Search Results (210)

The Gulf of Guinea is undergoing accelerated sea-level rise (SLR), with localized rates surpassing 10 mm yr⁻¹, more than double the global mean. Integrating GRACE/FO ocean mass data, reanalysis products, and machine learning, we identify a regime shift in the regional sea-level budget post-2015. Over 60% of observed SLR near major riverine outlets stems from ocean mass increase, driven primarily by intensified terrestrial hydrological discharge, marking a transition from steric to barystatic and manometric dominance. This shift coincides with enhanced monsoonal precipitation, wind-forced equatorial wave adjustments, and Atlantic–Pacific climate coupling. Piecewise regression reveals a significant 2015 breakpoint, with mean coastal SLR rates increasing from 2.93 ± 0.1 to 5.4 ± 0.25 mm yr⁻¹ between 1993 and 2014, and 2015 and 2023. GRACE data indicate extreme mass accumulation (>10 mm yr⁻¹) along the eastern Gulf coast, tied to elevated river discharge and estuarine retention. Dynamical analysis reveals the reorganization of wind field intensification, which modifies Rossby wave dispersion and amplifies zonal water mass convergence. Random forest modeling attributes 16% of extreme SLR variance to terrestrial runoff (comparable to wind stress at 19%), underscoring underestimated land–ocean interactions. Current climate models underrepresent manometric contributions by 20–45%, introducing critical projection biases for high-runoff regions. The societal implications are severe, with >400 km² of urban land in Lagos and Abidjan vulnerable to inundation by 2050. These findings reveal a hybrid steric–manometric regime in the Gulf of Guinea, challenging existing paradigms and suggesting analogous dynamics may operate across tropical margins. This calls for urgent model recalibration and tailored regional adaptation strategies. 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

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

Climate-driven hydrological extremes and anthropogenic interventions are increasingly altering streamflow regimes worldwide. While prior studies have explored climate or regulation effects separately, few have integrated multiple teleconnection indices and reservoir chronologies within a cross-basin comparative framework. This study addresses this gap by assessing long-term streamflow nonstationarity and its drivers at two key stations—Khabarovsk on the Amur River and Datong on the Yangtze River—representing distinct hydroclimatic settings. We utilized monthly discharge records, meteorological data, and large-scale climate indices to apply trend analysis, wavelet transform, percentile-based extreme diagnostics, lagged random forest regression, and slope-based attribution. The results show that Khabarovsk experienced an increase in winter baseflow from 513 to 1335 m³/s and a notable reduction in seasonal discharge contrast, primarily driven by temperature and cold-region reservoir regulation. In contrast, Datong displayed increased discharge extremes, with flood discharges increasing by +71.9 m³/s/year, equivalent to approximately 0.12% of the mean flood discharge annually, and low discharges by +24.2 m³/s/year in recent decades, shaped by both climate variability and large-scale hydropower infrastructure. Random forest models identified temperature and precipitation as short-term drivers, with ENSO-related indices showing lagged impacts on streamflow variability. Attribution analysis indicated that Khabarovsk is primarily shaped by cold-region reservoir operations in conjunction with temperature-driven snowmelt dynamics, while Datong reflects a combined influence of both climate variability and regulation. These insights may provide guidance for climate-responsive reservoir scheduling and basin-specific regulation strategies, supporting the development of integrated frameworks for adaptive water management under climate change. Full article

By utilizing daily precipitation data from 400 meteorological stations in the Yellow River Basin (YRB) of China, atmospheric and oceanic reanalysis data, this study investigates the climatological characteristics, leading modes, and relationships with atmospheric circulation and sea surface temperature (SST) of summer extreme precipitation in the YRB from 1981 to 2020 through the extreme precipitation metrics and Empirical Orthogonal Function (EOF) analysis. The results indicate that both the frequency and intensity of extreme precipitation exhibit an eastward and southward increasing pattern in terms of climate state, with regions of higher precipitation showing greater interannual variability. When precipitation in the YRB exhibits a spatially coherent enhancement pattern, high latitudes exhibits an Eurasian teleconnection wave train that facilitates the southward movement of cold air. Concurrently, the northward extension of the Western Pacific subtropical high (WPSH) enhances moisture transport from low latitudes to the YRB, against the backdrop of a transitioning SST pattern from El Niño to La Niña. When precipitation in the YRB shows a “south-increase, north-decrease” dipole pattern, the southward-shifted Ural high and westward-extended WPSH converge cold air and moist in the southern YRB region, with no dominant SST drivers identified. 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

In a warming climate, rising temperature are expected to influence atmospheric humidity. This study examined the spatio-temporal dynamics of temperature (TEMP) and relative humidity (RH) across Equatorial Africa from 1980 to 2020. The analysis used RH data from European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) reanalysis, TEMP and precipitation (PRE) from Climate Research Unit (CRU), and soil moisture (SM) and evapotranspiration (ET) from the Global Land Evaporation Amsterdam Model (GLEAM). In addition, four teleconnection indices were considered: El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). This study used the Mann–Kendall test and Sen’s slope estimator to analyze trends, alongside multiple linear regression to investigate the relationships between TEMP, RH, and key climatic variables—namely evapotranspiration (ET), soil moisture (SM), and precipitation (PRE)—as well as large-scale teleconnection indices (e.g., IOD, ENSO, PDO, and NAO) on annual and seasonal scales. The key findings are as follows: (1) mean annual TEMP exceeding 30 °C and RH less than 30% were concentrated in arid regions of the Sahelian–Sudano belt in West Africa (WAF), Central Africa (CAF) and North East Africa (NEAF). Semi-arid regions in the Sahelian–Guinean belt recorded moderate TEMP (25–30 °C) and RH (30–60%), while the Guinean coastal belt and Congo Basin experienced cooler, more humid conditions (TEMP < 20 °C, RH (60–90%). (2) Trend analysis using Mann–Kendal and Sen slope estimator analysis revealed spatial heterogeneity, with increasing TEMP and deceasing RH trends varying by region and season. (3) The warming rate was higher in arid and semi-arid areas, with seasonal rates exceeding annual averages (0.18 °C decade⁻¹). Winter (0.27 °C decade⁻¹) and spring (0.20 °C decade⁻¹) exhibited the strongest warming, followed by autumn (0.18 °C decade⁻¹) and summer (0.10 °C decade⁻¹). (4) RH trends showed stronger seasonal decline compared to annual changes, with reduction ranging from 5 to 10% per decade in certain seasons, and about 2% per decade annually. (5) Pearson correlation analysis demonstrated a strong negative relationship between TEMP and RH with a correlation coefficient of r = − 0.60. (6) Significant associations were also observed between TEMP/RH and both climatic variables (ET, SM, PRE) and large scale-teleconnection indices (ENSO, IOD, PDO, NAO), indicating that surface conditions may reflect a combination of local response and remote climate influences. However, further analysis is needed to distinguish the extent to which local variability is independently driven versus being a response to large-scale forcing. Overall, this research highlights the physical mechanism linking TEMP and RH trends and their climatic drivers, offering insights into how these changes may impact different ecological and socio-economic sectors. 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

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

The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs for their skill in simulating ENSO interdecadal variability and its teleconnection with precipitation globally. The results show that (1) only 22 out of 48 GCMs display interdecadal variability that is similar to the observations; (2) the ensemble of the 48 GCMs captures the ENSO–precipitation teleconnection at the global scale; (3) no single GCM can capture the observed ENSO–precipitation teleconnection globally; and (4) a GCM that can realistically simulate ENSO variability does not necessarily capture the ENSO-precipitation teleconnection, and vice versa. The results could also be used by climate change impact studies to select suitable GCMs, especially for regions with a statistically significant teleconnection between ENSO and precipitation, as well as for the comparison of CMIP5 and CMIP6. Full article

Statistical cluster analysis applied to monthly 1–100 m ocean temperatures reveals El Niño–Southern Oscillation (ENSO) dipole patterns with a leading mode having opposing centers of action across the dateline and tropical east Pacific. We focus on the La Niña cold phase and study its impact on the Caribbean climate over the period of 1980–2024. East dipole time scores are used to identify composite years, and anomaly patterns are calculated for Jan-Jun and Jul-Dec. Convective responses over the Caribbean exhibit seasonal contrasts: dry winter–spring and wet summer–autumn. Trade winds and currents across the southern Caribbean weaken and lead to anomalous warming of upper ocean temperatures. Sustained coastal upwelling off Peru and Ecuador during east La Niña is teleconnected with easterly wind shear and tropical cyclogenesis over the Caribbean during summer, leading to costly impacts. This ocean–atmosphere coupling is quite different from the more common central Pacific ENSO dipole. Full article

In arid regions, water scarcity necessitates reliance on surface runoff as a vital water source. Studying the impact of climate change on surface runoff can provide a scientific basis for optimizing water use and ensuring water security. This study investigated runoff patterns in the upper-middle Amu Darya River (UADR) from 1960 to 2015. Special emphasis was placed on the effects of climatic factors and the role of major atmospheric circulation indices, such as the Eurasian Zonal Circulation Index (EZI), Niño 3.4, and the Indian Ocean Dipole (IOD). The results show a significant linear decreasing annual trend in runoff at a rate of 2.5 × 10⁸ m³/year, with an abrupt change in 1972. Runoff exhibited periodic characteristics at 8–16 and 32–64 months. At the 8–16-month scale, runoff was primarily influenced by precipitation (PRE), actual evapotranspiration (AET), and snow water equivalent (SWE), and, at the 32–64-month scale, Niño 3.4 guided changes in runoff. In addition, El Niño 3.4 interacted with the EZI and IOD, which, together, influence runoff at the UADR. This study highlights the importance of considering multiple factors and their interactions when predicting runoff variations and developing water resource management strategies in the UADR Basin. The analysis of nonlinear runoff dynamics in conjunction with multiscale climate factors provides a theoretical basis for the management of water, land, and ecosystems in the Amu Darya Basin. Full article

The Antarctic sea ice concentration (SIC) plays a crucial role in global climate dynamics by influencing atmospheric and oceanic circulation. This study examines SIC variability and its relationship with major climate modes, including the El Niño-Southern Oscillation (ENSO), Pacific-South American (PSA) pattern, Southern Annular Mode (SAM), and Antarctic Dipole (ADP). Using NSIDC satellite-derived sea ice data and ERA5 reanalysis from 1980 to 2022, we analyzed SIC anomalies in the Weddell, Ross, and Bellingshausen and Amundsen (B&A) Seas, assessing their response to climatic forcings across different timescales. Our findings reveal strong linkages between SIC variability and large-scale atmospheric circulation. ENSO-related teleconnections drive a dipolar SIC response, with warming in the Pacific sector and cooling in the Atlantic during El Niño, and the opposite pattern during La Niña. PSA and ADP further modulate this response by altering Rossby wave propagation and heat fluxes, leading to significant SIC fluctuations. The ADP emerges as a dominant driver of interannual SIC anomalies, showing an out-of-phase relationship between the Atlantic and Pacific sectors of the Southern Ocean. Regional SIC trends exhibit contrasting patterns: the Ross Sea shows a significant positive SIC trend, while the B&A and Weddell Seas experience persistent negative anomalies due to enhanced meridional heat transport and stronger westerly winds. SAM strongly influences SIC, particularly in the Atlantic sector, with delayed responses of up to six months, likely due to ice-albedo feedbacks and ocean memory effects. These results enhance our understanding of Antarctic sea ice variability and its sensitivity to large-scale climate oscillations. Given the observed trends and ongoing climate change, further research is needed to assess how these processes will evolve under future warming scenarios. This study highlights the importance of continuous satellite observations and high-resolution climate modeling for improving projections of Antarctic sea ice behavior and its implications for the global climate system. Full article

The regularity of rainfall seasonality is very important for vegetation growth, the livelihood of the population, agricultural production, and ecosystem sustainability. Changes in precipitation and its extremes have been widely reported; however, the spatial and temporal variations in rainfall seasonality and their underlying mechanisms are less understood. Here, we analyzed the changes in rainfall seasonality and possible teleconnection mechanisms in the eastern China monsoon region during 1981–2022, with a special focus on the El Niño-Southern Oscillation (ENSO), El Niño Modoki (ENSO_M), and Indian Ocean Dipole (IOD). Our results show that due to the changes in rainfall concentration, rainfall magnitude, or both, rainfall seasonality has developed in the northern China (NC, 0.15 × 10⁻³ yr⁻¹) and central China (CC, 0.07 × 10⁻³ yr⁻¹) monsoon regions, and weakened in the northeastern China (NEC, −0.08 × 10⁻³ yr⁻¹) and southern China (SC, −0.15 × 10⁻³ yr⁻¹) monsoon regions during the recent decades. The large-scale circulation and SST anomalies induced by cold or warm phases of the IOD, ENSO_M, and (or) ENSO can explain the enhanced seasonality in the NC and CC monsoon regions and weakened seasonality in the NEC and SC monsoon regions. The wavelet coherence analysis further shows that the dominated climatic factors for rainfall seasonality changes are different in the CC, NC, SC, and NEC monsoon regions, and that rainfall seasonality is also affected by the coupling of the IOD, ENSO_M, and ENSO. Our results highlight that the IOD, ENSO_M, and ENSO are important climatic causes for rainfall seasonality changes in the eastern China monsoon region. Full article

To study the long-term hydroclimate variability in the Satluj Basin, streamflow data was reconstructed using tree-ring width datasets from multiple taxa available from the Kullu Valley, western (Indian) Himalaya. Five ring-width tree-ring chronologies of three conifer tree taxa (Abies pindrow, Cedrus deodara, and Pinus roxburghii) significantly correlate with the streamflow during the southwest monsoon season. Based on this correlation, a 228-year (1787–2014 CE) June–August streamflow was reconstructed using average tree-ring chronology. The reconstruction accounts for 34.5% of the total variance of the gauge records from 1964 to 2011 CE. The annual reconstruction showed above-average high-flow periods during the periods 1808–1811, 1823–1827, 1833–1837, 1860–1863, 1876–1881, and 1986–1992 CE and below-average low-flow periods during the periods 1792–1798, 1817–1820, 1828–1832, 1853–1856, 1867–1870, 1944–1947, and 1959–1962 CE. Furthermore, a period of prominent prolonged below-average discharge in the low-frequency streamflow record is indicated during the periods 1788–1807, 1999–2011, 1966–1977, 1939–1949, and 1854–1864. The low-flow (dry periods) observed in the present streamflow reconstruction are coherent with other hydroclimatic reconstructions carried out from the local (Himachal Pradesh and Kashmir Himalaya) to the regional (Hindukush mountain range in Pakistan) level. The reconstruction shows occurrences of short (2.0–2.8 and 4.8–8.3 years) to medium (12.5 years) periodicities, which signify their teleconnections with large-scale climate variations such as the El Niño–Southern Oscillation and the Pacific Decadal Oscillation. Full article