Extreme Precipitation Events Research Articles

Performance Assessment of Satellite-Based Precipitation Products in the 2023 Summer Extreme Precipitation Events over North China

In the summer of 2023, North China experienced a rare extreme precipitation storm due to Typhoons Doksuri and Khanun, leading to significant secondary disasters and highlighting the urgent need for accurate rainfall forecasting. Satellite-based quantitative precipitation estimation (QPE) products like Integrated Multi-Satellite Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) from the Global Precipitation Measurement (GPM) Mission have great potential for enhancing forecasts, necessitating a quantitative evaluation before deployment. This study uses a dense rain gauge as a benchmark to assess the accuracy and capability of the latest version 7B IMERG and version 8 GSMaP satellite-based QPE products for the 2023 summer extreme precipitation in North China. These satellite-based QPE products include four satellite-only products, namely IMERG early run (IMERG_ER) and IMERG late run (IMERG_LR), GSMaP near-real-time (GSMaP_NRT), and GSMaP microwave-infrared reanalyzed (GSMaP_MVK), along with two gauge-corrected products, namely IMERG final run (IMERG_FR) and GSMaP gauge adjusted (GSMaP_Gauge). The results show that (1) GSMaP_MVK, IMERG_LR, and IMERG_FR effectively capture the space distribution of the extreme rainfall, with relatively high correlation coefficients (CCs) of approximately 0.77, 0.75, and 0.79. The IMERG_ER, GSMaP_NRT, and GSMaP_Gauge products exhibit a less accurate spatial pattern capture (CCs about 0.66, 0.73, and 0.67, respectively). Each of the six QPE products tends to underestimate rainfall (RBs < 0%). (2) The IMERG products surpass the corresponding GSMaP products in serial rainfall measurement. IMERG_LR demonstrates superior performance with the lowest root-mean-square error (RMSE) (about 0.38 mm), the highest CC (0.97), and less underestimation (RB about −6.37%). (3) The IMERG products at rainfall rates ≥ 30 mm/h, GSMaP_NRT and GSMaP_MVK products at rainfall rates ≥ 55 mm/h, and GSMaP_Gauge products at ≥ 40 mm/h showed marked limitations in event detection, with a near-zero probability of detection (POD) and a nearly 100% false alarm ratio (FAR). In this extreme precipitation event, caution is needed when using the IMERG and GSMaP products.

A Concentrated Analysis of the Situation of Flood Control Management: A Review

Floods are happening more often and with greater severity due to socioeconomic development and climate change. Flood control is widely acknowledged as an effective means of reducing the negative effects, and recent research has aimed to develop a more robust and sustainable approach to flood management. A thorough bibliometric examination of terms, keywords, and dates in the flood research field was employed in this work. It provides new insight into the flood research trends, by examining the research frontiers from 2000 to 2021. We conclude that there has been a shift in the focus of flood research from flood management to flood resilience. Flood resilience management offers a more resilient and sustainable plan to deal with flood disasters, while flood risk management offers an adaptation approach by adjusting mitigation measures. The review demonstrates how flood research has progressed from traditional flood management, which provides mitigation strategies, to flood resilience management. Along with reviewing the definition of risk, risk analysis techniques, flood resilience, flood management, and flood risk management, we also provide a thorough introduction of the field of flood research. We come to the conclusion that a preferable strategy for future flood control directions is to incorporate the idea of resilience into the risk management framework. Consequently, employing the theories of risk, resilience, and sustainability, sensible choices and actions made before, during, and after a disaster will successfully minimize the negative effects. Devastating floods brought on by swift urbanization and severe weather patterns have claimed millions of lives and continue to inflict direct economic losses estimated at tens of billions of dollars annually. Furthermore, as extreme precipitation events intensify (Tabari, 2020) and the population at risk of water-related disasters rises (Jongman et al., 2012; Paudel et al., 2014; Tellman et al., 2021), these losses will only rise in the future due to global warming (Bloeschl et al., 2019; CRED and UNISDR, 2020; Hallegatte et al., 2013). Even worse, severe compound flooding from excessive river flow, intense rainfall, and storm surges might arise from the simultaneous occurrence of flash floods, river flooding, urban flooding, and coastal flooding (Ming et al., 2022). Given that the causes of coastal, urban, and river flooding vary, determining the locations most vulnerable to these types of floods is a challenging. While flood risk is known to rise in response to population growth, climate change, and the accumulation of economic assets, it is also known that this risk is dynamic and ever-changing due to changes in underlying surface conditions (Hallegatte et al., 2013; Lai et al., 2020). Thus, it is critical to manage flooding in order to address the rising risk of flooding. Prior studies have demonstrated the pressing need to address flood events (da Silva et al., 2020), and future flood mitigation measures must be developed in order to lessen the negative effects and handle increasingly complicated flood kinds.

Assessing Nitrate Leaching During Drought and Extreme Precipitation: Exploring Deep Vadose‐Zone Monitoring, Groundwater Observations, and Field Mass Balance

AbstractThe increasing concern over agricultural practices' impact on groundwater quality necessitates comprehensive studies to evaluate and compare monitoring strategies for nitrate leaching. This work addresses this imperative by examining three methodologies: deep vadose‐zone monitoring, shallow groundwater intensive monitoring, and field‐level mass balance. The primary objective of the study was to assess nitrate leaching from an intensively cropped processing tomato rotation field using three different methods. Additionally, this study focuses on contrasting conditions between the growing season (characterized by drought in some years) and the winter/rainy season (characterized by extreme precipitation in some years). Results indicate varying degrees of nitrate leaching across methods, with all approaches detecting leaching events during the growing season and off‐season precipitation. Despite uncertainties inherent in field‐level mass balance estimates, they align reasonably with intensive in‐situ monitoring results using the deep Vadose Monitoring System (VMS). Throughout two growing seasons and corresponding fall‐winter rainy periods, the VMS effectively tracked seasonal nitrogen leaching below the root zone, correlating with observed groundwater nitrate concentrations increases following extreme precipitation events. Nitrate leaching increased during heavy rainfall in the winter following dry summer periods observed across the deep vadose zone using two VMS systems. This underscores the importance of continuous monitoring and assessment in understanding nitrate dynamics and groundwater contamination risks. In conclusion, this study contributes to knowledge and ongoing research by providing insights into effective monitoring strategies for nitrate leaching into groundwater from intensive cropping systems.

Changes in Extreme Daily Precipitation over the Contiguous United States from Convection-Permitting Simulations

Abstract The potential for changes in extreme precipitation events due to anthropogenic climate change may have significant societal impacts (e.g., agricultural productivity, property loss, mortality). This project uses a dynamically downscaled, convection-permitting regional climate model to investigate extreme daily precipitation in the CONUS, defined explicitly as the 99th percentile 24-h accumulated value. The simulation output includes a historical baseline (HIST; 1990–2005) and two epochs at the end of the twenty-first century (EOC; 2085–2100) under intermediate and pessimistic emissions scenarios. Independent observations illustrate that HIST admirably represents extreme precipitation climatology for most locations in the domain. Comparisons between HIST and the two EOC scenarios for the 99th percentile of daily precipitation show statistically significant increases during Dec–May across the Midwest and Ohio Valley and statistically significant decreases for the southern Great Plains during Dec–Feb. Extreme value analysis further reveals increasing variability in precipitation extremes for eight climatologically unique cities across the CONUS by the end of the twenty-first century and significant increases in return period precipitation amounts for most cities examined. These results provide additional guidance for stakeholders to reduce societal impacts and economic loss from daily precipitation extremes and create a more climate-resilient society.

A Synoptic Scale Perspective of Solar Forcing on Extreme Precipitation and Floods Over Europe During Summer

AbstractThe relationship between total solar irradiance (TSI) forcing and summer extreme precipitation and flood frequency over western Europe is investigated from a synoptic‐scale perspective, with a focus on the role of Rossby wave packets (RWPs). Utilizing observational, model, and proxy data, we reveal a significant increase in RWP frequency along a zonal band centered around 50°N, extending from North America to western Europe, during periods of low TSI. This anomaly in RWP frequency is consistent with a significant increase in the frequency of extreme precipitation events recorded over western Europe. Sensitivity experiments conducted with a state‐of‐the‐art chemistry‐climate model corroborate our findings based on observational data. Additionally, a flood record from western Europe demonstrates a significant increase in flood frequency during low TSI years, a relationship that persists across timescales. We argue that the frequency patterns associated with TSI forcing presented in this study are robust and, therefore, valuable for estimating the frequency of extreme precipitation events over western Europe under various solar irradiance scenarios. Moreover, our findings indicate that the North Atlantic sector is more responsive to changes in solar forcing during the boreal summer than previously thought, with this effect manifesting primarily on synoptic timescales rather than the long‐term climatological mean.

Twentieth century extreme precipitation detected in a high-resolution, coastal lake-sediment record from California

AbstractCalifornia faces increasing economic and societal risks from extreme precipitation and flooding associated with atmospheric rivers (ARs) under projected twenty-first century climate warming. Lake sediments can retain signals of past extreme precipitation events, allowing reconstructions beyond the period of instrumental records. Here, we calibrate AR-related extreme precipitation from the last century to proxy data from lake sediments collected in the latitudinal zone of the highest frequency landfall for modern ARs in California. Excursions in erosional proxy data (Ti/Al) are positively and significantly correlated (rmedian = 0.45, pmedian = 0.04) with modern records of integrated vapor transport (IVT, kg m−1 s−1), a key metric of AR intensity, using correlations that incorporate age-model uncertainty. Despite the land-use change near the study site, the data suggest intense and long-lasting AR storms are identifiable in this sedimentary record. These results allow conservative inferences concerning past extreme hydrology at this site.

What Distinguishes Summer Extreme Precipitation From Non‐Extreme Precipitation Over the Tibetan Plateau?

AbstractThis study focuses on the primary synoptic‐scale patterns and precursors of extreme and non‐extreme precipitation over the Tibetan Plateau (TP). Atmospheric circulation anomalies and their precursors associated with regional extreme precipitation events (REPE) demonstrate distinct precursor wave train and heightened intensity than regional non‐extreme precipitation events (non‐REPE). Specifically, REPE over the northwestern TP (NWTP) exhibits a geopotential height anomaly induced by a latitudinal propagating Rossby wave train along 40°N. In contrast, over the southeastern TP (SETP), REPE is characterized by a geopotential height anomaly caused by a northwest‐southeastward propagating Rossby wave train. The ascending motion anomalies of REPE over both NWTP and SETP are primarily attributed to the geostrophic zonal temperature advection, which is significantly stronger during REPE compared to non‐REPE. This finding provides valuable insights for forecasting summer extreme precipitation over TP.

Investigating the Limitations of Multi‐Model Ensembling of Climate Model Outputs in Capturing Climate Extremes

ABSTRACTIn the context of climate change, the widespread practice of directly employing Multi‐Model Ensembles (MMEs) for projecting future climate extremes, without prior evaluation of MME performance in historical periods, remains underexplored. This research addresses this gap through a comprehensive analysis of ensemble means derived from CMIP6‐based models, including both simple and weighted averages of precipitation (SEMP and WEMP) and temperature (SEMT and WEMT) time series, as well as simple (SEME) and weighted (WEME) averages of extremes based on model‐by‐model analysis. The study evaluates the efficacy of MMEs in capturing mean annual values of ETCCDI indices over India for the period 1951–2014, utilising the IMD gridded data set as a reference. The results reveal that SEME and WEME consistently align closely with IMD data across various precipitation indices. At the same time, SEMP and WEMP consistently display underestimation biases ranging from 20% to 80% across all precipitation indices, except for CWD, where there is an overestimation bias. Moreover, SEMP and WEMP consistently underestimate CDD and overestimate CWD, indicating a systematic bias in these ensemble means, while WEME and SEME demonstrate satisfactory performance. SEMT and WEMT exhibit notable underestimation in temperature indices. In summary, adopting SEME and SEMT leads to a more robust assessment of precipitation and temperature extremes, respectively. These findings highlight the limitations of traditional MME methodologies in reproducing observed extreme precipitation events across various climatic zones in India, offering essential insights for refining climate models and improving the reliability of climate projections specific to the Indian subcontinent.

Deciphering the Characteristics and Drivers of the Summer Monsoon Precipitation Extremes Over the Indian Himalayas

AbstractThis study investigates the physical processes behind extreme precipitation events (EPEs) in the Himalayas, notorious for causing frequent floods and significant loss of life and property. Due to the presence of complex terrain, understanding the driving factors of these EPEs is challenging. Here, we decipher the precipitation characteristics and their driving factors responsible for the occurrence of EPEs in the Western Himalayas (WH) for the period 1979–2020. EPEs are defined as events exceeding the 99th percentile threshold. The extreme precipitation in the WH is contributed by both large‐scale precipitation (accounting for 61%) and convective precipitation (39%). Moreover, 25.49% of EPEs in this region are directly associated with monsoon depressions. The presence of distinct upper‐tropospheric gyres flanking the WH, along with a prominent zonal wave pattern, promotes a southward extension of the trough. This intensifies the low‐level convergence of moisture‐laden winds from the adjoining seas, resulting in substantial moisture availability for the EPEs. An omega‐type blocking pattern emerges 4 days before EPEs, facilitating the intrusion of an extratropical cyclonic circulation. This circulation, characterized by its slow eastward and equatorward movement, leads to low‐level moisture flux convergence and ascending motions, which in turn trigger the EPEs. This highlights the crucial role of extratropical signals in driving EPEs and implies that tropical‐extratropical interactions play an important role in these EPEs. Furthermore, the shifting of the Intertropical Convergence Zone is strongly linked to the enhancement of the intensity of EPEs. Moreover, moisture budget analysis shows that EPEs over the WH are primarily driven by vertical advection, with the dynamic (thermodynamic) terms explaining 92% (8%) contribution. The intensified diabatic heating structure further enhances the convection, facilitating the development of deep convection which controls the local thermodynamics of these EREs. Lastly, our study demonstrated that most intensified and persistent EPEs over the Himalayas are found to be linked with Quasi‐Resonance Amplification, which is driven by baroclinic waves with 5 and 8 zonal wave numbers that contribute to these EPEs.

Spatiotemporal Variation Characteristics of Extreme Precipitation in the Mid–Lower Reaches of the Yangtze River Basin Based on Precipitation Events

In addition to greater precipitation on extreme days of precipitation, preceding and succeeding precipitation (PSP) is often an objective component of flooding in the mid–lower reaches of the Yangtze River Basin (MLRYRB). In this study, focused on the temporal distribution pattern of precipitation, the concept of an extreme precipitation event (EPE), defined as a consecutive precipitation event having at least one daily precipitation extreme, is proposed to consider PSP in an extreme event. We analyzed the spatiotemporal variation of four types of EPEs based on daily data obtained from 130 monitoring stations covering 1960–2019. Extreme precipitation increased significantly over the last 60 years (p < 0.01). The frequency and precipitation amount of single-day EPEs accounted for only 13% and 21%, respectively, while multi-day continuous EPE types that are associated with PSP accounted for 87% and 79%, respectively, confirming the connotations of EPEs. The front and late EPEs under the 100-year return level reached 250 mm and 230 mm, respectively. Furthermore, climate warming could lead to significant increases in the frequency of single-day and late EPEs, particularly in the southern region. The EPE concept may be helpful in exploring disaster-causing processes under extreme weather, and it provides a theoretical basis for deriving the precipitation hazard chain, which is more applicable to basins with long precipitation durations.

ER-MACG: An Extreme Precipitation Forecasting Model Integrating Self-Attention Based on FY4A Satellite Data

Extreme precipitation events often present significant risks to human life and property, making their accurate prediction an essential focus of current research. Recent studies have primarily concentrated on exploring the formation mechanisms of extreme precipitation. Existing prediction methods do not adequately account for the combined terrain and atmospheric effects, resulting in shortcomings in extreme precipitation forecasting accuracy. Additionally, the satellite data resolution used in prior studies fails to precisely capture nuanced details of abrupt changes in extreme precipitation. To address these shortcomings, this study introduces an innovative approach for accurately predicting extreme precipitation: the multimodal attention ConvLSTM-GAN for extreme rainfall nowcasting (ER-MACG). This model employs high-resolution Fengyun-4A(FY4A) satellite precipitation products, as well as terrain and atmospheric datasets as inputs. The ER-MACG model enhances the ConvLSTM-GAN framework by optimizing the generator structure with an attention module to improve the focus on critical areas and time steps. This model can alleviate the problem of information loss in the spatial–temporal convolutional long short-term memory network (ConvLSTM) and, compared with the standard ConvLSTM-GAN model, can better handle the detailed changes in time and space in extreme precipitation events to achieve more refined predictions. The main findings include the following: (a) The ER-MACG model demonstrated significantly greater predictive accuracy and overall performance than other existing approaches. (b) The exclusive consideration of DEM and LPW data did not significantly enhance the ability to predict extreme precipitation events in Zhejiang Province. (c) The ER-MACG model significantly improved in identifying and predicting extreme precipitation events of different intensity levels.

Does ERA5-Land Effectively Capture Extreme Precipitation in the Yellow River Basin?

ERA5-Land is a valuable reanalysis data resource that provides near-real-time, high-resolution, multivariable data for various applications. Using daily precipitation data from 301 meteorological stations in the Yellow River Basin from 2001 to 2013 as benchmark data, this study aims to evaluate ERA5-Land’s capability of monitoring extreme precipitation. The evaluation study is conducted from three perspectives: precipitation amount, extreme precipitation indices, and characteristics of extreme precipitation events. The results show that ERA5-Land can effectively capture the spatial distribution patterns and temporal trends in precipitation and extreme precipitation; however, it also exhibits significant overestimation and underestimation errors. ERA5-Land significantly overestimates total precipitation and indices for heavy precipitation and extreme precipitation (R95pTOT and R99pTOT), with errors reaching up to 89%, but underestimates the Simple Daily Intensity Index (SDII). ERA5-Land tends to overestimate the duration of extreme precipitation events but slightly underestimates the total and average precipitation of these events. These findings provide a scientific reference for optimizing the ERA5-Land algorithm and for users in selecting data.

Drivers of Cold Frontal Hourly Extreme Precipitation: A Climatological Study Over Europe

AbstractIn the mid‐latitudes extreme precipitation events are strongly associated with cold fronts. By exploring drivers across different scales and relating them to precipitation, we aim to improve our understanding of processes influencing cold frontal extremes. Using hourly ERA5 data over Europe and the North Atlantic, cold fronts are detected and the associated conditions are identified. Quantile regression models are employed to find drivers of frontal precipitation and to quantify these relations. Additionally, we use composites to study the synoptic conditions and meso‐scale structure of extreme events. We find that humidity close to the detected fronts, convergence and the low level jet speed contribute most to the formation of extreme precipitation. Synoptic conditions favoring the formation of extreme events are also identified. These results improve our understanding of cold frontal processes leading to precipitation. Additionally, they provide the foundation for a process‐based evaluation of frontal dynamics in climate models.

Temporal connections between extreme precipitation and humid heat

Abstract Individually, extreme humid heat and extreme precipitation events can trigger widespread socioeconomic impacts which disproportionately affect vulnerable populations. These impacts might become greater when both events occur in close temporal proximity, for example if emergency responses to heat stress casualties are hindered by flooded roads. Improved understanding of the probabilities and physical mechanisms associated with these events’ temporal compounding might uncover causal interrelationships offering avenues for improving early warning systems and projecting changes in a warmer climate. We explore sequential humid heat and rainfall relationships during the local summer season, identifying two classes of temporal relationships. We find that high wet bulb temperature (WBT) anomalies in most mid- to high-latitude and tropical regions are preceded by anomalously low precipitation. In contrast, hot and dry subtropical regions generally experience elevated WBTs during and, to a somewhat lesser extent, before extreme precipitation events. High WBT events are followed by positive precipitation anomalies in many land regions.

Studies on Heavy Precipitation in Portugal: A Systematic Review

This systematic review, based on an adaptation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement from 2020, focuses on studies of the atmospheric mechanisms underlying extreme precipitation events in mainland Portugal, as well as observed trends and projections. The 54 selected articles cover the period from 2000 to 2024, in which the most used keywords are “portugal” and “extreme precipitation”. Of the 54, 23 analyse trends and climate projections of precipitation events, confirming a decrease in total annual precipitation, especially in autumn and spring, accompanied by an increase in the frequency and intensity of extreme precipitation events in autumn, spring and winter. Several articles (twelve) analyse the relationship between synoptic-scale circulation and heavy precipitation, using an atmospheric circulation types approach. Others (two) establish the link with teleconnection patterns, namely the North Atlantic Oscillation (NAO), and still others (three) explore the role of atmospheric rivers. Additionally, five articles focus on evaluating databases and Numerical Weather Prediction (NWP) models, and nine articles focus on precipitation-related extreme weather events, such as tornadoes, hail and lightning activity. Despite significant advances in the study of extreme precipitation events in Portugal, there is still a lack of studies on hourly or sub-hourly scales, which is critical to understanding mesoscale, short-lived events. Several studies show NWP models still have limitations in simulating extreme precipitation events, especially in complex orography areas. Therefore, a better understanding of such events is fundamental to promoting continuous improvements in operational weather forecasting and contributing to more reliable forecasts of such events in the future.

Resonant Forcing by Solar Declination of Rossby Waves at the Tropopause and Implications in Extreme Precipitation Events and Heat Waves—Part 2: Case Studies, Projections in the Context of Climate Change

Based on the properties of Rossby waves at the tropopause resonantly forced by solar declination in harmonic modes, which was the subject of a first article, case studies of heatwaves and extreme precipitation events are presented. They clearly demonstrate that extreme events only form under specific patterns of the amplitude of the speed of modulated airflows of Rossby waves at the tropopause, in particular period ranges. This remains true even if extreme events appear as compound events where chaos and timing are crucial. Extreme events are favored when modulated cold and warm airflows result in a dual cyclone-anticyclone system, i.e., the association of two joint vortices of opposite signs. They reverse over a period of the dominant harmonic mode in spatial and temporal coherence with the modulated airflow speed pattern. This key role could result from a transfer of humid/dry air between the two vortices during the inversion of the dual system. Finally, focusing on the two period ranges 17.1–34.2 and 8.56–17.1 days corresponding to 1/16- and 1/32-year period harmonic modes, projections of the amplitude of wind speed at 250 mb, geopotential height at 500 mb, ground air temperature, and precipitation rate are performed by extrapolating their amplitude observed from January 1979 to March 2024. Projected amplitudes are regionalized on a global scale for warmest and coldest half-years, referring to extratropical latitudes. Causal relationships are established between the projected amplitudes of modulated airflow speed and those of ground air temperature and precipitation rate, whether they increase or decrease. The increase in the amplitude of modulated airflow speed of polar vortices induces their latitudinal extension. This produces a tightening of Rossby waves embedded in the polar and subtropical jet streams. In the context of climate change, this has the effect of increasing the efficiency of the resonant forcing of Rossby waves from the solar declination, the optimum of which is located at mid-latitudes. Hence the increased or decreased vulnerability to heatwaves or extreme precipitation events of some regions. Europe and western Asia are particularly affected, which is due to increased activity of the Arctic polar vortex between longitudes 20° W and 40° E. This is likely a consequence of melting ice and changing albedo, which appears to amplify the amplitude of variation in the period range 17.1–34.2 days of poleward circulation at the tropopause of the Arctic polar cell.

The Coupled Application of the DB-IWHR Model and the MIKE 21 Model for the Assessment of Dam Failure Risk

The phenomenon of global climate change has led to an increase in the frequency of extreme precipitation events, an acceleration in the melting of glaciers and snow cover, and an elevation of the risk of flooding. In this study, the DB-IWHR model was employed in conjunction with the MIKE 21 hydrodynamic model to develop a simulation system for the dam failure flow process of an earth and rock dam. The study concentrated on the KET reservoir, and 12 dam failure scenarios were devised based on varying design flood criteria. The impact of reservoir failures on flood-risk areas was subjected to detailed analysis, with consideration given to a range of potential failure scenarios and flood sizes. It was determined that under identical inflow frequency conditions, the higher the water level, the more rapid the breakout process and the corresponding increase in flood peak discharge. Conversely, for a given frequency of incoming water, an elevated water level results in a transient breach process, accompanied by a reduction in flood peak flow. Moreover, for a given water level, an increase in water frequency results in a reduction in breaching time, an extension of flood duration, and an increase in flood peak flow. The observed trend of flood spreading is generally north-south, and this process is highly compatible with the topographic and geomorphological features, demonstrating good adaptability.

Analyzing the Spatiotemporal Changes in Climatic Extremes in Cold and Mountainous Environment: Insights from the Himalayan Mountains of Pakistan

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.

GA-SmaAt-GNet: Generative adversarial small attention GNet for extreme precipitation nowcasting

In recent years, data-driven modeling approaches have gained significant attention across various meteorological applications, particularly in weather forecasting. However, these methods often face challenges in handling extreme weather conditions. In response, we present the GA-SmaAt-GNet model, a novel generative adversarial framework for extreme precipitation nowcasting. This model features a unique SmaAt-GNet generator, an extension of the successful SmaAt-UNet architecture, capable of integrating precipitation masks (binarized precipitation maps) to enhance predictive accuracy. Additionally, GA-SmaAt-GNet incorporates an attention-augmented discriminator inspired by the Pix2Pix architecture. This innovative framework paves the way for generative precipitation nowcasting using multiple data sources. We evaluate the performance of SmaAt-GNet and GA-SmaAt-GNet using real-life precipitation data from The Netherlands, revealing notable improvements in overall performance and for extreme precipitation events compared to other models. Specifically, our proposed architecture demonstrates its main performance gain in summer and autumn, when precipitation intensity is typically at its peak. Furthermore, we conduct uncertainty analysis on the GA-SmaAt-GNet model and the precipitation dataset, providing insights into its predictive capabilities. Finally, we employ Grad-CAM to offer visual explanations of our model’s predictions, generating activation heatmaps that highlight areas of input activation throughout the network.

An extreme precipitation event over Dronning Maud Land, East Antarctica - A case study of an atmospheric river event using the Polar WRF Model

Extreme precipitation events (EPEs) are crucial in Antarctica, impacting the Antarctic ice sheet's surface mass balance and stability. Comprehensive case studies are essential for better understanding these events and the underlying processes driving them. Here, we investigate an extreme snowfall event in Dronning Maud Land (DML), East Antarctica on November 8 and 9, 2015. This event contributed approximately 22 % of the annual accumulation in less than two days and exhibited high spatial variability in precipitation distribution. We employed a high-resolution atmospheric model specifically optimized for the polar regions (Polar WRF) and ERA5 reanalysis data to analyze the event in detail. Our findings highlight the importance of a blocking high-pressure ridge of record strength that effectively blocked and diverted a strong extratropical cyclone into DML, ultimately leading to the heavy snowfall event. The sudden deepening of the cyclone was initiated by a ‘jet streak’ in the upper atmosphere that steered the system southeastwards towards the Antarctic coast. Notably, we observed an anomalously high poleward moisture transport in the form of a strong atmospheric river on November 7, 2015. This atmospheric river originated in the South Atlantic Ocean and tracked poleward from the 30°S-40°S latitude band. Vertical cross-sections of the model outputs indicate that most of the precipitation was concentrated in regions with steep orography along the path of the atmospheric river. This interaction between the atmospheric river and the steep terrain led to the uplift of maritime air, resulting in heavy snowfall. This study highlights the significance of extreme upper and lower atmospheric conditions in driving intense moisture transport towards coastal DML. The interaction between the atmospheric river and the steep orography contributed to heavy snowfall, underscoring the importance of considering orographic influences in understanding EPEs in Antarctica.