Search Results (218)

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

In the summer of 2022, central and eastern China experienced prolonged extreme high temperatures and severe drought, leading to significant economic losses. To gain a more profound understanding of this drought event and furnish a reference for forecasting similar events in the future, this study examines the circulation anomalies associated with the drought. Employing a diagnostic method focused on temperature and moisture anomalies, this study introduces a novel approach to quantify and compare the relative significance of moisture transport and warm air dynamics in contributing to the drought. This study examines the atmospheric circulation anomalies linked to the drought event and compares the relative contributions of water vapor transport and warm air activity in causing the drought, using two parameters defined in the paper. The results show the following: (1) The West Pacific Subtropical High (WPSH) was more intense than usual and extended westward, consistently controlling the Yangtze River Basin. Simultaneously, the polar vortex area was smaller and weaker, the South Asian High area was larger and stronger, and it shifted eastward. These factors collectively led to weakened water vapor transport conditions and prevailing subsiding air motions in the Yangtze River Basin, causing frequent high temperatures. (2) By defining I_q and I_t to represent the contributions of moisture and temperature to precipitation, we found that the drought event in the Yangtze River Basin was driven by both reduced moisture supplies in the lower troposphere and higher-than-normal temperatures, with temperature playing a dominant role. Full article

Multi-source fusion techniques have emerged as cutting-edge approaches for spatial precipitation estimation, yet they face persistent accuracy limitations, particularly under extreme conditions. Machine learning offers new opportunities to improve the precision of these estimates. To bridge this gap, we propose a hybrid artificial neural network–geographically weighted regression (ANN–GWR) model that synergizes event recognition and quantitative estimation. The ANN module dynamically identifies precipitation events through nonlinear pattern learning, while the GWR module captures location-specific relationships between multi-source data for calibrated rainfall quantification. Validated against 60-year historical data (1960–2020) from China’s Yongding River Basin, the model demonstrates superior performance through multi-criteria evaluation. Key results reveal the following: (1) the ANN-driven event detection achieves 10% higher accuracy than GWR, with a 15% enhancement for heavy precipitation events (>50 mm/day) during summer monsoons; (2) the integrated framework improves overall fusion accuracy by more than 10% compared to conventional GWR. This study advances precipitation estimation by introducing an artificial neural network into the event recognition period. Full article

Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where extreme drought events are prevalent due to complex terrain and climate warming, ET becomes a key factor in understanding water availability and drought dynamics. Using the SWAT model, this study investigates ET dynamics and influencing factors in the Jizi Basin, Yunnan Province, a small basin with over 71% forest coverage. The model calibration and validation results demonstrated a high degree of consistency with observed discharge data and ERA5, confirming its reliability. The results show that the annual average ET in the Jizi Basin is 573.96 mm, with significant seasonal variations. ET in summer typically ranges from 70 to 100 mm/month, while in winter, it drops to around 20 mm/month. Spring ET exhibits the highest variability, coinciding with the occurrence of extreme hydrological events such as droughts. The monthly anomalies of ET effectively reproduce the spring and early summer 2019 drought event. Notably, ET variation exhibits significant uncertainty under scenarios of +1 °C temperature and −20% precipitation. Furthermore, although land use changes had relatively small effects on overall ET, they played crucial roles in promoting groundwater recharge through enhanced percolation, especially forest cover. The study highlights that, in addition to climate and land use, soil moisture and groundwater conditions are vital in modulating ET and drought occurrence. The findings offer insights into the hydrological processes of small forested basins in southwestern China and provide important support for sustainable water resource management and effective climate adaptation strategies, particularly in the context of increasing drought vulnerability. Full article

As global climate change intensifies, extreme climate events are becoming more frequent, presenting significant challenges to socioeconomic systems and ecosystems. Northeast China, a region highly sensitive to climate change, has been profoundly impacted by compound drought and heat extremes (CDHEs), affecting agriculture, society, and the economy. To evaluate the characteristics and evolution of summer CDHEs in this region, this study analyzed observational data from 81 meteorological stations (1961–2020) and developed a Standardized Temperature–Precipitation Index (STPI) using the Copula joint probability method. The STPI’s effectiveness in characterizing compound drought and heat conditions was validated against historical records. Using the constructed STPI, this study conducted a comprehensive analysis of the spatiotemporal distribution of CDHEs. The Theil–Sen median trend analysis, Mann–Kendall trend tests, and the frequency of CDHEs were employed to examine drought and heatwave patterns and their influence on compound events. The findings demonstrated an increase in the severity of compound drought and heat events over time. Although the STPI exhibited a slight interannual decline, its values remained above −2.0, indicating the continued intensification of these events in the study area. Most of the stations showed a non-significant decline in the Standardized Precipitation Index and a significant rise in the Standardized Temperature Index, indicating that rising temperatures primarily drive the increasing severity of compound drought and heat events. The 1990s marked a turning point with a significant increase in the frequency, severity, and spatial extent of these events. Full article

The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified water quality classification system was applied, along with statistical methods, including multiple linear regression. The Glubochanka and Krasnoyarka rivers were identified as the most polluted (reaching classes 4–5), with multiple exceedances of Zn (up to 2.96 mg/dm³), Cd (up to 0.8 mg/dm³), and Cu (up to 0.051 mg/dm³). The most stable and highest water quality was recorded in the Oba River, where from 2021 to 2024, water consistently corresponded to Class 2. Regression models of water quality class as a function of time and annual precipitation were constructed to assess the influence of climatic factors. Statistical analysis revealed no consistent linear correlation between average annual precipitation and water quality (correlation coefficients ranging from −0.49 to +0.37), indicating a complex interplay between climatic and anthropogenic factors. Significant relationships were found for the Breksa (R² = 0.903), Glubochanka (R² = 0.602), and Tikhaya (R² = 0.555) rivers, suggesting an influence of temporal and climatic factors on water quality. In contrast, the Oba (R² = 0.130), Ulba (R² = 0.100), and Krasnoyarka (R² = 0.018) rivers exhibited low coefficients, indicating the predominance of other, likely local, sources of pollution. It was found that summer periods are characterized by the highest pollution due to low water flow, while episodes of acid runoff occur in spring. A decrease in pH below 7.0 was first recorded in 2023–2024 in the Ulba and Tikhaya rivers. Forecasts to 2030 suggest relative stability in water quality under current climatic conditions; however, by 2050, the risk of water quality deterioration is expected to rise due to increased precipitation and extreme weather events. This study presents, for the first time, a systematic long-term analysis of small rivers in the East Kazakhstan region, offering deeper insight into the dynamics of surface water quality and providing a scientific foundation for developing adaptive strategies for the protection and sustainable use of water resources under climate change and anthropogenic pressure. The results emphasize the importance of prioritizing rivers with high variability in water quality for regular monitoring and the development of adaptive conservation measures. The research holds strong applied significance for shaping a sustainable water use strategy in the region. Full article

The performance of monthly prediction of extreme precipitation from the BCC-CPSv3-S2Sv2 model over the Yellow River Basin (YRB) using historical hindcast data from 2008 to 2022 was evaluated in this study, mainly from three aspects: overall performance in predicting daily precipitation rates, systematic biases, and monthly prediction of extreme precipitation metrics. The results showed that the BCC-CPSv3-S2Sv2 model demonstrates approximately 10-day predictive skill for summer daily precipitation over the YRB. Relatively higher skill regions concentrate in the central basin, while skill degradation proves more pronounced in downstream areas compared to the upper basin. After correcting model systematic biases, prediction skills for total precipitation-related metrics significantly surpass those of extreme precipitation indices, and metrics related to precipitation amounts demonstrate relatively higher skill compared to those associated with precipitation days. Total precipitation (TP) and rainy days (RD) exhibit comparable skills in June and July, with August showing weaker performance. Nevertheless, basin-wide predictions within 10-day lead times remain practically valuable for most regions. Prediction skills for extreme precipitation amounts and extreme precipitation days share similar spatiotemporal patterns, with high-skill regions shifting progressively south-to-north from June to August. Significant skills for June–July are constrained within 10-day leads, while August skills rarely exceed 1 week. Further analysis reveals that the predictive capability of the model predominantly originates from normal or below-normal precipitation years, whereas the accurate forecasting of extremely wet years remains a critical challenge, which highlights limitations in capturing mechanisms governing exceptional precipitation events. Full article

In this study, diurnal characteristics and long-term changes in extreme precipitation (PR) in the Republic of Korea (KR) are investigated. Hourly PR data from 59 ASOS stations across the country over a 50-year period (1973–2022) are used. The focus is on the summer season (June to September), during which extreme PR frequently occurs. During the period 1973–1997 (FP), both the amount and frequency of extreme PR events peak between 01 and 09 LST. In contrast, during the period 1998–2022 (LP), a notable increase in extreme PR and its frequency is observed between 04 and 12 LST, with the peak occurrence hours shifting to this time frame. An analysis of atmospheric variables related to extreme PR is conducted for the 04–12 LST time frame. Compared to all PR events during the summer season, a low-level low-pressure anomaly is found west of the KR, leading to southerly winds and positive specific humidity anomalies over the south of the KR. Relative to the FP period, both the amplitude and frequency of high water vapor content have increased during the LP period. This intensified moisture may be associated with the observed increase in extreme PR during 04–12 LST. However, no significant changes are found in the strength and frequency of the southerly wind. Full article

Puerto Rico has experienced recent increases in annual, seasonal and daily temperatures that have been associated with climate change. More recently, the island has been experiencing an increase in the frequency of extremely warm days that are causing significant environmental and socio-economic impacts. This study focuses on examining how annual, seasonal and daily temperatures have changed over recent decades in 12 historical sites spread across the island for the 1970–2024 period and how it relates to climate change. The Mann–Kendall tests for trends were employed for the annual and seasonal series to identify areas of the island where warming has been found to be statistically significant. The 90th, 95th, and 99th percentiles of daily temperature series were also analyzed. This study found that Puerto Rico has experienced significant warming from 1970 to 2024, with the most consistent increases in minimum temperatures, especially during the summer and nighttime hours. The frequency of extreme heat events has increased across nearly all stations in different areas of the island. Stepwise regression models identified surface air temperature (SAT), sea surface temperature (SST), and total precipitable water (TPW) as the most influential regional climate predictors driving mean temperature trends and the occurrence of extreme heat events. Full article

The Mediterranean region is currently experiencing the effects of a climate crisis, marked by an increase in the frequency and intensity of drought events. Climate variability has led to prolonged periods of drought, even in areas not traditionally classified as arid. These events have significant impacts on water resources, agricultural productivity, and socioeconomic systems. This study investigates the evolution of meteorological, hydrological, and socioeconomic droughts using the Standardized Precipitation Index (SPI) at time scales of 3, 12, and 24 months in a Mediterranean region identified as particularly vulnerable to climate change. Observational data from local meteorological stations were used for the 1991–2020 baseline period. Future climate projections were derived from the MPI-ESM model under the RCP 4.5 and RCP 8.5 scenarios, extending to the year 2080. Data were aggregated on a 0.50° × 0.50° spatial grid and bias-corrected using linear scaling. The Kolmogorov–Smirnov test was applied to assess the statistical compatibility between observed and projected precipitation data. Results indicate a substantial decline in annual precipitation, with reductions of up to 20% under the RCP 8.5 scenario for the period 2051–2080, compared to the reference period. The frequency of severe and extreme drought events is projected to increase by 30–50% in several grid meshes, especially during summer. Conversely, altered weather patterns in other areas may increase the likelihood of flood events. This study identifies the grid meshes most vulnerable to drought, highlighting the urgent need for adaptive water management strategies to ensure agricultural sustainability and reduce the socioeconomic impacts of climate-induced drought. Full article

Droughts are among the most impactful climate extremes in Serbia, with significant socio-economic consequences, particularly in agriculture. The summer of 2012 was one of the most extreme drought events in Serbia’s history, characterized by record-breaking temperatures and prolonged precipitation deficits. In this study, we investigate the meteorological aspects of the 2012 drought, its progression, and its potential recurrence under future climate conditions. Using the high-resolution gridded observational dataset (EOBS) and Single-Model Initial-Condition Large Ensemble (SMILE) simulations from CMIP6—the Max Planck Institute Earth System Model version 1.2 (MPI-ESM 1.2) Grand Ensemble, we analyze precipitation deficits and assess the ability of MPI-GE CMIP6 to reproduce the observed event. We identify analogue events in MPI-GE CMIP6 that resemble the 2012 drought and examine their occurrence across historical and future climate scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Our results indicate that MPI-GE CMIP6 effectively captures precipitation deficit extremes and that events comparable to the 2012 drought become more frequent and severe under higher greenhouse gas concentration scenarios. This study underscores the importance of a large ensemble in understanding the full distribution of extreme drought events and provides Serbia-specific insights, which is valuable for regional climate adaptation planning. Full article

Based on the long-term daily historical rainfall data, this study analyzes the seasonal differences in extreme rainfall in the monsoon region with frequent extreme rainfall in China over the past 40 years. From the detailed analysis of extreme rainfall indicators, the spatial and temporal variation in extreme rainfall indicators in the monsoon region of China from 1980 to 2020 is explored. Through Mann–Kendall test and multi-index spatial and temporal analysis, the spatial and temporal evolution law and seasonal differentiation characteristics of extreme precipitation events are revealed. The results show the following: (1) The precipitation change presents a dipole pattern of southeast–northeast enhancement, northwest–central attenuation. (2) The precipitation intensity showed the spatial heterogeneity of latitude differentiation of “strong in summer and weak in winter, strong in south and weak in north”, and generally attenuated in winter after reaching the peak in summer. (3) There were significant dry and wet differences between continuous drought days (CDDs) and wet days (CWDs), reflecting the characteristics of “dry in winter and wet in summer”, and the seasonal differentiation of cumulative precipitation (PRCPTOT) was significant. (4) The extreme precipitation threshold is strengthened in winter, and the frequency shows the characteristics of “high in winter and spring, low in summer and autumn”. Studies have shown that extreme precipitation in the monsoon region of China has seasonal redistribution characteristics, which may aggravate the challenge of water resources management. It is necessary to further analyze its driving factors in combination with a dynamic climate mechanism. Full article

In the recent decades, an ongoing increase in maximum temperature during summer has been observed in Poland, especially in the central-southern and southeastern areas. This raises the vulnerability of these regions not only to heat waves and drought but also to floods. The potential effect of compound heat waves and extreme rainfall events may be more serious than the effects of these events occurring separately. This research is the first attempt in Poland to investigate whether the presence of a heat wave increases the likelihood of extreme rainfall events, if so, by how much, and whether this changes with warming. For this purpose, we used daily maximum temperature values and 6 h precipitation datasets from 44 meteorological stations in Poland for the 1966–2024 period. It was proven that compound heat wave and extreme rainfall events occurred in Poland with spatially differentiated frequency. They occurred the least frequently on the coast and the most frequently in southwestern, southeastern, and northeastern Poland. The extreme rainfall occurred most often between noon and midnight on the last heat wave day. During these hours, the likelihood of extreme rainfall is, on average, 3.5 times higher than that expected according to climatology norms. With warming, the frequency of days with these compound events increases at the rate of 1.22 days per decade, and the frequency of compound events increases at a rate of 3.75 events per decade. Although a detailed analysis of the mechanisms responsible for such events is planned for further research, the preliminary study revealed that in most cases, the approach of a cold front with a mesoscale thundercloud system was responsible for heat wave termination with extreme rainfall. Since we cannot prevent the growing number of heat waves or heavy precipitation events that terminate the heat wave events in Poland, the adaptation strategy needs to be implemented to meet the sustainable development goals regarding climate actions. This refers primarily to urban planning, agriculture (agroecosystems), social health, and well-being. Full article

This study evaluates the performance of the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) models in simulating the historical precipitation extremes and uses the best-performing model to project changes in extreme precipitation indices over the Missouri River Basin (MRB) in the United States. Five extreme precipitation indices are calculated to quantify the frequency and intensity of precipitation extremes, and the results are compared with gridded observations for summer (June–August, JJA) and winter (December–February, DJF). A majority of the NA-CORDEX models fairly reproduce the spatial patterns of the extreme precipitation indices and the seasonal patterns of mean precipitation with varying degrees of biases. Overall, the ensembles (either from all 16 NA-CORDEX members or grouped by individual regional climate models) show a reasonable performance in representing the spatial patterns of the precipitation extremes, but some models outperform the ensembles for individual precipitation indices in different seasons. By the end of the century, in a high-emission scenario, there is a significant increase in heavy precipitation intensity during the summer but with a projected increase in drought duration in the central areas. The winter season also shows a significant increase in heavy precipitation intensity, frequency, and duration, with a decrease in dry spells. Our results demonstrate variability in seasonal precipitation extremes over the MRB, highlighting the need for adaptive infrastructure and water resource planning to reduce vulnerability to extreme events. Full article

Understanding historical climatic extremes and variability is crucial for effective climate change adaptation, particularly for urban flood management in developing countries. This study investigates historical precipitation trends in the Kathmandu Valley, Nepal, focusing on precipitation frequency, intensity, and the influence of the El Niño–Southern Oscillation (ENSO), using extreme precipitation indices and the precipitation concentration index (PCI). The results reveal sharply fluctuating short-term precipitation from 1980 to 2022, with the exception of an increasing trend during spring (1.17 mm/year) and a decreasing trend in November and December. Trends in extreme precipitation indices are mixed: RX7day shows an increasing trend of 0.1 mm/year, with decadal analysis (1980–2001 and 2002–2022) indicating similar upward patterns. In contrast, RX1day, RX3day, RX5day, and R95pTOT exhibit inconsistent trends, while R99pTOT demonstrates a decreasing trend over the full period (1980–2022). Although the number of days with precipitation ≥ 35 mm has declined, the increasing trend in 7-day maximum precipitation, coupled with no significant change in total annual precipitation and highly variable short-term rainfall, points to a rising risk of unexpected extreme precipitation events. Precipitation patterns in the Kathmandu Valley remain highly irregular across seasons, except during summer. ENSO exhibits a negative correlation with annual precipitation, extreme precipitation indices, and the PCI but shows a positive correlation with the annual and summer PCI as well as 1-day maximum precipitation, emphasizing its significant influence on precipitation variability. These findings highlight the urgent need for targeted climate adaptation strategies and provide valuable insights for hydrologists, meteorologists, policymakers, and urban planners to enhance climate resilience and improve flood management in the Kathmandu Valley. Full article