Search Results (490)

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

Stable oxygen isotopes in tree rings (δ¹⁸O) serve as important proxies for climate change and offer unique advantages for climate reconstruction in arid and semi-arid regions. We established an annual δ¹⁸O chronology spanning 1964–2023 using Juniperus excelsa tree-ring samples collected from the Alborz Mountains in Iran. We analyzed relationships between δ¹⁸O and key climate variables: precipitation, temperature, Palmer Drought Severity Index (PDSI), vapor pressure (VP), and potential evapotranspiration (PET). Correlation analysis reveals that tree-ring δ¹⁸O is highly sensitive to hydroclimatic variations. Tree-ring cellulose δ¹⁸O shows significant negative correlations with annual total precipitation and spring PDSI, and significant positive correlations with spring temperature (particularly maximum temperature), April VP, and spring PET. The strongest correlation occurs with spring PET. These results indicate that δ¹⁸O responds strongly to the balance between springtime moisture supply (precipitation and soil moisture) and atmospheric evaporative demand (temperature, VP, and PET), reflecting an integrated signal of both regional moisture availability and energy input. The pronounced response of δ¹⁸O to spring evaporative conditions highlights its potential for capturing high-resolution changes in spring climatic conditions. Our δ¹⁸O series remained stable from the 1960s to the 1990s, but showed greater interannual variability after 2000, likely linked to regional warming and climate instability. A comparison with the δ¹⁸O variations from the eastern Alborz Mountains indicates that, despite some differences in magnitude, δ¹⁸O records from the western and eastern Alborz Mountains show broadly similar variability patterns. On a larger climatic scale, δ¹⁸O correlates significantly and positively with the Niño 3.4 index but shows no significant correlation with the Arctic Oscillation (AO) or the North Atlantic Oscillation (NAO). This suggests that ENSO-driven interannual variability in the tropical Pacific plays a key role in regulating regional hydroclimatic processes. This study confirms the strong potential of tree-ring oxygen isotopes from the Alborz Mountains for reconstructing hydroclimatic conditions and high-frequency climate variability. Full article

In Italy, beech and Turkey oak are among the most widespread tree species, thriving across various climatic zones. However, rising temperatures and prolonged droughts significantly affect their physiological performance and growth dynamics. To assess their long-term responses to climate change, mature beech and Turkey oak trees were studied in Central Italy at an elevation of 450 m. Using dendrochronological and stable isotope analyses (1981–2020), their growth patterns and physiological adaptations were evaluated. Beech exhibited a higher growth rate, with a basal area increment (BAI) of 17.1 ± 1.1 cm² year⁻¹, compared to Turkey oak, showing a BAI of 12.7 ± 0.96 cm² year⁻¹. Both species actively responded to increasing atmospheric CO₂ levels. Additionally, spring and the previous summer’s climatic conditions played a key role in growth, while summer temperature and precipitation influenced carbon discrimination. For beech, correlations between BAI and iWUE (intrinsic water efficiency, defined as the ratio between photosynthesis and stomatal conductance) were initially weak and not statistically significant. However, the correlation became significant, strengthening steadily into the early 2000s, likely related to thinning of the beech trees. For Turkey oak, the correlation was already significant and strong from the beginning of the analysis period (1981), persisting until the late 1990s. Our findings suggest that both species actively adjust their iWUE in response to an increasing atmospheric CO₂ concentration. However, while Turkey oak’s iWUE and BAI relationship remains unaffected by the likely thinning, beech benefits from reduced competition for light, nutrients, and water. Despite climate change’s impact on marginal populations, microclimatic conditions allow beech to outperform Turkey oak, a species typically better suited to drier climates. Full article

Accurate terrestrial evapotranspiration (ET) estimation is crucial for understanding land–atmosphere interactions, evaluating ecosystem functions, and supporting water resource management, particularly across climatically diverse regions. To address the limitations of traditional ET models, we propose a simple yet robust Sigmoid-RH model that characterizes the nonlinear relationship between relative humidity and ET. Unlike conventional approaches such as the Penman–Monteith or Priestley–Taylor models, the Sigmoid-RH model requires fewer inputs and is better suited for large-scale applications where data availability is limited. In this study, we applied the Sigmoid-RH model to estimate ET over mainland China from 2001 to 2018 by using satellite remote sensing and meteorological reanalysis data. Key driving inputs included air temperature (Ta), net radiation (Rn), relative humidity (RH), and the normalized difference vegetation index (NDVI), all of which are readily available from public datasets. Validation at 20 flux tower sites showed strong performance, with R-square (R²) ranging from 0.26 to 0.93, Root Mean Squard Error (RMSE) from 0.5 to 1.3 mm/day, and Kling-Gupta efficiency (KGE) from 0.16 to 0.91. The model performed best in mixed forests (KGE = 0.90) and weakest in shrublands (KGE = 0.27). Spatially, ET shows a clear increasing trend from northwest to southeast, closely aligned with climatic zones, with national mean annual ET of 560 mm/yr, ranging from less than 200 mm/yr in arid zones to over 1100 mm/yr in the humid south. Seasonally, ET peaked in summer due to monsoonal rainfall and vegetation growth, and was lowest in winter. Temporally, ET declined from 2001 to 2009 but increased from 2009 to 2018, influenced by changes in precipitation and NDVI. These findings confirm the applicability of the Sigmoid-RH model and highlight the importance of hydrothermal conditions and vegetation dynamics in regulating ET. By improving the accuracy and scalability of ET estimation, this model can provide practical implications for drought early warning systems, forest ecosystem management, and agricultural irrigation planning under changing climate conditions. Full article

Understanding vegetation responses to atmospheric drought is critical for arid ecosystem management under climate change. However, the threshold of the response mechanism of grassland in arid regions to atmospheric drought remains unclear. This study investigates how vapor pressure deficit (VPD) regulates grassland gross primary productivity (GPP) in Xinjiang, China, using MODIS and other multi-source remote sensing data (2000–2020). The results show intensified atmospheric drought in central Tianshan Mountains and southern Junggar Basin, with VPD exhibiting a widespread increasing trend (significant increase: 15.75%, extremely significant increase: 4.68%). Intensified atmospheric drought occurred in the central Tianshan Mountains and southern Junggar Basin. Integrated analyses demonstrate that VPD has a dominant negative impact on GPP (path coefficient = −0.58, p < 0.05), primarily driven by atmospheric drought stress. A ridge regression-derived threshold was identified at 0.61 kPa, marking the point where VPD transitions from stimulating to suppressing productivity. Spatially, 58.75% of the total area showed a significant increase in GPP. These findings advance the mechanistic understanding of atmospheric drought impacts on arid ecosystems and inform adaptive grassland management strategies. Full article

Drought stress severely limits agricultural productivity, with atmospheric and soil water deficits often occurring simultaneously in field conditions. While plant responses to individual drought factors are well-documented, recovery mechanisms following combined atmospheric–soil drought remain poorly understood, hindering drought resistance strategies and irrigation optimization. We set up two VPD treatments (low and high vapor pressure deficit) and two soil moisture treatments (CK: control soil moisture with sufficient irrigation, 85–95% field capacity; drought: soil moisture with deficit irrigation, 50–60% field capacity) in the pot experiment. We investigated wheat’s hydraulic transport (leaf hydraulic conductance, K_leaf) and gas exchange (stomatal conductance, g_s; photosynthetic rate, A_n) responses to combined drought stress from atmospheric and soil conditions at the heading stage, as well as rewatering 55 days after treatment initiation. The results revealed that: (1) high VPD and soil drought significantly reduced leaf hydraulic conductance (K_leaf), with a high VPD decreasing K_leaf by 31.6% and soil drought reducing K_leaf by 33.2%; The high VPD decreased stomatal conductance (g_s) by 43.6% but the photosynthetic rate (A_n) by only 12.3%; (2) After rewatering, g_s and A_n of atmospheric and soil drought recovered relatively rapidly, while K_leaf did not; (3) Atmospheric and soil drought stress led to adaptive changes in wheat’s stomatal regulation strategies, with an increasing severity of drought stress characterized by a shift from non-conservative to conservative water regulation behavior. These findings elucidate wheat’s hydraulic–stomatal coordination mechanisms under drought stress and their differential recovery patterns, providing theoretical foundation for improved irrigation management practices. Full article

Blocking anticyclones are important atmospheric phenomena generally associated with extreme weather (e.g., droughts and cold air surges). Blockings also constitute large-scale indicators of climate change. The study of blockings in the Southern Hemisphere (SH) has been traditionally carried out utilizing reanalysis products. This paper is aimed at presenting an updated, comprehensive climatology of blockings in the SH as extracted from the ERA5 and the NCEP/NCAR reanalysis datasets in the 1940–2022 and 1948–2022 periods, respectively. Blockings were located by means of a unidimensional index at 500 hPa. The results were stratified by season, longitude, region, persistence, and intensity, and the climatology from both datasets was compared. The primary location of blockings was close to the Date Line in every season. Additionally, depending on the season, up to fourth-rank maxima could be located. Generally, the secondary maxima were found in the south Atlantic; lower-order maxima were located in the south-eastern Pacific, west of South America, and in the south-western Indian Ocean east of South Africa. The most intense blockings were concentrated in the Pacific and in the south Atlantic in both datasets, and they were also located in the Indian Ocean, but in the ERA5 reanalysis only. The longest-lived blockings occurred in the south Pacific and in the south Atlantic during southern winter. Full article

Brazil is increasingly affected by extreme weather events due to climate change, with pronounced regional differences in temperature and precipitation patterns. The southeast region is particularly vulnerable, frequently experiencing severe droughts and extreme heatwaves linked to atmospheric blocking events and intense rainfall episodes driven by the South Atlantic Convergence Zone (SACZ). These phenomena contribute to recurring climate-related disasters. The country’s heavy reliance on hydropower heightens its susceptibility to droughts, while growing evidence points to intensifying dry spells and wildfires across multiple regions, threatening agricultural output and food security. Urban areas, particularly, are experiencing more frequent and severe heatwaves, posing serious health risks to vulnerable populations. This study investigates the links between global teleconnection indices and synoptic-scale systems, specifically blocking events and SACZ activity, and their influence on Brazil’s extreme heat, drought conditions, and river flow variability over the past 30 to 40 years. By clarifying these interactions, the research aims to enhance understanding of how large-scale atmospheric dynamics shape climate extremes and to assess their broader implications for water resource management, energy production, and regional climate variability. Full article

Soil moisture (SM) plays a fundamental role in the water cycle and is an important variable for all processes occurring at the lithosphere–atmosphere interface, which are strongly affected by climate change. Among the different fields of application, accurate SM measurements are becoming more relevant for all studies related to extreme event (e.g., floods, droughts, and landslides) mitigation and assessment. In this study, data acquired by the advanced microwave sounding unit (AMSU) onboard the European Meteorological Operational Satellite Program (MetOP) satellites were used for the first time to extract information on the variability of SM by implementing the original soil wetness index (SWI). Long-term monthly SWI time series collected for the Basilicata region (southern Italy) were analyzed for drought assessment during the period 2007–2021. The accuracy of the SWI product was tested through a comparison with SM products derived by the Advanced SCATterometer (ASCAT) over the 2013–2016 period, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the relevance of the long-term achievements in terms of drought analysis. The results indicate a satisfactory accuracy of the SWI, with the mean correlation coefficient values with ASCAT higher than 0.7 and a mean normalized root mean square error less than 0.155. A negative trend in SWI during the 15-year period was found using both the original and deseasonalized series (linear and Sen’s slope ~−0.00525), confirmed by SPEI (linear and Sen’s slope ~−0.00293), suggesting the occurrence of a marginal long-term dry phase in the region. Although further investigations are needed to better assess the intensity and main causes of the phenomena, this result indicates the contribution that satellite data/products can offer in supporting drought assessment. Full article

Land Surface Temperature (LST), as a core variable in the coupling of land–atmosphere energy transfers and ecological responses, relies heavily on the global coverage capacity of thermal infrared remote sensing (TIR-LST) for dynamic monitoring. Currently, the time reconstruction method of the TIR-LST products from China’s Fengyun polar-orbiting satellite under dynamic cloud interference remains under exploration. This study focuses on the Heihe River Basin in western China, and addresses the issue of cloud coverage in relation to the Fengyun-3C (FY-3C) satellite TIR-LST. An innovative spatiotemporal reconstruction framework based on multi-source data collaboration was developed. Using a hybrid ensemble learning framework of random forest and ridge regression, environmental parameters such as vegetation index (NDVI), land cover type (LC), digital elevation model (DEM), and terrain slope were integrated. A downscaling and multi-factor collaborative representation model for land surface temperature was constructed, thereby integrating the passive microwave LST and thermal infrared VIRR-LST from the FY-3C satellite. This produced a seamless LST dataset with 1 km resolution for the period of 2017–2019, with temporal continuity across space. The validation results show that the reconstructed data significantly improves accuracy compared to the original VIRR-LST and demonstrates notable spatiotemporal consistency with MODIS LST at the daily scale (annual R² ≥ 0.88, RMSE < 2.3 K). This method successfully reconstructed the FY-3C satellite’s 1 km level all-weather LST time series, providing reliable technical support for the use of domestic satellite data in remote sensing applications such as ecological drought monitoring and urban heat island tracking. Full article

This study investigates the impact of climate variability on wheat production in Algeria’s semi-arid interior plains from 2014 to 2024, aiming to curb the challenges of rainfed wheat cultivation, optimize irrigation, and improve water productivity. The Soil–Water–Atmosphere–Plant (SWAP) model-driven approach refined irrigation scheduling to mitigate climate-induced losses and improve resource efficiency. Using historical climate data, soil properties, and wheat growth observations from the experimental farm of the Technical Institute for Field Crops, the SWAP model was calibrated and validated using one-factor-at-a-time sensitivity analysis, achieving a coefficient of determination (R²) of 0.93 and a Normalized Root Mean Squared Error (NRMSE) of 17.75. Two drought-based irrigation indices, Soil Moisture Drought Index (SMDI) and Crop Water Stress Index (CWSI), guided adaptive irrigation strategies, showing a significant reduction in crop failure during drought periods. Results revealed a strong link between rainfall variability and wheat yield. Adopting a 9-day irrigation interval could increase water productivity to 18.91 kg ha⁻¹ mm⁻¹, enhancing yield stability under varying climatic conditions. The SMDI approach maintained soil moisture during extreme drought, while CWSI optimized water use in normal and wet years. This study integrates SMDI and CWSI into a validated irrigation framework, offering data-driven strategies to enhance wheat production resilience. Findings support sustainable water management and provide practical insights for policymakers and farmers to refine irrigation planning and climate adaptation, contributing to long-term agricultural sustainability. Full article

Water use efficiency (WUE), as an important metric for ecosystem resilience, has been identified to play a significant role in the coupling of carbon and water cycles. The farming–pastoral ecotone of Northern China (FPENC), which is highly susceptible to drought due to water scarcity, has long been recognized as an ecologically fragile zone. The ecological restoration projects in China have mitigated land degradation and maintain the sustainability of dryland. However, the process of greening in drylands has the potential to impact water availability. A comprehensive analysis of the WUE in the FPENC can help to understand the carbon absorption and water consumption. Using gross primary production (GPP) and evapotranspiration (ET) data from a MODerate resolution Imaging Spectroradiometer (MODIS), alongside biophysical variables data and land cover information, the spatio-temporal variations in WUE from 2003 to 2022 were examined. Additionally, its driving force and the ecosystem resilience were also revealed. Results indicated that the annual mean of WUE fluctuated between 0.52 and 2.60 gC kgH₂O⁻¹, showing a non-significant decreasing trend across the FPENC. Notably, the annual averaged WUE underwent a significant decline before 2012 (p < 0.05), and then showed a slight increased trend (p = 0.14) during the year afterward (i.e., 2013–2022). In terms of climatic controls, temperature (Temp) and soil volumetric water content (VSWC) dominantly affected WUE from 2003 to 2012; VPD (vapor pressure deficit), VSWC, and Temp showed comprehensive controls from 2013 to 2022. The findings suggest that a wetter atmosphere and increased soil moisture contribute to the decline in WUE. In total, 59.2% of FPENC was shown to be non-resilient, as grassland occupy the majority of the area, located in Mu Us Sandy land and Horqin Sand Land. These results underscore the importance of climatic factors in the regulation WUE over FPENC and highlight the necessity for focused research on WUE responses to climate change, particularly extreme events like droughts, in the future. Full article

Weather forecasting is essential for agriculture, yet current methods often lack the localized accuracy required to manage extreme weather events and optimize irrigation. The MAGDA Horizon Europe/EUSPA project addresses this gap by developing a modular system that integrates novel European space-based, airborne, and ground-based technologies. Unlike conventional forecasting systems, MAGDA enables precise, field-level predictions through the integration of cutting-edge technologies: Meteodrones provide vertical atmospheric profiles where traditional data are sparse; GNSS-reflectometry offers real-time soil moisture insights; and all observations feed into convection-permitting models for accurate nowcasting of extreme events. By combining satellite data, GNSS, Meteodrones, and high-resolution meteorological models, MAGDA enhances agricultural and water management with precise, tailored forecasts. Climate change is intensifying extreme weather events such as heavy rainfall, hail, and droughts, threatening both crop yields and water resources. Improving forecast reliability requires better observational data to refine initial atmospheric conditions. Recent advancements in assimilating reflectivity and in situ observations into high-resolution NWMs show promise, particularly for convective weather. Experiments using Sentinel and GNSS-derived data have further improved severe weather prediction. MAGDA employs a high-resolution cloud-resolving model and integrates GNSS, radar, weather stations, and Meteodrones to provide comprehensive atmospheric insights. These enhanced forecasts support both irrigation management and extreme weather warnings, delivered through a Farm Management System to assist farmers. As climate change increases the frequency of floods and droughts, MAGDA’s integration of high-resolution, multi-source observational technologies, including GNSS-reflectometry and drone-based atmospheric profiling, is crucial for ensuring sustainable agriculture and efficient water resource management. Full article

Climate change is increasing global temperatures and imposing new constraints on tree regeneration, especially in late-successional species exposed to simultaneous drought and low-light conditions. To disentangle the effects of warming from those of atmospheric drought, we conducted a multifactorial growth chamber experiment on Fagus sylvatica seedlings, manipulating temperature (25 °C and +7.5 °C above optimum), soil moisture (well-watered vs. water-stressed), and light intensity (high vs. low), while maintaining constant vapor pressure deficit (VPD). We assessed growth, biomass allocation, leaf gas exchange, water relations, and xylem hydraulic traits. Warming significantly reduced total biomass, leaf area, and water-use efficiency, while increasing transpiration and residual conductance, especially under high light. Under combined warming and drought, seedlings exhibited impaired osmotic adjustment, reduced leaf safety margins, and diminished hydraulic performance. Unexpectedly, warming under shade promoted a resource-acquisitive growth strategy through the production of low-cost leaves. These results demonstrate that elevated temperature, even in the absence of increased VPD, can compromise drought tolerance in beech seedlings and shift their ecological strategies depending on light availability. The findings underscore the need to consider multiple, interacting stressors when evaluating tree regeneration under future climate conditions. Full article

The increasing frequency, intensity, and duration of heatwaves and droughts pose significant societal and environmental challenges across Europe. This study analyzes land surface temperature (LST) observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) between 2003 and 2023 to identify thermal anomalies associated with heatwaves. Additionally, this study examines the role of different land cover types in modulating heatwave impacts, employing turbulent flux observations from micrometeorological towers. The interaction between heatwaves and droughts is further explored using the Standardized Precipitation Evapotranspiration Index (SPEI) and soil moisture data, highlighting the amplifying role of water stress through land–atmosphere feedbacks. The results reveal a statistically significant upward trend in LST-derived thermal anomalies, with the 2022 heatwave identified as the most extreme event, when approximately 75% of Europe experienced strong positive anomalies. On average, 91% of heatwave episodes identified in reanalysis-based air temperature records coincided with LST-defined anomaly events, confirming LST as a robust proxy for heatwave detection. Flux tower observations show that, during heatwaves, evergreen coniferous and mixed forests predominantly enhance sensible heat fluxes (mean anomalies during midday of 74 W/m² and 62 W/m², respectively), while grasslands exhibit increased latent heat flux (89 W/m²). Notably, under extreme compound heat–drought conditions, this pattern reverses for grassed sites due to rapid soil moisture depletion. Overall, the findings underscore the combined influence of surface temperature and drought in driving extreme heat events and introduce a novel, multi-source approach that integrates satellite, reanalysis, and ground-based data to assess heatwave dynamics across scales. Full article