Search Results (38)

Morocco, located at the southern margin of the Mediterranean climate-change hotspot, is exposed to a rapidly evolving precipitation regime whose national-scale characterization remains incomplete. This study delivers an integrated assessment of the spatio-temporal variability and trends of precipitation and its extremes over the country during the most recent World Meteorological Organization (WMO) climate-normal period (1991–2020), based on daily observations from 31 synoptic stations operated by the Direction Générale de la Météorologie (DGM). Trends in annual, seasonal and monthly precipitation were quantified using the non-parametric Mann–Kendall test combined with Sen’s slope estimator, while the structural transformation of the rainfall regime was characterized through three indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI): the Consecutive Dry Days (CDDs), the Simple Daily Intensity Index (SDII) and the amount of precipitation from very wet days (R95pTOT). The results reveal an apparent tendency toward a negative trend, with a predominance of negative precipitation trends in winter and early spring, most pronounced in February, that reach statistical significance at only a limited number of stations, partly offset by a spatially coherent wetting in November over central and eastern Morocco. The joint analysis of the three ETCCDI indices indicates a north–south contrasted reorganization: northern stations exhibit longer dry spells coexisting with intensified extreme rainfall, whereas southern stations show a generalized weakening of both intensity and extremes. These findings point to a structural shift toward more episodic and contrasted precipitation regimes, with the wet season starting later, ending earlier and concentrating rainfall into fewer but more intense events. The analysis provides an updated observational baseline for the validation of CMIP6 based regional projections and for the design of climate-resilient water and agricultural strategies in Morocco. Full article

Rainfall variability strongly influences both flood and drought hazards, especially in climatic transition zones where precipitation is highly seasonal and spatially heterogeneous. This study assessed long-term changes in rainfall patterns and compound flood–drought hazard in the Huaihe River Basin, China, using ERA5-Land-derived daily precipitation series at 174 spatial sampling locations during 1950–2025. Rainfall pattern indicators, flood-related rainfall extremes, and SPI-3-based drought indicators were calculated to characterize rainfall amount, frequency, intensity, dry–wet persistence, heavy rainfall events, and meteorological drought conditions. The Mann–Kendall test and Sen’s slope estimator were used to detect long-term trends, and a compound flood–drought hazard classification framework was developed based on a flood-related rainfall hazard index (FHI) and a drought-related hazard index (DHI). The results showed that annual total precipitation, wet days, and consecutive wet days decreased significantly, indicating reduced rainfall occurrence and wet spell persistence. Flood-related rainfall indicators generally showed decreasing tendencies, with more evident declines in persistent multi-day extremes than in single-day rainfall. In contrast, mean SPI-3 showed a significant drying tendency, although drought frequency, severe drought frequency, and drought intensity did not exhibit significant monotonic trends. Spatially, rainfall pattern, flood-related, and drought-related indicators showed clear heterogeneity across the basin. The compound hazard classification identified flood-dominated and drought-dominated areas as the two major hazard types, each accounting for 31.03% of the spatial sampling locations, while low compound hazard and compound flood–drought hazard areas each accounted for 18.97%. These findings indicate that flood- and drought-related hazards coexist but vary spatially across the Huaihe River Basin. The proposed framework provides preliminary rainfall-based information for differentiated flood–drought hazard assessment, climate-adaptive water resources planning, and the sustainable management of water resources in regions facing spatially heterogeneous hydroclimatic hazards. Full article

This study examines the hydrological response of the Klambu Dam Catchment in Central Java, Indonesia, to climatic and land cover changes from 2000–2023, with simulations extending to 2040. Utilizing CHIRPS satellite data calibrated with six ground stations, monthly precipitation and temperature datasets were analyzed and projected via linear regression aligned with IPCC scenarios, revealing a marginal temperature decline of 0.21 °C (from 28.25 °C in 2005 to 28.04 °C in 2023) and a 17% increase in rainfall variability. Land cover assessments from Landsat imagery highlighted drastic changes: a 73.8% reduction in forest area and a 467.8% increase in mixed farming areas, alongside moderate fluctuations in paddy fields and settlements. The Thornthwaite-Mather water balance method simulated monthly discharge, validated against observed data with Pearson correlations ranging from 0.5729 (2020) to 0.9439 (2015). Future projections using Cellular Automata-Markov modeling indicated stable volumetric flow but a temporal shift, including a 28.1% decrease in April rainfall from 2000 to 2040, contracting the wet season and extending dry spells. These shifts pose significant threats to agricultural and aquaculture activities, potentially exacerbating water scarcity and economic losses. The findings emphasize integrating dynamic land cover data, climate projections, and empirical runoff corrections for climate-resilient watershed management. Full article

Peatlands provide essential ecological services but are highly vulnerable to degradation from drainage, leading to greenhouse gas emissions, land subsidence, and increased fire susceptibility. This study investigates peat hydrology and its relationship to fire risk in a fire-prone area in South Sumatra, Indonesia. Groundwater levels and soil moisture were continuously monitored using automated loggers, and recession analysis quantified their rates of decline. Multispectral drone imagery (NDVI, NDWI) over a 44.1-ha area assessed vegetation and surface wetness, while fire occurrences (2019–2024) were analyzed using the Fire Information for Resource Management System (FIRMS). During a 58-day dry period, groundwater depth reached 78.5 cm with a recession rate of 9.68 mm day⁻¹, while soil moisture decreased by 0.00291 m³ m⁻³ per day over 27 consecutive dry days. Drone imagery revealed that unhealthy and dead grass covered nearly 90% of the site, although wetness remained moderate (NDWI = 0.02–0.58). FIRMS data indicated that rainfall below 2000 mm year⁻¹ and prolonged dry spells (>30 days) strongly trigger peat fires. These findings correspond with early-warning model outputs based on soil moisture recession and ignition thresholds. Maintaining a high groundwater level is, therefore, crucial for reducing peat fire vulnerability under extended dry conditions. Full article

This study evaluates the impacts of Solar Radiation Management (SRM) on precipitation-related climate extremes in Southeast Asia. Using simulations from the Geoengineering Large Ensemble (GLENS), we assess spatial anomalies and differences in extreme precipitation indices—number of wet days (RR1), very heavy precipitation days (R20mm), maximum 5-day precipitation (Rx5day), consecutive dry days (CDD), and consecutive wet days (CWD)—relative to historical (1980–2009) and Representative Concentration Pathway 8.5 (RCP8.5) baselines. The results reveal that SRM induces highly heterogeneous precipitation responses across the region. While SRM increases rainfall frequency in parts of Indonesia, it reduces the number of wet days and lengthens dry spells over Vietnam, Thailand, and the Philippines. Spatial variations are also observed in changes to heavy precipitation days and multi-day rainfall events, with potential implications for flood and drought risks. These findings highlight the complex trade-offs in hydrological responses under SRM deployment, with important considerations for agriculture, water resource management, and climate adaptation strategies in Southeast Asia. Full article

Fire-driven land cover change has generated a paradox: while habitat fragmentation from agriculture, livestock, and urban expansion has reduced natural fire occurrences, human-induced ignitions have increased wildfire frequency and intensity. In northern Colombia’s Magdalena Department, most of the territory faces moderate to high wildfire risk, especially during recurrent dry seasons and periods of below-average precipitation. However, knowledge of wildfire spatiotemporal occurrence and its drivers remains scarce. This work addresses this gap by identifying fire-prone zones and analyzing the influence of climate and vegetation in the Magdalena Department. Fire-prone zones were identified using the Getis–Ord Gi* method over fire density and burned area data from 2001 to 2023; then, they were analyzed with seasonally aggregated hydroclimatic indices via logistic regression to quantify their influence on wildfires. Vegetation susceptibility was assessed using geostatistics, obtaining land cover types most affected by fire and their degree of fragmentation. Fire-prone zones in the Magdalena Department covered ~744.35 km² (3.21%), with a weak but significant (τ = 0.20, p < 0.01) degree of coincidence between classification based on fire density, as pre-fire variable, and burned area, as a post-fire variable. Temporally, fire probability increased during the dry season, driven by short-lagged precursors such as Dry Spell Length and precipitation from the preceding wet season. Fire-prone zones were dominated by pastures (62.39%), grasslands and shrublands (19.61%) and forests (15.74%), and exhibited larger, more complex high-risk patches, despite similar spatial connectedness with non-fire-prone zones. These findings enhance wildfire vulnerability understanding, contributing to risk-based territorial planning. Full article

Drought is one of the most widespread natural disasters globally, and its spatiotemporal distribution is profoundly influenced by the El Niño-Southern Oscillation (ENSO). As a typical humid coastal basin, the Jiaojiang River Basin in southeastern China frequently experiences hydrological extremes such as dry spells during flood seasons. This study focuses on the Jiaojiang River Basin, aiming to investigate the response mechanisms of drought evolution to ENSO in coastal regions. This study employs 10-day scale data from 1991 to 2020 to investigate the drought mechanisms driven by ENSO through a comprehensive framework that combines standardized indices with climate–drought correlation analysis. The results indicate that the Comprehensive Drought Index (CDI), integrating the advantages of the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), effectively reflects the basin’s combined meteorological and hydrological wet-dry characteristics. A strong response relationship exists between drought indices in the Jiaojiang River Basin and ENSO events. Drought characteristics in the basin vary significantly during different ENSO phases. The findings can provide theoretical support for the construction of resilient regional water resource systems, and the research framework holds reference value for sustainable development practices in similar coastal regions globally. Full article

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. Full article

The intensification of extreme weather phenomena, ranging from torrential downpours to protracted dry spells, which trigger fluctuations at the groundwater level, poses a grave threat to the stability of embankments, giving rise to an array of concerns including cracking and differential settlement. Consequently, it is crucial to embark on research targeted at uncovering the settlement and deformation behaviors of pile-supported embankments amidst changes in water levels. In tackling this dilemma, a series of direct shear tests were carried out across a range of wet–dry cyclic conditions. The results confirmed that the occurrence of wet–dry cycles significantly impacted the resilience of silty clay. Additionally, it was observed that the erosion of cohesion and the angle of internal friction initially diminished sharply, subsequently leveling off, with the first wet–dry cycle exerting the most substantial influence on soil strength. Employing a holistic pile-supported embankment model, simulations revealed that variations in the groundwater level, fluctuations therein, varying descent rates, and periodic shifts in the groundwater level could all prompt alterations in soil settlement between embankment piles and could augment the peak tensile stress applied to geogrids. In summary, the orthogonal experimental method was utilized, indicating that, in terms of impacting embankment settlement under periodic water-level changes, the factors ranked in descending order were the following: pile spacing, pile length, embankment height, and the height of the groundwater table. Full article

As governments continue to address climate change when formulating policy, there remains a need to determine if such a change exists in the historical record to inform clear indices for monitoring the present climate for site-specific interventions. This study characterised trends and anomalies in rainfall and dry spells, providing local information often projected from satellites or regional data in data-scarce regions. From 1961 to 2007, daily rainfall records in Central Malawi were used to calculate indices for low-(Balaka), medium-(Bunda, Chitedze, KIA), and high-altitude (Dedza) sites, which were then subjected to Mann–Kendall’s, Cramer’s, and Spearman-Rho’s trend tests. Significant decreasing trends in terms of wet days and growing season length were evident across locations. Seasonal and extreme rainfall, dry spells, and inter-seasonal and near-decadal anomalies were not consistently or inevitably significant. Unexpectedly, rainfall anomalies were largest in Bunda and KIA, which have mild climatic regimes, while the lowest were in Balaka, a rainfall-averse zone. The relationship between El Niño-Southern Oscillation (ENSO) and extreme rainfall and dry spell events did not reach statistical significance. In conclusion, extreme precipitation and dry spell events show varied intensities and proportions rather than increased frequency. The disparate results largely justify the need for in-depth local-scale assessments for agroclimatic applications. Full article

This study analyses climate variability on the north coast of Peru to understand how the local weather is coupled with anomalous ocean conditions. Using high-resolution satellite reanalysis, statistical outcomes are generated via composite analysis and point-to-field regression. Daily time series data for 1979–2023 for Moche area (8S, 79W) river discharge, rainfall, wind, sea surface temperature (SST) and potential evaporation are evaluated for departures from the average. During dry weather in early summer, the southeast Pacific anticyclone expands, an equatorward longshore wind jet ~10 m/s accelerates off northern Peru, and the equatorial trough retreats to 10N. However, most late summers exhibit increased river discharge as local sea temperatures climb above 27 °C, accompanied by 0.5 m/s poleward currents and low salinity. The wet spell composite featured an atmospheric zonal overturning circulation comprised of lower easterly and upper westerly winds > 3 m/s that bring humid air from the Amazon. Convection is aided by diurnal heating and sea breezes that increase the likelihood of rainfall ~ 1 mm/h near sunset. Wet spells in March 2023 were analyzed for synoptic weather forcing and the advection of warm seawater from Ecuador. Although statistical correlations with Moche River discharge indicate a broad zone of equatorial Pacific ENSO forcing (Nino3 R~0.5), the long-range forecast skill is rather modest for February–March rainfall (R² < 0.2). Full article

The aim of this study is to present the spatial and temporal variability of the frequency of dry and wet days and dry and wet spells against the background of changes in precipitation and atmospheric circulation. The study is based on daily precipitation totals from 46 meteorological stations in Poland from 1966 to 2023. Additionally, seven circulation indices were used, namely GBI, NAO, AO, EA, EA/WR, SCAND, and AMO. Dry days are defined as days without precipitation. Wet days are days with at least 1 mm of precipitation. It was shown that dry spells are much more common than wet spells, are longer, and cover larger areas. Long-term changes in the annual characteristics of dry and wet days and spells are not statistically significant. Only the length of the most extended dry spell in the year increases. However, there are significant changes in their annual cycles. Spring is drier; in summer, precipitation decreases in the south and increases in the north; November and December, symbols of gloomy rainy weather, are increasingly drier; and rainy weather has shifted to January and February. The impact of circulation varies according to the season, with the NAO, AO, SCAND, and GBI indices having the greatest influence. Full article

In the past decade, Saudi Arabia has witnessed a surge in flash floods, resulting in significant losses of lives and property. This raises a need for accurate near-real-time precipitation estimates. Satellite products offer precipitation data with high spatial and temporal resolutions. Among these, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Dynamic Infrared Rain Rate near-real-time (PDIR-Now) stands out as a novel, global, and long-term resource. In this study, a rigorous comparative analysis was conducted from 2017 to 2022, contrasting PDIR-Now with rain gauge data. This analysis employs six metrics to assess the accuracy of PDIR-Now across various daily rainfall rates and four yearly extreme precipitation indices. The findings reveal that PDIR-Now slightly underestimates light precipitation but significantly underestimates heavy precipitation. Challenges arise in regions characterized by orographic rainfall patterns in the southwestern area of Saudi Arabia, emphasizing the importance of spatial resolution and topographical considerations. While PDIR-Now successfully captures annual maximum 1-day and 5-day precipitation measurements across rain gauge locations, it exhibits limitations in the length of wet and dry spells. This research highlights the potential of PDIR-Now as a valuable tool for precipitation estimation, offering valuable insights for hydrological, climatological, and water resource management studies. Full article

Understanding long-term variations in precipitation is crucial for identifying the effects of climate change and addressing hydrological and water management issues. This study examined the trends of the mean and four extreme precipitation indices, which are the max 1-day precipitation amount, the max 5-day precipitation amount, the consecutive wet days, and the consecutive dry days, for historical observations (1971–2000) and two future periods (2041–2060/2081–2100) under RCP2.6 and RCP8.5 emission scenarios over the Nile River Basin (NRB) at 11 major stations. Firstly, the empirical quantile mapping procedure significantly improved the performance of all RCMs, particularly those with lower performance, decreasing inter-model variability and enhanced seasonal precipitation variability. The Mann–Kendall test was used to detect the trends in climate extreme indices. This study reveals that precipitation changes vary across stations, scenarios, and time periods. Addis Ababa and Kigali anticipated a significant increase in precipitation across all periods and scenarios, ranging between 8–15% and 13–27%, respectively, while Cairo and Kinshasa exhibited a significant decrease in precipitation at around 90% and 38%, respectively. Wet (dry) spells were expected to significantly decrease (increase) over most parts of the NRB, especially during the second period (2081–2100). Thereby, the increase (decrease) in dry (wet) spells could have a direct impact on water resource availability in the NRB. This study also highlights that increased greenhouse gas emissions have a greater impact on precipitation patterns. This study’s findings might be useful to decision makers as they create NRB-wide mitigation and adaptation strategies to deal with the effects of climate change. Full article

The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change. Full article