Search Results (1,246)

Yan Mountain, located in the northern part of the Beijing–Tianjin–Hebei economic zone in northern China, serves as a crucial ecological barrier for this densely populated and industrialized region. However, vegetation phenology and its responses to climate change in this region remain unclear. This study utilized MODIS EVI data to extract key phenological metrics and identify dominant vegetation types in Yan Mountain from 2000 to 2022. We analyzed spatiotemporal dynamics and driving mechanisms of vegetation phenology by examining relationships among phenological parameters and their responses to climatic variables. Results revealed significant spatial heterogeneity and interannual variation in vegetation phenology. The start of the growing season (SOS) and peak of the growing season (POS) advanced significantly at rates of 0.54 and 0.19 days/year, respectively. Meanwhile, the end of the growing season (EOS) was delayed by 0.38 days/year, and the growing season length (GSL) was extended by 0.97 days/year. These shifts were more pronounced in grasslands and shrublands than in forests. Significant physiological correlations existed among phenological parameters. Earlier green-up probably advanced POS and significantly delayed EOS. SOS advancement exerted a greater influence on GSL extension than EOS delay, with variations across vegetation types. Mean annual temperature and precipitation jointly regulated phenological shifts; precipitation primarily drove SOS advancement and GSL extension, while temperature mainly advanced POS and delayed EOS. This study elucidates spatiotemporal changes in vegetation phenology and its climate change response patterns in Yan Mountain, providing a crucial reference for ecological management and climate change adaptation strategies. Full article

Since 2007, the Yellow Sea has experienced the world’s largest green tides, with Ulva prolifera O.F. Müller as the dominant species. Those blooms severely impacted the local tourism and aquaculture, resulting in significant economic losses, as well as negative social and ecological consequences. Unlike other global green tides, those in the Yellow Sea are characterized by long-distance drifting and an astonishing scale. These destructive events display significant temporal and spatial variability, which is largely driven by dynamic environmental conditions and human activities. In this review, we summarize recent advancements in understanding the spatiotemporal patterns of long-distance transport, the interannual variability in bloom size, and the underlying mechanisms driving these fluctuations. Additionally, we highlight important knowledge gaps that need further investigation to support the development of effective management strategies for mitigating the impacts of green tides in the Yellow Sea. Full article

Stochastic weather generators are commonly employed to create synthetic sequences of daily weather variables across diverse fields, including hydrological, ecological, and agricultural studies. Realistic precipitation sequences, in particular, serve as essential inputs in numerous modeling frameworks. Generalized linear models (GLMs) that incorporate covariates to capture seasonality and teleconnections represent one effective approach for stochastic weather generation. However, these models often underestimate the interannual variability of seasonally aggregated variables, notably precipitation intensity during wet seasons. Recent methods developed to mitigate the issue of overdispersion have nevertheless struggled to adequately replicate observed precipitation intensities in wet seasons. To overcome this limitation, we propose integrating a modified hybrid gamma and generalized Pareto distribution into the GLM-based weather generator. This enhanced method was evaluated using daily precipitation data from Seoul, Korea, and successfully reproduced realistic precipitation intensities while effectively addressing the overdispersion issue. Full article

Multimodal waves can significantly impact ocean–atmosphere interactions and affect coastal ecosystems. Due to the presence of waves created in different geographical areas, many wave systems coexist in coastal seas. Based on data collected with a directional waverider buoy, this study investigates fluctuations in multimodal sea states from March 2010 to May 2020 in the eastern Arabian Sea. The watershed-based spectral partitioning method is used to analyze 2D wave spectra obtained from measurements. Four-wave systems are present during pre- and post-monsoon periods, and three systems are detected during the monsoon (June–September). Interannual changes in significant wave height and peak wave period of different systems are investigated, revealing the maximum interannual variability of all wave systems in the inter-monsoon periods (May and October). The most energetic system during the pre-monsoon period is wind seas from the northwest direction, whereas during monsoon, swells from the southwest-west dominate. This pattern is similar across a spatial distance of 570 km along the western coastal waters of India. In the post-monsoon period, both systems (wind seas and swells) are present, with swells having slightly higher intensity. Full article

Urban green spaces (UGSs) are a vital component of urban landscapes nowadays, with an impact on energy distribution in cities and local climate regulation. This study aims to quantify the thermal and optical behavior of various materials in a small-scale Mediterranean UGS and provide insights into the use of green and artificial materials in urban parks. The analysis also includes the changes in the UGS’s optical and thermal properties following its restoration in 2024. The thermal comfort in the UGS is assessed for the 2020–2024 period, along with the reflectivity and surface temperatures of the different materials pre- (in 2022) and post-restoration (in 2024), using in situ measurements. The results show notable seasonal and interannual variability in the thermal comfort of the site. The impact of vegetation on the UGS was critical. The vegetation-covered surfaces exhibited surface temperatures close to ambient air temperature, highlighting their effective thermal regulation. During summer mornings, the average temperatures of the vegetation-covered surfaces were around 30.5 °C, lower compared to artificial or non-green materials, like asphalt, concrete, gravel, and dry bare soil, which were above 42 °C. The vegetation albedo was relatively lower (around 0.19), while artificial covers showed a greater reflectance (up to 0.35), thus boosting the heat retention. These results highlight the essential importance of green infrastructure incorporation to boost the thermal dynamics of urban open spaces and mitigate climate change effects. Full article

Temperate grasslands are highly sensitive to climate change and play a crucial role in terrestrial carbon cycling. In the context of global warming, heterotrophic respiration (Rh) has intensified, contributing significantly to atmospheric CO₂ emissions. However, seasonal patterns of Rh, particularly differences between the growing season (GS) and non-growing season (non-GS), remain poorly quantified. This study used daily eddy covariance data from multiple flux towers combined with MODIS GPP and NPP products to estimate Rh across temperate grasslands from 2002 to 2021. We examined interannual variations in GS and non-GS Rh contributions and assessed their relationships with key hydrothermal variables. The results showed that mean Rh during GS and non-GS was 527 ± 357 and 341 ± 180 g C m⁻² yr⁻¹, respectively, accounting for 57.8 ± 14.6% and 42.2 ± 14.6% of the annual Rh. Moreover, GS Rh exhibited a declining trend, while non-GS Rh increased over time, indicating a gradual convergence in their seasonal contributions. This pattern was primarily driven by increasing drought stress in GS and warmer, moderately moist conditions in non-GS that favored microbial activity. Our findings underscore the necessity of distinguishing seasonal Rh dynamics when investigating global carbon cycle dynamics. Future earth system models should place greater emphasis on seasonal differences in soil respiration processes by explicitly incorporating the influence of soil moisture on the decomposition rate of soil organic carbon, in order to improve the accuracy of carbon release risk assessments under global change scenarios. Full article

Wave climate variability, including seasonal cycles, long-term trends, and interannual anomalies of wave parameters, was investigated across five latitudinal sectors using ERA5 reanalysis data from 1980 to 2023. Pronounced seasonal cycles were observed in both Northern and Southern Hemisphere sectors, although the variability was more marked in the Northern Hemisphere. In contrast, the tropical region exhibited comparatively stable conditions throughout the year. Long-term trends revealed increases in both significant wave height and peak period across most sectors. The tropical region exhibited a trimodal regime driven by wind waves at low latitudes and remotely generated swells from both hemispheres. Teleconnections associated with the North Atlantic Oscillation (NAO) explained interannual variability in wind-wave direction in the tropics with an r² of 0.74 and wind-wave height variability in the Northern Hemisphere with an r² of 0.81. Additional indices, such as the Arctic Oscillation (AO), the Tropical North Atlantic (TNA) index, and the Northern Annular Mode (NAM), explained 30 to 60 percent of the directional variability. These results underscore the need to account for climate-driven variability in wave modeling frameworks to improve forecast accuracy and representation of directional trends. Full article

The spatiotemporal heterogeneity of hydrothermal conditions during the spring sowing period profoundly shapes cropping layouts and sowing strategies. Using NASA’s GLDAS remote sensing reanalysis, we developed a continuous agricultural climate risk index that integrates three remotely driven indicators—spring sowing window days (SWDs) derived from a “continuous suitable-day” logic, the hydrothermal coordination degree (D value), and a comprehensive suitability index (SSH_SI)—thus advancing risk assessment from single metrics to a multidimensional framework. Methodologically, dominant periodic structures of spring sowing hydrothermal risk were extracted via a combination of wavelet power spectra and the global wavelet spectrum (GWS), while spatial trend-surface fitting and three-dimensional directional analysis captured spatial non-stationarity. The index’s spatial migration trajectories and centroid-evolution paths were then quantified. Results reveal pronounced gradients along the Great Wall Belt: SWD displays a “central-high, terminal-low” pattern, with sowing windows restricted to only 3–6 days in northeastern Inner Mongolia and western Liaoning but extending to 11–13 days in the central plains of Inner Mongolia and Shanxi; SSH_SI and D values form an overall “south-west high, north-east low” pattern, indicating more favorable hydrothermal coordination in southwestern areas. Temporally, although SWD and SSH_SI show no significant downward trend, their interannual variability has increased, signaling rising instability, whereas the D value declines markedly in most regions, reflecting intensified hydrothermal imbalance. The integrated risk index identifies high-risk hotspots in eastern Inner Mongolia and northern North China, and low-risk zones in western provinces such as Gansu and Ningxia. Centroid-shift analysis further uncovers a dynamic regional adjustment in optimal sowing patterns, offering scientific evidence for addressing spring sowing climate risks. These findings provide a theoretical foundation and decision support for optimizing regional cropping structures, issuing climate risk warnings, and precisely regulating spring sowing schedules. Full article

The Amazon Basin plays a crucial role in the global hydrological cycle, where seasonal and interannual variations in terrestrial water storage (TWS) are essential for understanding climate–hydrology coupling mechanisms. This study utilizes data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its follow-on mission (GRACE-FO, collectively referred to as GRACE) to investigate the spatiotemporal dynamics of hydrological mass changes in the Amazon Basin from 2002 to 2021. Results reveal pronounced spatial heterogeneity in the annual amplitude of TWS, exceeding 65 cm near the Amazon River and decreasing to less than 25 cm in peripheral mountainous regions. This distribution likely reflects the interplay between precipitation and topography. Vertical displacement measurements from the Global Navigation Satellite System (GNSS) show strong correlations with GRACE-derived hydrological load deformation (mean Pearson correlation coefficient = 0.72) and reduce its root mean square (RMS) by 35%. Furthermore, the study demonstrates that existing hydrological models, which neglect groundwater dynamics, underestimate hydrological load deformation. Principal component analysis (PCA) of the Amazon GNSS network demonstrates that the first principal component (PC) of GNSS vertical displacement aligns with abrupt interannual TWS fluctuations identified by GRACE during 2010–2011, 2011–2012, 2013–2014, 2015–2016, and 2020–2021. These fluctuations coincide with extreme precipitation events associated with the El Niño–Southern Oscillation (ENSO), confirming that ENSO modulates basin-scale interannual hydrological variability primarily through precipitation anomalies. This study provides new insights for predicting extreme hydrological events under climate warming and offers a methodological framework applicable to other critical global hydrological regions. Full article

The rainy season characteristics are directly modulated by atmospheric circulation and moisture transport dynamics. Focusing on the characteristics of the rainy season onset date (RSOD), this study aims to advance the understanding and prediction of climate change impacts on agricultural production and disaster mitigation strategies. Based on rainfall data from 66 meteorological stations in northeast China (NEC) from 1961 to 2020, this study determined the patterns of the RSOD in the region and established its mechanistic linkages with atmospheric circulation and water vapor transport mechanisms. This study identifies a climatic regime shift around 2000, with the RSOD transitioning from low to high interannual variability in NEC. Further analysis reveals a strong correlation between the RSOD and atmospheric circulation characteristics: cyclonic vorticity amplifies before the RSOD and dissipates afterward. Innovatively, this study reveals a significant transition in the water vapor transport paths during the early rainy season in NEC around 2000, shifting from eastern Mongolia–Sea of Japan to the northwestern Pacific region. Moreover, the advance or delay of the RSOD directly influences the water vapor transport intensity—an early (delayed) RSOD is associated with enhanced (weakened) water vapor transport. These findings provide a new perspective for predicting the RSOD in the context of climate change while providing critical theoretical underpinnings for optimizing agricultural strategies and enhancing disaster prevention protocols. Full article

The application of satellite-derived sea surface temperature in coastal regions is critical for resolving the dynamics of frontal features and coastal upwelling. Here, we examine and compare sea surface temperature (SST) gradients derived from two satellite products, the Multi-Scale Ultra-High Resolution SST Product (MUR, 0.01° grid scale) and the Operational SST and Ice Analysis (OSTIA, 0.05° grid scale), available through the Group for High Resolution SST (GHRSST). Both products show similar seasonal variability, with maxima occurring in the summer time frame. Additionally, both products show an increasing trend of SST gradients near the coast. However, differences exist between the two products (maximum gradient intensities were around 0.11 and 0.06 °C/km for OSTIA and MUR, respectively). The potential contributions of both cloud cover and the collocation of the MUR SST onto the OSTIA SST grid product to these differences were examined. Spectra and coherences were examined at two specific latitudes along the coast where upwelling can occur. A major conclusion is that future work needs to focus on cloud cover and its impact on the derivation of SST in coastal regions. Future comparisons also need to apply collocation methodologies that maintain, as much as possible, the spatial variability of the high-resolution product. Full article

As a typical grain base with a dense population and high-level urbanization, the North China Plain (NCP) faces a serious threat to its sustainable development due to water shortage. Surface water area (SWA) is a key indicator for continuously measuring the trends of regional water resources and assessing their current status. Therefore, a deep understanding of its changing patterns and driving forces is essential for achieving the sustainable management of water resources. In this study, we examined the interannual variability and trends of SWA in the NCP from 1990 to 2023 using annual 30 m water body maps generated from all available Landsat imagery, a robust water mapping algorithm, and the cloud computing platform Google Earth Engine (GEE). The results showed that the SWA in the NCP has significantly increased over the past three decades. The continuous emergence of artificial reservoirs and urban lakes, along with the booming aquaculture industry, are the main factors driving the growth of SWA. Consequently, the expansion of artificial water bodies resulted in a significant increase in water evaporation (0.16 km³/yr). Moreover, the proportion of water evaporation to regional evapotranspiration (ET) gradually increased (0–0.7%/yr), indicating that the contribution of water evaporation from artificial water bodies to ET is becoming increasingly prominent. Therefore, it can be concluded that the ever-expanding artificial water bodies have become a new hidden danger affecting the water security of the NCP through evaporative loss and deserve close attention. This study not only provides us with a new perspective for deeply understanding the current status of water resources security in the NCP but also provides a typical case with great reference value for the analysis of water resources changes in other similar regions. Full article

This study investigates the effects of key atmospheric features on mineral dust emissions and transport in the Sahara–Sahel region, focusing on the Bodélé Depression, during June 2006 and 2011. We use a combination of high-resolution atmospheric simulations (AROME model), satellite observations (MODIS), and reanalysis data (ERA5, ECMWF) to examine the roles of the low-level jet (LLJ), Saharan heat low (SHL), Intertropical Discontinuity (ITD), and African Easterly Jet (AEJ) in modulating dust activity. Our results reveal significant interannual variability in aerosol optical depth (AOD) between the two periods, with a marked decrease in June 2011 compared to June 2006. The LLJ emerges as a dominant factor in dust uplift over Bodélé, with its intensity strongly influenced by local topography, particularly the Tibesti Massif. The position and intensity of the SHL also play crucial roles, affecting the configuration of monsoon flow and Harmattan winds. Analysis of wind patterns shows a strong negative correlation between AOD and meridional wind in the Bodélé region, while zonal wind analysis emphasizes the importance of the AEJ and Tropical Easterly Jet (TEJ) in dust transport. Surprisingly, we observe no significant correlation between ITD position and AOD measurements, highlighting the complexity of dust emission processes. This study is the first to combine climatological context and case studies to demonstrate the effects of African monsoon variability on dust uplift at intra-seasonal timescales, associated with the modulation of ITD latitude position, SHL, LLJ, and AEJ. Our findings contribute to understanding the complex relationships between large-scale atmospheric features and dust dynamics in this key source region, with implications for improving dust forecasting and climate modeling efforts. Full article

Tillage is a major factor influencing soil biological communities, particularly earthworms, which play a key role in soil structure and nutrient cycling. To address soil degradation, less-intensive tillage practices are increasingly being adopted globally and have shown positive effects on earthworm populations when applied consistently over extended periods. However, understanding of the earthworm population dynamics in the period following the implementation of changes in tillage practices remains limited. This three-year field study (2021–2023) investigates earthworm populations during the early transition phase (4–6 years) following the conversion from conventional ploughing to conservation (<8 cm depth, with residue retention) and no-tillage systems in a temperate arable system in central Slovenia. Earthworms were sampled annually in early October from three adjacent fields, each following the same three-year crop rotation (maize—winter cereal + cover crop—soybeans), using a combination of hand-sorting and allyl isothiocyanate (AITC) extraction. Results showed that reduced tillage practices significantly increased both earthworm biomass and abundance compared to conventional ploughing. However, a significant interaction between tillage and year was observed, with a sharp decline in earthworm abundance and mass in 2022, likely driven by a combination of 2022 summer tillage prior to cover crop sowing and extreme drought conditions. Juvenile earthworms were especially affected, with their proportion decreasing from 62% to 34% in ploughed plots and from 63% to 26% in conservation tillage plots. Despite interannual fluctuations, no-till showed the lowest variability in earthworm population. Long-term monitoring is essential to disentangle management and environmental effects and to inform resilient soil management strategies. Full article

In this case study, we used the Delta Simulation Model II (DSM2) to study the salt balance at the land–water interface in the river delta of California’s San Francisco Estuary. Drainage, a source of water and salt for adjacent channels in the study area, is affected by channel salinity. The DSM2 approach has been adopted by several hydrodynamic models of the estuary to enforce water volume balance between diversions, evapotranspiration and drainage at the land–water interface, but does not explicitly enforce salt balance. We found deviations from salt balance to be quite large, albeit variable in magnitude due to the heterogeneity of hydrodynamic and salinity conditions across the study area. We implemented a procedure that approximately enforces salt balance through iterative updates of the baseline drain salinity boundary conditions (termed loose coupling). We found a reasonable comparison with field measurements of drainage salinity. In particular, the adjusted boundary conditions appear to capture the range of observed interannual variability better than the baseline periodic estimates. The effect of the iterative adjustment procedure on channel salinity showed substantial spatial variability: locations dominated by large flows were minimally impacted, and in lower flow channels, deviations between baseline and adjusted channel salinity series were notable, particularly during the irrigation season. This approach, which has the potential to enhance the simulation of extreme salinity intrusion events (when high channel salinity significantly impacts drainage salinity), is essential for robustly modeling hydrodynamic conditions that pre-date contemporary water management infrastructure. We discuss limitations associated with this approach and recommend that—for this case study—further improvements could best be accomplished through code modification rather than coupling of transport and island water balance models. Full article