Extreme Daily Precipitation Research Articles

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

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

Extreme Precipitation Over the Southern Slope of the Tibetan Plateau and the Associated Atmospheric Circulation Anomalies

AbstractThe southern slope of the Tibetan Plateau (SSTP) is one of the rainiest regions in the world where geological hazards caused by extreme precipitation often occur. This study investigates the characteristics and mechanisms of extreme precipitation over SSTP from June to September during 2001–2020 using Global Precipitation Measurement satellite observation. The extreme precipitation days are defined as the days with top 5% of regional‐mean daily precipitation over SSTP in this period, which has an average precipitation of 27.2 mm/d. Averaging over the extreme precipitation days, precipitation peaks at an altitude of about 300 m, coinciding with the climatological maximum precipitation, but with a much larger value of 37.2 mm/d than the climatology of 11.9 mm/d. Composite analysis of circulations on extreme days reveals significant circulation anomalies in both the lower and upper troposphere. Specifically, the lower‐tropospheric circulations are characterized by significant westerly anomalies over northern India, and the upper‐tropospheric circulations are characterized by northerly anomalies over the central Tibetan Plateau, which are statistically independent. The lower‐tropospheric westerly anomalies blowing toward SSTP are blocked by the topography, favoring extreme precipitation over SSTP. The upper‐tropospheric northerly anomalies, on the other hand, correspond to anomalous northeasterlies north of SSTP in the middle troposphere and southeasterlies to the south in the lower troposphere, and the convergence of these circulation anomalies favors extreme precipitation over SSTP. Lastly, the lower‐tropospheric westerly and upper‐tropospheric northerly anomalies, respectively, correspond to less precipitation over the South Asian monsoon region and the Tibetan Plateau.

Projecting future excess deaths associated with extreme precipitation events in China under changing climate: an integrated modelling study

Climate-change-induced extreme precipitation events have attracted global attention; however, the associated excess deaths burden has been insufficiently explored and remains unclear. We first defined an extreme precipitation event for each county when the daily total precipitation exceeded the county-specific 99·5th percentile of the daily precipitation from 1986 to 2005; then we estimated the associations between extreme precipitation events and cause-specific deaths in 280 Chinese counties using a two-stage time-series model. Second, we projected the excess deaths related to extreme precipitation events by combining the bias-corrected multi-model precipitation predictions derived under different combined emission-population scenarios of three representative concentration pathways (RCPs; RCP2·6, RCP4·5, and RCP8·5) and three shared socioeconomic pathways (SSP2, a business-as-usual scenario) populations (S1, low fertility rate; S2, medium fertility rate; and S3, high fertility rate). We quantified the climate and population contributions to the changes of future excess deaths nationwide and by climatic zones. Compared with the non-extreme precipitation days, the percentage increase of deaths associated with exposure to extreme precipitation days is 13·0% (95% CI 7·0-19·3) for accidental cause, 4·3% (2·0-6·6) for circulatory disease, and 6·8% (2·8-10·9) for respiratory disease. The number of annual average excess deaths related to extreme precipitation events during 1986-2005 was 2644 (95% CI 1496-3730) for accidental cause, 69 (33-105) for circulatory disease, and 181 (79-279) for respiratory disease. In the 2030s, the total number of excess deaths of these three causes will increase by 1244 (43%), 1756 (61%), and 2008 (69%) under RCP2·6, RCP4·5, and RCP8·5 scenarios combined with a medium-fertility-rate population (SSP2-S2), respectively, but will decrease by 3% under RCP2·6-SSP2-S2 and increase by 25% under RCP8·5-SSP2-S2 in the 2090s. Humid and water-limited regions in subtropical, middle-temperate, and plateau climate zones will face highly increased risks. Climate and population factors contributed disproportionally among the five climate zones. This study is the largest integrated projection exploring the disease burden associated with extreme precipitation events. The excess deaths will be amplified by climate and population changes. Improving mitigation and adaptation capacities is crucial when responding to precipitation extremes. National Natural Science Foundation of China and Wellcome Trust.

Breaking Rossby waves drive extreme precipitation in the world’s arid regions

More than a third of the world’s population lives in drylands and is disproportionately at risk from hydrometeorological hazards such as drought and flooding. While weather systems governing precipitation formation in humid regions have been widely explored, our understanding of the atmospheric processes generating precipitation in arid regions remains fragmented at best. Here we show, using a variety of precipitation datasets, that Rossby wave breaking is a key atmospheric driver of precipitation in arid regions worldwide. Rossby wave breaking contributes up to 90% of daily precipitation extremes and up to 80% of total precipitation amounts in arid regions equatorward and downstream of the midlatitude storm tracks. The relevance of Rossby wave breaking for precipitation increases with increasing land aridity. Contributions of wave breaking to precipitation dominate in the poleward and westward portions of arid subtropical regions during the cool season. Our findings imply that Rossby wave breaking plays a crucial role in projections and uncertainties of future precipitation changes in societally vulnerable regions that are exposed to both freshwater shortages and flood hazards.

Simulating springtime extreme rainfall over Southern East Asia: unveiling the importance of synoptic-scale activities

This study investigates the influence of synoptic-scale activities on extreme precipitation during March–April–May (MAM) over Southern East Asia (SEA) using observational data and compares the results with the outputs from 20 Coupled Model Intercomparison Project phase 6 (CMIP6) historical runs. Observations show that SEA intense daily precipitation in MAM is linked to enhanced upper-level synoptic-scale waves; these disturbances are associated with significant anomalous temperature advection as well as moisture flux convergence, creating favorable conditions for extreme rainfall. Furthermore, it is found that a temperature advection index (TAI) can be utilized to characterize such synoptic-scale activities. Inspection of CMIP6 historical runs reveals that, among 20 models, 13 models perform well in accurately capturing the observed SEA rainfall pattern; such extreme events are also closely linked to TAI in the model environment. Overall, observed (simulated) results show that 78% (75%) of extreme events in the Yangtze River Basin–South Korea–south of Japan region can be attributed to positive TAI. Additionally, the related circulation anomalies such as the upper-level synoptic-scale wave feature, temperature advection, and moisture anomalies from these models closely resemble those observed during extreme precipitation days in SEA. Our findings suggest that TAI can effectively indicate both the frequency and intensity of extreme rainfall events in SEA, along with the associated synoptic-scale activities. Further study reveals a close lead-lag correlation between TAI and rainfall patterns over SEA. This correlation is characterized by eastward-propagating wave trains across the entire troposphere. Consequently, TAI not only acts as a benchmark for quantifying synoptic-scale extreme rainfall in SEA but also shows potential in predicting SEA rainfall linked to synoptic-scale disturbances.

Interannual relationship of the extreme precipitation dipole mode over South China and Indochina Peninsula with the tropical Pacific-Indian Ocean sea surface temperature anomaly in May

This study investigates the interannual relationship of extreme precipitation days (EPD) over South China (SC) and Indochina Peninsula (ICP) with tropical Pacific-Indian Ocean Sea surface temperature (SST) anomalies during May, utilizing observations, reanalysis, and Coupled-Model Intercomparison Project 6 (CMIP6) model outputs. The results uncover a dipole mode in the interannual variations of May EPD over SC and ICP, characterized by an east–west inverse pattern. This dipole mode is significantly attributed to large-scale circulation anomalies induced by tropical Pacific–Indian Ocean mode (PIM). During the positive phase of PIM, SST anomalies in the tropical east-central Pacific and western Indian Oceans are anomalously warm, contrasted with negative SST anomalies in the western Pacific, leading to anomalous Walker circulations. Accordingly, two robust anticyclones appear in the lower levels of the Northwest Pacific and the Bay of Bengal, respectively. The southwesterlies on the western flank of the anticyclone in the Northwest Pacific cause moisture convergence over SC, favoring the occurrence of extreme precipitation in SC. Conversely, the anticyclonic circulation centered at the Bay of Bengal is not conducive to the transport of warm water vapor from oceans to ICP, resulting in reduced occurrence of extreme precipitation there. The results derived from CMIP6 models unequivocally support the notion that the dipole mode is predominantly shaped by large-scale circulation anomalies induced by PIM. Our results underscore the importance of accounting for the collective impact of oceanic drivers in the tropics, laying a scientific foundation for enhanced precision in simulating extreme precipitation across SC and ICP.

Differing Contributions of Anthropogenic Aerosols and Greenhouse Gases on Precipitation Intensity Percentiles Over the Middle and Lower Reaches of the Yangtze River

AbstractIn June–July 2020, the middle and lower reaches of the Yangtze River (MLYR) were hit by a Meiyu event characterized by a long duration, abundant precipitation, and frequent heavy rainfall, resulting in destructive flooding. We found that the extreme cumulative precipitation in 2020 was mainly contributed by more moderate to heavy daily precipitation rather than extreme daily events. Although some previous studies have been conducted to attribute the 2020 Meiyu event in the MLYR, most of them focused on the cumulative precipitation amount. This attribution case study complements previous attribution analyses and reveals many new features. Our results show that anthropogenic climate change—primarily driven by greenhouse gas (GHG) forcing, anthropogenic aerosol (AA) forcing, and land‐use—has led to a decrease in the number of light to heavy precipitation days, while concurrently increasing the number of extreme precipitation days in the MLYR. Specifically, GHG and AA forcings decreased the frequency of light and moderate precipitation, but only GHG increased the frequency of extreme precipitation. An increasing trend in very heavy precipitation days has been observed. The competitive effects of GHG and AA forcings make it challenging to detect the signal of human activities, which could be intermingled with effects from natural variability. Under the SSP5‐8.5 scenario, the probability of experiencing both light and extreme precipitation events will significantly increase in the MLYR. By 2050–2100, these events are projected to be nearly 4 times more frequent compared to the current climate, which poses significant challenges to water security and economic development decision makers.

Risk of Natural Hazards Caused by Extreme Precipitation in Poland in 1951–2020

Extreme precipitation of a minimum daily value of >30 mm often initiates natural hazards such as floods, which in turn may not only lead to property damage but also present a danger to people’s health and lives. This paper mainly focuses on examining the trends and frequency of extreme daily precipitation (EDPr) in Poland. Also, it determines natural risk zones caused by EDPr of >30 mm, >50 mm, >70 mm, and >100 mm. In Poland, a significant positive trend was found for EDPr > 30 mm, >50 mm, and >70 mm in September, and for EDPr >100 mm in May. The most frequently recorded EDPr in Poland was >30 mm, the frequency of which ranged from 0.04% in February to nearly 3% in July. EDPr of >100 mm was recorded in 4 months, from May to August. An increase in the frequency of monthly EDPr in Poland occurred mainly in the southwestern and western parts. In Poland, three hazard zones of various frequencies of EDPr events were determined. In Zone III, which is in the southwestern and southern parts of the country, EDPr events occurred far more often than in Zone I; on average, four times more in the spring–summer season and slightly more than five times more in the autumn–winter season. The obtained results may help in the building of modern management and monitoring systems for the prevention of natural hazards caused by extreme precipitation.

Relationship Between Circulation Types and Extreme Precipitation Over Scandinavia Is Stable Under Climate Change

AbstractThe atmospheric large‐scale environment determines the occurrence of local extreme precipitation, and it is unclear how climate change affects this relationship. Here we investigate the present‐day relationship between large‐scale circulation types (CTs) and daily precipitation extremes over Scandinavia and its future change. A 50‐member EC‐Earth3 large ensemble is used to assess future changes against internal variability. We show that CTs are related to extreme precipitation over the entire domain. The intensity of extreme daily precipitation increases in all seasons in the future climate, generally following the strength of warming in the six different future scenarios considered. However, no significant future change is found in the relationship between extreme precipitation and the CTs in any season or scenario. The results have important implications for applications that rely on the stability of this relationship, such as statistical and event‐based dynamical downscaling of future weather and climate predictions and long‐term climate projections.

Projected changes in heat, extreme precipitation, and their spatially compound events over China’s coastal lands and seas through a high-resolution climate models ensemble

China’s coastal lands and seas are highly susceptible to the changing environment due to their dense population and frequent economic activities. These areas experience more significant impacts from climate change-induced extreme events than elsewhere. The most noticeable effects of climate change are extreme high temperatures and extreme precipitation. We employ an ensemble of RCMs (Regional Climate Models) to investigate and project changes in temperature, precipitation, and Compound Heat-Precipitation Extreme events (CHPEs) over selected China’s coastal lands and seas for both historical (1985–2004) and future periods (2080–2099). The multi-model ensemble projects that daily temperature extremes will increase by 2.9 °C to 5.4 °C across China’s coastal lands and seas, with land areas showing a higher temperature increase than marine areas. Extreme precipitation shows a high geographical heterogeneity with a 2.8–3.9 mm d−1 reduction over the 15–25°N marine areas while a 2.2–5.4 mm d−1 increment over the 25°N-35°N land areas. We use the Clausius–Clapeyron relationship to reveal that the peak of daily extreme precipitation will increase by 2–7 mm d−1 and the temperature at which extreme precipitation peaks will increase by 2 °C to 6 °C by warming. The land area of 25–30°N has the highest peak precipitation increase of 9.87 mm d−1 and a peak temperature increase of 6 °C. As precipitation extremes intensify with daily temperature extremes increase, CHPEs are projected to occur more frequently over both land and marine areas. Compared with the historical period, the frequency of CHPEs will increase by 40.9%-161.2% over marine areas, and by 36.2%-163.6% over land areas in the future. The 15–20°N area has the highest frequency increase of CHPE events, and the 25–30°N area has the largest difference in frequency increase under two different scenarios. It indicated that the 25–30°N area will be more easily affected by climate change.

Projected changes in extreme daily precipitation linked to changes in precipitable water and vertical velocity in CMIP6 models

Understanding the drivers of precipitation and their changes in a non-stationary climate is crucial for effective climate adaptation and water resource management, as it helps us anticipate and respond to shifting precipitation patterns and their impacts. Here, analysing simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) we show that the conditional probability of extreme daily precipitation given joint extremes of two drivers (precipitable water and vertical velocity) will be stable in a 3 °C warmer future. Consistent with earlier work, we find that the near-global increase in precipitable water (thermodynamic influence) is the baseline for changes in extreme precipitation, which are modulated by changes in vertical velocity (dynamic influence). Thus, in regions where vertical velocity increases, the effect of the two drivers is additive and their changes contribute to an increase in extreme precipitation. The changes of the two drivers are opposite where vertical velocity decreases, resulting in only small increases in extreme precipitation or even a decrease. Furthermore, we reveal that there are moderate changes in the dependence between the drivers, which are larger over the ocean than over landmasses, but they contribute only little to the overall changes in extreme precipitation. We conclude that the use of two very simple drivers that are readily available from climate models can be of great utility for evaluating precipitation extremes in models and understanding their projected changes.

Hybrid multilayer perceptron and convolutional neural network model to predict extreme regional precipitation dominated by the large-scale atmospheric circulation

Recent advances in deep learning have provided tools that enable meteorologists to predict extreme precipitation using massive atmospheric data. However, individual models are constrained by imbalanced samples and prone to false alarms owing to the rarity of extreme precipitation events. In this study, a novel ensemble learning model, that is, hybrid multilayer perceptron and convolutional neural network (MLP-CNN) model is proposed for the binary prediction of extreme precipitation in Central-Eastern China (CEC), with a daily time horizon. The MLP-CNN model achieves an overall accuracy of 86% in predicting extreme and non-extreme precipitation days using the anomalous fields of two large-scale atmospheric predictors, i.e., geopotential height at 500 hPa and vertically integrated water vapor transport. Subsequently, we employ the MLP-CNN to predict extreme precipitation with a 1–15 day leadtime. The performance of MLP-CNN tends to decrease with increasing leading time of circulation anomalies. However, 1–2 days of advance forecasting can be considered a reference for predicting the occurrence probabilities of extreme precipitation. Finally, based on various evaluation metrics, MLP-CNN outperforms the independent predictions from MLP, CNN, and two other machine learning models (i.e., random forest and support vector machine). Overall, in scenarios where samples are limited, the utilization of hybrid models presents an opportunity for optimizing predictions for extreme precipitation.

Global warming and heat extremes to enhance inflationary pressures

Climate impacts on economic productivity indicate that climate change may threaten price stability. Here we apply fixed-effects regressions to over 27,000 observations of monthly consumer price indices worldwide to quantify the impacts of climate conditions on inflation. Higher temperatures increase food and headline inflation persistently over 12 months in both higher- and lower-income countries. Effects vary across seasons and regions depending on climatic norms, with further impacts from daily temperature variability and extreme precipitation. Evaluating these results under temperature increases projected for 2035 implies upwards pressures on food and headline inflation of 0.92-3.23 and 0.32-1.18 percentage-points per-year respectively on average globally (uncertainty range across emission scenarios, climate models and empirical specifications). Pressures are largest at low latitudes and show strong seasonality at high latitudes, peaking in summer. Finally, the 2022 extreme summer heat increased food inflation in Europe by 0.43-0.93 percentage-points which warming projected for 2035 would amplify by 30-50%.

On the uncertainty of long-period return values of extreme daily precipitation

Methods for calculating return values of extreme precipitation and their uncertainty are compared using daily precipitation rates over the Western U.S. and Southwestern Canada from a large ensemble of climate model simulations. The roles of return-value estimation procedures and sample size in uncertainty are evaluated for various return periods. We compare two different generalized extreme value (GEV) parameter estimation techniques, namely L-moments and maximum likelihood (MLE), as well as empirical techniques. Even for very large datasets, confidence intervals calculated using GEV techniques are narrower than those calculated using empirical methods. Furthermore, the more efficient L-moments parameter estimation techniques result in narrower confidence intervals than MLE parameter estimation techniques at small sample sizes, but similar best estimates. It should be noted that we do not claim that either parameter fitting technique is better calibrated than the other to estimate long period return values. While a non-stationary MLE methodology is readily available to estimate GEV parameters, it is not for the L-moments method. Comparison of uncertainty quantification methods are found to yield significantly different estimates for small sample sizes but converge to similar results as sample size increases. Finally, practical recommendations about the length and size of climate model ensemble simulations and the choice of statistical methods to robustly estimate long period return values of extreme daily precipitation statistics and quantify their uncertainty.

Intensification of daily tropical precipitation extremes from more organized convection.

Tropical precipitation extremes and their changes with surface warming are investigated using global storm resolving simulations and high-resolution observations. The simulations demonstrate that the mesoscale organization of convection, a process that cannot be physically represented by conventional global climate models, is important for the variations of tropical daily accumulated precipitation extremes. In both the simulations and observations, daily precipitation extremes increase in a more organized state, in association with larger, but less frequent, storms. Repeating the simulations for a warmer climate results in a robust increase in monthly-mean daily precipitation extremes. Higher precipitation percentiles have a greater sensitivity to convective organization, which is predicted to increase with warming. Without changes in organization, the strongest daily precipitation extremes over the tropical oceans increase at a rate close to Clausius-Clapeyron (CC) scaling. Thus, in a future warmer state with increased organization, the strongest daily precipitation extremes over oceans increase at a faster rate than CC scaling.

Comparing the mechanisms of two types of summer extreme precipitation in Beijing-Tianjin-Hebei region, China: Insights from circulation patterns and moisture transports

Beijing-Tianjin-Hebei (BTH) is undergoing huge risks from severe precipitation extremes, but their climate features and underlying mechanisms are not fully understood and warrant in-depth investigations. Here, the summer extreme precipitation events in BTH are objectively divided into two types according to the spatial distribution i.e., Northeast precipitation (NEP) and Southwest precipitation (SWP) and their underlying mechanisms are revealed and compared from perspectives of circulation patterns and moisture transports. In the case of Type NEP, the anomalous deep low-pressure (high-pressure) systems respectively cover over the west (east) of BTH, which jointly induce strong anomalous southwesterly and southerly airflows converging over BTH. The converging airflows strengthen water vapor transports from the western and southern boundaries of BTH and result in a strong convection over northeastern BTH, thereby triggering Type NEP precipitation. Compared with Type NEP, the circulation pattern of Type SWP is characterized by an anomalous deep (shallow) high-pressure (low-pressure) system over northeast (southwest) of BTH, respectively. The circulation patterns could induce strong anomalous southerly and easterly airflows converging over BTH and thus strengthen water vapor transports from the southern and eastern boundaries of BTH, resulting in a strong convection over southwestern BTH. Over the long-term period, the summer extreme precipitation days with multiple return periods extracted by the Generalized extreme value distribution theory show significantly increasing trends in Beijing-Tianjin and surrounding areas, particularly in urban regions, indicating that summer extreme precipitation events are becoming more frequent. These findings provide theoretical basis for summer extreme precipitation forecasting and scientific insight for taking effective measures to mitigate the corresponding disasters in BTH.

Predictability of the extreme precipitation days in central Eastern Africa during january to may period

Predictability of the extreme precipitation days in central Eastern Africa during january to may period

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

AbstractThe rise of extreme precipitation events has attracted wide attention throughout the world. However, the analysis of precipitation extremes is not sufficient in the short period of instrumental observation and it is complicated by their non‐stationary behaviours. As a period dominated by natural forcing, the last millennium is helpful for understanding long‐term changes in precipitation extremes. Therefore, this study aimed to (1) investigate changes in daily and subdaily precipitation extremes in China from the last millennium to the end of the twenty‐first century, (2) detect the non‐stationarity of precipitation extremes and (3) compare design storms by using stationary and non‐stationary distributions. The annual maximum 1‐day precipitation (RX1day) and annual maximum 3‐hour precipitation (RX3hour) are used to quantify variations of precipitation extremes. The results show that the trend of RX1day was insignificant for the Medieval Climate Anomaly (MCA, 950–1250) and the Little Ice Age (LIA, 1500–1800). For the historical period (1850–2014), the trend of RX1day and RX3hour was insignificant in most subregions. In addition, the differences for RX1day between the historical period and the MCA/LIA were mostly in the range of −5% to 5%. For the future period (2015–2100), RX1day and RX3hour are projected to increase in almost all land grids compared with the historical period, and they show greater increases in western China than eastern China. The non‐stationarity of RX1day and RX3hour is mainly found under the high‐emission scenario. Moreover, stationary generalized extreme value (GEV) distribution underestimates 50‐year return levels for RX1day and RX3hour in most areas compared with non‐stationary GEV distribution under the high‐emission scenario. Overall, this study suggests that daily and subdaily extreme precipitation will intensify over China in the future. For design storms, non‐stationary methods need to be used for risk management and engineering design under the high‐emission scenario.

On the response of daily precipitation extremes to local mean temperature in the Yangtze River basin

This study explores the response of daily extreme precipitation (PEX) to local mean temperatures (T) of the previous 0-day (T0), 1-day (T1), and 1 to 9-days (T1–9) in the Yangtze River basin (YRB) using the non-stationarity test, binning method and copula theory. Results show that the annual scaling rate of PEX with T during 1961–2020 exhibits positive, negative and positive changing trends from southwest to northeast with the maximum magnitudes in the west, and experiences significant abrupt change only at 14.1% grids. The PEX-T scaling relation in the entire study period is predominantly characterized by a peak pattern over the YRB, with precipitation peaking at about 8 °C in the western highlands and at 25 °C in the east-central lowlands. However, the use of T1–9 yields a positive PEX-T pattern at more grids compared to T1 and T0, which highlights the important role of atmospheric moisture residence time in minimizing cooling artefacts in the scaling estimation. Generally, the full scaling rate of PEX with T in the study period is larger in the west-central part but smaller in the eastern YRB, and more sensitive to antecedent temperatures, with the ranges of −8–20%/°C, −8–30%/°C and −10–30%/°C against T0, T1 and T1–9, respectively. As precipitation intensifies, the full scaling decreases in plateau-mountain areas but increases in low-lying regions, gradually approaching the Clausius-Clapeyron (CC) scaling and exhibiting a “super-CC, CC-like and sub-CC scaling” pattern from west to east. Additionally, heavier precipitation events are most likely to occur at higher local temperatures in most areas even with peak structure. These findings provide new insights into the PEX-T relationships, which is conducive to understanding future changes in precipitation extremes and assessing precipitation-related risks under climate change.

Inferring the impacts of climate extreme in the Kabul River Basin

The increasing temperature and variability in precipitation, in terms of both frequency and intensity, are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extremes in the Kabul River Basin (KRB) of the western Himalaya using high-resolution climate datasets. We selected four representative General Circulation Model (GCM) runs from Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, based on future projections, climatic extremes and their abilities to represent the historical climate cycle (1981–2010) of KRB. The seasonal analysis of precipitation shows decreasing pattern during the winter and pre-monsoon seasons and annual mean temperature will increase consistently by 3 to 5 °C in RCP4.5 and 8.5 scenarios. Ten indices were selected to study climatic extremes pertaining to the health, agriculture and water resources sectors. The extremes, like consecutive summer days, warm days and heatwaves, will increase, whereas the frost days, cold nights, cold waves and extreme precipitation days will decrease towards the end of this century. Besides, the extremes are not homogenous in time and space. Based on the results of this study, there is a need for prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build resilient livelihoods in the KRB.