Decrease In Precipitation Research Articles

32 years of changes in river paths and coastal landscape in Bangladesh, Bengal Basin

AbstractThis study examines the geomorphological changes and environmental impacts on the coastline and the evolution of major river systems in Bangladesh over the past 32 years using remote sensing and GIS analyses. The central coastal area, characterized by fine sediments, has experienced significant land erosion due to the dynamics of the Meghna Estuary and its depositional patterns. In contrast, the southwestern Sundarbans Forest coast has remained relatively stable, aided by mangrove root stabilization despite anthropogenic threats. Channel migration analysis revealed the Brahmaputra River’s persistent braided configuration, while its tributaries, Teesta and Dharla, increased meandering nature due to reduced water availability and human interventions. The Ganges-Padma system displayed a shift towards a more sinuous channel pattern driven by reduced water discharge due to the Farakka Barrage construction in the upstream and a minor decrease in precipitation. The Upper Meghna River maintained moderate sinuosity with stable anastomosed patterns, whereas the lower Meghna River’s convergence with the Jamuna and Padma Rivers increased its susceptibility to erosion. These findings highlight the interplay of natural processes and human activities in shaping the coastal and fluvial landscapes of Bangladesh and the Bengal Basin, emphasizing the need for sustainable land-use practices and adaptive management strategies to mitigate future risks associated with sea-level rise and river course changes.

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.

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.

Investigating a Century of Rainfall: The Impact of Elevation on Precipitation Changes (Northern Tuscany, Italy)

Precipitation is crucial for water resource renewal, but climate change alters their frequency and amounts, challenging societies for correct and effective water management. However, modifications of precipitation dynamics appear to be not uniformly distributed, both in space and time. Even in relatively small areas, precipitation shows the coexistence of positive and negative trends. Local topography seems to be a strong driver of precipitation changes. Understanding precipitation changes and their relationship with local topography is crucial for society’s resilience. Taking advantage of a dense and long-lasting (1920–2019) meteorological monitoring network, we analyzed the precipitation changes over the last century in a sensitive and strategic area in the Mediterranean hotspot. The study area corresponds to northern Tuscany (Italy), where its topography comprises mountain ridges and coastal and river plains. Forty-eight rain gauges were selected with continuous annual precipitation time series. These were analyzed for trends and differences in mean annual precipitation between the stable period of 1921–1970 and the last 30-year 1990–2019. The relationship between precipitation changes and local topography was also examined. The results show the following highlights: (i) A general decrease in precipitation was found through the century, even if variability is marked. (ii) The mountain ridges show the largest decrease in mean annual precipitation. (iii) The precipitation change entity over the last century was not homogenous and was dependent on topography and geographical setting. (iv) A decrease in annual precipitation of up to 400 mm was found for the mountainous sites.

Study on the performance temporal variation of rainwater harvesting systems based on the dynamic change of rainfall pattern and domestic water demands

Rainwater harvesting systems (RWHs) in buildings are benefits in alleviating urban water scarcity. However, climate change and changes in building water demand affect the expected performance of RWHs over their life cycle. Previous studies have only focused on the adaptability of RWHs to climate change without considering the changes in building water demand. To address this issue, this study explores the impact of combined changes in precipitation patterns and domestic water demand on the water-saving efficiency of RWHs over their 25-year life cycle based on historical observations. Three cities in Japan were selected as case studies. The results indicate that during 25-year life cycle of RWHs, precipitation in different cities in Japan shows an increasing trend, while domestic water demand shows a decreasing trend. Such trend resulted in a change of -2.90–4.02% in the water-saving efficiency of the established RWHs and a change of -2.90–3.82% in the theoretical optimal water-saving efficiency, and these effects were greater in RWHs in buildings with high non-potable water demands. Therefore, RWHs in buildings with low non-potable water demand can appropriately reduce the rainwater tanks, while RWHs in buildings with high non-potable water demand must increase the rainwater tank size to eliminate this adverse effect. Furthermore, both reductions in domestic water demand and increases in precipitation have a positive effect on the water-saving efficiency of RWHs. However, when both domestic water demand and precipitation increase or decrease simultaneously, the change in water-saving efficiency of RWHs is related to the non-potable water demand of the building. This study can provide data support and theoretical evidence for the further implementation of RWHs under climate change, and can help stakeholders to optimize and update RWHs to ensure system feasibility.

Quantifying Climate Change Variability for the Better Management of Water Resources: The Case of Kobo Valley, Danakil Basin, Ethiopia

Alterations in the hydrological cycle due to climate change are one of the key threats to the future accessibility of natural resources. This study used 12 GCM climate models from CMIP6 to evaluate future climate change scenarios by applying model performance measures and trend analysis in Kobo Valley, Ethiopia. The models were ranked based on their ability to analyze the historical datasets. The result of this study showed that the outputs of the FIO-ESM-2-0 CIMP6 model had a good overall ranking for both precipitation and temperature. After bias correction of the model-based projections with the observed data, the average annual precipitation in the average scenario (SSP2-4.5) decreased by 4.4% and 13% in 2054 and 2084, respectively. Similarly, in the worst-case scenario (SSP5-8.5), by the end of 2054 and 2084, decreases of 4% and 12.8%, respectively, were predicted. The average annual maximum temperature under the SSP2-4.5 scenario increased by 1.5 °C in 2054 and by 2.1 °C in 2084. The average annual maximum temperature under the worst-case (SSP5-8.5) scenario increased by 1.7 °C in 2054 and by 3.2 °C in 2084. In the middle scenario (SSP4.5), the average annual minimum temperature increased by 2.2 °C in 2054 and by 3 °C in 2084. The average annual minimum temperature under the worst-case (SSP5-8.5) scenario increased by 2.6 °C in 2054 and by 4.3 °C in 2084. The seasonal variability in precipitation in the studied valley will decrease in the winter and increase in the summer. A decrease in precipitation combined with an increase in temperature will strengthen the risk of drought events in the future.

The contribution of Arabian Sea warming to decreasing summer precipitation in the northern Greater Mekong Subregion

The Greater Mekong Subregion (GMS) is one of the world's most important agricultural regions. Over recent decades, the declining trend in precipitation has caused more frequent droughts over the northern plateau of the GMS, and this has led to a significant reduction in agricultural productivity. These drought events can also affect agriculture within the middle and lower parts of the Mekong River basin. To reveal the main causes of the decline in precipitation, this study investigates interdecadal variations in summer precipitation over the northern GMS during 1979–2022. Results indicate that summer conditions over the northern GMS entered a relatively dry period after the late 1990s. The interdecadal decrease in summer precipitation is closely associated with the warming of the northern Arabian Sea (AS), which induces a cyclonic anomaly that enhances local precipitation and associated diabatic heating. The anomalous diabatic heating induces a downstream Rossby wave train that intensifies the circumglobal teleconnection (CGT) pattern and causes the South Asian high (SAH) to extend farther southeastwards. The southeastward-displaced SAH induces easterly anomalies over the northern Bay of Bengal (BOB) that weaken the Indian summer monsoon (ISM) southwesterly flows and reduce moisture transport from the northern BOB to the northern GMS. The southeastward displacement of the SAH also causes anomalous descent over the northern GMS. Both conditions result in reduced precipitation over the northern GMS. Numerical experiments substantiate the proposed modulating role of AS warming in the interdecadal decrease in summer precipitation over the northern GMS.

Using hydrological modeling and satellite observations to elucidate subsurface and surface hydrological responses to the extreme drought

Climate change and anthropogenic activities have intensified extreme weather events globally. In the summer of 2022, the Yangtze River Basin (YRB) in China experienced an extreme drought, significantly impacting the ecosystems and society. However, the specific effects of this extreme drought on surface and subsurface hydrological dynamics remain unclear. Here we employed satellite-observed terrestrial water storage anomaly (TWSA) and a modified hydrological model with consideration of reservoir operation, human water consumption, and water diversion engineering to quantify how subsurface and surface water in YRB responded to such an extreme drought in 2022. Validation against a series of observations shows that the modified model has good performance in reproducing daily streamflow, reservoir water storage, lake water storage, and snow water equivalent. It achieved more precise GRACE TWSA estimates in the YRB with significant human intervention, and therefore it can fairly accurately quantify both surface and subsurface hydrological responses to the 2022 extreme drought. Compared to the same months (July-December) in 2015–2021, the drought in 2022 resulted in a decrease in precipitation and discharge of 373 km3 (36 %) and 324 km3 (50 %), respectively, while an increase in evapotranspiration of 156 km3 (29 %) in the YRB. In general, the surface water storage (SWS) is relatively low from July 2022, followed by subsurface water storage (SSWS) from August 2022, indicating an approximately one-month lag from the former to the latter. During the latter half year of 2022, the SWS and SSWS reduced by 48 km3 and 83 km3, respectively, suggesting the changes in the latter dominated the TWS variations. This study sheds light on the responses of surface and subsurface hydrology to extreme droughts, and the hydrological modeling framework with consideration of human activities proposed here holds applicability beyond the YRB.

Drought vulnerability assessment and its impact on crop production and livelihood of people: An empirical analysis of Barind Tract

North-Western section of Bangladesh is experiencing a protracted decrease in precipitation, irregular rainfall, and the depletion of ground water, which results in water scarcity and extreme dry weather that impedes the production of agricultural commodities and threatens the people's way of life. Analyzing the precipitation deficit and ground water deficit, along with vegetation cover, temperature condition, and the condition of the vegetation is a crucial component of drought vulnerability assessment. Rajshahi Zilla, a region of Bangladesh located in the middle of the Barind tract, is experiencing a severe water shortage. The irregular rainfall, decrease in rainfall, prolonged absence of rainfall and ground water depletion results in drought. This study aims to access the vulnerability of drought by analyzing precipitation rates, ground water depletion levels, temperature condition, vegetation condition and the vegetative droughts to find out the severe condition of droughts and the severe effects of this in the livelihoods of the farmers and their crop production practices. In this case the study focuses on determining NDVI, NDWI, NDMI, VCI, TCI, and VHI. The VHI results show a significant increase in extreme drought conditions from 2013 (4 %) to 2021 (7 %). By conducting a few questionnaire surveys and Focus Group Discussion the present situation of crop production and the livelihoods of people has been analyzed. Almost 18.3 % of farmers have made a permanent move away from agriculture, and 80 % of permanently relocated farmers report an improvement in their quality of life. Nearly 60 % of farmers believe that the construction of deep ditches has enhanced their crop yield. Once again, more than 20 % are in the same predicament as previously, with over 19 % reporting that deep irrigation has lowered agricultural yield. Comprehending the potential consequences of drought will enable planners and decision-makers to implement mitigation measures aimed at improving the communities' ability to manage drought risk. After analyzing data, it has been found that Rajshahi is facing a critical drought problem, which has led to water scarcity, severely affecting agricultural production and livelihoods.

Projected changes of thermal, rainfall and drought indices in Morocco from high resolution climate models

Abstract Over the past decade, global changes in temperature, average and extreme precipitation have been observed many times. The increase in temperature or even the change in precipitation systems is directly affect extreme weather events, for example, heat waves, heavy rainfall, storms, and droughts are becoming more frequent and more powerful worldwide due to climate change caused by several factors including human activity. This is why there is a necessity to monitor future changes in climate extremes. The objective of this paper is to evaluate the future changes in thermal and rainfall extremes projected by the four climate models over time horizon 2041-2060 relative to the 1981-2010 reference period, based on the 5 climate indices, including Tmm, Tx90p, WSDI, PRCPTOT and SPI. The projections are given under the RCP 4.5 medium scenario. The analysis in thermal aspect shows that Morocco could experience by 2041-2060, a significant warming, has manifested by an increase in average temperature. Future changes in rainfall indices show that the spatial distribution of rainfall in Morocco could change significantly by 2041-2060 compared to the reference period 1971-2010. The four climate models agree on a decrease in annual precipitation that could affect most of the Kingdom. In the same way to dryness, the future changes of the SPI index that characterizes the drought, indicates a move to a dry climate.

Influence of precipitation and temperature on burned areas in the agricultural and cattle ranching frontier of the Brazilian Amazon.

Fire occurrence, intensity, and spread are highly influenced by climatic variables. This study investigates the correlation between burned area, precipitation, and temperature in Rondônia, an agricultural frontier in the southwestern Brazilian Legal Amazon, from 2001 to 2022. The analysis utilized climatological data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and MODIS product MOD11A1.061 for temperature, along with MODIS product MCD64A1 for burned area. The study was conducted on a monthly scale, employing the cross-correlation function to determine the lagged effects of temperature and precipitation on burned areas. Trend analysis was performed using the Mann-Kendall test, with the magnitude of trends estimated by Sen's Slope. Results indicated a significant negative correlation between burned areas and precipitation, with a 2-month lag and an R2 of - 0.51. In contrast, temperature exhibited a significant positive correlation with burned areas, showing a 1-month lag and an R2 of 0.55. Trend analysis revealed a decrease in precipitation by - 0.0542mm.month-1, temperature increased by 0.006°C.month-1, while burned areas decreased by - 111.13 km2.month-1. These findings underscore the intricate relationship between climate variables and fire occurrences, highlighting the urgent need for policies addressing climate change and environmental degradation in the Amazon.

Urban trees left high and dry – Modelling urban trees´ water supply and evapotranspiration under drought

Abstract Long-lasting extreme weather conditions are expected to occur more frequently in the future owing to climate change, as demonstrated by the recent heat waves. In particular, the decrease in precipitation during the summer months had a significant impact on urban tree water availability. Therefore, it is imperative to develop methodologies for determining the available water supply and evaporation rates for urban trees. We mapped data from 49 urban small-leaved linden trees with varying characteristics including groundwater levels, shading situations, tree pit sizes, pavement materials, and sealing ratios. By combining these data with an adapted Penman-Monteith method to calculate evapotranspiration, we simulated the soil water storage and evapotranspiration rates of these trees during the very dry year of 2018 as an example. Model validations were performed using lysimeter and sap-flow studies on Tilia cordata trees in 2022.
During the growing season, most trees experienced water stress on > 85% of the days because of weak precipitation events that failed to refill soil water storage. In contrast, trees with additional water supply through capillary rise reached water stress approximately 45 d later. The model results suggest that many trees will require additional water supply during predicted droughts in the future, which could have significant implications for urban forestry management. This model approach can be used to test and refine future water supply management strategies, making it a useful planning tool for improving the water efficiency of trees in urban areas and blue-green infrastructure.

Effects of simulated precipitation changes on soil respiration:Progress and prospects.

Soil respiration, the main pathway for transferring terrestrial carbon pool to atmospheric carbon pool, is profoundly affected by the intensification in global precipitation variability in the context of climate change. Nowadays, variable controlling methods and field manipulation experiments are two main methods widely used to investigate the effects of simulated precipitation changes on soil respiration. Yet, due to the heterogeneity of soil properties, vegetation types, and the magnitude of precipitation change, there is substantial inconsistency in the conclusions of simulated precipitation change effects on soil respiration. Here, we analyzed data from domestic and foreign literature, and examined the effects of simulated precipitation change on soil respiration. Firstly, we described the response pattern of soil respiration to soil moisture fluctuation and pointed out that the magnitude and direction of the response of soil respiration to simulated precipitation change depended on whether soil moisture was optimally conditioned at different precipitation treatments. Second, we summarized the response patterns of soil respiration to symmetric increase and decrease in precipitation, which mainly included symmetric and asymmetric responses (positive and negative asymmetric). Meanwhile, the adaptation of plants and soil microorganisms to drought stress and soil oxygen limitation, as well as the reduction of organic substrates, were the main mechanisms accounting for the shifts of soil respiration response patterns to simulated precipitation change from symmetric to asymmetric responses. Third, we identified a significant effect of ambient climate on soil respiration in response to precipitation treatments as increasing duration of the experimental treatments. In addition, cumulative or buffering effects of ambient climatic conditions on precipitation treatment could affect the sensitivity of soil respiration along precipitation gradient by altering hydrothermal conditions. Finally, to accurately assess the implications of precipitation changes on soil carbon balance processes, we proposed three aspects of future precipitation effects on soil respiration for attention: 1) focusing on the phenomenon of "threshold effects" in the asymmetric response of soil respiration along precipitation gradients; 2) distinguishing the intrinsic mechanisms of autotrophic and heterotrophic components in soil respiration in response to precipitation changes; and 3) focusing on the impacts of intensified precipitation variability on soil respiration in the context of future climate extremes. In conclusion, with the intensified variability in global precipitation patterns, clarifying the response mechanism of soil respiration to precipitation changes is of great significance for accurately predicting and evaluating the alterations of soil carbon cycle processes and carbon balance in the context of global changes.

Understanding tropical cyclone persistence over land: A case study of Cyclone Gulab

Abstract Tropical Cyclone (TC) Gulab originated in the Bay of Bengal during the post-monsoon season of 2021. Following an unusual westward trajectory, TC Gulab made landfall on the east coast of India, traversed central India, and reintensified over the Arabian Sea into TC Shaheen. This study employed an online Eulerian water vapor tracer (WVT) tool embedded within the Weather Research and Forecasting (WRF) model to investigate the role of land in terms of soil moisture and Land Use Land Cover (LULC) in persistance of TC Gulab over central India. We quantified the contributions of sub-regions and dominant LULC types within the Indian subcontinent to the precipitation associated with TC Gulab. Our findings indicate that evapotranspiration across the entire Indian subcontinent contributed approximately 30% to the post-landfall precipitation associated with TC Gulab. The highest contribution originated from the northwestern region, followed by the northeast. Croplands, the dominant LULC type, were the primary contributors, followed by forests. Despite changing the dominant land cover from cropland to forest, the low-pressure system persisted over land while altering the spatial patterns of precipitation. Sensitivity experiments demonstrated a linear decrease in precipitation originating from land with decreasing soil moisture (SM). Notably, there is a disproportionate decline in total precipitation with decreasing SM. Further analysis separating atmospheric vapor sources into land and ocean contributions using WVT revealed a compensatory mechanism. The contribution of oceanic vapor to atmospheric vapor over land increased when SM decreased due to increase in the latent heat over ocean. However, the total atmospheric vapor remained low, ultimately leading to a lower total precipitation. Although SM plays a role, our results highlight the importance of oceanic and atmospheric processes in determining TC persistence over land. This study offers valuable insights into the dynamics of land-atmosphere interactions during low-pressure systems of TCs.

Early PSA-NCAM reduction in the dentate gyrus and impaired plasticity in the Alzheimer´s disease 3xTg-mice model

Neurodegenerative diseases such as Alzheimer´s (AD) and physiological ageing are characterized by a decline in neurogenesis and in the polysialylated isoforms of neural cell adhesion molecule (PSA-NCAM) expression within the hippocampus and specifically in the dentate gyrus (DG). In the 3xTG-AD mouse model, which mimics the human disease in both pathological and behavioral features, this decline in PSA-NCAM is associated with the presence of Aβ plaques at 9 months and Tau tangles at 12–15 months. In this work we studied the presence of PSA-NCAM at early ages (1–6 months) in the same model. Our results demonstrated that even as early as the first month of age there is a strong decrease in PSA-NCAM dendritic tree mainly altering the molecular layer (MolL) coverage affecting the synaptic plasticity and furthermore confirmed by the reduction of PSA-NCAM area density (Sv) in the 3xTG-AD. Similar and more marked early changes were seen during aging in both NTG and 3xTg-AD animals. Our results demonstrate for the first time a precipitate decrease of PSA-NCAM cells at such very early phases of the disease. This result suggests an early effect of the disease in the progression of immature and pluripotent cells resulting in an ulterior and early diminution of neurogenesis and therefore an impaired hippocampal cellular and synaptic plasticity.

Interannual Variation of Summer Compound Hot and Drought Events in Xinjiang and Its Relationship with the North Atlantic Sea Surface Temperature

Abstract Xinjiang suffers compound hot and drought events under global warming. However, less attention has been paid to physical mechanisms of the variability of compound hot and drought events in this region. This article investigates the interannual variation of summer (June–August) compound hot and drought events in Xinjiang and its relationship with the sea surface temperature (SST) over the North Atlantic. The results show that its first empirical orthogonal function (EOF) mode features a spatially homogenous pattern. This mode is closely connected with the simultaneous meridional negative–positive–negative SST anomalies over the North Atlantic. The summer North Atlantic tripole SST anomalies can trigger a remarkable wave train extending from the North Atlantic to Eurasia, consequently inducing an anomalous high pressure system over the Iran–Pamir Plateau, which is conducive to the increase in air temperature from the surface to the upper troposphere over Xinjiang. The warmer troposphere further strengthens the western Asian subtropical meridional temperature gradient and thereby enhances the westerly wind to the north flank of the West Asian subtropical westerly jet (WASWJ). As a result, the WASWJ is displaced northward, which intensifies the sinking motion and prevents the water vapor transport to Xinjiang, leading to a decrease in precipitation in the target region. The higher temperature and less precipitation contribute to the occurrence of compound hot and drought events over Xinjiang. Numerical simulations based on the Community Atmosphere Model, version 4 (CAM4), further confirm the relationship between the North Atlantic tripole SST anomalies and compound hot and drought events in Xinjiang during summer on the interannual time scale. Significance Statement Xinjiang, located in northwest China, suffers from frequent and intense compound hot and drought events in recent decades. It is thus urgent to understand the physical mechanisms associated with its occurrence in order for disaster prevention and mitigation. In this study, we reveal that the leading mode of summer compound hot and drought events over Xinjiang, featuring a spatially homogenous pattern, is closely correlated with the simultaneous meridional negative–positive–negative SST anomalies over the North Atlantic. The North Atlantic tripole SST anomalies can lead to an anomalous high pressure system over the Iran–Pamir Plateau and a northward shift of the West Asian subtropical westerly jet through exciting a wave train propagating from the North Atlantic to Eurasia, which consequently contributes to the occurrence of compound hot and drought events over Xinjiang.

Plant functional trait is a strong predictor of ecosystem productivity under altered precipitation in desert steppes

AbstractThe relationship between biodiversity and ecosystem function has always been one of the hot issues in the field of ecology. With the acceleration of global warming, the precipitation pattern has become one of the main drivers of biodiversity loss, which has a profound impact on ecosystem functional services and stability. However, the studies on the effects and mechanisms of plant community diversity and ecosystem productivity under precipitation changes in desert steppe are still unclear. According to the change rate (−41.1% to 39.2%) of precipitation in the study area in recent 50 years, five precipitation gradients (i.e., −40%, −20%, CK, +20% and +40%) were set to simulate the possible future precipitation pattern changes. Aboveground biomass increased with the increase of precipitation. Compared with CK, the aboveground biomass increased by 22.81% with +40% and decreased by 80.71% with −40%, and the negative impact of precipitation decrease on aboveground biomass was more significant. Through multiple stepwise regression analyses, species diversity, functional diversity and phylogenetic diversity were identified as the best models of aboveground biomass. The results showed that the aboveground biomass changes could be explained by 51.3%, 81.6%, 32.6% and 60% respectively. Combined with plant community diversity, the final index model was obtained through multiple stepwise regression analyses, which could explain 88.3% of changes in aboveground biomass. In this model, The average coefficient of specific leaf area and leaf thickness had a very high significance level, and these two functional traits of dominant species had a greater explanatory power for ecosystem system function. There was a nonlinear correlation between precipitation and aboveground biomass, and drought had a more significant negative effect on aboveground biomass. Compared with species diversity and phylogenetic diversity, plant functional traits can better explain ecosystem productivity. Selection effects are the main maintenance mechanism of desert steppe community productivity under the background of precipitation change.

Combined impacts of aerosols and urbanization on a highly threatened extreme precipitation event in Beijing, China

On July 21, 2012, a catastrophic precipitation event occurred in Beijing, highlighting the serious threat of extreme precipitation on socio-economic development and human health under climate change. Nevertheless, whether, how and to what extent aerosols and urbanization, as the two main influencing factors of urban extreme precipitation, have affected this highly damaging extreme event remains largely unexplored. Here, we employed the weather research and forecasting model coupled with chemistry (WRF-Chem) and a single-layer urban canopy model to investigate the influences of urbanization, aerosols and their interactions on this extreme precipitation event. We found that the joint intensification effects of urbanization and aerosols on extreme precipitation events greatly enhance its negative influence on megacities. The results indicate that aerosols are enhanced by increasing cloud droplet numbers, thereby intensifying the feedback between precipitation and latent heating. Consequently, the total precipitation increased by 22.6%, raising the precipitation in the Beijing area increase by at least 50 mm. By stimulating atmospheric instability and strengthening vertical air motion (over 0.25 m s−1), the urban heat island effect considerably influences the temporal and spatial distributions of extreme precipitation events, resulting in an increase in warm cloud precipitation (80%) and a decrease (30%) in frontal precipitation. Consequently, joint intensification effects resulted in more concentrated precipitation in the southwest of Beijing, leading to a substantial increase (more than 40%, ∼80 mm). This condition may be an important reason for the most severe disasters in the southwest of Beijing.

Assessing the impact of climate change on agricultural production in central Afghanistan

Afghanistan has faced extreme climatic crises such as drought, rising temperature, and scarce precipitation, and these crises will likely worsen in the future. Reduction in crop yield can affect food security in Afghanistan, where the majority of population and economy are completely dependent on agriculture. This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference (1990–2020) and future (2025–2100) periods. Climate data (1990–2020) were collected from four meteorological stations and three local organizations, and wheat yield data (1990–2020) were acquired from the United States Agriculture Department. Data during the reference period (1990–2020) were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG). Furthermore, the auto-regression model was used for trend analysis. The results showed that an increase in the average annual temperature of 2.15°C, 2.89°C, and 4.13°C will lead to a reduction in the wheat yield of 9.14%, 10.20%, and 12.00% under Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5 during the future period (2025–2100), respectively. Moreover, an increase in the annual maximum temperature of 1.79°C, 2.48°C, and 3.74°C also causes a significant reduction in the wheat yield of 2.60%, 3.60%, and 10.50% under RCP2.6, RCP4.5, and RCP8.5, respectively. Furthermore, an increase in the annual minimum temperature of 2.98°C, 2.23°C, and 4.30°C can result in an increase in the wheat yield of 6.50%, 4.80%, and 9.30% under RCP2.6, RCP4.5, and RCP8.5, respectively. According to the SDSM, the decrease of the average monthly precipitation of 4.34%, 4.10%, and 5.13% results in a decrease in the wheat yield of 2.60%, 2.36%, and 3.18% under RCP2.6, RCP4.5, and RCP8.5, respectively. This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.

Evaluation of the impact of hydrological changes on reservoir water management: A comparative analysis the CanESM5 model and the optimized SWAT-SVR-LSTM

This research examines the impacts of climate change and socio-economic variables on the hydrological cycle, reservoir water management, and hydropower capacity at the Gezhouba Dam. The Gezhouba Dam serves as a crucial hydroelectric power station and dam, playing a vital role in regulating river flow and generating electricity. In this study, an innovative method is employed, combining the Soil and Water Assessment Tool (SWAT), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM) models. This model is optimized using the Developed Thermal Exchange Optimizer. This optimized combined model significantly enhances the reliability and precision of the forecasting inflow and reservoir levels. By utilizing the Canadian Earth System Model version 5 (CanESM5), we examine climate variables across various scenarios of Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP). Under the SSP5-RCP8.5 scenario, the most aggressive in terms of emissions, we project a temperature rise of 2.6 % and a precipitation decrease of 2.7 %. This scenario leads to the most substantial changes in the hydrological cycle and altered river flow patterns. The results show a direct correlation between precipitation and inflow (0.952) and a strong inverse correlation between temperature and inflow (0.893). The study predicts significant decreases in all flow metrics, with mean high flow (Q5) periods affecting hydropower generation, especially under the SSP5-RCP8.5 scenario. Additionally, the filling frequency rate (FFR) and mean filling level (MFL) are projected to decrease, with a more pronounced decline in the far future, indicating a potential compromise of the reservoir's water storage and power generation capabilities, especially under the SSP5-RCP8.5 scenario.