Dry Days Research Articles

Exposure of African ape sites to climate change impacts

Large gaps remain in our understanding of the vulnerability of specific animal taxa and regions to climate change, especially regarding extreme climate impact events. Here, we assess African apes, flagship and highly important umbrella species for sympatric biodiversity. We estimated past (1981–2010) and future exposure to climate change impacts across 363 sites in Africa for RCP2.6 and RCP6.0 for near term (2021–2050) and long term (2071–2099). We used fully harmonized climate data and data on extreme climate impact events from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Historic data show that 171 sites had positive temperature anomalies for at least nine of the past ten years with the strongest anomalies (up to 0.56°C) estimated for eastern chimpanzees. Climate projections suggest that temperatures will increase across all sites, while precipitation changes are more heterogeneous. We estimated a future increase in heavy precipitation events for 288 sites, and an increase in the number of consecutive dry days by up to 20 days per year (maximum increase estimated for eastern gorillas). All sites will be frequently exposed to wildfires and crop failures in the future, and the latter could impact apes indirectly through increased deforestation. 84% of sites are projected to be exposed to heatwaves and 78% of sites to river floods. Tropical cyclones and droughts were only projected for individual sites in western and central Africa. We further compiled available evidence on how climate change impacts could affect apes, for example, through heat stress and dehydration, a reduction in water sources and fruit trees, and reduced physiological performance, body condition, fertility, and survival. To support necessary research on the sensitivity and adaptability of African apes to climate change impacts, and the planning and implementation of conservation measures, we provide detailed results for each ape site on the open-access platform A.P.E.S. Wiki.

Responses of annual streamflow variability to annual precipitation, extreme climate events and large-scale climate phenomena in the Qinghai-Tibet Plateau

Solar activity and large-scale climate phenomena have significant effects on extreme climate events and streamflow variability. As the roof of the world and the water tower of Asia, the Qinghai-Tibet Plateau (QTP) is highly sensitive to climate change. Therefore, it is of great significance to study the relationship between extreme hydrometeorological events of the QTP and climate change for global hydroclimate research. In this study, we analyzed the spatiotemporal variation and significant oscillation period of several hydrometeorological variables such as extreme precipitation indices (EPIs), extreme temperature indices (ETIs) and annual streamflow variability based on the observation data of hydrometeorological stations in the QTP during 1962–2019 using Sen’s slope estimator, Mann-Kendall test and continuous wavelet analysis (CWT). And the teleconnection patterns and the lead-lag relationship between annual precipitation, extreme climate events, multiple nonstationary climate mode and annual streamflow were evaluated using wavelet coherence (WTC). The results show that the climate of the QTP has been wetter and warmer in the past 58 years. The annual streamflow of several natural rivers in the QTP mainly show an increasing trend over the last 60 years. The annual streamflow of natural river (except Yellow River) increases significantly in three-rivers headwater region, and the rivers in the northeast and northwest also show a significant increase trend, but there is no significant change in the natural river streamflow in the south of QTP. In addition, the annual streamflow of natural rivers had significant periodicities in the bands of 2–4 years, 4–7 years and 7–11 years. The significant coherence of WTC spectra between annual precipitation and streamflow indicate that precipitation is the main reason for annual streamflow variation in the QTP. The variation of extreme climate events significantly regulates the regional annual streamflow. All EPIs except consecutive dry days show an in-phase correlation with annual streamflow of most headwater. Annual streamflow of Naijin River is positively and negatively correlated with extreme warm and extreme cold, respectively, and has a clearer lead-lag relationship than that with EPIs. Annual streamflow of headwater has higher correlations with EI Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) than with sunspot number (SSN). Solar activity may first affect ENSO and PDO, and then this effect is transferred sequentially to the hydrological cycle of the QTP by SSN-modulated PDO and PDO-SSN co-modulated ENSO. It is of great significance to investigate the response of streamflow variation to annual precipitation, extreme climate events and large-scale climate phenomena for water resources management, flood control, ecosystem restoration, and the well-being of surrounding residents and sustainable development in the QTP.

Extreme weather events and Spatio-temporal characterization of climate change variables in Bangladesh during 1975–2019

Bangladesh is susceptible to climate change, thus a detailed study, including the analyses of trends, sub-trends, extreme events and indices was conducted to obtain a complete picture of the climate change pattern in Bangladesh utilizing daily rainfall, maximum, minimum and average temperature data of 26 stations from 1975 to 2019 using R 4.0.2 software. For the trend analysis Mann Kendal (MK), modified Mann Kendall (mMK), Innovative Trend Analysis (ITA) and Sen’s slope methods were used. Sub-trend analysis was conducted using ITA. Standard Anomaly Index (SAI) has been used to identify the frequency and severity of extreme events. ClimPACT2 software was used to check the homogeneity and calculate the extremes of temperature and rainfall data. Our analysis showed that during the last four decades, climate variables changed their patterns and trend heterogeneously over Bangladesh. Most stations showed decremental rainfall trend when central part of the country showed a substantial decrease. The northern and central parts of the country showed significant growth of trend for annual average temperature. The temperature in the monsoon season increased, whereas those in dry season decreased. The rainfall and maximum temperature were inversely related during monsoon whereas during dry season both of them decrease. The pre-monsoon and post-monsoonal rainfall also showed decreasing trends, indicating prevailing drought conditions especially in northern and central parts of the country. The SAI analysis showed alternating drought and wet years in almost all the stations. In the past 20 years, the country’s western region experienced more drought years than before whereas the coastal region experienced more wet years. The analysis of climate extreme indices suggests that, Consecutive Dry Days (CDD), Hot Days (TX90P) and Hot Nights (TN90P) show significant increasing trend throughout the country. The agricultural productivity, water resource management and food security are anticipated to benefit from this study.

Assessment of mean precipitation and precipitation extremes in Iran as simulated by dynamically downscaled RegCM4

This paper aims to assess the mean precipitation and precipitation extremes over Iran as simulated by the Regional Climate Model (RegCM4). A simulation spanning 20 years (1991–2010) at a horizontal resolution of 20 Km is driven by the NCEP / NCAR reanalysis. We evaluated the model by comparing simulated precipitation with observations using Bias, Root-Mean-Square Error, and Index of Agreement metrics. We examined the extreme precipitations based on a set of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) in three categories of intensity (Rx1day and SDII), duration (CDD and CWD), and frequency (R10mm and R20mm). The linear trends are calculated using the Theil–Sen estimator method, and the statistical significance (95% confidence level) is determined by using a modified Mann-Kendall (MMK) trend test. The RegCM4 model satisfactory captured the spatial distribution of precipitation and precipitation extremes, although high bias remained in small parts of Iran, including the northwest and southeast. The northwest bias is due to spring convectional precipitation and the southeast bias could be caused by precipitation from the Asian summer monsoon system, which both of them may not be well simulated by the applied Grell convective scheme. Results indicate that the model reasonably captures Rx1day, SDII, CWD, R10mm, and R20mm Indices over Iran. In good agreement with precipitation observations, the southern coast of the Caspian Sea represents the second-highest extreme precipitation, except for SDII, which is probably due to the high frequency of rainy days in this region. The highest CDD of more than 200 days is found in the arid and semi-arid regions of the southeast. In general, precipitation decreased in most regions of Iran, especially the western, southern, and interior regions. In addition, the results reveal that heavy (R10mm) and very heavy (R20mm) precipitation events have also decreased in the same regions. Results also emphasize an increase in consecutive dry days (CDD) in most parts, especially in the southeast, which deserves more attention in future research. The decreasing trend of precipitation and the increasing trend of CDD show that Iran has become drier in the 2000 s compared to the 1990 s

Screening of representative rainfall event series for long-term hydrological performance evaluation of grassed swales.

Evaluation of the hydrological performance of grassed swales usually needs long-term monitoring data. At present, suitable techniques for simulating the hydrological performance using limited monitoring data are not available. Therefore, current study aims to investigate the relationship between saturated hydraulic conductivity (Ks) fitting results and rainfall characteristics of various events series length. Data from a full-scale grassed swale (Enschede, the Netherlands) were utilized as long-term rainfall event series length (95 rainfall events) on the fitting outcomes. Short-term rainfall event series were extracted from these long-term series and used as input in fitting into a multivariate nonlinear model between Ks and its influencing rainfall indicators (antecedent dry days, temperature, rainfall, rainfall duration, total rainfall, and seasonal factor (spring, summer, autumn, and winter, herein refer as 1, 2, 3, and 4). Comparison of short-term and long-term rainfall event series fitting results allowed to obtain a representative short-term series that leads to similar results with those using long-term series. A cluster analysis was conducted based on the fitting results of the representative rainfall event series with their rainfall event characteristics using average values of influencing rainfall indicators. The seasonal index (average value of seasonal factors) was found to be the most representative short rainfall event series indicator. Furthermore, a Bayesian network was proposed in the current study to predict if a given short-term rainfall event series is representative. It was validated by a data series (58 rainfall events) from another full-scale grassed swale located in Utrecht, the Netherlands. Results revealed that it is quite promising and useful to evaluate the representativeness of short-term rainfall event series used for long-term hydrological performance evaluation of grassed swales.

Wastewater generation model to predict impacts of urine separation on wastewater treatment plants.

Wastewater treatment plants (WWTPs) are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. The separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central WWTPs. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study focuses on an adapted stochastic wastewater generation model, which allows the simulation of various wastewater streams (e.g., urine) on a household level. This enables the non-uniform separation of urine across a catchment area. The model is part of a holistic modelling framework to determine the influence of targeted urine separation in catchments on the operation and emissions of central WWTPs, which will be briefly introduced. The wastewater generation model is validated through an extensive sampling and measurement series. Results based on observed and simulated wastewater quantity and quality for a catchment area of 366 residents for two dry weather days indicate the suitability of the model for wastewater generation and transport modelling. Based on this, four scenarios for urine separation were defined. The results indicate a potential influence of spatial distribution on the peaks of total nitrogen and total phosphorus.

Variability of Metal(loid) Contamination in Road Dust from an Urban Park and a Traffic Intersection Between Two Rainfall Events and Its Implications

ABSTRACT Metal(loid) pollutants in road dust (road-deposited sediment) show obvious seasonal characteristics under the influence of sources. However, the short-term (days to weeks) variations of metal contamination in road dust in different functional areas with antecedent dry days (ADDs) and their relationships with the source factors were poorly understood, which reduced the comparability of researches and effectiveness of pollution remediation. Herein, temporal characteristics of As, Ba, Ca, Cd, Cr, Cu, Pb and Zn contamination in road dust were studied in two distinct functional areas in Nanjing, i.e. an urban park (Xuanwu, XW) and a stop light-controlled traffic intersection (Baima, BM), following a continuous 23-day sampling between two rainfall events. Mean concentrations of each metal at BM and XW were 1.6–29.5 and 1.3–10.8 times higher than those in the background soil, respectively. The enrichment factor (EF) was used to compensate for grain-size effect. EFs of metals were between 1.3 and 50.3, showing minor to extremely high contamination and different temporal trends. Combined with the EFs and positive matrix factorization (PMF) results, dry atmospheric deposition of industrial and construction sources was the main cause for comparable contamination levels of As, Ca, Cd and Zn between BM and XW and those stable temporal trends. Due to the traffic contribution, contamination levels of Cu, Ba, Pb and Cr at BM were higher (p < .05) than at XW. Different from the stable contamination levels at XW, contamination levels of Cu, Ba, Pb and Cr decreased at BM with the ADDs due to the dilution of traffic particles by less metal enriched atmospheric deposition. These results shed light on the quite different variations of metal contamination in road dust from different functional areas with ADDs under the influence sources, and have instructive significance on road dust sampling, metal contamination remediation and comparison between studies.

Changes in Weather Systems during Anomalously Wet and Dry Years in Southeastern Australia

Abstract This study focuses on the rainfall-producing weather systems in the southern Murray–Darling Basin (MDB), Australia. These weather systems are divided into objects: cyclones, fronts, anticyclones, warm conveyor belt (WCB) inflows, WCB ascents, potential vorticity (PV) streamers, and cutoff lows. We investigate the changes in the frequency, amplitude, and relative position of these objects as the daily and seasonal rainfall change. Days on which the rainfall is heavy, especially in winter, are characterized by more PV streamers, cutoff lows, cyclones, fronts, and WCBs in the region. In contrast, dry days are characterized by more anticyclones over southeastern Australia in winter and summer. The effect of upper-level weather objects (PV streamers and cutoff lows) on lower-level objects, and their importance in producing rainfall, is quantified using the quasigeostrophic ω equation and separating the vertical motion into that induced by the upper and lower levels. On heavy rainfall days in winter, PV streamers and cutoff lows force strong upward motion in the lower troposphere, promoting cyclogenesis at lower levels, forcing ascent in the WCBs, and producing rain downstream of the southern MDB. Lower-level ascent forced by upper-level objects is important for the development of heavy rainfall in both seasons, although particularly in winter. Rainfall is attributed to individual objects. PV streamers and WCBs contribute most to the winter and summer rainfall, respectively. The difference in rainfall between anomalously wet and dry years can be explained in winter by the changes in the rainfall associated with PV streamers, whereas in summer it is mostly due to a reduction in the rainfall associated with WCBs. Significance Statement The aim of the present study is to better understand how synoptic-scale weather systems differ in southeastern Australia in dry and wet periods, by considering a wide range of weather systems. We found weather systems are more closely aligned in the vertical on heavy rainfall days, and the majority of rainfall in this region is associated with warm conveyor belts. These results point to warm conveyor belts being an important, but not well recognized, contributor to rainfall in this region. Future work may investigate the roles of the various modes of variability and climate change in modulating warm conveyor belts and hence the regional rainfall variability in Australia.

Impacts of Climate Change on Teesta River Basin Char Lands: A Study of Livelihood and Ecosystem Dynamics in Bangladesh

This study anticipates identifying how does climate change affect the livelihood and ecosystem of char land of Teesta River basin char land. Structured questionnaire and related documents were used for both primary and secondary data collection. Survey was conducted in two districts (Rangpur and Nilphamari) and four unions (Lakhitari, Topa Madhupur, Shatibari, Gulmund) of four upazilas (Gangachara, Kaunia, Dimla, Jaldhaka). A total of 50 respondents from each selected char union was selected following a multistage random sampling procedure. Thus, there was altogether 200 respondents selected for this study. Data related to age, education level, occupation, knowledge about climate change of char inhabitants and perception of char dwellers regarding climate change was measured. A total number of 93% of the respondents clearly grasp that climate change refers to changes in long-term typical weather. It was observed that ongoing climate change has 78% impact on agriculture followed by health of peoples and other animals that is 20%. In the rainy season they observed increase in lightning from sun as the highest effect of climate change that has a WAI of 1.77. Teesta river basin people perceived dry spell frequency as the second highest extent of climate change that had a WAI of 1.74 followed by timing of rain offset, uneven distribution of rainfall and timing of rain onset. According to their perception it was found that great extent of loss was found in skills of char peoples (48.35%) followed by knowledge of char peoples (44.27%). It was also observed that a third great extent of loss was found in char peoples good health (41.67%) followed by ability to work (39.06%). Out of all the respondents 166 (43.2%) observed that soil is becoming dry day by day due to climate change followed by rivers becoming dry (37.8%) (Table 8). They found that growing trees have become difficult (45.1%), due to drought underground water is decreasing (61.7%) and air became dry due to climate change, and these are small extent of loss. Char inhabitants observed that climate change impact on physical capital and great extent impact was perceived on people's migration to another place (41.4%). Teesta River basin char dwellers opined about 24 adaptation strategies to reduce the impact of climate change on livelihood and ecosystem in that area.

Evaluasi Efisiensi Air Gedung Perkantoran Pada Musim Kering Pada Perencanaan Bangunan Gedung Hijau

Water is necessary for various human activities. The larger the population, the greater the water consumption. Harnessing rainwater and reusing recycled grey and black water can reduce consumption. Water efficiency needs to be a concern because of the limited availability of water and to maintain limited water availability. Water consumption in buildings for office functions is relatively high. Therefore, office buildings are very important to be designed as environmentally friendly buildings. Water efficiency is a criterion for eco-friendly buildings, more commonly known as green buildings. This research aims to improve water efficiency by utilizing rainwater and recycled water in the Waskita Karya building. The secondary data collection required is at the planning stage. The data collected are water-saving features, rainfall, building area of each floor, site plan, and other relevant data. Water efficiency calculations take into account wet and dry days. On wet days because water comes from rain, and on dry days, the water source is only from PDAM and recycled water. Software issued by the Directorate General of Copyright calculates the water balance. The calculation will result in water savings on dry days. Conventional water consumption amounted to 83,153 lt / day, water source from recycled grey water 29,216 lt / day, black water 14,143 lt / day, efficiency on dry days amounted to 76.8%. This research needs to be implemented so that building owners know their water consumption and can support green building performance and water cost savings.

Upper Colorado River Streamflow Dependencies on Summertime Synoptic Circulations and Hydroclimate Variability

Abstract The southwestern United States is highly sensitive to drought, prompting efforts to understand and predict its hydroclimate. Oftentimes, the emphasis is on wintertime precipitation variability, yet the southwestern United States exhibits a summertime monsoon where a significant portion of annual precipitation falls through daily convection activities manifested by a midtropospheric ridge of high pressure. Here, we examine synoptic patterns of the southwestern ridge through a k-means clustering analysis and assess how these synoptic patterns translate into streamflow changes in the upper Colorado River basin. A linear perspective suggests ∼17% of upper Colorado River discharge at the Lee’s Ferry, Arizona, gauge comes from summertime monsoon rains. The ridge of high pressure exhibits diversity in its intensity, structure, and position, inducing changes in moisture advection and precipitation. A ridge shifted north or east of its climatological center increases moisture and precipitation over the southwestern United States, while a ridge toward the south or northwest inhibits precipitation. A ridge east of its climatological center contributes to increased streamflow, whereas a ridge west or northwest of its climatological center decreases streamflow. Cooling in the central tropical Pacific and the Pacific meridional mode region favors an eastward shift of the ridge of high pressure corresponding to wet days. Eastern tropical Pacific warming favors a southward shift of the ridge corresponding to dry days. These results support an intermediate scale between climate forcing and summertime Colorado River discharge through changes in the intensity, structure, and position of the southwestern ridge of high pressure, integral to the U.S. Southwest hydroclimate.

Evaluation of Five Reanalysis Products over France: Implications for Agro-Climatic Studies

Agro-climatic indicators (AgcIs) provide a suitable tool to evaluate the implications of climate change on agriculture by simplifying plant–climate interactions. However, developing reliable AgcIs requires high-quality historical climate datasets. Consequently, reanalysis products (RPs) are frequently used as a potential reference dataset for observed climate in agricultural studies. This study aims to compare five RPs (ERA5, ERA5-Land, SCOPE Climate, FYRE Climate, and RFHR) at reproducing observed AgcIs over France. The RPs are evaluated against the SYNOP meteorological data over the 1996–2012 period, focusing on six AgcIs specific to apple, maize, and vine crops. The findings show that RPs perform well in reproducing temperature-based AgcIs, with some slight discrepancies in areas with complex topography. However, all RPs tend to overestimate precipitation amounts and to underestimate dry days, leading to a poor performance in reproducing precipitation-based AgcIs. This study emphasizes the need for a thorough evaluation of the RPs in developing both temperature-based and precipitation-based AgcIs, especially if findings are intended to support operational agricultural decision-making.

Evaluation of the Performance of Nature-Based Constructed Wetlands for Treating Wastewater from Various Land Uses in Korea

Land use changes, specifically the growth of impervious areas due to urbanization, exacerbate non-point-source pollutants in stormwater runoff, surpassing discharge from point sources in Korea. The application of nature-based solutions, such as constructed wetlands (CWs), is becoming popular for stormwater treatment, but challenges arise when background concentrations are overlooked, leading to reduced pollutant removal efficiency. This study aims to propose a plan for the sustainability of CWs by evaluating design appropriateness and utilizing existing monitoring results. The evaluation of 63 CWs reveals that meteorological factors, specifically antecedent dry days and rainfall depth, have significant impacts on urban stormwater runoff quality in various land uses, affecting the performance of CWs. Designing CWs considering land use is crucial due to the considerable concentration variations across different land uses. Improving CW performance requires proper maintenance strategies to ensure effective pollutant removal mechanisms, especially for poorly degradable organic substances post treatment. Rainfall characteristics play a pivotal role in CW design and operation, affecting capacity, efficiency estimation, and maintenance frequency. Considering various factors such as land use, watershed characteristics, and ease of maintenance is essential when utilizing CWs. This study’s findings contribute to the design and operation of future CWs, emphasizing the need for continuous performance analyses through long-term monitoring.

The Effect of Incorporating Juncus Fibers on the Properties of Compressed Earth Blocks Stabilized with Portland Cement

This study investigates the impact of incorporating Juncus fibers (JF) into compressed earth blocks (CEBs) stabilized with varying Portland cement contents, aiming to enhance local construction materials’ performance and reduce housing costs. CEB composites were produced with soil stabilized using different cement contents (4%, 8%, and 12% by weight) and JF reinforcement (0 to 0.2% by weight), compressed at 10 MPa with a hydraulic press. After 28 days of drying, the CEBs underwent diverse experimental characterizations to assess their physical, mechanical, thermal, and durability properties. The results revealed that incorporating JF led to a reduction in unit weight, ultrasonic pulse velocity (up to 36%), and dry compressive strength (approximately 17%). Higher fiber content correlated with increased water absorption and an increased capillarity coefficient. Thermal conductivity analysis indicated improved thermal performance, decreasing from 0.4350 W/m·K (12% cement without fibers) to 0.2465 W/m·K (4% cement with 0.2% JF). Despite the decrease in mechanical strength, CEBs with lower cement (4%) and higher fiber content (0.2%) demonstrated satisfactory durability (abrasion and erosion) and thermal insulation properties. This research suggests the potential of this material as a promising composite for the building materials industry. The findings contribute valuable insights into sustainable construction materials and have implications for cost-effective housing solutions.

Assessing Future Precipitation Patterns, Extremes and Variability in Major Nile Basin Cities: An Ensemble Approach with CORDEX CORE Regional Climate Models

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.

Evaluation of precipitation across the contiguous United States, Alaska, and Puerto Rico in multi-decadal convection-permitting simulations

This study is an early effort to generate a multi-decadal convection-permitting regional climate dataset that covers nearly the entire North American continent. We assessed a 20 year dynamically downscaled regional climate simulation at a 4 km spatial resolution with explicit convection across the contiguous United States (CONUS), Alaska, and Puerto Rico. Specifically, we evaluated the model’s performance in representing mean, 95th percentile, and extreme precipitation across regions. Our findings indicate that when compared with ERA5 reanalysis, the forcing data, convection-permitting simulation improves representations of seasonal, 95th percentile, and extreme precipitation over a large portion of the CONUS, Alaska, and Puerto Rico, particularly in areas where precipitation is heaviest. The simulation adds value over its forcing data (ERA5) in up to 53% of all grid cells in the CONUS, 68.8% in Alaska, and 84.0% in Puerto Rico. It is important to note that, however, despite improvements, model errors in Puerto Rico remain large. Similar improvements are observed in extreme indices, including consecutive dry days, maximum 5 days precipitation, and extreme precipitation. Analysis of the diurnal cycle of mean hourly precipitation suggests that representations of convective processes—including onset, dissipation, suppression, downstream propagation, and local circulation—improved overall.

Untreated Rainfall Runoff Water Quality Characteristics of Different Land Uses in Infilled Lake Areas—The Case of Wuhan Shahu

Fast urbanization in developing countries contributes to heavier pollution in urban water environments, as urbanization enhances land development and even requires lake filling to meet urban land needs, which produces significant water runoff pollution. Centralized construction brings heavier non-point source pollution, which is one of the most crucial types of pollution in urban areas. However, the pollution caused by urbanization in infilled lake areas is lack of attention. To reduce the negative impact of pollution brought on by urbanization, it is important to monitor the characteristics of runoff water qualities and their relationship with rainfall features. In this study, runoff water quality was monitored from 10 rainfall events, totaling 157 samples in the Wuhan Shahu area, an infilled lake area, to characterize the pollutant event mean concentrations (EMCs) and to explore the different effects of land-use types. COD (chemical oxygen demand), TN (total nitrogen), and TP (total phosphorus) were selected as water quality indicators. The results show that the pollutants have a significant spatial variation. Residential runoff had the largest COD (averaged EMC = 54.02 (mg/L)) and TN (averaged EMC = 2.69 (mg/L)) pollution, while road runoff had the second largest COD (averaged EMC = 48.05 (mg/L)) and TN (2.572 (mg/L)) pollution. The TP pollution level is opposite to COD and TN, as commercial and green spaces have heavier pollution, while the differences in TP pollution levels between the four types of land are not significant. The release of organic matter and nitrogen is closely related to human activities on land types, while phosphorus emission is relatively stable, indicating that it is not easily affected or controlled. In addition, the variation in pollutants between land types is also related to a certain extent. The correlation analysis shows that parameters like antecedent dry days (ADDs), rainfall intensity, and rainfall duration most significantly affect the EMCs of commercial and green spaces. Phosphorus pollutants on roads are harder to reduce. These results may help researchers to identify the specific pollutant source and find an effective method to reduce pollution in infilled lake areas and other areas.

Comprehensive analysis of spatiotemporal variability of rainfall-based extremes and their implications on agriculture in the Upper Ganga Command Area.

The agricultural sector in India primarily relieson monsoon rains, making it necessary for agricultural water managers to study variations in water availability by analyzing rainfall patterns. This information is critical for deciding cropping patterns and irrigation approaches, managing water resources, and improving crop water productivity. The long-term spatiotemporal variability over the command area, India Meteorological Department (IMD) based selection of thresholds for extremes indices, and thorough analysis of the consequences of extreme on agriculture make the study unique. These aspects collectively enhance the perception of the climate-agriculture relationship, which is essential for promoting agriculture resilience under changing rainfall patterns. This type of research is very limited in the literature. Therefore, the present study focuses on comprehensively analyzing the spatiotemporal variability of rainfall and extreme precipitation indices and their implications on agriculture. The study is carried out in the UpperGanga Command Area (UGCA), India's oldest irrigation canal system, by using long-term (1901-2021) high-resolution (0.25 × 0.25°) daily rainfall gridded data obtained from IMD, Pune. Eight different extreme rainfall indices are used to assess spatiotemporal variations. The Mann-Whitney-Pettitt test identified 1970 as a significant change point. Rainfall trends and extreme indices for pre- and post-1970 periods were examined using the non-parametric modified Mann-Kendall test. The results show significant increases in rainfall trends for the annual, monsoon, and kharif seasons from 1901 to 1970, but significant decreases were observed during 1971-2021. This difference resulted in a noticeable decrease in average precipitation in the latter period, approximately 62mm less than in 1901-1970. Similarly, extreme precipitation indices, including the number of rainy days (NxRainy), consecutive dry days (CWD), simple daily intensity index (SDII), and total precipitation (PRCPTOT), exhibited increasing trends in 1901-1970, but they showed significant decreasing trends in 1971-2021. In addition, there is a strong positive correlation between these indices and total precipitation. The study also found that geographical factors influence these trends, with all indices, except SDII, strongly correlated with latitude and elevation, but not with longitude. The implications of these negative rainfall and extreme rainfall trends were further analyzed, and the results indicate a significant impact on the cropping patterns in the study area. The present research findings will be beneficial for regional water resource managers and policymakers in better understanding the existing trends in rainfall distribution over the UGCA.

Combined influence of El Niño, IOD and MJO on the Indian Summer Monsoon Rainfall: Case Study for the years 1997 and 2015

To find out how El Niño, the positive Indian Ocean Dipole (IOD), and the Madden-Julian Oscillation (MJO) affect the Indian Summer Monsoon Rainfall (ISMR), this study looks at two different monsoon years: 1997 (normal ISMR) and 2015 (below-normal ISMR). These two years were ideal for examining their combined effects on the performance of ISMR because they both experienced super El Niño conditions over the Pacific Ocean and positive IOD over the Indian Ocean. In these two years, spatial diversity associated with sea surface temperature (SST) was found over the Indian Ocean as well as the Pacific Ocean. The analysis of the large-scale circulation showed a distinct difference: the below-normal monsoon in 2015 was due to weak southwesterly flow toward the Indian landmass as well as anomalous subsidence compared to 1997. Analysis of rainy and dry days shows that 2015 had a greater (less) number of dry (rainy) days compared to 1997, contributing to a below-normal ISMR in 2015. The study also looked at the role of MJO in the observed rainfall anomalies over India during these two years, when there was both El Niño and positive IOD. This was done by looking at the composite of rainfall anomalies for different MJO phases. In 1997, during the monsoon season, MJO showed prolonged activity over the Indian Ocean (favorable MJO phases), which contributed to normal ISMR. However, in 2015, MJO was found active for many days over the western Pacific (unfavorable MJO phases), which contributed to below-normal ISMR. Overall, this case study highlights the complex interactions between El Niño, IOD, MJO, and monsoon dynamics, emphasizing the need for a comprehensive study of these factors to understand the behaviour of ISMR.

Future changes in the precipitation regime over the Arabian Peninsula with special emphasis on UAE: insights from NEX-GDDP CMIP6 model simulations

Global warming can profoundly influence the mean climate over the Arabian Peninsula, which may significantly influence both natural and human systems. The present study aims to investigate the changes in the precipitation regime in response to climate change over the Arabian Peninsula, with special emphasis on the United Arab Emirates (UAE). This work is performed using a sub-set of high-resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data derived from Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models under three different Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The changes are analyzed in three phases such as 2021–2050 (near future), 2051–2080 (mid future) and 2080–2100 (far future), with the period of 1985–2014 as the baseline. This study represents the first attempt to utilize data from NEX-GDDP models to project the regional patterns of precipitation regime across the Arabian Peninsula. Results suggest that the annual precipitation is expected to increase over most of the UAE by up to 30%, particularly intense from the mid-future onwards in all scenarios. Specifically, the spatiotemporal distribution of precipitation extremes such as intensity, 1-day highest precipitation, and precipitation exceeding 10 mm days are increasing; in contrast, the consecutive dry days may decrease towards the end of the century. The results show that the changes in extreme precipitation under a warming scenario relative to the historical period indicate progressive wetting across UAE, accompanied by increased heavy precipitation events and reduced dry spell events, particularly under the high emission scenarios. A high-resolution dataset is essential for a better understanding of changes in precipitation patterns, especially in regions where more detailed information is needed on a local scale to achieve water, food security, and environmental sustainability to formulate effective adaptation strategies for mitigating the potential risks and consequences associated with variations in wet and dry conditions.