Search Results (136)

Determining long-term changes in global ice and water storage from satellite gravimetry remains challenging due to the limited temporal coverage of high-resolution missions. Here, we combine Satellite Laser Ranging (SLR) and Gravity Recovery and Climate Experiment (GRACE) data to reconstruct large-scale, non-linear mass variations from 1995 to 2024, extending gravity-based observations into the pre-GRACE era while preserving spatial detail through backward extrapolation. The combined model reveals widespread and statistically significant accelerations in global water and ice mass changes and enables the identification of key turning points in their temporal evolution. Results indicate that in Svalbard, a non-linear transition in ice mass balance occurred in late 2004, followed by a pronounced acceleration of mass loss due to climate warming. Glaciers in the Gulf of Alaska exhibit persistent mass loss with a marked intensification after 2012, while in the Antarctic Peninsula, ice mass loss substantially slowed and a potential trend reversal emerged around 2021. The reconstructed mass anomalies show strong consistency with independent satellite altimetry and climate indicators, including a clear response to the 1997/1998 El Niño event prior to the GRACE mission. These findings demonstrate that integrating SLR with GRACE enables robust detection of non-linear, climate-driven mass redistribution on a global scale and provides a physically consistent extension of satellite gravimetry records beyond the GRACE era. Full article

The genus Pavona includes massive to submassive hermatypic corals and represents one of the main reef builders of the coral reefs in the Eastern Tropical Pacific (ETP). However, its development and specific ecological role, particularly on offshore reefs (e.g., oceanic Atolls), remain poorly understood. This study aims to determine the sclerochronological characteristics of the four Pavona species (Pavona duerdeni, Pavona clavus, Pavona maldivensis, and Pavona varians) in Clipperton Atoll, and their contributions to reef maintenance. Using the optical densitometry technique, Pavona annual growth parameters were obtained, showing that skeletal density (1.26 ± 0.23 g cm⁻³), extension rate (0.94 ± 0.31 cm year⁻¹), and calcification rate (1.17 ± 0.36 g cm⁻² year⁻¹) were consistent with previous data from the ETP. However, differences at the species level showed that P. duerdeni, P. varians, and P. maldivensis invested their calcification resources into building denser skeletons, demonstrating the morphological plasticity of the genus, likely driven by local factors, such as strong hydrodynamics and depth, rather than regional conditions (e.g., El Niño-Southern Oscillation events). Pavona’s growth strategies contribute to the preservation potential on a geological timescale of Clipperton Atoll, highlighting their importance as one of the main reef builders at a massive coral-dominated reef. Full article

Heat extremes or heatwave events have significantly impacted socioeconomic activities and ecological systems, causing serious health issues and increased mortality rates in Pakistan over the past few decades. This study investigates the relationship between heat extremes in the northern Indian Ocean’s sea surface temperature (SST) and atmospheric temperature over Land (ATL) in Pakistan, and their connection to the Niño 3.4 Index, for monthly (March–August) and seasonal (spring and summer) basis from 1979 to 2015. Results show that SST has a higher frequency of heat extreme anomalies over different stretches of days than ATL. On a seasonal scale, heat extremes in ATL showed a significant correlation with SST, while the relationship was insignificant on a monthly basis. Both ATL and SST exhibited strong associations with the Niño 3.4 Index for land and ocean. These findings suggest that large-scale ocean-atmosphere interactions, particularly El Niño Southern Oscillation (ENSO), play a key role in modulating heat extremes in the region. The results of this study support SDGs by improving adaptive capacity and resilience on health, hunger, and climate by guiding policymakers in mitigating heat extremes. Integrating the findings of this study into national and provincial heat extreme plans may facilitate timely resource allocation and adaptation strategies in one of the world’s most climate-vulnerable regions. Full article

The influence of tropical oscillations on the thermodynamics of the middle and upper atmosphere at high latitudes was studied using a nonlinear model of the general circulation of the middle and upper atmosphere (MUAM). The observed oscillations include the quasi-biennial oscillation of the zonal wind in the equatorial stratosphere (QBO) and the El Niño–Southern Oscillation (ENSO). The main focus of this work is to study the influence of these oscillations on the strength and persistence of the stratospheric polar vortex. Four ensemble calculations were carried out (10 runs for each QBO and ENSO phase combination) for January–February. It was shown that the polar vortex and Eliassen–Palm (EP) flux divergence were especially strong under La Niña and the westerly QBO phase (wQBO). This was accompanied by a strengthening of the residual mean circulation (RMC) from the summer to the winter hemisphere, causing positive temperature anomalies in the polar mesosphere and negative anomalies in the stratosphere. The greatest RMC weakening and the weakest and warmest polar vortex occurred during El Niño and eQBO conditions in January and during El Niño and wQBO conditions in February. Such diverse manifestations of tropical oscillations via teleconnections can provide valuable information for predicting the frequency and intensity of sudden stratospheric warmings (SSWs) and subsequent extreme cold wave events in the troposphere. Specifically, SSWs are the least probable during La Niña and wQBO conditions in both January and February. The QBO phase most significantly influences the polar vortex during El Niño events in both months. We conclude that SSW development is more favorable during eQBO in January and wQBO in February under El Niño conditions. Full article

China’s Yangtze and Yellow River Basins exhibit divergent drought patterns, yet the underlying mechanisms driving these differences remain underexplored. This study compares their drought characteristics from 1961 to 2022 using the Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, and Palmer Drought Severity Index, and identifies their drivers through attribution models and interpretable machine learning. Our results reveal two distinct paradigms: the Yangtze Basin is characterized by high-frequency, over 14% in all seasons, short-duration droughts, reflecting a rapid hydrological response, while the Yellow River Basin experiences low-frequency, long-duration events indicative of strong soil moisture memory. Quantitative attribution demonstrates that atmospheric evaporative demand (VPD) plays a significantly greater role in the Yellow River Basin, contributing over 20% to soil drought, far exceeding its 14.4% contribution in the Yangtze Basin. Furthermore, their large-scale drivers differ fundamentally: the Yangtze Basin responds primarily to the Atlantic Multidecadal Oscillation (AMO) and Arctic Oscillation (AO), whereas the Yellow River Basin is mainly influenced by solar activity and the El Niño-Southern Oscillation (ENSO). These findings reveal that Yangtze drought is primarily driven by precipitation deficits, while Yellow River drought is a composite phenomenon amplified by evaporative demand. This distinction underscores the need for basin-specific water management strategies. Full article

Given the high sensitivity of small estuaries to environmental changes, the present study aimed to investigate how climate-induced stressors—particularly rainfall and salinity—affect zooplankton community structure in the Amazonian Taperaçu estuary (northern Brazil), where limited spatial scale amplifies ecological responses. This study evaluated the effects of the extremely dry 2015–2016 El Niño period on hydrological patterns and zooplankton dynamics in this shallow tropical estuary. Eight sampling campaigns were conducted, with water and zooplankton samples analyzed using standard methods. Salinity, dissolved inorganic nutrients, and chlorophyll-a concentrations were affected by the marked decrease in rainfall caused by the El Niño event. These changes significantly impacted zooplankton community dynamics, especially the densities of marine-estuarine species Acartia lilljeborgii, Euterpina acutifrons, and Oikopleura dioica, which peaked during months of highest salinity. High recruitment of copepod larval stages was also observed, with peak densities coinciding with dominant adult forms. In contrast, coastal and estuarine species such as Acartia tonsa, Pseudodiaptomus marshi, Oithona oswaldocruzi, and Oithona hebes were negatively affected by reduced rainfall. Species richness, diversity, and evenness during the El Niño period were relatively high compared to previously reported values under normal conditions in the same ecosystem. Environmental and temporal variables accounted for over half the variance in predominant taxa density, indicating that El Niño–driven changes influenced zooplankton structure over time. This suggests that El Niño may have strong impacts at the secondary trophic level, likely to cascade throughout the estuarine food web, altering its dynamics and the flow of carbon and energy through the system. Full article

Analysis of global mean sea-level (GMSL) variations provides insights into their spatial and temporal characteristics. To analyze the sea-level cycle and its correlation with the El Niño–Southern Oscillation (ENSO, represented by the Oceanic Niño Index), this study proposes an enhanced analytical framework integrating Local Mean Decomposition with an improved wavelet thresholding technique and wavelet transform. The GMSL time series (January 1993 to July 2020) underwent multi-scale decomposition and noise reduction using Local Mean Decomposition combined with improved wavelet thresholding. Subsequently, the Morlet continuous wavelet transform was applied to analyze the signal characteristics of both GMSL and the Oceanic Niño Index. Finally, cross-wavelet transform and wavelet coherence analyses were employed to investigate their correlation and phase relationships. Key findings include the following: (1) Persistent intra-annual variability (8–16-month cycles) dominates the GMSL signal, superimposed by interannual fluctuations (4–8-month cycles) related to climatic and seasonal forcing. (2) Phase analysis reveals that GMSL generally leads the Oceanic Niño Index during El Niño events but lags during La Niña events. (3) Strong El Niño episodes (May 1997 to May 1998 and October 2014 to April 2016) resulted in substantial net GMSL increases (+7 mm and +6 mm) and significant peak anomalies (+8 mm and +10 mm). (4) Pronounced negative peak anomalies occur during La Niña events, though prolonged events are often masked by the long-term sea-level rise trend, whereas shorter events exhibit clearly discernible and rapid GMSL decline. The results demonstrate that the proposed framework effectively elucidates the multi-scale coupling between ENSO and sea-level variations, underscoring its value for refining the understanding and prediction of climate-driven sea-level changes. Full article

The Western and Central Pacific Ocean (WCPO), the key global purse seine fishing ground for skipjack tuna (Katsuwonus pelamis), sees frequent ENSO events. These events drastically alter marine ecosystems and fishery resource patterns, complicating fisheries management—given skipjack tuna’s high mobility and sensitivity to marine environmental changes. To address this, the study proposes an improved spatial prediction framework that incorporates the MGWR model to capture environmental changes. The spatial regression results generated by the MGWR model are incorporated as the mean-field input for the BME model. Additionally, the interannual standard deviation of skipjack tuna resources is fed into the BME model as a measure of spatial uncertainty. The results indicate that the mean field and uncertainty field exhibit a strong correlation, with an R² of 0.54, an RMSE of 583.32, an MAE of 377.22, and an ME of 334.77. Compared to the single prediction models BME and MGWR, the MGWR-BME integrated framework has improved R² by 12%, 30%, and 13% in the 2021–2023 predictions, respectively. Additionally, its prediction performance for distinguishing El Niño, La Niña, and normal years has significantly improved, with R² increasing from 0.6 to 0.67 in 2021, from 0.34 to 0.62 in 2022, and from 0.30 to 0.40 in 2023. According to the evaluation results based on Kernel Density Estimation (KDE) curves, the model performs well in fitting low values but shows weaker performance in fitting high values. By applying this approach, we have clarified the multiscale driving mechanisms through which marine environmental heterogeneity affects the distribution of skipjack tuna under ENSO conditions. This insight enables fishery managers to more accurately predict the dynamic changes in skipjack tuna fishing grounds under different climatic scenarios, thereby providing a reliable scientific basis for formulating rational fishing quotas, optimizing fishing operation layouts, and implementing targeted conservation measures—ultimately contributing to the balanced development of fishery resource utilization and ecological protection. Full article

Background: Ecuador presents a unique epidemiological laboratory for studying arboviral dynamics due to its diverse ecological zones and exposure to climatic variability. Methods: We conducted a comprehensive 36-year analysis (1988–2024) of dengue (DENV), Zika (ZIKV), and chikungunya (CHIKV) using national surveillance data from Ecuador’s Ministry of Public Health. Statistical analyses included time series decomposition, change-point detection, correlation analysis, and climate association studies. Results: Ecuador reported 387,543 arboviral cases, with dengue comprising 91.3% (353,782 cases). Dengue exhibited endemic–epidemic cycles with major peaks during El Niño events (1994: 10,247 cases; 2000: 22,937 cases; 2015: 42,483 cases; 2024: 23,156 cases through week 26). CHIKV emerged explosively in 2015 (29,124 cases, incidence 181.10 per 100,000), followed by ZIKV in 2016 (2947 cases). Both showed rapid decline post-epidemic. Severe dengue cases paradoxically decreased from 2–4% of total cases in early 2000s to <0.1% post-2016, suggesting immunological modulation. Cross-correlation analysis revealed significant associations between climatic indices and epidemic timing ($r=0.67$, $p<0.001$), particularly for the El Niño-Southern Oscillation. Conclusions: Arboviral diseases in Ecuador function as an integrated epidemiological system with evidence of viral interactions, cross-protective immunity, and strong climate forcing. These findings emphasize the need for integrated surveillance and adaptive control strategies. Full article

Understanding precipitation variability is essential for assessing climate dynamics and their impacts on agriculture, water resources, and infrastructure. This study analyzes subseasonal precipitation patterns in Rio Grande do Sul, Brazil, using 45-day accumulated intervals over a 17-year period (2006–2022), a timescale critical for understanding drivers of extreme events like the catastrophic floods of 2024. A total of 138 precipitation fields were generated from 670 spatial points. Spatial analysis revealed median precipitation values ranging from 130 to 329 mm/45 days, with the northeast showing the highest accumulations and the southwest showing the driest conditions. Temporal variability was marked by abrupt anomalies, with median peaks up to 462 mm and minima of 33 mm. Significant temporal autocorrelation (lag-1, 45 days) was identified in the central and northern regions, while lag-2 (90 days) showed inverse patterns in the south (correlation coefficient ≈ −0.45). Principal component analysis (KMO = 0.909; Bartlett’s χ² = 187,990.945; p < 0.05) identified seven dominant modes, with PC1 explaining 26% of total variance and highlighting extremely wet anomalies (e.g., SPI > 2.0). Correlation with the Oceanic Niño Index revealed heterogeneous responses to ENSO phases, with strong El Niño episodes (2009, 2015–2016) associated with precipitation peaks up to 966 mm/45 days. These results underscore the importance of subseasonal scales for understanding climate anomalies and support the development of regional forecast strategies and water management policies under increasing climate variability. Full article

The Amazon River Basin (ARB) experienced an extreme drought from summer 2023 to spring 2024, driven by complex interactions among multiple climatic and environmental factors. A detailed investigation into this drought is crucial in understanding the entire process of the drought. Here, we employ drought indices derived from the Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GFO), and Swarm missions to reconstruct the drought’s progression, combined with reanalysis datasets and extreme-climate indices to analyze atmospheric and hydrological mechanisms. Our findings reveal a six-month drought from September 2023, reaching a drought peak of −1.29 and a drought severity of −5.62, with its epicenter migrating systematically from the northwestern to southeastern basin, spatially mirroring the 2015–2016 extreme drought pattern. Reduced precipitation and abnormal warming were the direct causes, which were closely linked to the 2023 El Niño event. This event disrupted atmospheric vertical movements. These changes led to abnormally strong sinking motions over the basin, which interacted synergistically with anomalies in land cover types caused by deforestation, triggering this extreme drought. This study provides spatiotemporal drought diagnostics valuable for hydrological forecasting and climate adaptation planning. 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

Precipitation concentration reflects the uneven temporal distribution of rainfall. It plays a critical role in water resource management and flood–drought risk under climate change. However, its long-term trends, associations with atmospheric teleconnections as potential drivers, and links to extreme heavy precipitation events remain poorly understood in complex basins like the Yangtze River Basin. This study analyzes these aspects using ground station data from 1960 to 2019 and conducts a comparison using the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM (GPM IMERG) satellite product. We calculated three indices—Daily Precipitation Concentration Index (PCID), Monthly Precipitation Concentration Index (PCIM), and Seasonal Precipitation Concentration Index (SPCI)—to quantify rainfall unevenness, selected for their ability to capture multi-scale variability and associations with extremes. Key methods include Mann–Kendall trend tests for detecting changes, Hurst exponents for persistence, Pettitt detection for abrupt shifts, random forest modeling to assess atmospheric teleconnections, and hot spot analysis for spatial clustering. Results show a significant basin-wide decrease in PCID, driven by increased frequency of small-to-moderate rainfall events, with strong spatial synchrony to extreme heavy precipitation indices. PCIM is most strongly associated with El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). GPM IMERG captures PCIM patterns well but underestimates PCID trends and magnitudes, highlighting limitations in daily-scale resolution. These findings provide a benchmark for satellite product improvement and support adaptive strategies for extreme precipitation risks in changing climates. 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

Observations indicate a robust relationship between the magnitude of El Niño events and the longitudinal displacement of the eastern edge of the Western Pacific Warm Pool (WPWP). Are the state-of-the-art coupled models also capturing this strong relationship? Here, we address this question by analyzing the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The results show that 31 out of 33 models replicate the observed strong correlation between El Niño magnitude and WPWP displacement. However, the models overestimate both El Niño strength and the extent of eastward WPWP movement, while underrepresenting the inter-event variability. These findings support the notion that El Niño may be largely regarded as an eastward extension of the WPWP, while also highlighting some model–observation discrepancies that may warrant particular attention. Full article