annual variability for all the indices and SA regions. When analyzing the observed trends, all models better reproduced the long-term variability of extreme temperature indices than those of rainfall. More disagreement was observed for Rx5day and CDD indices trends, including substantial spatial heterogeneities in both magnitude and sign of tendency. Climate change projections exhibited significant agreement to warmer conditions in TXx and TNn, but precipitation signals differed between RCMs and the driving GCM within each regional model. Maximum dry spells are expected to increase in almost all SA regions, whereas the climate change signals in extreme precipitation events are more consistent over southeastern SA (northern and southwestern SA), with positive (negative) changes by the end of the century. [ABSTRACT FROM AUTHOR]

In the context of ongoing global warming, understanding the East Asian Summer Monsoon (EASM) dynamics is of great significance for predicting future climate changes. This study reconstructed the mid-Holocene precipitation variations on the basis of pollen data obtained from Taojiacun section in the Luoyang Basin within the Central Plains of China. Our research results show that the region experienced three dry intervals during the data-covering period (~ 8.08 to ~ 4.76 cal. kyr BP): ~8.08 to ~ 7.35, ~ 6.42 to ~ 5.59, and ~ 4.94 to ~ 4.76 cal. kyr BP. The intervened were two wet intervals: ~7.35 to ~ 6.42 and ~ 5.59 to ~ 4.94 cal. kyr BP. The chronological correspondence between drier (wetter) intervals in the Luoyang Basin and warmer (cooler) intervals in the western Tropical Pacific implies that the north-south shifts of the Western Pacific Subtropical High (WPSH), driven by the western Tropical Pacific Sea Surface Temperature (SST), regulated the positions of the EASM-related rain-belt during the data-covering period. We compared the mean annual precipitation (Pann) sequence from Taojiacun section with those from the southern and northern neighboring areas. With a full consideration of chronological uncertainties and sampling resolution differences, it can be generalized that those drier (wetter) intervals in the Luoyang Basin within the Central Plains of China were broadly correspondent with those drier (wetter) intervals expressed in the sequences of the southern neighboring areas (i.e., the middle and lower reaches of the Yangtze River with an addition of the Huai River Basin). It means that the changes in precipitation in the Central Plains was most likely coincident with that in the southern neighboring areas during the data-covering period (~ 8.08 to ~ 4.76 cal. kyr BP). [ABSTRACT FROM AUTHOR]

The Three-River Headwater Region (TRHR) has undergone significant hydrological changes and affects the water resources security in the local and downstream areas. We use multiple observational precipitation product, as well as the ERA5 reanalysis dataset to investigate the precipitation variations over the TRHR during the rainy season from 1990 to 2020, and to analyze the contributions of local evaporation and remote water vapor transport to the precipitation and its variations. The precipitation shows a significant increasing trend (17.8 mm decade−1). The precipitation variability (PV) is larger at daily scale and smaller at interannual scale. The spatial distribution of PV varies on different timescales, which reflects the different dominant regimes driving the moisture transport. The mean precipitation in the TRHR is predominantly contributed by western and southern moisture influxes, and the increasing trend of these influxes (10.8 kg s−1 decade−1) determines the precipitation increase. Local evaporation provide about 6% of water vapor for the precipitation, while it has little influence on the precipitation change. The anomalous precipitation in wet and dry years is mainly controlled by the atmospheric circulation over the Tibetan Plateau, which regulates the southwestern moisture transport towards the TRHR. Additionally, the precipitation during 1990–2020 increases by about 3.9% compared to that during 1960–1989. It is related to the higher conversion ratio of water vapor influxes to precipitation and larger evaporation over the TRHR. These findings improve our understanding of the precipitation variations in the TRHR and provide insights for policy makers to optimize water resources management to cope with the global climate change. [ABSTRACT FROM AUTHOR]

In this study, using the NCAR Community Earth System Model (CESM1.2.2), we investigate the changes in the characteristics of the summer monsoon low pressure systems (LPS) over India in a twenty-first century climate change simulation corresponding to the RCP8.5 scenario. A slight weakening in monsoon circulation and an increase in mean summer monsoon precipitation over India are simulated in a warmer climate, consistent with several previous studies. The weakening of the monsoon circulation is associated with a pair of anticyclonic anomalies straddling the equator in the low level, weakening the cross-equatorial monsoonal flow from the southern hemisphere. These low-level circulation anomalies appear to be robust features in the equatorial Indian Ocean under climate change. An increase in moisture flux is also simulated over the Indian subcontinent. However, we find no significant change in the number of LPS or their spatial distribution under the RCP8.5 scenario. This is attributed to a small but non-significant decrease in the low-level meridional cyclonic shear in zonal winds. An increase in the intensity and frequency of extreme precipitation over India in a warmer world is simulated and is likely associated with an increase in moisture content. Our study shows that the fractional contribution of LPS to mean and extreme precipitation over India in a warmer world is likely unchanged, but the frequency and intensity of extreme events are larger. Because of the diversity in the results from single model studies on LPS characteristics in a warmer world, a future study that uses CMIP6 multi-model data would be valuable to assess the robustness and the uncertainty in changes in LPS activities under climate change. [ABSTRACT FROM AUTHOR]

We study inter-model spreads of the climatological annual mean Hadley circulation (HC), using 37 models from Coupled Model Intercomparison Project phase 6 (CMIP6) Atmospheric Model Intercomparison Project (AMIP). Our results show significant inter-model spreads of the climatological annual mean HC although the models are driven with identical sea surface temperatures (SSTs). Two leading modes of inter-model HC spreads are identified, using the method of inter-model empirical orthogonal function (EOF) decomposition. The EOF1 mode exhibits an equatorial symmetric dipole pattern, explains 40.5% of the total inter-model variance of mean meridional mass streamfunction (MMS), and reflects inter-model spreads of the HC strength and latitudinal locations of the ascending branch in AMIP simulations. The EOF2 mode explains 23.1% of the MMS variance, and mainly reflects inter-model spreads of latitudinal locations of the ascending branch and poleward edges of the Hadley cells. Regression of tropical precipitation on PC1 and PC2 shows that both two leading modes are closely related to model performance in simulating tropical convective precipitation. It suggests that inter-model spreads of the HC are due to different cloud-convection parameterization schemes among the AMIP models. Models that simulate heavier tropical convective precipitation generate concentrated equatorial convective heating and stronger, but narrower, Hadley cells, and the associated ascending branch is located more southward. Models that simulate stronger tropical convective precipitation in the south of the equator exhibit southward biases of the latitudinal position of the ascending branch and a narrower Northern-Hemispheric cell. This study indicates that improvements of cloud-convection parameterizations are of critical importance in simulating the HC. [ABSTRACT FROM AUTHOR]

European heatwaves at the 0.5, 1.0, 1.5 and 2.0 ∘ C global warming levels above the pre-industrial temperature are examined using bias-corrected daily-mean temperature data from 60 simulations performed with 25 global climate models (GCMs). A heatwave event is defined here to consist of at least three consecutive days above the 90th percentile of summer daily-mean temperatures and a break of 1 day is allowed. At the 2.0 ∘ C global warming level compared with 0.5 ∘ C, the multi-GCM mean annual count of heatwave days is projected to be three to fourfold in northern and more than sixfold in southern Europe. The total annual heatwave extremity index, or the sum of exceedings above the threshold temperature over all the heatwave days, becomes approximatively fourfold in the north and tenfold in the south. In central Europe, the date of the strongest heatwave of year is delayed by about 1 week. By concatenating the bias-corrected output data of all the GCM runs, 1200-year samples were created from which probabilities of occurrence of the strongest heatwaves can be determined very robustly under all four warming levels. An intense heatwave occurring once in 10 years at the 0.5 ∘ C warming level has an annual probability of about 50% in northern and 80–90% in southern Europe under 2.0 ∘ C. Corresponding probabilities for 100-year heatwaves would be nearly 20% in the north and about 60% in the south. Finally, we discuss factors that explain the stronger increase in heatwave duration and extremity in the south than north. [ABSTRACT FROM AUTHOR]

It is essential to identify water sectors that will be significantly impacted by climate change and to develop strategies to enhance the resiliency of these sectors against climate change impacts. The Arabian Peninsula (AP) is an arid region facing increasingly more severe water-scarcity issues due to climate change impacts. We investigate abrupt changes in the AP's climate, and examined the spatial relationships between climatic changes, ENSO, and Indian Ocean Dipole (IOD). An analysis was conducted to examine how hydroclimatic changes impact the frequency of droughts in AP. The results show that AP is very sensitive to climate change impacts since 1990s. Regional climatic change hotspots in AP include an increase in geopotential height (GPH), surface temperature, potential evapotranspiration (PET), and a decrease in relative humidity, soil moisture, and rainfall between 1985 and 2020. The northern and northwestern areas of AP, specifically Hail, Al Qassim, Tabuk, and Al Jouf, experienced the most significant increases in GPH, warming, and PET. The meridional wind (zonal wind) speed has decreased (increased) between 1985 and 2020. Climate scenarios of CMIP6 of IPCC (Intergovernmental Panel of Climate Change) project future warmer and drier conditions over AP under significant warming and marginal increase in rainfall between 2020 and 2100. Furthermore, positive ENSO and IOD episodes are associated with negative rainfall and surface moisture anomalies, and positive surface temperature and PET anomalies over irrigated areas of AP. Climate warming in AP has also resulted in persistent drought conditions after 1998, which have significantly affected the agricultural sector of AP due to higher water demand for irrigated crops because of higher evaporation losses under climate warming. Therefore, representative estimations of regional water demand for irrigation in AP are essential in developing effective adaptation strategies against climate change impacts, such as introducing crop patterns of lower transpiration losses to achieve water saving and providing optimal irrigation water requirements for AP of arid climate. In conclusion, regions with limited water resources, such as the AP, will likely experience more significant water scarcity and drought. Therefore, identifying the water sectors most impacted by climate change and developing strategies to enhance their resiliency is essential. [ABSTRACT FROM AUTHOR]

The Sierra Nevada and Southern Cascades—California's snowy mountains—are primary freshwater sources and natural reservoirs for the states of California and Nevada. These mountains receive precipitation overwhelmingly from wintertime storms including atmospheric rivers (ARs), much of it falling as snow at the higher elevations. Using a seven-decade record of daily observed temperature and precipitation as well as a snow reanalysis and downscaled climate projections, we documented historical and future changes in snow accumulation and snowlines. In four key subregions of California's snowy mountains, we quantified the progressing contribution of ARs and non-AR storms to the evolving and projected snow accumulation and snowlines (elevation of the snow-to-rain transition), exploring their climatology, variability and trends. Historically, snow makes up roughly a third of the precipitation affecting California's mountains. While ARs make up only a quarter of all precipitating days and, due to their relative warmth, produce snowlines higher than do other storms, they contribute over 40% of the total seasonal snow. Under projected unabated warming, snow accumulation would decline to less than half of historical by the late twenty-first century, with the greatest snow loss at mid elevations (from 1500 to 3300 m by the mountain sub-regions) during fall and spring. Central and Southern Sierra Nevada peaks above 3400 m might see occasionally extreme snow accumulations in January–February resulting entirely from wetter ARs. AR-related snowlines are projected to increase by more than 700 m, compared to about 500 m for other storms. We discuss likely impacts of the changing climate for water resources as well as for winter recreation. [ABSTRACT FROM AUTHOR]

The response of lightning to a changing climate is not fully understood. Historic trends of proxies known for fostering convective environments suggest an increase of lightning over large parts of Europe. Since lightning results from the interaction of processes on many scales, as many of these processes as possible must be considered for a comprehensive answer. Recent achievements of decade-long seamless lightning measurements and hourly reanalyses of atmospheric conditions including cloud micro-physics combined with flexible regression techniques have made a reliable reconstruction of cloud-to-ground lightning down to its seasonally varying diurnal cycle feasible. The European Eastern Alps and their surroundings are chosen as reconstruction region since this domain includes a large variety of land-cover, topographical and atmospheric circulation conditions. The most intense changes over the four decades from 1980 to 2019 occurred over the high Alps where lightning activity doubled in the 2010 s compared to the 1980 s. There, the lightning season reaches a higher maximum and starts one month earlier. Diurnally, the peak is up to 50% stronger with more lightning strikes in the afternoon and evening hours. Signals along the southern and northern alpine rim are similar but weaker whereas the flatlands surrounding the Alps have no significant trend. [ABSTRACT FROM AUTHOR]

Assessing the regional responses to different Global Warming Levels (GWLs; e.g. + 1.5, 2, 3 and 4 ºC) is one of the most important challenges in climate change sciences since the Paris Agreement goal of keeping global temperature increase well below 2 °C with respect to the pre-industrial period. Regional responses to global warming were typically analyzed using global projections from Global Climate Models (GCMs) and, more recently, using higher resolution Regional Climate Models (RCMs) over limited regions. For instance, the IPCC AR6 WGI Atlas provides results of the regional response to different GWLs for several climate variables from both GCMs and RCMs. These results are calculated under the assumption that the regional signal to global warming is consistent between the GCMs and the nested RCMs. In the present study we investigate the above assumption by evaluating the consistency of regional responses to global warming from global (CMIP5) and regional (CORDEX) projections. The dataset aggregated over the new IPCC reference regions, available from the IPCC AR6 WGI Atlas repository, is analyzed here for temperature and precipitation. The existing relationships between the regional climate change signals and global warming are compared for both CMIP5 and CORDEX. Our results show significant linear scaling relationships between regional changes and global warming for most of the regions. CORDEX and CMIP5 show remarkably similar scaling relationships and similar robustness in the emergence of the climate change signal for most of the regions. These results support the use of regional climate models in the context of global warming level studies. [ABSTRACT FROM AUTHOR]

The potential changes in the characteristics and damage potential of three of the most damaging tropical cyclone (TC) events (Haiyan 2013, Bopha 2012, Mangkhut 2018) in the Philippines have been simulated using the pseudo global warming (PGW) technique. Simulations were performed using the Weather Research and Forecasting model at 5 km resolution with cumulus parameterization (5 kmCU) and 3 km without cumulus parameterization (3 kmNoCU), with PGW deltas derived from a selection of the CMIP6 models. We found that re-forecasting the three TCs under future warming leads to more intense TCs, with changes in maximum wind of 4%, 3%, and 14% for the 5 kmCU runs, and 14%, 4%, and 12% for the 3 kmNoCU runs of Typhoon Haiyan, Bopha, and Mangkhut, respectively. The changes in track, translation speed, and size are relatively small. The TC cases have a higher impact potential in the future, as expressed by the cyclone damage potential index, ranging from ~ 1% to up to 37% under the SSP5-8.5 scenario. Based on the pre-industrial runs, climate change has had, so far, only a weak influence on TC intensity and not much influence on track, translation speed, and size. Simulations without convective parameterization show similar changes in the sign of the projected TC intensity response, but different signals of change in translation speed and size. [ABSTRACT FROM AUTHOR]

Clear-air turbulence (CAT) has a large impact on the aviation sector. Our current understanding of how CAT may increase with climate change in future is largely based on simulations from CMIP3 and CMIP5 global climate models (GCMs). However, these models have now been superseded by high-resolution CMIP6 GCMs, which for the first time have grid lengths at which individual turbulence patches may start to be resolved. Here we use a multi-model approach to quantify projected moderate CAT changes over the North Atlantic using CMIP6 models. The influence of the model resolution on CAT projections is analysed. Twenty-one CAT diagnostics are used, in order to represent uncertainties in CAT production mechanisms. Each diagnostic responds differently in time, but the majority display an increase in moderate CAT between 1950 and 2050. Although winter is historically the most turbulent season, there is strong multi-model agreement that autumn and summer will have the greatest overall relative increase in CAT frequency. By 2050, summers are projected to become as turbulent as 1950 winters and autumns. The global-mean seasonal near-surface temperature is used as a comparative metric. For every 1 °C of global near-surface warming, autumn, winter, spring, and summer are projected to have an average of 14%, 9%, 9%, and 14% more moderate CAT, respectively. Our results confirm that the aviation sector should prepare for a more turbulent future. [ABSTRACT FROM AUTHOR]

The El Niño Southern Oscillation (ENSO) has profound impacts on weather patterns across the globe, yet there is no consensus on its response to global warming. Several modelling studies find a stronger ENSO in global warming scenarios, while other studies suggest ENSO weakening. Using a broad range of models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and four types of warming experiments, here we show that the majority of the models predict a stronger ENSO by century-end in Shared Social Pathway (SSP) experiments, and in idealized 1pctCO2 and abrupt 4xCO2 experiments. Several models, however, do predict no change or ENSO weakening, especially in the idealized experiments. Critically, the strongest forcing (abrupt-4xCO2) does not induce the strongest ENSO response, while differences between the models are much greater than those between warming scenarios. For the long-term response (over 1000 years) the models disagree even on the sign of change. Furthermore, changes in ENSO sea surface temperature (SST) variability are only modestly correlated with the tropical Pacific mean state change. The highest correlation for ENSO SST amplitude is found with the mean zonal SST gradient in the SSP5-8.5 experiment (R = − 0.58). In contrast, changes in ENSO rainfall variability correlate well with changes in the mean state, as well as with changes in ENSO SST variability. When evaluating the Bjerknes Stability Index for a subset of models, we find that it is not a reliable predictor of ENSO strengthening, as this index tends to predict greater stability with warming. We argue that the enhanced ENSO stability is offset by increases in atmospheric noise or/and potential nonlinear effects. However, a robust inter-model mechanism that can explain a stronger ENSO simulated with global warming is still lacking. Therefore, caution should be exercised when considering ENSO changes based on a single model or warming scenario. [ABSTRACT FROM AUTHOR]

The analysis of seasonal and long-term changes of the Caspian Sea level examined from historical long time tide gauge data in order to consider the influence of climate factors on sea level changes in this lake system using spectral analysis method. The major peak at spectra corresponds to the annual cycle and semiannual oscillations peak is located at next vigorous. Effects of different global and regional factors on lake level changes are investigated by signal processing methods. Results show that annual cycle of Siberian High and Volga River discharge have the considerable effects on the Caspian Sea level changes in global and regional scales, respectively. Analyzing of seasonal cycle revealed that Volga river discharge is significant on sea level fluctuations by 1-month lag in northern and central sub-basins and 2 months delay for southern sub-basin. The results of long-term cycle show ascending trend of evaporation in Caspian central sub-basin, which it is the main driver of decreasing trend of the Caspian Sea level since 1990s. [ABSTRACT FROM AUTHOR]

Being strongly influenced by internal climate variability, the atmospheric circulation response to greenhouse gas forcing in the future climate is uncertain. This study addresses atmospheric circulation through representative circulation types (CTs) and investigates the CTs' changes with respect to frequency and effect on surface temperature and precipitation over a pan-Scandinavian domain. The analysis is based on the Swedish Meteorological and Hydrological Institute Large Ensemble performed with EC-Earth3: 50-member ensembles from one historical and six scenario simulations for the twenty-first century are used to assess internal variability and significance of changes. Although the results show no strong future changes in the CTs' sea level pressure patterns, CT frequency changes suggest a future extension of summer conditions towards spring and autumn and point towards a clearer distinction between summer and winter. The present-climate CT effect on surface temperature is found to generally weaken which is consistent with a general decrease in temperature variability. Largest-scale and strongest temperature effect changes are projected between March and May for CT3, a cyclone towards the east of the domain associated with a domain-wide cooling effect that will likely be decreased towards the end of the twenty-first century. Similarly but of opposite sign, the CT effect on precipitation is strengthening as a result of the increased precipitation variability. Here, largest-scale and strongest effect enhancement is found for CT6, thus increasing its wetting effect over southern Scandinavia and drying effect west of the Scandes. Changes are generally largest towards the end of the twenty-first century and tend to increase with the forcing strength, thus maximizing for SSP585. [ABSTRACT FROM AUTHOR]

This study looks at the evolution of trends in the dynamic sea level (DSL) component of sea-level rise for the North Atlantic (18°–67° N), primarily over the twenty-first century but with some analysis extending to 2300. We use an 18-member climate model ensemble of projections under medium and high greenhouse gas scenarios. We find that the long-term trend pattern (1950–2099) tends to be indicated in the early twenty-first century: 14 (11) of the 18 models have pattern correlations between this period and 1993–2022 of > 0.5 under the medium (high) greenhouse gas scenario. Whether a particular 1993–2022 DSL trend indicates the long-term trend in our ensemble can be assessed from concurrent changes in the Atlantic Meridional Overturning Circulation (AMOC) at 30° N: those cases with larger AMOC weakening trends have high DSL-trend pattern correlations. This suggests that the observed AMOC (or a proxy for that) could indicate whether observed DSL trends are likely to be a constraint on projections, provided suitable AMOC trend indicators can be determined. More generally, North Atlantic DSL and the AMOC show a similar evolution of measures of their successive 30-year trends (with these being projection-onto-a-pattern and the ratio with the long-term trend, respectively), both in the ensemble mean and for individual models. Model-to-model differences in this evolution indicate that the changing DSL and AMOC trends are more interconnected than solely the common influence of external forcings associated with the climate-change scenario. Model simulations extending to 2300 indicate that the twenty-first century trend patterns do not generally persist into subsequent centuries, as has been shown in previous studies. [ABSTRACT FROM AUTHOR]

Climate change is imminent and threatens the largest watershed in the world, the Amazon basin. As general circulation models may fail to represent cloud-scale phenomena, precipitation in a changing climate under global warming is still a factor of great uncertainty, especially in Tropical regions. In this study, we used long-term high-resolution simulations from a global cloud-resolving model under the scope of the Coupled Model Intercomparison Project (CMIP6) to verify the climate change impacts on the mesoscale convective systems (MCSs) over the Amazon basin. We generated a complete spatial, temporal, and statistical characterization of the MCSs for the past (1950–1960), present (2000–2010), and near-future (2040–2050). We found that MCSs are a critical mechanism for precipitation, especially in austral winter. The simulations are consistent with the observed precipitation and MCSs patterns over the Amazon basin, indicating that MCSs are less frequent compared to the past and are expected to continuously decline in the near-future. Most decreases are projected from September to December, while an increase between June to August, mainly in the southern portion of the Amazon basin. In addition, the investigation presented here shows the great potential of using a global cloud-resolving model under the CMIP6 scope to investigate mesoscale systems in a warming climate. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of high-temperature events in response to climate change can potentially impact the aviation industry, since aircraft takeoff and landing performances depend on near-surface air temperature. Previous studies have combined climate data with aircraft technical data to estimate the future impact of rising high temperatures on aircraft takeoff. They found a decrease of maximum takeoff weights and the lengthening of takeoff distances. The Mediterranean region is a climate change "hot spot" area, specially concerned by extreme high-temperatures increase. In this study, the magnitude and trends of the daily maximum near-surface temperature extremes in summer were analysed over major airports in Southwestern Europe. Trends in the period 1961–2014 were analysed from observations and reanalysis. Future changes by 2021–2050 and 2071–2100, with respect to 1961–2005, were analysed from simulations performed with Regional and Global Climate Models (RCMs and GCMs). Before assessing future climate projections, climate models were evaluated in present climate, and the RCM and GCM ensembles were compared to each other. No clear added value was found for RCMs over GCMs in present climate at the airport scale in these terms. GCMs project larger temperature changes than RCMs over the same locations. Multi-model ensemble mean projected changes under the RCP8.5 scenario range between + 1.7 and + 3.2 ∘ C by the near term, and between + 4.9 and + 8.5 ∘ C by the long term, across the airports and the RCM and GCM ensembles. This increase of high-temperature extremes would impact airport operations. Adaptation or mitigation policies would become necessary. [ABSTRACT FROM AUTHOR]

Transitional climate zone (TCZ) over East Asia is located between humid and arid regions, which is a highly sensitive and disaster-prone region especially under global climate change. Due to limited water resources, the atmospheric moisture availability has a dominant control on the precipitation variability. Hence, this study is motivated to reveal the key teleconnection patterns and associated moisture processes that govern the interannual variability of the summer precipitation over TCZ. In order to better diagnose moisture budget, the Lagrangian particle dispersion model FLEXPART is employed for quantifying contribution from moisture sources. Above all, the observational analysis highlights two critical modes, one is Eurasian teleconnection (EU) and the other is Circumglobal Teleconnection (CGT). As regards EU pattern, positive EU phase corresponds to ample precipitation in TCZ. In the presence of positive phase, it underlines a "+-+-" pattern of geopotential height anomalies stretching from western Europe to Mongolia plateau. In the context, the cyclonic flow and low pressure over Mongolia plateau act to enhance moisture flux from the west and the south and to prompt upward motions. Further moisture diagnoses illuminate largest increase of moisture uptake in monsoon dominated region, followed by the westerlies dominated region. However, the eventual contribution of summer monsoon is a little bit less than that of westerlies, due to the grand loss en route. In addition, the local evaporation exerts little impact. CGT propagates along the mid-latitude westerly jet, which is positively coupled with the precipitation in TCZ. Under the positive phase, there is an ascending motion over TCZ, which bears great resemblance to the EU case. However, unlike the result of moisture attribution in EU case, the southerly monsoon has the largest contribution followed by local effect, while the westerlies have little impact due to the cancellation of wetting and drying regimes along the pathway. [ABSTRACT FROM AUTHOR]

Ozone is the third most important greenhouse gas in driving global warming, mainly due to increased tropospheric ozone. About 50% of the growth of global tropospheric ozone since preindustrial time occurred during 1955–2005, with continued growth since then. This study quantifies the relative contributions of ozone changes during 1955–2005 to total observed global and Arctic climate changes by comparing CESM1 historical simulations with all anthropogenic and natural radiative forcings including realistic ozone changes, and with the same forcings except with constant ozone or well-mixed greenhouse gases (WMGHG). Results indicate that ozone changes during 1955–2005 have strongly enhanced the downwelling longwave flux and increased net shortwave flux at the surface, and thus significantly contributed about 0.15 °C of global mean surface warming, roughly 21%, 26% and 16% of the observed, all-forcing and WMGHG-driven trends, respectively. In the Arctic in the same period, corresponding ozone-driven warming was about 0.63 °C, roughly 48%, 40% and 25% of the same three trends. During 1979–2005, these ozone changes have markedly added about 0.25 × 106 km2 to the decrease in the Arctic sea ice extent (SIE), or roughly 25%, 48%, and 40% of the same three trends. Considering that the ozone-driven radiative forcing of about 0.22 (0.06) W·m−2 in 1955–2005 (1979–2005) was about 12% (6%) of the corresponding WMGHG forcing, ozone changes had contributed disproportionately to global and Arctic warming and Arctic sea ice decline during the second half of the twentieth century. Tropospheric ozone has shown relatively steady growth since 2006 and might have significantly contributed recent observed warming over the global and the Arctic. [ABSTRACT FROM AUTHOR]

The interaction of stratospheric chemistry with a changing climate from an abrupt CO2 quadrupling is assessed using the coupled atmosphere–ocean Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM). Two abrupt 4 × CO2 experiments were performed, one with interactive stratospheric chemistry and the other with a prescribed stratospheric chemistry that does not simulate stratospheric ozone response to 4 × CO2. The interactive and prescribed chemistry experiments simulate similar global mean surface temperature change. Nevertheless, interactive chemistry is critical to capture the Southern Hemisphere tropospheric midlatitude jet response to 4 × CO2. When stratospheric ozone response to 4 × CO2 is neglected, GEOSCCM overestimates Southern Hemisphere tropospheric circulation change. This stratospheric chemistry-induced climate impact has large seasonal variability. During the austral spring season September–October–November (SON), prescribed chemistry yields a stronger poleward shift and intensification of the Southern Hemisphere midlatitude tropospheric jet, surface wind stress, and the Southern Ocean meridional overturning circulation than occurs with interactive chemistry. In other seasons interactive and prescribed chemistry have similar effects on the Southern Hemisphere circulation. The seasonality of stratospheric chemistry-induced climate impact is related to the seasonality of Antarctic lower stratospheric ozone response to 4 × CO2. In contrast to this stratospheric ozone response to 4 × CO2, stratospheric ozone recovery from decline of the ozone depleting substances has its largest impact on the Southern Hemisphere tropospheric circulation in austral summer (December–January–February), but no effects in SON. It is found that the different seasonality for these two stratospheric ozone layer change scenarios is related to the different seasonality of tropopause meridional temperature gradient response. [ABSTRACT FROM AUTHOR]

Correct simulation of land surface energy balance is critically important in reliably projecting future climate change. In this study, simulated surface energy fluxes including net radiation, latent heat, and sensible heat from 22 CMIP6 models are evaluated against ERA5 reanalysis data during 1950–2014 over global land surface to assess the performance of CMIP6 models in simulating surface energy balance. Results reveal significant differences in seasonal and regional characteristics of CMIP6 model simulations in the surface energy flux predictions. Net radiation is slightly overestimated in JJA (June, July, August) but underestimated in DJF (December, January, and February). Most models overestimate net radiation in both seasons over Africa, Australia, and Latin America. The inter-model variability of biases is substantial in DJF net radiation simulations over Asia, Europe and Siberia, and North America, although there is a good agreement between simulations of selected models and the ERA5 reanalysis data in JJA except for Greenland. Moreover, models overestimate latent heat and underestimate sensible heat in DJF, although latent heat and sensible heat simulations match well with the reference values in JJA. Latent heat is overestimated in DJF over Australia, Europe and Siberia, and Latin America. Sensible heat is underestimated during DJF over Europe and Siberia and Latin America. The performance of CMIP6 in Rn simulation is better than LH simulation and SH simulation for both JJA and DJF. Findings from this study will provide useful references for surface energy data users and future model development. [ABSTRACT FROM AUTHOR]

In the coming few decades, projected increases in global temperature and humidity are generally expected to exacerbate human exposure to climate extremes (e.g., humid-heat and rainfall extremes). Despite the growing risk of humid-heat stress (measured by wet-bulb temperature), it has received less attention in East Africa, where arid and semi-arid climatic conditions prevail. Moreover, no consensus has yet been reached across models regarding future changes in rainfall over this region. Here, we screen Global Climate Models (GCMs) from CMIP5 and CMIP6 and use, for boundary conditions, simulations from only those GCMs that simulate successfully recent climatic trends. Based on these GCMs and Regional Climate Model (RCM) simulations, we project that annual mean temperature is likely to rise by 2 ℃ toward midcentury (2021–2050) ​at a faster rate than the global average (about 1.5 ℃), under the RCP8.5 and SSP5-8.5 scenarios, associated with more frequent and severe climate extremes. In particular, low-lying regions in East Africa will be vulnerable to severe heat stress, with an extreme wet-bulb temperature approaching or exceeding the US National Weather Service's extreme danger threshold of 31 ℃. On the other hand, population centers in the highlands of Ethiopia will receive significantly more precipitation during the autumn season and will see more extreme rainfall events, with implications for flooding and agriculture. The robustness of these results across all GCM and RCM simulations, and for both of CMIP5 and CMIP6 frameworks (CMIP: Coupled Model Inter-comparison Project) supports the reliability of these future projections. Our simulations of near-term climate change impacts are designed to inform the development of sound adaptation strategies for the region. [ABSTRACT FROM AUTHOR]

The present study investigated future temperature and precipitation changes over Greece using the Weather Research and Forecasting (WRF) model. WRF was driven by EC-EARTH over Greece at very high resolution for the historical period (1980–2004), along with projected simulations, in the near future (2025–2049) and far future (2075–2099) under the Representative Concentration Pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). Climatic variables were produced at 5-km grid spacing and 6-h interval. The historical simulation was evaluated against the available station observations. The analysis showed that the model underestimated the maximum temperatures and slightly overestimated the minimum temperatures. Also, the model simulated a small dry bias in precipitation with an excellent representation of the spatial patterns. The model projections for temperature under the two emission scenarios compared to the historical simulation revealed a robust magnitude of future warming with the most pronounced changes predominantly over the eastern areas of the country under the RCP8.5 in the far future. Projected precipitation changes were more evident in the far future with an overall decrease of the annual precipitation all over the eastern part of the country (with islands included) with the most dramatic reductions (above 40%) of seasonal precipitation observed under RCP8.5. Increases in the number of hot days were found everywhere with more pronounced changes over the plain areas under RCP8.5 in the far future. Significant increases of dry days were projected over the eastern part of the mainland and more intensely under RCP8.5 in the far future. [ABSTRACT FROM AUTHOR]

Understanding the cloud feedback (CFB) process remains a critical challenge for climate projection. While previous studies have mainly focused on the globe, the tropics, or the Southern Ocean, this study analyzes the long-term CFB over East Asia (EA) using data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and radiative kernels newly developed. We find that the overall CFBs over EA act to amplify warming in an annual scale, with mean values of 0.66 ± 0.47 and 0.63 ± 0.39 W m−2 K−1 for the SSP2-4.5 and SSP5-8.5 scenarios, respectively, although remarkable seasonal discrepancies. There are two distinct subregions: the positive center over the East Asian monsoon region, primarily due to the significant reduction in low cloud cover; the negative center over the Tibet Plateau, largely owing to the reduced high cloud cover and the ice-to-liquid conversion of cloud phase. Furthermore, the CFB over EA changes from negative to positive in the early 1980s, and then enhance at a rate faster than the global average until the early years of the twenty-first century, which may be linked with the weakening and subsequent recovery of the East Asian summer monsoon. Generally, inter-kernel uncertainty is markedly smaller than inter-model uncertainty; however, in regional scale, inter-kernel uncertainty is larger and inter-model uncertainty is smaller than those in the global scale. This feature implies that ignoring inter-kernel uncertainty may bring additional errors to regional CFB quantification. Notably, these results are comparable between the SSP2-4.5 and SSP5-8.5 scenarios, suggesting that CFB processes may be insensitive to emission scenarios. [ABSTRACT FROM AUTHOR]

The North Atlantic eddy-driven jet (EDJ) is an essential component of the Euro-Atlantic atmospheric circulation. It has been typically described in terms of latitude and intensity but this is not enough to fully characterize its variability and complex EDJ configurations. Here, we present a set of daily parameters of the EDJ based on low-tropospheric zonal wind data for the 1948–2020 period. They describe the intensity, sharpness, location, edges, tilt and other zonal asymmetries of the EDJ, therefore dissecting its structure beyond the latitudinal regimes. This allows for assessments of specific EDJ aspects and a multi-parametric treatment of EDJ configurations in a manageable way. Overall, variations in EDJ parameters reflect distinctive patterns of eddy forcing and wave breaking, with anticyclonic eddies playing a major role in shaping the EDJ structure. A multimodal behavior of the EDJ is only detected in latitude, which largely influences the longitudinal position of the EDJ. Other aspects of the EDJ are less constrained by the latitude and display a variety of configurations. Four multi-parametric states (northern, central, tilted and split EDJs) provide a satisfactory description of recurrent patterns of the EDJ. They participate in meridional migrations of the EDJ, but yield less dramatic transitions than viewed from the latitudinal perspective. Finally, the EDJ parameters help to better understand the EDJ influence on European climate. In many regions, latitude and intensity contain limited information on near-surface anomalies, and their signals can be masked by the additional effect of other EDJ parameters. [ABSTRACT FROM AUTHOR]

Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex's map by selecting those with the lowest Euclidean distance from Alex. We term these "analogues" of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. [ABSTRACT FROM AUTHOR]

Colombia is highly vulnerable to climate change which may be intensified due to the climatic effects of regional deforestation. Here, we quantify the impact of historical (1900–2011) land cover changes (LCC) and of global warming during ENSO events (CC) on precipitation, temperature and surface energy balance components by running the Weather Research and Forecasting model WRF v3.9 at 10 km resolution. We find that historical anthropogenic CC causes a mean temperature increase of 0.77 ± 0.02 °C in Colombia, which is more pronounced in high altitudes. Precipitation is enhanced by 0.98 ± 0.30 mm/day (+ 9%), particularly over forested areas and reduced at the Pacific coast. LCC imply a reduction of precipitation particularly above the Andes (− 0.48 ± 0.10 mm/day) and Caribbean Coast (− 0.67 ± 0.12 mm/day), where LCC effects dampen CC effects by 24% and 72%, respectively. La Niña tends to intensify LCC and CC effects in the Andes but dampens them at the Coast, roughly by a factor of two compared to El Niño impacts in both regions. At the subregional level, LCC and CC can have impacts of similar magnitude on precipitation highlighting the need to precisely account for both drivers in hydroclimatic assessments. Contrary to almost all observations and similar simulations with climate models, WRF simulates a cooling bias after historical deforestation in Colombia, even with alternative WRF land surface models. We identify two main sources of biases in the default WRF parametrization to explain this inaccuracy: (1) surface shortwave radiation reflected after deforestation is overestimated; (2) associated evapotranspiration loss is underestimated. Improved model representation and validation of tropical vegetation properties are necessary to provide more robust and confident projections. [ABSTRACT FROM AUTHOR]

A hybrid statistical dynamical downscaling method intended to emulate regional climate models is described and applied to Western Europe. The method is based on a constructed analogues algorithm, already used for statistical downscaling. For emulation, the statistical downscaling relationship is not derived from observations but from climate projections at low and high resolution. The hybrid approach therefore does not rely on the stationarity assumption inherent to conventional statistical downscaling. Within a perfect model framework, and using a large number of regional projections, the hybrid method is shown to reproduce climate change signals very well and to outperform a conventional statistical downscaling method also based on constructed analogues. The hybrid approach remains skillful even when applied to very low resolution climate data. In practice, two emulation modes exist. In the GCM/RCM mode, the downscaling relationship is built between a RCM and its forcing GCM. In the RCM/RCM mode, the relationship is built between a RCM and the same RCM after aggregation of its results to a low resolution grid. The large-scale climate change signal of the downscaled GCM is generally retained with the RCM/RCM mode, but not with the GCM /RCM mode. Additionally, the choice of the GCM/RCM pair used for learning leads to large differences in downscaling results at large scale (i.e. at low resolution) with the GCM /RCM mode, but not with the RCM/RCM mode. These results are explained by the differences that generally exist at large scale between projected changes by current RCMs and their forcing GCMs. Whether these differences are a testimony of a real added value of RCMs at large scale in the climate change context, or whether they have other causes, is therefore a crucial question. [ABSTRACT FROM AUTHOR]

Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales. [ABSTRACT FROM AUTHOR]

Climate models are vital to the assessment of the impacts of climate change in the Central African regions. Establishing how well models reproduce key processes is important to the confidence we attach to these tools. This study examines model representation of the September to November characteristics, such as location and intensity, of the African Easterly Jet (AEJ) north and south in a sample of 16 commonly evaluated CMIP5 and CMIP6 models and in two reanalyses (ERA5 and MERRA2). The analysis evolves to assess key drivers of the AEJ from energetic interactions, the characteristics of mid-level highs and thermal lows and the nature of surface thermal heating. Over West Africa, several models miss the southeast-northwest orientation of the AEJ-N core, leading to a gap of around 60 in the location of the jet while most CMIP5 models also fail to locate AEJ-S over southern Central Africa. In general, the spread of simulated AEJ locations around reanalyses is larger for the CMIP5 sample compared to CMIP6 equivalent models, indicating improvement from CMIP5 to CMIP6 in this 16 model subset. However, this improvement in some CMIP6 models (e.g. GISS-E2-1-G and MIROC6) is not related to a maximum surface meridional gradient in temperature. Most CMIP5 and CMIP6 models underestimate the surface temperature gradient over AEJ-N region. As a first order diagnostic of the jet's acceleration, most coupled models better simulate the atmospheric energetic interactions over AEJ-N region that leads to its strong contribution to AEJ-N maintenance compared to AEJ-S. This study strengthens our understanding of the mid-level circulation over Central Africa by detecting gaps in the mechanisms maintaining the AEJ in coupled models and highlights processes that should be improved in future ensembles. [ABSTRACT FROM AUTHOR]

Recent assessments of climate sensitivity per doubling of atmospheric CO2 concentration have combined likelihoods derived from multiple lines of evidence. These assessments were very influential in the Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) assessment of equilibrium climate sensitivity, the likely range lower limit of which was raised to 2.5 °C (from 1.5 °C previously). This study evaluates the methodology of and results from a particularly influential assessment of climate sensitivity that combined multiple lines of evidence, Sherwood et al. (Rev Geophys 58(4):e2019RG000678, 2020). That assessment used a subjective Bayesian statistical method, with an investigator-selected prior distribution. This study estimates climate sensitivity using an Objective Bayesian method with computed, mathematical priors, since subjective Bayesian methods may produce uncertainty ranges that poorly match confidence intervals. Identical model equations and, initially, identical input values to those in Sherwood et al. are used. This study corrects Sherwood et al.'s likelihood estimation, producing estimates from three methods that agree closely with each other, but differ from those that they derived. Finally, the selection of input values is revisited, where appropriate adopting values based on more recent evidence or that otherwise appear better justified. The resulting estimates of long-term climate sensitivity are much lower and better constrained (median 2.16 °C, 17–83% range 1.75–2.7 °C, 5–95% range 1.55–3.2 °C) than in Sherwood et al. and in AR6 (central value 3 °C, very likely range 2.0–5.0 °C). This sensitivity to the assumptions employed implies that climate sensitivity remains difficult to ascertain, and that values between 1.5 °C and 2 °C are quite plausible. [ABSTRACT FROM AUTHOR]

Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts. Therefore, this study first evaluates the capabilities of one 11-single run multi-model ensemble (CMIP6) and one 40-member single model initial-condition large ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature–precipitation correlations and their historical changes. Next, the ensembles' correlations for the end of the 21st century are compared. Over the historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalysis displays significant correlation changes, none of the ensembles can reproduce them, with internal variability representing only 30% on the inter-model variability. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes. In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation. These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations. [ABSTRACT FROM AUTHOR]

The present study uses observation-based gridded air temperature and precipitation datasets to investigate the spatiotemporal changes in meteorological drought from 1981 to 2020 in South Asia (SA). The drought characteristics i.e., duration, area, frequency, intensity, and severity are calculated using Run theory and the Standardized Precipitation Evapotranspiration Index (SPEI) on annual and seasonal timescales. SA is divided into four homogeneous subregions using the k-means clustering algorithm, while the trends were estimated using Sen's Slope estimator and modified Mann-Kendall (MMK) test. A state-of-the-art Bayesian Dynamic Linear (BDL) model was employed to assess the sub-regional drought variability and their possible links with large-scale atmospheric drivers such as the Indian Ocean Dipole (IOD), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO). It is found that the SA winter season experienced a significant drying long-term trend, especially southwestern and northeastern parts of SA. Drought durations show dipolar patterns with longer drought duration in the southwestern compared to the northern parts of SA. Notably, arid and semi-arid regions have shown significant drying trends in terms of their area, frequency, and severity, implying that meteorological droughts are relatively more severe in those regions. Similarly, the relationship varies over time between drought variability and climate drivers. In particular, the IOD has an impact on drought episodes over southwest SA relative to the northern parts and is mostly affected by the Sea surface temperature (SST) variability. The study results contribute to a better understanding of the meteorological drought characteristics over SA, which is important for disaster risk managers and policymakers to mitigate drought impacts. [ABSTRACT FROM AUTHOR]

The interactions between the tropical Indian Ocean and Pacific Ocean via the Walker circulation and the Indonesian Throughflow (ITF) play an important role in the inter-basin exchange and climate variations. The effects of the eastern Indian Ocean subsurface temperature conditions during the 2019 Indian Ocean dipole (IOD) event on the development of the 2020/2021 La Niña event are investigated of the National Marine Environmental Forecasting Center of China. Results of pacemaker experiments comparing the effects of the atmospheric bridge and the oceanic channel suggest that the subsurface temperature anomalies in the tropical Indian Ocean dominates the inter-basin forcing leading to the outburst of the 2020/2021 La Niña event. The strong subsurface cooling is found to propagate to the eastern equatorial Pacific Ocean through the Indonesian seas and induce a strong La Niña event at the end of 2020, showing the long memory of the oceanic channel dynamics and the amplification by the ocean-atmospheric coupling. In comparison, experiments forced by surface temperature anomalies over the tropical Indian Ocean show that the atmospheric bridge alone is unable to induce the onset of the 2020 La Niña. The results suggest the importance of the Indo-Pacific oceanic channel dynamics in ENSO forecasts. [ABSTRACT FROM AUTHOR]

The climate change projections of the Intergovernmental Panel on Climate Change are based on scenarios for future emissions, but these are not statistically-based and do not have a full probabilistic interpretation. Raftery et al. (Nat Clim Change 7:637–641, 2017) and Liu and Raftery (Commun Earth Environ 2:1–10, 2021) developed probabilistic forecasts for global average temperature change to 2100, but these do not give forecasts for specific parts of the globe. Here we develop a method for probabilistic long-term spatial forecasts of local average annual temperature change, combining the probabilistic global method with a pattern scaling approach. This yields a probability distribution for temperature in any year and any part of the globe in the future. Out-of-sample predictive validation experiments show the method to be well calibrated. Consistent with previous studies, we find that for long-term temperature changes, high latitudes warm more than low latitudes, continents more than oceans, and the Northern Hemisphere more than the Southern Hemisphere, except for the North Atlantic. There is a 5% chance that the temperature change for the Arctic would reach 16 ∘ C. With probability 95%, the temperature of North Africa, West Asia and most of Europe will increase by at least 2 ∘ C. We find that natural variability is a large part of the uncertainty in early years, but this declines so that by 2100 most of the overall uncertainty comes from model uncertainty and uncertainty about future emissions. [ABSTRACT FROM AUTHOR]

The impact of the enhancing Pacific-North American teleconnection (PNA) on the intensity of the first mode of SST anomalies (SSTa) in wintertime North Pacific [known as the Pacific decadal oscillation (PDO)-like SST pattern] under global warming is studied using reanalysis datasets and 12 selected CMIP5 models. The robust observational result of the PNA one month ahead of the PDO shows that the PNA has a great effect on the PDO-like SSTa. The intensities of PNA and PDO are defined with elimination of the ENSO signals to evaluate the direct impact of PNA on the PDO in the North Pacific under global warming. By comparing RCP8.5 and historical scenario of selected multi-models (PNA enhanced models), future projection illustrates that the PDO intensity will intensify 2.2 times its internal variability. Approximately 67% of the increase in PDO variations is contributed by the PNA-induced SSTa in the future warming scenario of multi-models ensemble mean. Models with stronger intensification of PNA variability tends to have larger magnitude of SSTa response in the North Pacific, which has more contributions to the enhancement of PDO intensity change in a warmer climate. This may shed some light on the projection of PDO variability and the relative role of PNA forcing under the global warming. [ABSTRACT FROM AUTHOR]

Three consecutive dry summers in western Europe (2018–2019–2020) had widespread negative impacts on society and ecosystems, and started societal debate on (changing) drought vulnerability and adaptation measures. We investigate the occurrence of multi-year droughts in the Rhine basin, with a focus on event probability in the present and in future warmer climates. Additionally, we investigate the temporally compounding physical drivers of multi-year drought events. A combination of multiple reanalysis datasets and multi-model large ensemble climate model simulations was used to provide a robust analysis of the statistics and physical processes of these rare events. We identify two types of multi-year drought events (consecutive meteorological summer droughts and long-duration hydrological droughts), and show that these occur on average about twice in a 30 year period in the present climate, though natural variability is large (zero to five events can occur in a single 30 year period). Projected decreases in summer precipitation and increases in atmospheric evaporative demand, lead to a doubling of event probability at 1 ∘ C additional global warming relative to present-day and an increase in the average length of events. Consecutive meteorological summer droughts are forced by two, seemingly independent, summers of lower than normal precipitation and higher than normal evaporative demand. The soil moisture response to this temporally compound meteorological forcing has a clear multi-year imprint, resulting in a relatively larger reduction of soil moisture content in the second year of drought, and potentially more severe drought impacts. Long-duration hydrological droughts start with a severe summer drought followed by lingering meteorologically dry conditions. This limits and slows down the hydrological recovery of soil moisture content, leading to long-lasting drought conditions. This initial exploration provides avenues for further investigation of multi-year drought hazard and vulnerability in the region, which is advised given the projected trends and vulnerability of society and ecosystems. [ABSTRACT FROM AUTHOR]