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BACKGROUND RESULTS CONCLUSIONS ‘Xynisteri’ is considered as the reference white grape cultivar in Cyprus with remarkable adaptation to adverse edaphoclimatic conditions and appreciable oenological properties that renders it as an appropriate cultivar for studies within a global context due to climate change. To this aim, two distinct non‐irrigated plots with different climatic conditions, soil properties and levels of rainfall were selected; Koilani [KO, altitude 800 m, 76% calcium carbonate (CaCO3) content, pH 7.97, average temperature: 16.5 °C, rainfall: 229 mm] and Kyperounda (KY, altitude 1200 m, CaCO3‐free soil, pH 6.47, average temperature: 14.9 °C, rainfall: 658 mm). An array of physiological, biochemical and qualitative indices during successive developmental stages (BBCH 75–89) were determined. During the advanced on‐vine developmental stages (BBCH 85–89), the aromatic profile of grapes was assessed with the employment of gas chromatography–mass spectrometry (GC–MS). Such analysis was complemented with non‐destructive chemometric analyses.Berry ripening process substantially differed on the examined plots; BBCH 89 stage reached at 267 and 303 Julian days for KO and KY, respectively. Results indicated that berry weight, soluble solids content (SSC) and α‐amino nitrogen were higher in KO than in KY, with exception made for ammonium nitrogen content. A total of 75 compounds, including aliphatic alcohols, benzenic compounds, phenols, vanillins, monoterpenes and C13‐norisoprenoids were identified and quantified. The variations of mesoclimatic conditions affected the volatile organic compound (VOC) profiles at the fully‐ripe stage, showing a considerable rise in glycosylated aroma compounds, especially monoterpenes and benzenic compounds. In particular, the higher amount of glycosylated aroma compounds were obtained in KY berries up to mid‐ripe, whereas KO showed higher glycosylated aroma compounds at fully‐ripe stage. Results reported herein indicate that aroma profile of ‘Xynisteri’ grapes varied substantially in the examined terroirs. Interestingly, the limited rainfall in KΟ non‐irrigated vine did not compromise qualitative and aromatic properties of berries.The present study aimed at dissecting the impact of terroir on bush‐trained, non‐irrigated grapevines of a cultivar appropriate for extreme climate change scenarios. The volatilome fingerprint was highly variable among the examined plots; such results can be further exploited at vinification level towards production of single vineyard premium end products. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of "high in the south and low in the north, high in the east and low in the west" and "high in the southeast and low in the northwest", respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change. [ABSTRACT FROM AUTHOR]

Nutrient enrichment impacts grassland plant diversity such as species richness, functional trait composition and diversity, but whether and how these changes affect ecosystem stability in the face of increasing climate extremes remains largely unknown. We quantified the direct and diversity‐mediated effects of nutrient addition (by nitrogen, phosphorus, and potassium) on the stability of above‐ground biomass production in 10 long‐term grassland experimental sites. We measured five facets of stability as the temporal invariability, resistance during and recovery after extreme dry and wet growing seasons. Leaf traits (leaf carbon, nitrogen, phosphorus, potassium, and specific leaf area) were measured under ambient and nutrient addition conditions in the field and were used to construct the leaf economic spectrum (LES). We calculated functional trait composition and diversity of LES and of single leaf traits. We quantified the contribution of intraspecific trait shifts and species replacement to change in functional trait composition as responses to nutrient addition and its implications for ecosystem stability. Nutrient addition decreased functional trait diversity and drove grassland communities to the faster end of the LES primarily through intraspecific trait shifts, suggesting that intraspecific trait shifts should be included for accurately predicting ecosystem stability. Moreover, the change in functional trait diversity of the LES in turn influenced different facets of stability. That said, these diversity‐mediated effects were overall weak and/or overwhelmed by the direct effects of nutrient addition on stability. As a result, nutrient addition did not strongly impact any of the stability facets. These results were generally consistent using individual leaf traits but the dominant pathways differed. Importantly, major influencing pathways differed using average trait values extracted from global trait databases (e.g. TRY). Synthesis. Investigating changes in multiple facets of plant diversity and their impacts on multidimensional stability under global changes such as nutrient enrichment can improve our understanding of the processes and mechanisms maintaining ecosystem stability. [ABSTRACT FROM AUTHOR]

• Identified the severity and frequency of drought in Singbhum Protocontinent, India. • Meteorological and remote sensing indices are used to identify drought dynamics. • 1.67 to 1.05 percent extreme drought frequency shows in the western part. • Poor aquifer properties and extreme climate are the main reason for droughts. • Sustainable watershed management is highly required. Drought is an extremely hazardous situation that predominantly affects ecosystems, hydrological systems, and agricultural mechanisms in different pockets of the world. Management of water resources in dry and semi-arid environments has become a critical challenge in the last few decades. The principal objectives of this study are (i) to categorize the severity and frequency of drought events using the Reconnaissance Drought Index and Rainfall Deviation Index and ii) to evaluate the spatial extension of drought in particular drought times of severe and extreme droughts through Remote Sensing Drought Indices (RSDIs). This drought monitoring index is commonly used index for its high degree of resilience and sensitivity to droughts. The result shows that severe to extreme drought occurred in Bero, Tulin, Sirkabad, Manbazar and Bundwan which are 22, 28, 23, 14 and 25 months correspondingly based on RDI3 whereas RDI12 values indicated 26, 47, 42, 22 and 38 months in the study period (1981 to 2021). Bundwan area faced the most extreme drought occurrence in May month of 1996 with −3.58 values followed by Sirkabad, Bero, Manbazar and Tulin. Manbazar is going through severe to extreme drought months (for short time) whereas 'extreme drought' frequency (1.67 % to 1.05 %) is higher in the western part mainly in Jhalda I, Jhalda II, Bagmundi, and Arsha blocks of Purulia district (part of Manbhum Singhbhum Plateau). Additionally, the recurrence of 'moderate drought' is much greater in Balarampur along with some portions of Purulia I block. The whole study can be summarized as the northeastern portion being challenged with moderate or severe drought conditions while mild or severe drought is a considerable recurrence in the northern section. The outcome of this study will be helpful for local planners and management officials during implementation strategies related to water resource management. [ABSTRACT FROM AUTHOR]

An accurate analysis of climate extremes is essential for impact assessment and devising appropriate adaptation measures. There is an urgent need to assess precipitation products in capturing the increasing occurrence of climate extremes. This study evaluates the ability of 20 observational datasets, including gauge-based, satellite-based and reanalyses, in representing different drought severity (moderate, severe and extreme drought) over Africa and its nine sub-regions at varying time scales (3-, 6- and 12-months) during 1983–2014. Drought is represented using the Standardized Precipitation Index (SPI). The results demonstrate that while most datasets are suitable for drought studies over the continent, the African Rainfall Climatology version 2 (ARC2) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Records (PERSIANN_CDR_v1r1) are less fitted for such investigations. Moreover, regions such as the Sahara (SAH), Central Africa (CAF) and North Eastern Africa (NEAF) show a larger disparity among the datasets, requiring more caution when selecting a dataset for use in such areas. Generally, the datasets present low agreement toward the lower end of the range (5–30%) because the individual datasets estimate varying drought severities at different grids and months. This is observed in the coefficient of variation of 20–25% of the datasets falling outside the ± 1 standard deviation range. Therefore, using an ensemble to represent the datasets remains an indispensable tool. The datasets present better agreement in the timing of drought events than the spatial distribution. The findings provide valuable insights into the complexity of drought assessment using diverse precipitation datasets. Furthermore, the results highlight the significance of considering spatial and temporal dimensions, as datasets may capture drought events at varying locations and times, revealing subtle variations in drought impact. [ABSTRACT FROM AUTHOR]

In the current study, three optimistic (SSP1-2.6), medium (SSP2-4.5), and pessimistic (SSP5-8.5) scenarios were used to examine changes in precipitation based on the sixth phase of Coupled Model Intercomparison Project (CMIP6) in the Gorganrood watershed over two time periods: the near future (2021–2060) and the far future (2061–2100). To do this, the rainfall of 27 meteorological stations was studied. Using the RClimdex software in the R software, precipitation extreme indicators (11 indicators) were determined for different scenarios and periods, and Mann-Kendall (MK) and Sen's estimator tests were then used to detect the trend. The results showed that in the near future under SSP1-2.6, the indicators of consecutive dry days (CDD) and consecutive wet days (CWD) have a significant downward and upward trend, respectively. While in the SSP5-8.5, the indicators of maximum five-day rainfall (RX1day), CDD, number of very wet days (R95p) and total wet day precipitation (PRCPTOT) have a significant downward trend in some stations. Similarly, in the far future, in the SSP5-8.5, the trend of rainfall indicators is insignificant compared to the near future, but still a significant decreasing trend can be seen in R95p, R99p, and PRCPTOT. Z score index (ZI) values ​​in both future periods showed that drought peaks occurred in the optimistic scenario and drought peaks occurred in the pessimistic scenario, and almost normal conditions prevailed in the intermediate scenario. The results can be effective in policies to deal with global warming and climate change. [ABSTRACT FROM AUTHOR]

Central America and the Caribbean are regularly battered by megadroughts, heavy rainfall, heat waves, and tropical cyclones. Although 21st‐century climate change is expected to increase the frequency, intensity, and duration of these extreme weather events (EWEs), their incidence in regional protected areas (PAs) remains poorly explored. We examined historical and projected EWEs across the region based on 32 metrics that describe distinct dimensions (i.e., intensity, duration, and frequency) of heat waves, cyclones, droughts, and rainfall and compared trends in PAs with trends in unprotected lands. From the early 21st century onward, exposure to EWEs increased across the region, and PAs were predicted to be more exposed to climate extremes than unprotected areas (as shown by autoregressive model coefficients at p < 0.05 significance level). This was particularly true for heat waves, which were projected to have a significantly higher average (tested by Wilcoxon tests at p < 0.01) intensity and duration, and tropical cyclones, which affected PAs more severely in carbon‐intensive scenarios. PAs were also predicted to be significantly less exposed to droughts and heavy rainfall than unprotected areas (tested by Wilcoxon tests at p < 0.01). However, droughts that could threaten connectivity between PAs are increasingly common in this region. We estimated that approximately 65% of the study area will experience at least one drought episode that is more intense and longer lasting than previous droughts. Collectively, our results highlight that new conservation strategies adapted to threats associated with EWEs need to be tailored and implemented promptly. Unless urgent action is taken, significant damage may be inflicted on the unique biodiversity of the region. [ABSTRACT FROM AUTHOR]

The Huaihe River basin (HRB) of China located in the climate transition zone between warm temperate and subtropical areas is highly sensitive to climatic change. However, the changes in future climate extreme events under anthropogenic warming and the population exposure to these climate extremes in HRB remain unexplored. Here, using the eight commonly used extreme climate indices and based on the bias‐corrections of 16 global climate models (GCMs) in CMIP6, we present a projection and uncertainty analysis of extreme events and investigate the corresponding population exposure risk in HRB under three shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, SSP5‐8.5). The 16‐GCM ensemble mean projects an evident warming trend under all three scenarios with a total increase of 25.6–68.0 days in summer days (>25°C) by the end of the century in HRB. Larger increases (decreases) in maximum and minimum temperatures (frost days) are projected in the western HRB. Very heavy rain days (R20mm), maximum 5‐day precipitation (RX5day) and simple daily intensity index (SDII) will experience intensification across most of HRB (especially in southern and western HRB). The consecutive dry days is projected to decrease in northwestern HRB and increase in southern HRB. However, there is a large spatial variability in GCM uncertainty with a higher SSP scenario generally having higher uncertainty. Increases in summer days and R20mm exacerbate population exposure in HRB in near future (2030–2059), but in far future (2070–2099) although summer days (R20mm) continues to rise, population exposure is expected to decrease due to the rapid decline in population density. [ABSTRACT FROM AUTHOR]

The study focuses on understanding the future exposure to rainfall and temperature extremes in one of the world's most populous islands, Java, Indonesia. We use the high‐resolution climate projections from the Coordinated Regional Climate Downscaling Experiment (CORDEX) simulation for Southeast Asia by 2100 under RCP4.5 and RCP8.5 scenarios. Results show that the island will likely experience drying in the lowlands due to annual rainfall decline by approximately 13%–18%, potentially exposing around 27%–73% of the population (varying under different scenarios) during the end of the century (2060–2099). Additionally, the future drying condition may be exacerbated by extreme temperatures with a 1.7–3.1°C increase in maximum daily temperature, linked with more than half of the population (63%) likely to experience at least an unprecedented temperature of 3°C under RCP8.5. Our seasonal analysis also suggests that dry seasons get even drier, and wet seasons get wetter. In terms of landuse areas exposed, we show a higher fraction of crop and forest areas may face both drying and warming, which can potentially lead to crop failure and wildfire. Our study indicates that compound drought and heat may be a common threat in lowland Java in the future, while intensifying rainfall extremes in the uplands may lead to flash flooding downstream and landslides. These findings highlight the urgent need for adaptation and mitigation strategies to reduce the risks associated with climate change in Java as one of Indonesia's most critical regions in the future. [ABSTRACT FROM AUTHOR]

This study analyzes fluctuations in the atmospheric boundary layer height (aBLH) over a Caribbean island using hourly measured and model-interpolated data from the 2019–2023 period. Our focus is the mean structure, diurnal cycle, and aBLH correlation with meteorological parameters on the leeward coast at Mayaguez (18.2 N, 67.1 W). The mean diurnal cycle of the aBLH increases from 300 m near sunrise (07:00) to 1200 m by 13:00 because of turbulent heating. Summer-time thermal circulations lead to a 3 °C increase in near-surface dewpoint temperature (Td) that propagates upward to 3000 m by 16:00. A case study demonstrates how mid-day trade winds turn onshore and generate significant rainfall and river discharge across the island. The context for this study is provided by a 24 yr cluster analysis that identifies rainfall over the island's northwest interior driven by upstream heating. Analysis of linear trends from 1979 to 2023 shows that Td declined by −0.02 °C/yr above 1500 m because of large-scale subsidence. However, cool interior forests transpire humidity and instill contrasting trends that may amplify climate extremes. A better understanding of entrainment at the top of the atmospheric boundary layer could be critical for managing future water resources in Caribbean islands. [ABSTRACT FROM AUTHOR]

Landslides triggered by extreme rainfall events often cause losses of life, property damage, and environmental alterations. While past studies have assessed landslide hazards using various indices, how to select rainfall indices in rainfall-induced landslide hazard assessment is still a challenge due to the spatiotemporal asymmetry of rainfall indices. In this study, we employed three machine-learning models, namely the Random forest (RF), Support vector machine (SVM), and logistics regression models, and developed an extreme rainfall index-based model to evaluate rainfall-induced landslide hazards. To eliminate the effect of spatiotemporal asymmetry in indices, we selected six extreme rainfall indices that are highly correlated with rainfall-induced landslides and tested 63 combinations. Over the past four decades, extreme rainfall events have become more frequent and intense. Both the number and type of rainfall indices affected the assessment results of landslides in the study area. The RF model showed a better accuracy in landslide hazard assessments than did the other two models. To better predict rainfall-induced landslide hazards, an optimal model based on three extreme rainfall indices, i.e., PSSPTOT, R25mm, and Rx5day, was proposed for the study area. With climate change, the study area may encounter more intense rainfall events and experience high levels of rainfall-induced landslide hazards. Compared to the baseline, landslide hazards in the study area are projected to increase by 9.9% and 11.9% in the 2030s (2021–2050). Areas with high- and very high- levels of landslide hazards will account for more than 50% of the study area and will be mainly distributed in the central and eastern parts of the study area. This study suggested an optimal combination of extreme precipitation indicies and provided scientific information about rainfall-induced landslide hazard management under climate change. [ABSTRACT FROM AUTHOR]

Pastoralism is a livelihood system for millions of people around the world and a great majority of them are found in Africa. The indigenous knowledge and strategies on pastoralism are not well understood and properly documented. Hence, this study sheds light on location-specific indigenous climate change adaptation strategies and explores the pastoralist and agro-pastoralist households' perceptions against the meteorological records. Data were collected from 191 sample households, 12 key informants, 32 focus group participants, and National Meteorological Services. The results reveal that there is a high climate variability (CV = 30), high rainfall intensity, and longer dry periods. Almost every year the Rainfall seasonality index (SI) value predicts a longer dry season. The community's perception matched with recorded climate data of the past 36 years and identified 10 major climate extremes orally recounted in history. Indigenous strategies include indigenous weather forecasts, mating calendar, destocking, herd mobility, herd diversification, traditional rotational grazing system ('Seri'), and also emerging adaptation strategies (farming, petty trade, handcraft, charcoal sale, and casual labor) utilized as a result of the severity of climate variability and extremes in the region. The results indicate that emerging adaptation strategies are replacing the preexisting pastoralist livelihood system and that indigenous strategies need support to withstand the current and predicted weather and climate variability in the sites. Pastoralists and agro-pastoralists will be in a better position to adapt to the consequences of climate variability and extremes if indigenous institutions are revitalized with innovations. [ABSTRACT FROM AUTHOR]

The importance and vulnerability of municipalities in the eastern Amazon led to the evaluation of the distribution of seasonal precipitation and extreme events over protected and deforested sites along the Carajás Railroad (EFC) based on three datasets: Brazilian Daily Weather Gridded Data (BR-DWGD), European Reanalysis (ERA5-Land), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). The main purpose is the understanding of the relationship between local land use change and the occurrence of extreme climate events. Results suggested that large-scale deforestation has a regional impact occasionally outweighing local effect. Significant trends reveal a general pattern of drought that has been more intense in the north of the study area, regardless of land cover, whether preserved or deforested. Moreover, the dry season is getting drier, but the wet season is not getting wetter over the entire area, as Carajás National Forest and Curionópolis (southern sector) deliver positive and accentuated trends in the rainy season. Extreme events are becoming more frequent. The number of consecutive dry days has increased in the north revealing an extension of dry periods, whereas, the maximum one-day precipitation has soared in the south indicating the intensification of rainfall. CHIRPS provides stronger correlations with the standard dataset (BR-DWGD), as both furnish primary data based on rain gauges observations. It also outperforms ERA5-Land in annual and seasonal analyses, which does not invalidate the latter as a great alternative to use in data-poor locations. Ultimately, further research and technology implementation were recommended to improve reforestation efforts given the reported results. [ABSTRACT FROM AUTHOR]

Contrasting the extensive research on summer atmospheric rivers (ARs) in the Antarctic Peninsula (AP), winter AR impacts are less understood. This study examines a unique warming event from 1 to 3 July 2023, using in situ winter observations and ERA5 reanalysis. On 2 July, Frei station experienced an extreme warm event with a temperature of 2.7°C and a significant rise in the freezing level, coinciding with winter rainfall. A pressure dipole pattern over the AP, with contrasting circulations over Bellingshausen and Weddell Seas, facilitated an AR, carrying warm, humid air initially from South America/Atlantic and then the southeast Pacific. This shift resulted in anomalous water stable isotope composition in precipitation. Trends suggest a strengthening winter pressure dipole, associated with increased AR frequency and higher temperatures in northern AP. These findings highlight the importance of winter observations in exploring AR impacts, bridging knowledge gaps about winter AR behaviors. Plain Language Summary: The Antarctic Peninsula is increasingly witnessing climate extremes during summer, while the understanding of such extremes in winter remains limited. Our study explores a significant warming event in the northern Peninsula in early July 2023, utilizing recent winter in situ observations and atmospheric analysis. On 2 July, an exceptional temperature of 2.7°C was recorded, significantly altering the atmospheric freezing level and causing rainfall instead of snow. Our analysis revealed a unique atmospheric pattern around the Peninsula, characterized by varying air movements over the Bellingshausen and Weddell Seas. This pattern facilitated an "atmospheric river," a flow of warm and moist air from lower latitudes, including continental South America/Atlantic and the southeast Pacific, as reflected in the precipitation's water stable isotope composition. This event is indicative of a potential trend toward more frequent and severe occurrences, emphasizing the urgent need for comprehensive winter research in the Antarctic Peninsula to understand the broader implications of extreme weather events and climate change. Key Points: Early July 2023 had extreme winter warmth with rainfall in the northern Antarctic Peninsula, favored by an atmospheric riverIn recent decades, strengthened winter pressure dipole has directed northerly warm and moist air, resulting in warm events in the regionWe highlight the need for expanded winter research in the Antarctic Peninsula to better understand climate change and extreme weather events [ABSTRACT FROM AUTHOR]

Stationarity, a cornerstone in hydraulic design, is now under scrutiny due to anthropogenic activities and climate change. Numerous studies have sought to identify non‐stationarity (NS); however, a comprehensive assessment of time invariance in all statistical properties of a time series is less explored. This study presents a non‐overlapping block‐stratified random sampling (NBRS) framework leveraging the strengths of several nonparametric tests to assess NS. The NBRS approach exclusively detects NS and distinguishes between various forms of stationarity, including weak and strict. A variant of NBRS is proposed in this study to identify the underlying stochastic process(es) influencing NS in hydroclimatic extremes. Furthermore, a nonparametric clustering approach is used to unveil spatial clusters showcasing NS due to shifts in mean, variance, distribution of time series or a combination of these factors. A comparative assessment of the modified NBRS approach with traditional trend and change point methods is also performed. The proposed methodology is applied to assess the presence of NS in 28 hydroclimatic indices derived for the west‐central river basins of India, exhibiting diverse physio‐climatic settings, for the study period 1973–2021. The modified NBRS approach rigorously explores NS within extreme hydroclimatic indices, conclusively pinpointing its root causes and profound implications for hydrologic design. The applicability of the modified NBRS approach to gridded and point datasets is also demonstrated. The findings highlight the limitations of conventional trend and change point tests in capturing time‐invariant characteristics in heteroscedastic variables (such as streamflow and rainfall extremes) compared to the NBRS approach. The research reveals that NS in rainfall and streamflow extremes primarily results from distributional shifts, whilst temperature extremes are influenced by changes in mean and distribution properties. This research deepens our understanding of the evolving patterns in hydroclimatic extremes in a changing climate. [ABSTRACT FROM AUTHOR]

The La Plata basin is one of the largest river basins in the world, draining about a fifth of the South American continent. It is a system of great hydrological significance, sensitive to extreme events, and also has the most economic development in the region. This work analyses the total water storage (TWS) changes over the La Plata basin from the GRACE (Gravity Recovery And Climate Experiment) mission and compares it with TRMM (Tropical Rainfall Measuring Mission) rainfall data. Subsequently, a study was conducted on the main sub-basins for the period 2003 to 2017 to identify regional-scale variations in TWS. Precipitation and GLDAS (Global Land Data Assimilation System) runoff data was evaluated in these areas, along with their connections to ENSO (El Niño Southern Oscillation) episodes. The results suggest that the majority of TWS variations are associated with extreme climatic events, such as the 2009 drought, and are linked to ENSO periods. The statistical analysis indicates a significant correlation between severe Niño/Niña episodes and changes in TWS in the sub-basins. [ABSTRACT FROM AUTHOR]

The escalating frequency and intensity of extreme climate events pose significant challenges in the context of the climate crisis, leading to substantial human and economic losses. This study aims to assess trends and disruptions in extreme climate indicators, focusing on precipitation and air temperature, within the watersheds of eastern Paraná state. Data from 1976 to 2015 were used, ensuring record failure rates below 5%. Trend analysis employed the extreme climate indicators developed by the Canadian Meteorological Service and the Mann-Kendall test, while discontinuities in the historical series were identified using normality tests (Pettitt, SNHT, and Buishand). Results revealed increasing trends in annual precipitation totals (PRCPTOT), the annual total of rainfall exceeding 95% of percentiles (R95p), and, notably, the index of daily rainfall concentration (SDII). The Upper Ribeira watershed displayed the highest frequency of trends associated with SDII. Moreover, widespread upward trends in air temperature were observed, particularly in Curitiba, where the average annual minimum temperature rose by 1.8 °C. Notably, many discontinuities in the historical climatic series were detected between the late 1980s and early 2000s. This research provides a comprehensive understanding of the modifications in extreme climate indicators in the study area, emphasizing significant trends of more heavy and concentrated rainfall and a robust increase in average air temperature. [ABSTRACT FROM AUTHOR]

In a warming climate, an intensifying fire regime and higher likelihood of extreme rain are expected to increase watershed sediment yield in many regions. Understanding regional variability in landscape response to fire and post‐fire rainfall is essential for managing water resources and infrastructure. We measured sediment yield resulting from sequential wildfire and extreme rain and flooding in the upper Carmel River watershed (116 km2), on the central California coast, USA, using changes in sediment volume mapped in a reservoir. We determined that the sediment yield after fire and post‐fire flooding was 854–1,100 t/km2/yr, a factor of 3.5–4.6 greater than the long‐term yield from this watershed and more than an order of magnitude greater than during severe drought conditions. In this first large‐scale field validation test of the WEPPcloud/wepppy framework for the Water Erosion Prediction Project (WEPP) model on a burned landscape, WEPP predicted 81%–106% of the measured sediment yield. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean climate and indicate that the increasingly widespread use of WEPP is appropriate for evaluating post‐fire hillslope erosion even across 100‐km2 scales under conditions without debris flows. Plain Language Summary: In a warming climate, more wildfire and more extreme rain will cause more erosion, producing more sediment that will be carried downstream by rivers. Understanding how much sediment a landscape produces after fire and extreme rain is essential for managing water resources and infrastructure, because sediment fills up storage space in reservoirs and can interfere with proper functioning of water systems and roads. We measured how much sediment was produced in a watershed due to wildfire followed by extreme rain and flooding, studying the Carmel River on the central California coast, USA. We evaluated how much sediment this watershed produced by measuring the volume of sediment deposited within a reservoir that the watershed drains into. We determined that the rate of sediment exported from the study watershed due to a large fire and post‐fire floods was much greater than the long‐term rate there. Having compared our results with the amount of sediment predicted by a model called the Water Erosion Prediction Project model, we found that the model performed well and realistically predicted the amount of sediment that this landscape would shed. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean‐type climate. Key Points: A 116‐km2 central California watershed produced sediment yield of 854–1,100 t/km2/yr in the first year after a fire and extreme rainPost‐fire sediment yield in an extremely wet year without debris flows was 3.5–4.6 times greater than the long‐term rateThe Water Erosion Prediction Project model predicted 81%–106% of the measured post‐fire sediment eroded from hillslopes [ABSTRACT FROM AUTHOR]

Devising effective strategies to retard the negative impacts of extreme climatic events on water security in general and environmental water balance in specific is imperative, especially in semi-arid rural-Western-India, where climate change has markedly increased water scarcity in domestic and agricultural sectors. This exploratory research thus aimed at investigating the water budget against mismanagement of available water resources for remote-marginalized villages in rural-Nashik (West-India). Investigation entailed visual interpretation of LULC analysis (2008–2017) using fine-scale Google Earth imageries, rainfall-runoff analysis using SCS-CN method, determining the supply-demand potential of water storage structures using field-experimentations and PRA tools, and estimation of season-wise water-budget using hydrological (water-balance) equations. Results identified agriculture as the major land-use (~ 78%) followed by hilly regions (~ 16%) and water bodies (~ 3%). Surface runoff was found as the dominating hydrological phenomenon (33–89% of monsoonal rainfall) followed by surface storage (6–36% of annual rainfall) and groundwater flow (4–82% of annual rainfall). Deforestation over hills for firewood, which reduced forest cover by 52%, was observed as the primary concern for soil erosion, thereby siltation of water bodies and higher runoff against percolation. Erratic rainfall patterns (departure range − 42 to 83% during 1998–2017) coupled with sub-graded irrigational systems confined the agricultural practices to one season [South–West monsoon (June–September)]. High unmet drinking water demand (73% to 98%) forced women communities to fetch water by walking 4.5 ± 1.5 km. Considering the urgent response to collectively combat water-budget imbalance, integrated water security plans were proposed using decentralized participatory watershed development approaches. [ABSTRACT FROM AUTHOR]

The frequent occurrence of El Niño events, in the context of climate change, brings heavy precipitation and extreme heat, severely disrupting agricultural production. Previous efforts have focused on monitoring crop planting areas and evaluating affected crops during disasters. Nevertheless, a comprehensive analysis, including crop planting area mapping, crop damage assessment, and mitigation effectiveness throughout the entire course of a disaster, has been seldom addressed. In this study, we built a comprehensive framework to rapidly investigate the areas of early rice, the extent of flooding impacts, and the post-flood mitigations of early rice during the El Niño flooding event in a typical rice production region – Jiangxi Province in 2023. Early rice planting areas were first mapped by integrating 15-day time series gap-filled Sentinel-1/2 datasets using the Google Earth Engine (GEE) platform, based on a random forest classifier built with the 55 optimized training features. Then the flood-affected early rice map was produced by integrating the early rice planting areas and the Sentinel-1 images-based flood map. Finally, the post-flood newly planted rice fields were identified using the random forest algorithm and classification features from the Sentinel-1/2 images composited during four phenology phases of newly planted rice. The results showed the early rice planting area map, the flooding map, and the newly planted early rice map have overall accuracies of over 90 %. The early rice planting areas reached 120 × 104 ha, and an area of 3.60 × 104 ha (3 %) was flooded due to the heavy rain, and 3.43 × 104 ha flooded areas were newly planted, eventually mitigating the flooding impacts on the production of early rice. This study showcases the potential of all the available Sentinel-1/2 data, cloud computing, and well-established mapping algorithms for tracking rice areas, flooding impacts, and mitigations (i.e., after-flooding replanting) during extreme climate events. The established framework is expected to serve as an early warning system for agricultural adaptation to extreme climate events. [ABSTRACT FROM AUTHOR]

Deciphering how modern precipitation patterns became established in monsoon‐dominated East Asia and the arid interior Asia is crucial for predicting future precipitation trends under accelerated global warming and increased climate extremes. However, this effort is hindered by a scarcity of quantitative paleo‐precipitation data in this region. Here we reconstruct the pattern of Middle to Late Miocene paleo‐precipitation across an east‐to‐west transect from the summer monsoon‐dominated East Asian region through the transition zone and into interior Asia. Our work is based on a newly established precipitation calculation equation and quantitative pollen‐based precipitation conversion. Analysis indicates a common trend of precipitation across the studied region prior to ca, 11 Ma, followed by a clear divergence of precipitation variations between East and interior Asia since at least 11–9 Ma. This divergence is characterized by increasing precipitation in East Asia, but a coeval decrease in rainfall in the transition zone and interior Asia. The timing of this precipitation divergence was contemporaneous with intense tectonic activity in the northern Tibetan Plateau, which differentially affected the efficacy of water vapor transport into East and interior Asia. Modeling work using different topographic settings corroborates this tectonic influence. Our study demonstrates the early establishment of modern‐like precipitation patterns in East‐interior Asia at least in the early Late Miocene. Plain Language Summary: The present Asian climate consists of a monsoon‐dominated East Asia, and arid interior Asia. Increasing catastrophic flooding and storm events in monsoon region and an increasing dust storm events within interior Asia in recent years indicate an accelerated divergence in the climate conditions of these two regions. As such, deciphering how modern precipitation patterns became established in East‐interior Asia is crucial for understanding their future climate trends and mitigating possible damaging consequences. Here we developed a quantitative proxy for paleo‐precipitation and reconstruct the Middle to Late Miocene paleo‐precipitation pattern across an east‐to‐west transect from the summer‐monsoonal transition zone to interior Asia. We find that the modern precipitation pattern was established across East to interior Asia during ∼11–9 Ma, distinct with their parallel precipitation variations before this interval. We link the timing of this precipitation divergence to the contemporaneous extensive tectonism associated with the uplift of the northern Tibetan region. This speculation was further corroborated by our high resolution climate modeling. Our study demonstrates an early establishment of modern precipitation patterns in East‐interior Asia at least 9 Ma. Their further precipitation patterns may be subsequently enhanced by global warming events, thus providing corresponding implications for future climate trends in Asia. Key Points: Late Miocene quantitative precipitation reconstruction for different sites in AsiaA modern precipitation pattern between East and Interior Asia established at 11–9 MaIntense upgrowth‐eastward outgrowth of northern Tibetan Plateau is the driving force [ABSTRACT FROM AUTHOR]

Rodents are one of the most abundant and diverse groups of mammals in arid zones. Their population and community dynamics are closely linked to climatic factors and pulses of primary productivity activation. In the future, climatic conditions in arid ecosystems could become more extreme as a consequence of climate change, which could affect the species that inhabit these regions. In this paper, we review the literature on the ecological response of rodents in the world's arid zones, at the population and community levels, to climatological factors (temperature and precipitation), climatic events and the possible impact of climate change. We used the PRISMA protocol to systematically search the literature, and the “vote‐counting” method to count positive, null or negative responses of the rodents. At the population level, rodent density and abundance responded positively to precipitation, while biomass responded negatively and reproduction responded positively to increasing temperature. At the community level, rodent density, biomass and diversity increased after rainfall. El Niño events were positively related to rodent population increases. In contrast, intense storms affected the survival of some species. Rodents with physiological adaptations suited to living in arid areas, for example, the heteromyids, responded positively to precipitation and could suffer fewer negative ecological consequences in the future when exposed to increased temperature and changes in precipitation. [ABSTRACT FROM AUTHOR]

With the increase in global extreme climate events, the frequency of urban waterlogging caused by extreme rainstorms is increasing, resulting in serious economic losses and risk to local residents. Understanding the influence of impervious surfaces on urban waterlogging is of great significance for reducing urban waterlogging disasters. Based on InfoWorks ICM, the urban waterlogging model of Lin'an City was established, and the multi-scenario design method was used to analyze the characteristics and causes of urban waterlogging under different designed rainfall return periods. The results show that the maximum stagnant water depth and area are positively correlated with the proportion of impervious surfaces and rainfall return periods. In addition, urban waterlogging is related to the fragmentation of impervious surfaces, pipeline network, and so on. Based on the findings, it is suggested that impervious surfaces should be placed upstream and along roads where feasible. It is also recommended that the aggregation of impervious surfaces is minimized to prevent urban waterlogging. The results provide technical support and reference for local governments to prevent waterlogging disasters. [ABSTRACT FROM AUTHOR]

Three out of the five highest daily winter rainfall totals on record over Northern England have occurred from 2015 onwards. Heavy rainfall events in the winters of 2013–2014, 2015–2016 and 2019–2020 led to more than 2.8‐billion‐pounds of insurance losses from flooding in the UK. Has the frequency of these events been influenced by human‐induced climate change? Winter rainfall in the UK is extremely variable year‐to‐year, which makes the attribution of rainfall extremes particularly challenging. To tackle this problem, we introduce an UNprecedented Simulated Extreme Ensemble (UNSEEN) approach for the attribution of such extremes, thereby increasing the data available, and apply this approach to five recent flooding events on a regional scale. Using this method, for all five events we found a significant climate signal in the extreme regional rainfall totals immediately preceding the flooding. Results were fairly similar for each—with the events being found to become from 1.4 to 2.6 times more likely. An alternative attribution method that uses a different model with substantially less data did not find significant increases, reinforcing the need for very large amounts of data to detect significant changes in extreme rainfall against a noisy background of natural variability. We also examine how extreme rainfall is changing more broadly across English regions in winter, finding that 1‐in‐10 to 1‐in‐90‐year winter rainfall totals have changed significantly in Northern England. The high volume of data using UNSEEN has enabled us to examine the dynamics of these events, showing that daily extremes in winter are likely to have increased across all the circulation patterns responsible for high rainfall in English regions. [ABSTRACT FROM AUTHOR]

India is dependent on rainfall for agriculture, food security and economic advancements. Spatial and temporal variability of rainfall is well reported, as well as the recent upsurge of extremes due to climate change. In Maharashtra, rainfall intensity varies widely from very high (coasts) to low (west-interior). Extreme value analysis (EVA) of heavy annual rainfall for the various districts of Maharashtra was conducted to ascertain the following for each district: suitable extreme value distribution; extreme (high) annual rainfall; efficacy of gap-filling for missing annual record/s. The suitability of various statistical distributions for representing high annual rainfall values was evaluated using Anderson–Darling test (quantitative), quantile and probability plots (qualitative). The gap-filling exercise resulted in minor variations (<10%) in the estimated extremes, positive as well as negative, for different cases. Therefore, the results of EVA on the actual records are advocated. The suitable distributions for 35 districts are presented in maps and Frechet distribution was adjudged suitable for almost 60% of districts. The estimated extremes for all districts are listed for different return periods for ready reference. These values would be useful for the planning and construction of hydraulic structures, water resources and reservoir management, design and planning of irrigation. Research highlights: Suitable probability distribution functions for modelling the extremes of annual rainfall in each district of Maharashtra have been identified and the parameters have been provided. Extreme values of annual rainfall for each district in Maharashtra for selected return periods have been presented. Evaluation was performed on whether the gaps in the annual rainfall records would affect EVA of the annual rainfall in the districts of Maharashtra. [ABSTRACT FROM AUTHOR]

Arctic precipitation in the form of rain is forecast to become more prevalent in a warmer world but with seasonal and interannual changes modulated by natural modes of variability. Experiencing rapid hydroclimatic changes in the Arctic, Svalbard serves as an ideal study location due to its exposure to oceanic and atmospheric variability in the North Atlantic region. Here we use climate data from paleoproxies, observations, and a climate model to demonstrate that wet and warm extremes in Svalbard over the last two millennia are linked to the presence of atmospheric blocking regimes over Scandinavia and the Ural mountain region. Rainfall episodes lead to the deposition of coarse sediment particles and high levels of calcium in Linnévatnet, a lake in southwest Svalbard, with the coarsest sediments consistently deposited during atmospheric blocking events. A unique annually resolved sediment record from Linnévatnet confirms that this linkage has been persistent over the past 2000 years. Our record also shows that a millennial-scale decline in Svalbard precipitation ended around the middle of the 19th century, followed by several unprecedented extreme events in recent years. As warming continues and sea ice recedes, future Svalbard floods will become more intense during episodes of Scandinavian and Ural blocking. The study links heavy past rainfall events in Svalbard to Scandinavian blocking. Lake sediment data spanning the last 2 millennia warns of worse floods with continued warming, especially intense during atmospheric blocking conditions. [ABSTRACT FROM AUTHOR]

This study examines the spatial and temporal changes in temperature and precipitation extremes from 1951 to 2020 in the West African transboundary Benue River Basin, which frequently experiences impacts from extreme events. The existing studies in the region have relied on sparse observation data, hindering a comprehensive understanding of the spatial variability of climate extremes. High-resolution gridded climate data can be used to explore how climate extremes vary spatially and temporally across transboundary river basins. This study is the first attempt to employ 0.25° × 0.25° daily ERA5 temperature and precipitation data to comprehensively assess spatiotemporal changes of climatic extremes in a West African transboundary river basin. The study applied the non-parametric Mann-Kendall test and Sen's slope method to analyze temperature and precipitation extremes in the Benue River Basin. Results show a significant increase in mean maximum temperature (Tmax) of approximately ≥ 2 °C, indicating rising mean Tmax. Analysis of temperature indices reveals significant positive trends, with the number of warm days (TX90p) increasing by 8%. In contrast, evaluations of maximum 1-day (RX1day) and 5-day (RX5day) precipitation exhibit widespread reductions of 22.5% and 45%, respectively, indicating decreasing rainfall over most areas. Examinations of consecutive dry days (CDD) display higher mean changes in the northern basin extending to western Chad (70 to ≥ 110 days), revealing a link between lower annual precipitation and increased temperatures. However, we also found a basin-wide decrease in CDD ranging from ≤-2 to ≥-10 days. Overall, this study shows that the maximum temperature increases faster than the minimum temperature in the study area and that extreme temperature changes are more pronounced than extreme precipitation. These findings hold crucial implications for understanding the evolving climate dynamics in this vulnerable basin, emphasizing the urgency for adaptive measures in the face of escalating climate challenges. [ABSTRACT FROM AUTHOR]

Estimating the effects of extreme drought on the photosynthetic rates (Pn) of dominant plant species is crucial for understanding the mechanisms driving the impacts of extreme drought on ecosystem functioning. Extreme drought may result from either reduced rainfall amount or decreased rainfall frequency, and the impacts of different patterns of extreme drought may vary greatly. In addition, different grasslands likely appear various sensitivity to different extreme drought patterns. However, there have been no reports on the effects of different extreme drought patterns on dominant species Pn in different grassland types. Here, we conducted multi-year extreme drought simulation experiments (reducing each rainfall event by 66% during the growing season, CHR vs. completely excluding rainfall during a shorter portion of the growing season, INT) in two different grasslands (desert grassland vs. typical grassland) from 2014. The Pn of two dominant species in each grassland was measured in July and August 2017. Both CHR and INT significantly decreased dominant species Pn, with INT causing more negative impacts on Pn regardless of grassland types. The response ratios of Pn in desert grassland were generally higher than that of typical grassland, especially for Leymus chinensis in CHR. These results demonstrated that decreased rainfall frequency had a more negative effect on Pn compared with reduced rainfall amount, with grassland types changing the magnitude, but not the direction, of the effects of extreme drought patterns. These findings highlight the importance of considering extreme drought patterns and grassland types in ecosystem management in the face of future extreme droughts. [ABSTRACT FROM AUTHOR]

Vulnerability evaluation plays a key role in risk assessment and reduction and is essential for defining strategies for climate change adaptation and mitigation. In dealing with the safeguarding of cultural heritage at risk, we are still far from adopting and applying an agreed methodology for vulnerability assessment. With the aim to support practitioners, heritage managers, and policy and decision makers to undertake actions that address the protection of cultural heritage at risk, the methodology set up in the framework of the Interreg Central Europe STRENCH is illustrated and discussed here. Based on three major requirements (susceptibility, exposure, and resilience) and a continuous consultation with local stakeholders, the proposed methodology is applicable for evaluating the vulnerability of built heritage and cultural landscape exposed to hydrometeorological hazards, such as heavy rains, floods, and droughts. The results obtained through its validation on 15 case studies from seven Central European regions are shown to underline the strengths and limitations of the methodological approach. Iterative consultation with local stakeholders was fundamental for the definition of the criteria/subcriteria and related values for the assessment of the requirements. Application to further sites in other contexts would surely contribute to strengthening the reliability of the methodological approach. [ABSTRACT FROM AUTHOR]

This study aims to reveal the long-term station-based characteristics of precipitation in Istanbul, a mega city located on the continents of Europe and Asia, with complex topography and coastline along the Marmara and Black Seas. Using data from five different stations, three located in the European continent and two in the Asian continent, with measurement periods ranging from 72 to 93 years, wet and dry days have been identified, statistics on precipitation conditions during the warm and cold seasons have been generated, categorization based on precipitation intensities has been performed, and analyses have been conducted using extreme precipitation indices. At stations located in the northern part of the city, higher annual total precipitation has been observed compared to those in the south. A similar situation applies to the number of wet days. While during the cold season, the wet and dry day counts are nearly the same across all stations, this condition exhibits significant differences in favor of dry days during the warm season. Apart from dry conditions, "moderate" precipitation is the most frequently observed type across all stations. However, "extreme" events occur significantly more often (6%) during the warm season compared to the cold season (2%). Long-term anomalies in terms of annual precipitation totals have shown similarity between stations in the north and south, which has also been observed in longitudinally close stations. Despite the longer duration of the cold season and stronger temperature gradients, extreme rainfall events are more frequent during the warm season, primarily due to thunderstorm activity. While trend analyses revealed limited significant trends in precipitation intensity categories and extreme indices, the study highlights the importance of comprehensive examination of extreme rainfall events on both station-based and regional levels, shedding light on potential implications for regional climate change. Lastly, during the cold season, the inter-station correlation in terms of annual total precipitation amounts has been considerably higher compared to the warm season. [ABSTRACT FROM AUTHOR]

A large stretch of the east coast of Australia experienced unprecedented rainfall and flooding over a two‐week period in early 2022. It is difficult to reliably estimate the likelihood of such a rare event from the relatively short observational record, so an alternative is to use data from an ensemble prediction system (e.g., a seasonal or decadal forecast system) to obtain a much larger sample of simulated weather events. This so‐called 'UNSEEN' method has been successfully applied in several scientific studies, but those studies typically rely on a single prediction system. In this study, we use data from the Decadal Climate Prediction Project to explore the model uncertainty associated with the UNSEEN method by assessing 10 different hindcast ensembles. Using the 15‐day rainfall total averaged over the river catchments impacted by the 2022 east coast event, we find that the models produce a wide range of likelihood estimates. Even after excluding a number of models that fail basic fidelity tests, estimates of the event return period ranged from 320 to 1814 years. The vast majority of models suggested the event is rarer than a standard extreme value assessment of the observational record (297 years). Such large model uncertainty suggests that multi‐model analysis should become part of the standard UNSEEN procedure. [ABSTRACT FROM AUTHOR]

The diversity of flood‐generating mechanisms superimposed on catchment physiographic features with non‐stationary meteorological drivers makes future flood hazard assessment a grand challenge. To date, many studies have examined patterns in rainfall and streamflow, but far fewer have investigated trends in the other drivers of flooding. The complex transfer function between precipitation and flooding makes it potentially misleading to simply look at the change in rainfall to express the hazard. Furthermore, there are very few studies that have directly used output from km‐scale climate models in flood modeling. Coarse resolution climate data sets may not credibly resolve local climate and weather extremes. Changes in rainfall distribution and antecedent moisture over extended time periods due to climate change have so far been ignored when assessing urban pluvial flood risk. In this paper, an urban flood hazard assessment framework using the latest 2.2 km resolution UK Climate Projections Local is proposed. Global warming induced changes in pluvial flood risks under RCP8.5 are projected, focusing on the impact of changing precipitation patterns and soil moisture dynamics on flood generation. Results indicate a strong increase in the frequency of occurrence of extreme floods, and the resultant future (2060–2080) annual flood volume is expected to increase up to 52.6% relative to 1980–2000 over a major UK urban region, and these patterns are likely to hold more generally elsewhere in the UK. Shifts to a later occurrence of extreme flooding is identified under global warming. Previous studies that have neglected soil moisture dynamics are unlikely to give accurate flood estimates. Plain Language Summary: The future flood hazard status over the major UK urban region of Bristol (domain size ∼746 km2) is evaluated using the latest 12‐member UK Climate Projections Local ensemble rainfall data set at the hourly and kilometer scale. A total of 30,098 rainfall events from an equivalent 720 years of climate data are identified and used for flood modeling. Impact of changing precipitation pattern and soil moisture dynamics on surface water floods are evaluated, and the interaction between precipitation, inundation, infiltration, and soil wetness are handled simultaneously at a spatial resolution of ∼30 m or less using an improved hydrodynamic model (LISFLOOD‐FP). Our findings highlight a shift toward a later seasonal occurrence of extreme flooding under global warming. Specifically, a large proportion of future extreme flood hazards is projected to manifest in December, contrasting with historical trends where most extreme events occurred in November. Extreme precipitation can be magnified in rainy seasons due to amplified moisture convergence, while in dry periods limited moisture availability may offset precipitation increases. Despite an overall increase in the total annual rainfall volume, the future summer is anticipated to be much drier due to limited rainfall availability, leading to a further reduction in soil moisture availability. Key Points: Shifts to a later seasonal occurrence of extreme flooding is identified under global warming in the UKIncrease in annual total rainfall leads to a disproportionate rise in the resultant flood volumeImpact of the antecedent soil moisture on flood generation shows seasonality [ABSTRACT FROM AUTHOR]

The aim of this investigation is to identify a representative set of climate model projections for the Awash Basin using accessible general circulation model (GCM) predictors from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive. Various approaches were employed to systematically shortlist and select suitable climate models under two representative concentration pathways (RCPs). For RCP4.5, 105 GCMs were used and for RCP8.5, 78 GCMs were used to select the best performance models for a climate change impact study in this basin. These approaches are combined in the current study to create a three-step sequential procedure for choosing climate models: (1) initial selection of climate models based on the range of projected changes in climatic means, (2) refined selection based on the range of projected changes in climatic extremes, and (3) final selection based on the ability of the climate models to simulate historical climate changes between 1971–2000 and 2071–2100 were analyzed. Five corners of possible extreme future scenarios (wet-warm, wet-cold, dry-warm, dry-cold, and the 50th percentile of the temperatures) were used. A total of 25 GCMs were selected for RCP4.5 and RCP8.5 based on the range of expected mean temperature and rainfall change. Based on the range of extreme changes, 10 GCMs were chosen. Five GCMs were ultimately selected for each RCP4.5 and RCP8.5 by merging all three stages. The findings of this study will contribute valuable insights to better understand and adapt to the impacts of climate change in the Awash River Basin and similar regions. [ABSTRACT FROM AUTHOR]

This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change. [ABSTRACT FROM AUTHOR]

In the railway sector, rolling stock and infrastructure must be maintained in perfect condition to ensure reliable and safe operation for passengers. Climate change is affecting the urban and regional infrastructure through sea level rise, water accumulations, river flooding, and other increased-frequency extreme natural situations (heavy rains or snows) which pose a challenge to maintenance. In this paper, the use of artificial intelligence based on predictive maintenance implementation is proposed for the early detection of degraded conditions of a bridge due to extreme climatic conditions. For this prediction, continuous monitoring is proposed, with the aim of establishing alarm thresholds to detect dangerous situations, so restrictions could be determined to mitigate the risk. However, one of the main challenges for railway infrastructure managers nowadays is the high cost of monitoring large infrastructures. In this work, a methodology for monitoring railway infrastructures to define the optimal number of transductors that are economically viable and the thresholds according to which infrastructure managers can make decisions concerning traffic safety is proposed. The methodology consists of three phases that use the application of machine learning (Random Forest) and artificial cognitive systems (LSTM recurrent neural networks). [ABSTRACT FROM AUTHOR]

Global climate change, with warming as its main feature, has altered the spatial-temporal evolution of factors such as precipitation and temperature that can cause meteorological disasters. The complex and changeable climate has led to frequent natural disasters, while the frequency and intensity of extreme climate events have also significantly increased, posing an enormous threat to societal production and human life. As the most important geoecological transitional zone of mainland China, the stability of agricultural production in China's north–south transitional zone is crucial for ensuring food security under climate change. With the use of daily precipitation and potential evapotranspiration data from 1961 to 2018, this study focused on analysing disturbances such as extreme precipitation and drought disasters at different time scales during the winter wheat and summer maize growing seasons in the north–south transitional zone of China from an agricultural production perspective and attempted to answer the following questions: first, from an agricultural production perspective, what are the temporal and spatial distribution patterns of extreme precipitation and arid climate events in the north–south transitional zone? Second, which areas are at high risk of being disturbed by different types of meteorological disasters and require increased attention? The results indicated that (1) in terms of the overall temporal variation, the degree of extreme precipitation and drought stress faced by agricultural production in the region is decreasing. However, the temporal variation at each station in the north–south transitional zone was not completely consistent with the overall trend, and both increasing and decreasing trends were observed. The sites exhibiting an increase overlapped with typical regions of the north–south transitional zone to varying degrees, indicating that the typical regions represented not only theoretical potential risk areas under climate change but also suffered from meteorological disaster disturbances. (2) The precipitation distribution during the winter wheat growth period in the south–north transitional zone was uneven and varied significantly. High values of extreme precipitation indices during the winter wheat growth period were mainly concentrated in the southern part of the eastern section of the north‒south transitional zone. The precipitation distribution during the summer maize growth period significantly differed, with the highest amount of heavy rain and largest number of rainstorm days concentrated in the southeastern part of the north‒south transitional zone. The spatial distribution of the drought frequency in the north–south transitional zone, as indicated by the monthly standardized precipitation evapotranspiration index (SPEI1), showed that the areas with high total drought frequencies were mainly concentrated in northeast Jiangsu, southeast Henan, and north Anhui, which primarily experienced light drought. The central part of Jiangsu Province exhibited a high frequency of moderate drought, while southern Jiangsu Province and southwestern Shaanxi Province were prone to severe drought. Additionally, southeastern Hebei and eastern Henan were identified as areas with a high frequency of extreme drought. Finally, the central region of Sichuan Province was characterized by both severe and extreme drought conditions. Based on the SPEI12-derived spatial distribution of the drought frequency in the north–south transitional zone, the areas with a high total drought frequency were mainly concentrated in central and eastern Henan, southeast Shaanxi, southeast Shandong, and central Sichuan, which primarily experienced light to moderate drought. The northwestern part of Jiangsu, the southern part of Hebei, and the western part of Shandong are regions with a high frequency of severe drought, while the eastern part of Henan is an area with high frequencies of both severe and extreme drought. (3) High-value areas of extreme precipitation and drought disturbance in the north–south transitional zone overlapped with the edge of the transitional zone to varying degrees. Approximately 63.58% of the north‒south transitional zone of China was characterized by moderate or high stress levels, primarily concentrated along the southern boundary and central core area, and nearly 39.5% of all counties experienced two or more types of disaster stresses. [ABSTRACT FROM AUTHOR]

The present paper aims to study the Wachau Valley in Austria as a representative Cultural Landscape under threat from extreme hydrometeorological hazards linked to climate change. The primary objective is to investigate the impacts and assess the vulnerability associated with the events of heavy rain and flooding. The methodology employed consists of an investigation of recorded past events impacting the Wachau; a vulnerability ranking system; a climate time series analysis based on earth observation products; and future hazard maps at territorial level, developed with outputs from regional and global climate models. The investigation we carried out provides a vulnerability assessment of two terraced areas with a surface of about 10,000 m2 in total, characterized by the presence of dry stone walls, with different state of conservation in the Municipality of Krems (Wachau). In addition, climate projections at territorial level for the extreme climate indices R20mm, R95pTOT, and R×5day—selected for investigating the likelihood of increases/decreases in events of heavy rain and large basin flooding—are provided, with a spatial resolution of ~12 km for the near and far future (2021–2050; 2071–2100) under stabilizing (RCP 4.5) and pessimistic (RCP 8.5) scenarios. The results indicate a general increase for the three indices in the studied areas during the far future under the pessimistic scenario, suggesting a heightened risk of heavy rain and flooding. These findings aim to inform policymakers and decision-makers in their development of strategies for safeguarding cultural heritage. Furthermore, they serve to assist local stakeholders in enhancing their understanding of prioritizing interventions related to preparedness, emergency response, and recovery. [ABSTRACT FROM AUTHOR]

Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring in the Vojvodina region, covering both past (1971–2019) and future (2020–2100) periods. We utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, selecting the RCP8.5 scenario to examine future Rx3day amounts. The probabilities of occurrences of Rx3day were modeled using the GEV distribution, while the number of events where Rx3day in spring exceeds specific thresholds was modeled using the Poisson distribution. The results indicate that Rx3day with a ten-year return period during the spring months is expected to increase by 19% to 33%. Additionally, the probabilities of having more than one event where Rx3day exceeds thresholds are projected to rise by 105.6% to 200.0% in the future compared to the historical period. The analysis comparing the design values of Rx3day with future projections for the period 2020–2100 revealed that 51 drainage systems are likely to function without difficulties under future climate conditions. However, for the remaining 235 drainage systems, an increased risk of pluvial flooding was identified, as their design precipitation amounts are lower than the future projections. This study reveals that analyzing extreme rainfall events in the context of climate change yields crucial information that facilitates effective planning and policy making in water management, particularly flood protection. [ABSTRACT FROM AUTHOR]

Climate change is threatening global food security by instigating hot and dry spells of varying intensity and frequency, driven by the increased atmospheric concentration of greenhouse gasses. Agriculture is the main economic driver in North-Central Nigeria; however, the influence and contribution of climate extremes in inducing maize yield variations are not well reported. In this study, 26 agriculturally related extreme climate indices were derived using a 39-year (1982 − 2020) daily temperature and rainfall data collected from 25 weather stations. Stepwise regression was used to identify the nine most influential climate extreme indices that elucidate the variations in rainfed maize yield. Across all weather stations, a gradual drying was observed, supported by statistically significant (p < 0.05) declining trends in most rainfall-related extreme indices, particularly consecutive wet days and heavy rainfall days. Most temperature-related extreme indices showed notably higher and statistically significant warming rates (p < 0.05), except for the cold spell duration indicator and cold nights. Warm nights, featuring significantly increasing rates of 0.12–1.1 days per decade, were the most influential factor contributing to a reduction in maize yield by 19.6 kg/ha per unit increase. Additionally, maize yield increased at a rate of 32.5 kg/ha per unit increase in the daily diurnal temperature. The selected climatic extremes from the stepwise regression analysis demonstrated a good predictive capacity for rainfed maize yield variations. The study showed that North-Central Nigeria is particularly susceptible to severe droughts and heat waves that can seriously deteriorate sustainable maize production in the future. [ABSTRACT FROM AUTHOR]

Global gridded data sets of observed extremes indices underpin assessments of changes in climate extremes. However, similar efforts to enable the assessment of indices relevant to different sectors of society have been missing. Here we present a data set of sector‐specific indices, based on daily station data, that extends the HadEX3 data set of climate extremes indices. These additional indices, which can be used singly or in combinations, have been recommended by the World Meteorological Organization and are intended to empower decision makers in different sectors with accurate historical information about how sector‐relevant measures of the climate are changing, especially in regions where in situ daily temperature and rainfall data are hard to come by. The annual and/or monthly indices have been interpolated on to a 1.875° × 1.25° longitude‐latitude grid for 1901–2018. We show changes in globally‐averaged time series of these indices in comparison with reanalysis products. Changes in temperature‐based indices are consistent with global scale warming, with days with Tmax > 30°C (TXge30) increasing virtually everywhere with potential impacts on crop fertility. At the other end of the scale, the number of days with Tmin < −2°C (TNltm2) are reducing, decreasing potential damage from frosts. Changes in heat wave characteristics show increases in the number, duration and intensity of these extreme events in most places. The gridded netCDF files and, where possible, the underlying station indices are available from https://www.metoffice.gov.uk/hadobs/hadex3 and https://www.climdex.org. Plain Language Summary: To be able to assess changes in extreme temperature and rainfall events across the globe, data sets which capture characteristics of these extreme events are required. The use of indices for these characteristics further enables both data sharing and the comparison of events across the world. Extreme events have impacts across human health, our infrastructure and the natural environment. So far there has not been a global product which presents indices which are relevant for different sectors of our society, including health, agriculture and water resources. In this work we present an extension to an existing data set of extremes indices, HadEX3, by including indices defined by the World Meteorological Organization which were developed with sector specific applications in mind. We have used the same approach and methodology, and where possible the same underlying daily temperature and rainfall observations. The temperature indices show changes consistent with global scale warming, with heat wave characteristics showing increases in the number, duration and intensity of these extreme events in most places. The data files are available for use by interested researchers in their work. Key Points: We present a sector specific extension to a data set of gridded temperature and precipitation extremesThis first quasi‐global product of these indices will support decision makers in a wide range of sectorsLong‐term changes show increases in intensity, frequency, and duration of warm extremes, and corresponding decreases in cool extremes [ABSTRACT FROM AUTHOR]

One measurement modality for rainfall is a fixed location rain gauge. However, extreme rainfall, flooding, and other climate extremes often occur at larger spatial scales and affect more than one location in a community. For example, in 2017 Hurricane Harvey impacted all of Houston and the surrounding region causing widespread flooding. Flood risk modeling requires understanding of rainfall for hydrologic regions, which may contain one or more rain gauges. Further, policy changes to address the risks and damages of natural hazards such as severe flooding are usually made at the community/neighborhood level or higher geo-spatial scale. Therefore, spatial-temporal methods which convert results from one spatial scale to another are especially useful in applications for evolving environmental extremes. We develop a point-to-area random effects (PARE) modeling strategy for understanding spatial-temporal extreme values at the areal level, when the core information are time series at point locations distributed over the region. [ABSTRACT FROM AUTHOR]

Abstract Contrasting the extensive research on summer atmospheric rivers (ARs) in the Antarctic Peninsula (AP), winter AR impacts are less understood. This study examines a unique warming event from 1 to 3 July 2023, using in situ winter observations and ERA5 reanalysis. On 2 July, Frei station experienced an extreme warm event with a temperature of 2.7°C and a significant rise in the freezing level, coinciding with winter rainfall. A pressure dipole pattern over the AP, with contrasting circulations over Bellingshausen and Weddell Seas, facilitated an AR, carrying warm, humid air initially from South America/Atlantic and then the southeast Pacific. This shift resulted in anomalous water stable isotope composition in precipitation. Trends suggest a strengthening winter pressure dipole, associated with increased AR frequency and higher temperatures in northern AP. These findings highlight the importance of winter observations in exploring AR impacts, bridging knowledge gaps about winter AR behaviors.

Intensification of short‐duration rainfall extremes contributes to increased urban flood risk. Yet, it remains unclear how upper‐tail rainfall statistics could change with regional warming. Here, we characterize the non‐stationarity of rainfall extremes over durations of 1–24 hr for the rapidly developing coastal megalopolis of the Greater Bay Area, China. Using high‐resolution, multi‐source, merged and gridded data we observe greater increases in rainfall intensities over the north‐central part of the region compared with the southern coastal region. Our results show, for the first time, that urbanization nonlinearly increases rainfall intensities at different durations and return periods. Over short durations (≤3‐hr) and short return periods (2‐yr), urban areas have the greatest scaling rates (≥19.9%/°C). However, over longer durations (≥9‐hr) rural areas have greater scaling rates, with a lower degree of dependency on both durations and return periods. Plain Language Summary: Short‐duration (sub‐daily) rainfall extremes are major drivers of flash floods and hence significant disruptions to society. Previous modeling and statistical studies show that urbanization intensifies short‐duration rainfall extremes. However, there has been less attention to regional variations in rates of rainfall intensification under a warming climate, particularly for extreme events with return periods that are comparable to or longer than the years of record. In this study, we investigate changes in rainfall extremes over the Greater Bay Area, China using long records of high‐resolution data merged from gauge networks, satellite observations, and reanalysis products. This enables us to evaluate changes in low‐frequency rainfall extremes (2‐ to 100‐yr return periods) over different land surfaces, under a warming climate. We find that increases in rainfall extremes significantly depend on the duration and return period of events, with the largest scaling occurring for short‐duration "nuisance" rainfall intensities over urban areas. Key Points: Non‐stationarities of sub‐daily rainfall extremes over a coastal megalopolis exhibit marked land cover and duration dependenciesUrban areas show more prominent intensification of events over short durations and short return periods compared with rural areasRural areas show smaller nonstationary variabilities across durations and return periods and a lower peak scaling rate than urban areas [ABSTRACT FROM AUTHOR]

During 26–27 June 2022, mainly influenced by three mesoscale vortices, central‐eastern China (particularly for Henan and Shandong) experiences the first widespread torrential rainfall event of the 2022 flood season (maximum 24‐hr accumulated precipitation is ∼380.9 mm), resulting in severe social impacts. The three mesoscale vortices form and sustain under favorable background conditions, mainly including a strong upper‐level divergence, an intense middle‐level warm advection, and a powerful lower‐level convergence associated with a low‐level jet. Among the vortices, the vortex which forms over Shandong, lasts for ∼9 hr, and makes a much larger contribution than the other vortices to the accumulated precipitation, is defined as the primary vortex. More than a half of the hourly precipitation peaks in this event appear in the life span of the primary vortex, which is closely related to the variations of the vortex in its cyclonic‐vorticity and vertical extent. Backward trajectory analysis indicates that air particles originating from the lower troposphere southwest of the primary vortex contribute the most to its formation (∼82.7%). These air particles mainly experience a notable increase in their cyclonic‐vorticity due to convergence‐related vertical stretching, which directly renders the formation of primary vortex. During the whole life span of the primary vortex, convergence‐related vertical stretching is the most favorable factor for its development/sustainment, and the convection‐related vertical transport of cyclonic vorticity ranks second; whereas, the horizontal transport is the most detrimental factor. Moisture budget shows that Southeast China is the most important moisture source for this event (accounting for ∼48.9%). Plain Language Summary: Due to global warming, extreme weather and climate events occur with a higher frequency and a stronger intensity in China. Of these, a widespread heavy rainfall occurs in central‐eastern China during 26–27 June 2022, which causes severe impacts on society. Our attention is drawn to understand how the extreme rainstorm forms and where the main moisture sources are located. For this, we analyze this event by using automatic station data and reanalysis data and discover that three mesoscale vortices are the primary reason for the heavy rainfall. Among the vortices, the one with the longest life span contributes the most to the accumulated precipitation. The strong convergence in the lower troposphere dominates the formation/maintenance of the vortex. Southeast China continuously supplies moisture for the rainfall (∼48.9% in contribution). This research is helpful to enhance the understanding of this type of heavy rainfall event. Key Points: Affected by three mesoscale vortices, central‐eastern China experiences torrential rainfall, with a rainfall peak of ∼380.9 mm observedThe primary vortex, which is produced by vertical stretching, is directly related to more than a half of the hourly rainfall peaksSoutheast China provides ∼48.9% of the moisture for the rainfall, which is mainly transported by the Southwesterly/southerly wind [ABSTRACT FROM AUTHOR]

In May 2023, a major snowstorm occurred in Canaan Valley, West Virginia, dropping 20 inches of snow. This event was unusual because it contradicted global and local warming trends that typically decrease snowfall in warmer months. While some people use events like this to deny global warming, there is evidence that extreme weather events are increasing in frequency and intensity alongside overall warming. The Canaan Valley has a cold, humid-type climate, and its high elevation allows for more snowfall. The storm was well-forecasted, and weather watchers can analyze how forecasters handle such unusual events. [Extracted from the article]

The study used a hybrid approach to evaluate the performance of 20 global climate models (GCMs) from CMIP6 in reproducing 20 extreme temperature and precipitation indices over Pakistan. This study first analysed the future simulations of extremes and discarded the GCMs whose projections fell outside the 95% confidence interval. The remaining GCMs' performance was evaluated using the Kling Gupta Efficiency‐based criteria. The changes in extreme climatic events in Pakistan were projected using the multi‐model ensemble (MME) median of the selected GCMs for four shared socioeconomic pathways (SSPs) in two future periods, 2020–2059 and 2060–2099. Four GCMs' showed inconsistency in projecting future climatic extremes and were discarded initially. The past performance of the remaining GCMs revealed EC‐Earth3‐Veg‐LR, GFDL‐ESM4, MRI‐ESM2‐0 and NOR‐ESM2‐MM to be effective in reproducing extreme indices for the historical period. The MME median of the selected GCMs showed a gradual increase in most of the temperature and precipitation extreme indices in the future periods for all SSPs across the country. Specifically, it showed a higher increase in daily maximum temperature (TXx) by 4.5–5°C, daily minimum temperature (TNn) by more than 4.5°C, consecutive days with a temperature higher than the 95th percentile (WSDI) by >160 days, one‐day maximum rainfall by 9–15 mm and days with precipitation above the 95th percentile by >50 mm in northern high‐elevated areas during 2060–2099 for SSP585. Similarly, a higher increase in TXx by 4.5–5°C, TNn by >4.5°C, WSDI by 140 days and tropical nights by 40–60 days was also found in the western arid region during 2060–2099 for SSP585. The study highlights that northern high‐elevated and western arid regions are at a higher risk of extreme temperatures and precipitation due to climate change. [ABSTRACT FROM AUTHOR]

Climate change is affecting the global hydrological cycle, causing drastic changes in precipitation patterns. Extreme climatic events are becoming more frequent and intense than in the past, leading to water-level fluctuations and affecting aquatic ecosystems. Semiarid regions are very susceptible to changing climate. We analyzed a 10 years dataset from a tropical semiarid reservoir during extreme hydrological events (heavy rains and prolonged drought), and evaluated phytoplankton functional responses to environmental conditions. We found, as hypothesized, that phytoplankton functional structure change in a temporal scale due to water–volume fluctuation induced by the rainfall pattern. Depth and inorganic material acted as environmental filters selecting phytoplankton groups. High water level seems to improve water quality and low water level worsen it. Colonial and filamentous cyanobacteria dominate the wet period; however, it may have a critical threshold during severe periods of drought, which will lead to dominance of groups well adapted to low light conditions and with mixotrophic metabolism. Phytoplankton functional approaches can simplify phytoplankton identification and reflect better the environmental conditions than the taxonomic approach. Therefore, these approaches can help to understand the shifts in aquatic ecosystems under extreme hydrological events and predict functional response of phytoplankton being an important tool to water management and conservation. [ABSTRACT FROM AUTHOR]

Contextualizing historic hydroclimate variability in the southeastern USA has relied significantly on proxy indicators such as tree-ring data, and while previous studies have reconstructed total precipitation, less is known about the historic variability of intense rainfall events, which are climatologically and ecologically important and distinct from non-intense rainfall events. Here, a combined longleaf pine and shortleaf pine adjusted latewood chronology spanning 1770–2020 was used to reconstruct July–September total precipitation and intense rainfall event precipitation in central North Carolina, USA. The adjusted latewood chronology explains 46% of the variance in July–September total precipitation and 37% of the variance in July–September intense rainfall event precipitation during the 1940–2020 instrumental period with intense rainfall event precipitation amounts comprising 52% of total precipitation amounts. The models provide context about historic hydroclimate variability at this location and suggest overall stability in both total and intense rainfall event precipitation amounts during the instrumental and reconstruction periods with three identical significant regime shifts during 1770–2020: 1770–1935, 1936–1959 (above-average moisture), 1960–2020 (below-average moisture). To compare model strength, the models were split into early (1940–1980) and late (1981–2020) analysis periods with the intense rainfall event precipitation model exhibiting greater skill during the early analysis period. The early analysis period has a greater frequency and magnitude of intense rainfall events, and these results suggest the influence of intense rainfall event precipitation on latewood growth and the potential susceptibility of reconstruction models to decreased skill and/or error with differing frequencies of extreme events, a finding of particular importance to future dendroclimatic research. [ABSTRACT FROM AUTHOR]

Background: Treeline ecotones of Mediterranean ecoregions have been affected by the increasing intensity and severity of droughts. Even though the effect of droughts on forest dynamics has been widely documented, knowledge is relatively scarce of how extreme climate episodes affect the hydraulic structure and, therefore, the physiology of woody plants. The Mediterranean Andes have experienced an uninterrupted period of drought since 2010, including an extremely dry year in 2019 with approximately 80% rainfall deficit. Here, we investigated shifts in wood anatomical and physiological traits of Kageneckia angustifolia, an endemic treeline species, in response to this drought period. Methods: We evaluated the xylem plasticity of three K. angustifolia populations across their natural distribution (31–35° SL) based on anatomical (vessel structure and distribution) and physiological (intrinsic water-use efficiency) variables in the tree rings. We focused on the period 2000–2020 that corresponds to before the megadrought (2000–2007), (ii) megadrought (2008–2018) and (iii) hyperdrought (2019–2020). The variables were annualized and analyzed by linear mixed-effects models. Results: Our results provide insights to the anatomical and physiological mechanisms underlying the resilience of treeline forests to persistent droughts in central Chile. We found that the extreme drought in 2019–2020 triggered shifts in vessel size and frequency that increased hydraulic safety. These significant shifts in vessel traits occurred in parallel with a decrease in pit aperture area and an increase in water-use efficiency, further increasing the resilience of K. angustifolia to extreme drought stress. Conclusions: Our results revealed coordinated shifts in vessel size and frequency and water-use efficiency in response to the megadrought, thereby reducing vulnerability to hydraulic failure. The apparent resilience of K. angustifolia to extreme droughts suggests that this adaptation to drought stress may increase its ability to tolerate novel climatic conditions of treeline environments of the Mediterranean Andes, although it is not clear whether these adaptations will be sufficient to persist in scenarios that predict intensification of climate stress. Finally, our results provide empirical evidence that integrating wood anatomical and physiological traits facilitates the understanding of resilience mechanisms that treeline forests develop in the face of increasing drought stress. [ABSTRACT FROM AUTHOR]

The topography significantly influences local climate precipitation and the intensity of precipitation events, yet the specific differences in its elevational effects require further understanding. This study focuses on precipitation in Zhengzhou City, Henan Province, utilizing hourly data and a topographic elevation precipitation increment model to assess the impact of topography on local climate precipitation and extreme heavy rainfall events. The results indicate that the daily precipitation attributed to topographic elevation in Zhengzhou in July was 0.21 mm, accounting for 4.9% of the total precipitation. In the extreme heavy rainfall event on 20 July 2021 ("7.20" event), the precipitation due to topographic elevation reaches 48.7 mm, constituting 15.8% of the total precipitation. Additionally, numerical simulations using the Weather Research and Forecasting (WRF) model for the 20–21 July 2021 rainfall event in Zhengzhou show that the WRF model effectively reproduces the spatiotemporal characteristics of the precipitation process. The simulated topographic elevation precipitation intensity is 49.8 mm/day, accounting for 16.6% of daily precipitation, closely resembling observational data. Sensitivity experiments further reveal that reducing the heights of the Taihang Mountains and Funiu Mountains weakens the low-level easterly winds around Zhengzhou. Consequently, as the center of the heavy rainfall shifts northward or westward, the intensity of topographic elevation-induced precipitation decreases to 7.3 mm/day and 12.9 mm/day. [ABSTRACT FROM AUTHOR]