Search Results (307)

In recent years, China has experienced growing impacts from extreme weather events, emphasizing the importance of understanding regional atmospheric moisture dynamics, particularly Precipitable Water Vapor (PWV), to support sustainable environmental and urban planning. This study utilizes ten years (2013–2022) of Global Navigation Satellite System (GNSS) observations in typical cities in eastern China and proposes a comprehensive multiscale frequency-domain analysis framework that integrates the Fourier transform, Bayesian spectral estimation, and wavelet decomposition to extract the dominant PWV periodicities. Time-series analysis reveals an overall increasing trend in PWV across most regions, with notably declining trends in Beijing, Wuhan, and southern Taiwan, primarily attributed to groundwater depletion, rapid urban expansion, and ENSO-related anomalies, respectively. Frequency-domain results indicate distinct latitudinal and coastal–inland differences in the PWV periodicities. Inland stations (Beijing, Changchun, and Wuhan) display annual signals alongside weaker semi-annual components, while coastal stations (Shanghai, Kinmen County, Hong Kong, and Taiwan) mainly exhibit annual cycles. High-latitude stations show stronger seasonal and monthly fluctuations, mid-latitude stations present moderate-scale changes, and low-latitude regions display more diverse medium- and short-term fluctuations. In the short-term frequency domain, GNSS stations in most regions demonstrate significant PWV periodic variations over 0.5 days, 1 day, or both timescales, except for Changchun, where weak diurnal patterns are attributed to local topography and reduced solar radiation. Furthermore, ERA5-derived vertical temperature profiles are incorporated to reveal the thermodynamic mechanisms driving these variations, underscoring region-specific controls on surface evaporation and atmospheric moisture capacity. These findings offer novel insights into how human-induced environmental changes modulate the behavior of atmospheric water vapor. Full article

Groundwater is a critical yet understudied resource in Peru, where surface water has traditionally dominated national assessments. This study provides the first country-scale analysis of groundwater storage (GWS) variability in Peru from 2003 to 2023 using satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We used the GRACE Data Assimilation-Data Mass Modeling (GRACE-DA-DM GLV3.0) dataset at 0.25° resolution to estimate annual GWS trends and evaluated the influence of El Niño–Southern Oscillation (ENSO) events and anthropogenic extraction, supported by in situ well data from six major aquifers. Results show a sustained GWS decline of 30–40% in coastal and Andean regions, especially in Lima, Ica, Arequipa, and Tacna, while the Amazon basin remained stable. Strong correlation (r = 0.95) between GRACE data and well records validate the findings. Annual precipitation analysis from 2003 to 2023, disaggregated by climatic zone, revealed nearly stable trends. Coastal El Niño events (2017 and 2023) triggered episodic recharge in the northern and central coastal regions, yet these were insufficient to reverse the sustained groundwater depletion. This research provides significant contributions to understanding the spatiotemporal dynamics of groundwater in Peru through the use of satellite gravimetry data with unprecedented spatial resolution. The findings reveal a sustained decline in GWS across key regions and underscore the urgent need to implement integrated water management strategies—such as artificial recharge, optimized irrigation, and satellite-based early warning systems—aimed at preserving the sustainability of the country’s groundwater resources. Full article

Coastal wetlands play important environmental roles. However, their hydrogeomorphological dynamics remain poorly understood under scenarios of extreme climate events. The aim of this study was to characterize the temporal and spatial variability of hydrogeomorphological attributes (vegetation, water, and soil) in the wetlands of Lagoa do Peixe National Park, Brazil. The methodology involved applying Principal Component Analysis (PCA) in both temporal (T) and spatial (S) modes, decomposing spectral indices for each attribute to identify variability patterns. The results revealed that vegetation and water are strongly correlated with seasonal dynamics influenced by ENSO (El Niño/La Niña) events. Soils reflected their textural characteristics, with a distinct temporal response to the water balance. PCA proved to be a useful tool for synthesizing large volumes of multitemporal data and detecting dominant variability patterns. It highlighted the Lagoon Terraces and the Lagoon Fringe, where low slopes amplified hydrological variations. Temporal variability was more responsive to climate extremes, with implications for ecosystem conservation, while spatial variability was modulated by geomorphology. Full article

In recent years, under the influence of climate change and human activities, droughts and floods have occurred frequently in the Yangtze River Basin (YRB), seriously threatening socioeconomic development and ecological security. The topography and climate of the YRB are complex, so it is crucial to develop appropriate drought and flood policies based on the drought and flood characteristics of different sub-basins. This study calculated the water storage deficit index (WSDI) based on the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GFO) mascon model, extended WSDI to the bidirectional monitoring of droughts and floods in the YRB, and verified the reliability of WSDI in monitoring hydrological events through historical documented events. Combined with the wavelet method, it revealed the heterogeneity of climate responses in the three sub-basins of the upper, middle, and lower reaches. The results showed the following. (1) Compared and verified with the Standardized Precipitation Evapotranspiration Index (SPEI), self-calibrating Palmer Drought Severity Index (scPDSI), and documented events, WSDI overcame the limitations of traditional indices and had higher reliability. A total of 21 drought events and 18 flood events were identified in the three sub-basins, with the lowest frequency of drought and flood events in the upper reaches. (2) Most areas of the YRB showed different degrees of wetting on the monthly and seasonal scales, and the slowest trend of wetting was in the lower reaches of the YRB. (3) The degree of influence of teleconnection factors in the upper, middle, and lower reaches of the YRB had gradually increased over time, and, in particular, El Niño Southern Oscillation (ENSO) had a significant impact on the droughts and floods. This study provided a new basis for the early warning of droughts and floods in different sub-basins of the YRB. Full article

This study investigated the influence of long-term climatic phenomena on the hydroclimatic dynamics of the Grey River Basin in Chilean Patagonia. By analyzing hydroclimatological datasets from the last four decades (1980 to 2020), including precipitation, temperature, wind speed, potential evapotranspiration, and streamflow, we identified key trends and correlations with three large-scale climate indices: the Antarctic Oscillation (AAO), El Niño—Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO). Statistical methods such as the Mann–Kendall test, Sen’s slope, PCA, and wavelet coherence were applied. The results indicate a significant upward trend in streamflow, with Sen’s slope of 0.710 m³/s/year (p-value = 0.020), particularly since 2002, while other variables showed limited or no significant trends. AAO exhibited the strongest correlations with streamflow and wind speed, while ENSO 3.4 was the most influential ENSO index, especially during the two extreme El Niño events in 1982, 1997, and 2014. PDO showed weaker relationships overall. Wavelet analysis revealed coherent periodicities at 1- and 2-year frequencies between AAO and flow (wavelet coherence = 0.44), and at 2- to 4-year intervals between ENSO and precipitation (wavelet coherence = 0.63). These findings highlight the sensitivity of the Grey River basin to climatic variability and reinforce the need for integrated water resource management in the face of ongoing climate change. Full article

Ocean ecosystem services provisioning is driven by phytoplankton, which form the base of the ocean food chain in aquatic ecosystems and play a critical role as the Earth‘s carbon sink. Phytoplankton is highly sensitive to temperature, making it vulnerable to the effects of temperature variations. The aim of this research was to develop and test a workflow analysis to monitor the impact of sea surface temperature (SST) on phytoplankton biomass and primary production by combining field and remote sensing data of Chl-a and net primary production (NPP) (as proxies of phytoplankton biomass). The tropical zone was used as a case study to test the procedure. Firstly, machine learning algorithms were applied to the field data of SST, Chl-a and NPP, showing that the Random Forest was the most effective in capturing the dataset’s patterns. Secondly, the Random Forest algorithm was applied to MODIS SST images to build Chl-a and NPP time series. The time series analysis showed a significant increase in SST which corresponded to a significant negative trend in Chl-a concentrations and NPP variation. The recurrence plot of the time series revealed significant disruptions in Chl-a and NPP evolutions, potentially linked to El Niño–Southern Oscillation (ENSO) events. Therefore, the analysis can help to highlight the effects of temperature variation on Chl-a and NPP, such as the long-term evolution of the trend and short perturbation events. The methodology, starting from local studies, can support broader spatial–temporal-scale studies and provide insights into future scenarios. Full article

Paleoclimate records have long documented the existence of multicentury hydroclimate anomalies in the Altiplano of South America. However, the causes and mechanisms of these extended events are still unknown. Here, we present a climate modeling experiment that explores the oceanic drivers and atmospheric mechanisms conducive to long-term precipitation variability in the southern Altiplano (18–25° S; 70–65 W; >3500 masl). We performed a series of 100-year-long idealized simulations using the Weather Research and Forecasting (WRF) model, configured to repeat annually the oceanic and atmospheric forcing leading to the exceptionally humid austral summers of 1983/1984 and 2011/2012. The aim of these cyclical experiments was to evaluate if these specific conditions can sustain a century-long pluvial event in the Altiplano. Unlike the annual forcing, long-term negative precipitation trends are observed in the simulations, suggesting that the drivers of 1983/1984 and 2011/2012 wet summers are unable to generate a century-scale pluvial event. Our results show that an intensification of the anticyclonic circulation along with cold surface air anomalies in the southwestern Atlantic progressively reinforce the lower and upper troposphere features that prevent moisture transport towards the Altiplano. Prolonged drying is also observed under persistent La Niña conditions, which contradicts the well-known relationship between precipitation and ENSO at interannual timescales. Contrasting the hydroclimate responses between the Altiplano and the tropical Andes result from a sustained northward migration of the Atlantic trade winds, providing a useful analog for explaining the divergences in the Holocene records. This experiment suggests that the drivers of century-scale hydroclimate events in the Altiplano were more diverse than previously thought and shows how climate modeling can be used to test paleoclimate hypotheses, emphasizing the necessity of combining proxy data and numerical models to improve our understanding of past climates. Full article

Rainfall variability in the sensitive Kalahari semi-desert in Southern Africa, a region of strong climatic gradients, has not been much studied and is poorly understood. Here, anomalies in rainfall totals and moderate and heavy rain day frequencies are examined for both the summer half of the year and three bi-monthly seasons using CHIRPS rainfall data and ERA5 reanalysis. Peak rainfall occurs in January–February, with anomalously wet summers marked by a significant increase in the number of rainy days rather than rainfall intensity. Wet summers are linked to La Niña events, cyclonic anomalies over Angola, and a weakened Botswana High, which enhances low-level moisture transport and convergence over the region as well as mid-level uplift. Roughly the reverse patterns are found during anomalously dry summers. On sub-seasonal scales, ENSO and the Botswana High (the Southern Annular Mode) are negatively (positively) significantly correlated with early summer rainfall, while in mid-summer, and for the entire November–April season, only ENSO and the Botswana High are correlated with rainfall amounts. In the late summer, weak negative correlations remain with the Botswana High, but they do not achieve 95% significance. Full article

El Niño–Southern Oscillation (ENSO), as the strongest source of interannual variability in the tropics, has far-reaching impacts on global climate through teleconnections. As a key factor modulating the vegetation changes, the impact of ENSO has been studied over the past two decades using satellite observations. The paper aims to review results from the past 10–20 years and put together into a consistent picture of ENSO global impacts on vegetation. While ENSO affects vegetation worldwide, its impact varies regionally. Different ENSO flavors, Central Pacific and Eastern Pacific events, can have distinct impacts in the same regions. The underlying mechanisms involve ENSO-driven changes in precipitation and temperature, modulated by the background climate states, with varying response from vegetations of different types. However, the interactions between vegetation and ENSO remain largely unexplored, highlighting a critical gap for future research. 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

This study delves into the once-in-a-century extreme precipitation events in the northern region of the Pearl River Basin during the 2022 Dragon Boat Festival period. Through a comprehensive analysis spanning various temporal scales, from synoptic-scale systems to subseasonal oscillations, including the rare triple-peaked La Niña phenomenon, we illuminate the intricate interactions among these factors and their impact on extreme precipitation events. Specifically, we present a conceptual model of multiscale interaction systems contributing to extreme precipitation in the BeiJiang Basin. Our findings reveal that, during the 2022 Dragon Boat Festival period, precipitation in the BeiJiang Basin exhibited characteristics across multiple time scales, with the synoptic-scale environment proving highly conducive. Systems such as the South Asian High, Western Pacific Subtropical High, and South China Sea summer monsoon were identified as the direct influencing factors of precipitation. Importantly, our study highlight the pivotal role of subseasonal oscillation propagation stagnation in extreme precipitation in the BeiJiang Basin, with synoptic-scale systems playing a contributing role. We emphasize the indirect influence of ENSO signals, regulating not only monsoons but also the propagation of subseasonal oscillations. The interplay of these factors across different temporal scales significantly impacts flood hazards. Overall, our study significantly enhances the understanding of mechanisms driving extreme precipitation events in the Pearl River Basin, with profound implications for water resource management and disaster prevention. Full article

As important components of the equatorial current system in the Indian Ocean, Wyrtki jets (WJs) play a significant role in distributing heat and matter in the East and West Indian Oceans. By dividing the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events into several phases, we find that the spring branch exhibits positive (negative) anomalies during the El Niño (La Niña) decaying phase, while the fall branch exhibits negative (positive) anomalies during the El Niño (La Niña) developing phase. The spring and fall branches are characterized by negative (positive) anomalies under the influence of positive (negative) dipole events, and these anomalies are particularly pronounced during fall. This study systematically analyzes the characteristics of WJs under the interactions between the Indo-Pacific ocean and the atmosphere, based on the phase-locking characteristics of ENSO, and reveals the regulatory mechanisms underlying their different response patterns. Full article

Climate change manifests itself in rising temperatures across the continent and affects the El Niño–Southern Oscillation (ENSO) by changing sea surface temperatures and atmospheric circulation. This affects precipitation and temperature patterns, with South Africa normally experiencing drier conditions during El Niño events. These weather anomalies influence crop yields and food prices. Spatial price transmission indicates the extent to which prices of agricultural goods are linked across different geographical areas and how quickly price signals from one area are passed on to another. Although numerous studies explore spatial price transmission between various countries, there is a gap in the literature on price transmission between the US and South African maize markets during ENSO events. Therefore, we investigate how ENSO-related events impacted maize price transmission between the Chicago Mercantile Exchange and the Johannesburg Stock Exchange from 1997 to 2024. The empirical analysis starts with a correlation analysis, followed by tests for cointegration and error correction models. The results confirm the dominating impact of US maize prices on South African prices, but also how this relationship changes based on the nature of the ENSO event. There is some indication of lower levels of integration and higher levels of price diversion during El Niño periods. Full article

The coral reefs in the Philippines are facing an unprecedented crisis. This study, based on a comprehensive analysis of marine heatwaves (MHWs), degree heating weeks (DHWs), and ocean acidification (OA) indices derived from satellite observations and reanalysis data, reveals how thermal stress and OA have progressively eroded coral ecosystems from 1985 to 2022. This study analyzed 12 critical coral habitats adjacent to the Philippines. The monthly average sea surface temperature (SST) in the study area ranged from 26.6 °C to 29.3 °C. The coast of Lingayen Gulf was identified as the most vulnerable coral reef site in the Philippines, followed by Davao Oriental and Polillo Island. The coast of Lingayen Gulf recorded the highest total MHW days in 2022, amounting to 293 days. The coast of Lingayen Gulf also reached the highest DHW values in July and August 2022, with 8.94 °C weeks, while Davao Oriental experienced the most extended average duration of MHWs in 2020, lasting 90.5 days per event. Large-scale climate features such as the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) significantly influenced the study area’s SST anomalies and MHW events. High-risk coral bleaching periods, such as 1988–1989, 1998–1999, 2007–2008, and 2009–2010, were characterized by transitions from El Niño and positive PDO phases, to La Niña and negative PDO phases. However, since 2015, global warming has led to high cumulative heat stress without specific climate background patterns. We propose a Coral Marine Environmental Vulnerability Index (CoralVI) to integrate the spatiotemporal dynamics of warming and acidification and their impacts on coral habitats. The data show a rapid increase in the marine environmental vulnerability of coral habitats in the Philippines in recent years, extending to almost the entire coastline, posing significant threats to coral survival. Full article

Drought is one of the most widespread natural disasters globally, and its spatiotemporal distribution is profoundly influenced by the El Niño-Southern Oscillation (ENSO). As a typical humid coastal basin, the Jiaojiang River Basin in southeastern China frequently experiences hydrological extremes such as dry spells during flood seasons. This study focuses on the Jiaojiang River Basin, aiming to investigate the response mechanisms of drought evolution to ENSO in coastal regions. This study employs 10-day scale data from 1991 to 2020 to investigate the drought mechanisms driven by ENSO through a comprehensive framework that combines standardized indices with climate–drought correlation analysis. The results indicate that the Comprehensive Drought Index (CDI), integrating the advantages of the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), effectively reflects the basin’s combined meteorological and hydrological wet-dry characteristics. A strong response relationship exists between drought indices in the Jiaojiang River Basin and ENSO events. Drought characteristics in the basin vary significantly during different ENSO phases. The findings can provide theoretical support for the construction of resilient regional water resource systems, and the research framework holds reference value for sustainable development practices in similar coastal regions globally. Full article