Search Results (199)

Oceanic mesoscale activity influences the atmosphere in the southwestern and southern sectors of the Atlantic Ocean. However, the influence of high latitudes, specifically sea ice, on mid-latitudes and a better understanding of mesoscale ocean–atmosphere thermodynamic interactions still require further study. To quantify the effects of oceanic mesoscale activity during the periods of maximum and minimum Antarctic sea ice extent (September 2019 and February 2020), numerical experiments were conducted using a coupled regional model and an online two-dimensional spatial filter to remove high-frequency sea surface temperature (SST) oscillations. The largest SST anomalies were observed in the Brazil–Malvinas Confluence and along oceanic fronts in September, with maximum SST anomalies reaching 4.23 °C and −3.71 °C. In February, the anomalies were 2.18 °C and −3.06 °C. The influence of oceanic mesoscale activity was evident in surface atmospheric variables, with larger anomalies also observed in September. This influence led to changes in the vertical structure of the atmosphere, affecting the development of the marine atmospheric boundary layer (MABL) and influencing the free atmosphere above the MABL. Modulations in precipitation patterns were observed, not only in oceanic regions, but also in adjacent continental areas. This research provides a novel perspective on ocean–atmosphere thermodynamic coupling, highlighting the mesoscale role and importance of its representation in the study region. 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

Based on the Clouds and the Earth’s Radiant Energy System (CERES) satellite data from 2001 to 2023 and the climate indices from the National Oceanic and Atmospheric Administration (NOAA), this study analyzes the solar irradiance over mainland China and the impacts of clouds and aerosols on it and constructs monthly forecasting models to analyze the influence of climate indices on irradiance forecasts. The irradiance over mainland China shows a spatial distribution of being higher in the west and lower in the east. The influence of clouds on irradiance decreases from south to north, and the influence of aerosols is prominent in the east. The average explained variance of clouds on irradiance is 86.72%, which is much higher than that of aerosols on irradiance, 15.62%. Singular Value Decomposition (SVD) analysis shows a high correlation between the respective time series of irradiance and cloud influence, with the two fields having similar spatial patterns of opposite signs. The variation in solar irradiance can be attributed mainly to the influence of clouds. Empirical Orthogonal Function (EOF) analysis indicates that the variation in the first mode of irradiance is consistent in most parts of China, and its time coefficient is selected for monthly forecasting. Both the traditional multiple linear regression method and the Long Short-Term Memory (LSTM) network are used to construct monthly forecast models, with the preceding time coefficient of the first EOF mode and different climate indices as input. Compared with the multiple linear regression method, LSTM has a better forecasting skill. When the input length increases, the forecasting skill decreases. The inclusion of climate indices, such as the Indian Ocean Basin (IOB), El Nino–Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD), can enhance the forecasting skill. Among these three indices, IOB has the most significant improvement effect. The research provides a basis for accurate forecasting of solar irradiance over China on monthly time scale. Full article

Earth’s energy imbalance (EEI) is a major indicator of climate change. Its metrics are top of the atmosphere radiation imbalance (EEI TOA) and net internal heat uptake. Both EEI and temperature are expected to respond gradually to forcing on annual timescales. This expectation was tested by analyzing regime changes in the inputs to EEI TOA along with increasing ocean heat content (OHC). Outward longwave radiation (OLR) displayed rapid shifts in three observational and two reanalysis records. The reanalysis records also contained shifts in surface fluxes and temperature. OLR, outward shortwave radiation (OSR) and TOA net radiation (Net) from the CERES Energy Balanced and Filled Ed-4.2.1 (2001–2023) record and from 27 CMIP5 historical and RCP4.5 forced simulations 1861–2100, were also analyzed. All variables from CERES contained shifts but the record was too short to confirm regime changes. Contributions of OLR and OSR to net showed high complementarity over space and time. EEI TOA was −0.47 ± 0.11 W m⁻² in 2001–2011 and −1.09 ± 0.11 W m⁻² in 2012–2023. Reduced OSR due to cloud feedback was a major contributor, coinciding with rapid increases in sea surface temperatures in 2014. Despite widely varying OLR and OSR, 26/27 climate models produced stable regimes for net radiation. EEI TOA was neutral from 1861, shifting downward in the 26 reliable records between 1963 and 1995, with 25 records showing it stabilizing by 2039. To investigate heat uptake, temperature and OHC 1955/57–2023 was analyzed for regime change in the 100 m, 700 m and 2000 m layers. The 100 m layer, about one third of total heat content, was dominated by regimes. Increases became more gradual with depth. Annual changes between the 700 m layer and 1300 m beneath were negatively correlated (−0.67), with delayed oscillations during lag years 2–9. Heat uptake at depth is dynamic. These changes reveal a complex thermodynamic response to gradual forcing. We outline a complex arrangement of naturally evolved heat engines, dominated by a dissipative heat engine nested within a radiative engine. EEI is a property of the dissipative heat engine. This far-from-equilibrium natural engine has evolved to take the path of least resistance while being constrained by its maximum power limit (~2 W m⁻²). It is open to the radiative engine, receiving solar radiation and emitting scattered shortwave and longwave radiation. Steady states maximize entropy within the dissipative engine by regulating spatial patterns in surface variables that influence outgoing OLR and OSR. Regime shifts to warmer climates balance the cost of greater irreversibility with increased energy rate density. The result is the regulation of EEI TOA through a form of thermodynamic metabolism. Full article

The Northwestern Pacific Subtropical High (NPSH), usually enhanced by the basin-scale warming of the Indian Ocean (IOBW), plays a major role in controlling the summertime East Asian climate. To assess factors contributing to the decadal modulation of the NPSH and IOBW relationship in recent years, we conducted sensitivity experiments using an atmospheric general circulation model. We particularly focused on decadal-scale differences between the periods of 1982–2001 and 2002–2021, with the contribution of the climatological sea surface temperature (SST) as the background, in combination with the tropical Pacific SST anomaly in relation to the rapid or slow decay of the El Niño Southern Oscillation (ENSO). The results indicate that the IOBW-related SST anomalies in the Indian and tropical Pacific Oceans—which, overall, represent the well-known characteristics of the so-called Indo-western Pacific Ocean Capacitor effects—cooperatively enhanced the NPSH in the earlier period (1982–2001). On the other hand, the suppressed and westward-shifted SST anomalies in the tropical Pacific Ocean and the resultant changes in the diabatic heating of cumulus convection suppressed the NPSH enhancement in recent years (2002–2021). These results indicate that the modulation in the NPSH responses linked to the IOBW is primarily due to the so-called ENSO diversity rather than climatology. Full article

The forest ecosystems of large Mediterranean islands are critical hubs of evolutionary diversity with unique floristic composition and distinctive vegetation patterns reflecting long-term population dynamics and ecological legacies. Mediterranean islands provide invaluable natural archives, preserving crucial insights into the resilience of past forest ecosystems and their responses to climate variability. In this paper, we provide a comprehensive overview of the Holocene vegetation history of major western Mediterranean islands, with the twofold aim of examining the timing, extent, and rates of vegetation changes over the last few thousand years, and evaluating the influence of Rapid Climate Changes (RCCs) on forest ecosystems. The rate of change analysis allowed the identification of a distinct pattern of rapid shifts in forest composition, corresponding to periods of climate instability. These shifts align with the periodicity of Bond events, suggesting synchronicity between changes in forest ecosystems and centennial-scale climatic oscillations at a supra-regional scale. A REDFIT spectral analysis applied to palynological proxies of forest cover changes identified prominent periodicities suggesting a direct influence of solar activity and/or a relation with complex ocean–atmosphere circulation mechanisms triggered by global climate forcings. Full article

Since 2011, pelagic sargassum blooms (S. fluitans and S. natans) have impacted coastal communities, aquaculture, tourism, and biodiversity across the Tropical Atlantic region. Whilst the initial event is generally attributed to an anomalous North Atlantic Oscillation (2009–2010), the drivers of sargassum movement and proliferation remain unclear. This research gap is particularly evident in West Africa, where annual and seasonal sargassum variability is under-researched, and a lack of consensus exists on seasonal and annual trends. This paper addresses these gaps by (1) providing a first attempt at characterising the seasonal and annual trends of sargassum biomass in the Eastern Tropical Atlantic, through using satellite imagery to create a time-series for 2011–2022; and (2) exploring the hypothetical drivers of movement and proliferation of sargassum for this area, through assessing its co-variation with potential drivers including atmospheric, oceanic, and policy, establishing a historical timeline of events. The time-series analysis reveals an annual biomass peak in September and a second peak between March and May. The exploration of potential drivers reveals that alongside sea surface temperature there are multiple factors that could be influencing sargassum biomass, and that further research is necessary to clarify primary and secondary drivers. The results contribute to understanding drivers, impacts, and predictions of sargassum blooms in the Eastern Tropical Atlantic. We anticipate that our findings will enable sargassum-affected areas to better anticipate the size and timing of sargassum events in West Africa and offer researchers a new perspective on possible drivers of proliferation within the wider Tropical Atlantic region. Full article

Recent studies have identified a near six-year oscillation (SYO) in Global Navigation Satellite Systems (GNSS) surface displacements, with a degree 2, order 2 spherical harmonic (SH) pattern and retrograde motion. The cause is uncertain, with proposals ranging from deep Earth to near-surface sources. This study investigates the SYO and possible causes from surface loading. Considering the irregular spatiotemporal distribution of GNSS data and the variety of contributors to surface displacements, we used synthetic experiments to identify optimal techniques for estimating low degree SH patterns. We confirm a reported retrograde SH degree 2, order 2 displacement using GNSS data from the same 35 stations used in a previous study for the 1995–2015 period. We also note that its amplitude diminished when the time span of observations was extended to 2023, and the retrograde dominance became less significant using a larger 271-station set. Surface loading estimates showed that terrestrial water storage (TWS) loads contributed much more to the GNSS degree 2, order 2 SYO, than atmospheric and oceanic loads, but TWS load estimates were highly variable. Four TWS sources—European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5), Modern-Era Retrospective analysis for Research and Applications (MERRA), Global Land Data Assimilation System (GLDAS), and Gravity Recovery and Climate Experiment (GRACE/GRACE Follow-On)—yielded a wide range (24% to 93%) of predicted TWS contributions with GRACE/GRACE Follow-On being the largest. This suggests that TWS may be largely responsible for SYO variations in GNSS observations. Variations in SYO GNSS amplitudes in the extended period (1995–2023) were also consistent with near surface sources. 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

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

Xinjiang, an arid area located in the central part of the Eurasian continent with high evaporation and low precipitation, experiences frequent droughts. This study builds on previous research by incorporating five key ocean-atmosphere oscillations and using the one-month SPEI as a meteorological drought indicator. Monthly time series of precipitation and temperature from 53 meteorological stations are utilized to calculate the monthly SPEI time series, and the seasonal Kendall test analyzes trends. Despite increased precipitation, the drought conditions in Xinjiang worsened due to increased temperatures, especially in the south, during 1961–2017. The 53 monthly SPEI time series are clustered using the agglomerative hierarchical method, basically reflecting Xinjiang’s topographical and climatic diversity. However, classical correlation methods show a weak or negligible overall correlation between the SPEI and large-scale ocean-atmosphere oscillators. Therefore, the partial wavelet coherence (PWC) method was used to detect the scale-specific correlations. Both bivariate wavelet coherence (BWC) and PWC detected significant correlations between the SPEI and the ocean-atmosphere oscillators at some specific time scales. Our analyses indicate that southern Xinjiang droughts are more influenced by Pacific or Indian Ocean oscillators, while northern droughts are affected by Atlantic or Arctic climate variations. Full article

The Southern Ocean (SO) plays a fundamental role in the planet’s climate system, due to its ability to absorb and redistribute heat and CO₂ (an important greenhouse gas). In addition, the SO connects three large oceanic basins the Pacific, the Atlantic, and the Indian Oceans, and it has an important role in the nutrient distribution in these oceans. However, the SO is poorly sampled, with most measurements made in austral spring and summer. The variability in the air–sea CO₂ flux is estimated, as well as the role of atmospheric and oceanic variables in this variability. The CO₂ fluxes are calculated using the bulk parameterization method, in the Atlantic sector of the Southern Ocean, from 2003 to 2022, using in situ measurements, satellites, and a reanalysis data set. A neural network model is built to produce maps of the partial pressure of CO₂ in seawater (pCO_2sea). The CO₂ flux varies from −0.05 to 0.05 gC m⁻² month⁻¹. The Atlantic sector of the SO is a sink of CO₂ in summer and spring and becomes a source in austral winter and autumn. The CO₂ absorption intensifies from 2003 to 2022 by 7.6 mmol m⁻² month⁻¹, due to stronger westerly winds, related to the trend in the positive phase of the Antarctic Oscillation and the extreme El Niño Southern Ocean (ENSO) events (e.g., El Niño and La Niña). 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

In this work, the preindustrial control (piControl) and Historical experiments results from climatic Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are analyzed for their ability to predict the El Niño–Southern Oscillation (ENSO). Using the principal component method, it is shown that the Global Atmospheric Oscillation (GAO), of which the ENSO is an element, is the main mode of interannual variability of planetary anomalies of surface air temperature (SAT) and atmospheric sea level pressure (SLP) in the ensemble of 50 CMIP6 models. It turns out that the CMIP6 ensemble of models reproduces the planetary structure of the GAO and its west–east dynamics with a period of approximately 3.7 years. The models showed that the GAO combines ENSO teleconnections with the tropics of the Indian and Atlantic Oceans, and with temperate and high latitudes. To predict strong El Niño and La Niña events, we used a predictor index (PGAO) obtained earlier from observation data and reanalyses. The predictive ability of the PGAO is based on the west–east propagation of planetary structures of SAT and SLP anomalies characteristic of the GAO. Those CMIP6 models have been found that reproduce well the west–east spread of the GAO, with El Niño and La Niña being phases of this process. Thanks to this, these events can be predicted with approximately a year’s lead time, thereby overcoming the so-called spring predictability barrier (SPB) of the ENSO. Thus, the influence of global anomalies of SAT and SLP on the ENSO is shown, taking into account that it may increase the reliability of the early forecast of El Niño and La Niña events. Full article

This study investigates cyclone dynamics and impacts in the Southwestern Atlantic, with a focus on their effects on southern Brazil. As climate change intensifies coastal vulnerability, understanding cyclone behavior has become essential. Using the TRACK and cycloTRACK algorithms, we examined cyclone trajectories and cyclogenesis densities from 1979 to 2019 to analyze seasonal and spatial patterns shaped by large-scale atmospheric circulations, including the Antarctic Oscillation (AAO). The analysis explores trends in cyclone activity across various temporal and spatial scales, identifying key regions of cyclogenesis and trajectory density. Results indicate that the cycloTRACK algorithm is more effective at tracking more intense and consistent cyclones, excluding weaker systems. Seasonal patterns suggest variability in cyclone formation, likely associated with atmospheric instability and ocean–atmosphere interactions. While trends reveal an increase in cyclone passages in southern Brazil, these systems are strongly associated with extreme climatic events in the region, including coastal storms, intense precipitation, strong winds, and high waves. By clarifying cyclone dynamics and seasonal patterns, this study enhances our understanding of cyclone behavior and contributes to improved assessments of regional climate resilience in southern Brazil. Full article