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From February to March 2024, the equatorial Atlantic experienced its highest sea surface temperatures in at least 40 years. This extreme warm event was triggered by a favorable combination of El‐Niño‐induced westerly wind anomalies in the western equatorial Atlantic and Rossby wave reflection at the western boundary, leading to an exceptionally strong downwelling Kelvin wave. The warm event was extinguished abruptly around May by a locally‐forced upwelling Kelvin wave, causing an unprecedented rapid transition to a cold phase which lasted until August. The cold event did not fully develop into an Atlantic Niña due to weak Bjerknes feedback, warming from surface heat fluxes, and thermocline deepening due to a series of equatorial wave reflections. Nevertheless, the cold event is consistent with a northward shift of the intertropical convergence zone, increased rainfall over West Africa, Sahel, and Sahara, reduced rainfall over the Gulf of Guinea, and an earlier onset of the West African monsoon.

During the Late Cretaceous, Earth's climate oscillated between warm and cool states, and global oceans changed between anoxic and oxic conditions, resulting in black/gray shales and oceanic red beds (ORBs) deposition, respectively. To understand such climate/ocean dynamics, this study investigated bulk Hg and Hg isotopes, as well as Fe3+/Fe2+ in Upper Cretaceous sediments deposited in southern Tibet and the North Atlantic. In both areas, black/gray shales show much higher Hg concentrations than ORBs, indicating enhanced Hg flux to global oceans during time of black/gray shale deposition. Black/gray shales show lower Fe3+/Fe2+ and positive Δ199Hg, suggesting a significant input of Hg into the anoxic/dysoxic ocean via atmospheric deposition. The isotope values are consistent with a volcanic source for this excess Hg. ORBs show high Fe3+/Fe2+ and negative shifts of Δ199Hg, suggesting that the dominant source of Hg into the oxic oceans was via terrestrial runoff. This study suggests that volcanism was an important driver of the climate/ocean dynamics during the Late Cretaceous. Plain Language Summary The Late Cretaceous ocean developed widespread black/gray shales and oceanic red beds which were deposited in warm‐anoxic/dysoxic and cool‐oxic oceanic conditions, respectively. The driving force for such climate/ocean dynamics remains unclear. This study demonstrates distinct Hg concentrations and isotopic composition in black/gray shales and oceanic red beds, which suggest that volcanism was a major trigger of the climate/ocean dynamics in the Late Cretaceous. Key Points The Late Cretaceous black/gray shales and oceanic red beds display opposing mass‐independent fractionation of Hg isotopes Changes in climate/ocean conditions had strong control on the sources of Hg in the Late Cretaceous ocean Volcanism served as an important driving force of the climate/ocean dynamics during the Late Cretaceous

The present study examines changes in the low-level summer monsoon circulation over the Arabian Sea and their impact on the ocean dynamics using reanalysis data. The study confirms intensification and northward migration of low-level jet during 1979 to 2015. Further during the study period, an increase in the Arabian Sea upper ocean heat content is found in spite of a decreasing trend in the net surface heat flux, indicating the possible role of ocean dynamics in the upper ocean warming. Increase in the anti-cyclonic wind stress curl associated with the change in the monsoon circulation induces downwelling over the central Arabian Sea, favoring upper ocean warming. The decreasing trend of southward Ekman transport, a mechanism transporting heat from the land-locked north Indian Ocean to southern latitudes, also supports increasing trend of the upper ocean heat content. To reinstate and quantify the role of changing monsoon circulation in increasing the heat content over the Arabian Sea, sensitivity experiment is carried out using ocean general circulation model. In this experiment, the model is forced by inter-annual momentum forcing while rest of the forcing is climatological. Experiment reveals that the changing monsoon circulation increases the upper ocean heat content, effectively by enhancing downwelling processes and reducing southward heat transport, which strongly endorses our hypothesis that changing ocean dynamics associated with low-level monsoon circulation is causing the increasing trend in the heat content of the Arabian Sea.

Satellite altimetry offers a unique approach for direct sea surface current observation, but it is limited to measuring the surface‐constrained geostrophic component. Ageostrophic dynamics, prevalent at horizontal scales below 100 km and time scales below 10 days, are often underestimated by ocean reanalyzes employing data assimilation schemes. To address this limitation, we introduce a novel deep learning scheme, rooted in a variational data assimilation formulation with trainable observations and a priori terms, that harnesses the synergies between satellite‐derived sea surface observations, namely sea surface height (SSH) and sea surface temperature (SST), to enhance sea surface current reconstruction. Numerical experiments, conducted using realistic simulations, in a case study area of the Gulf Stream, demonstrate the potential of the proposed scheme to capture ageostrophic dynamics at time scales of 2.5–3.0 days and horizontal scales of 0.5°–0.7°. The analysis of diverse observation configurations, encompassing nadir along‐track altimetry, wide‐swath SWOT (Surface Water and Ocean Topography) altimetry, and SST data, highlights the pivotal role of SST features in retrieving a significant portion of the ageostrophic dynamics (approximately 47%). These findings underscore the potential of deep learning and 4DVarNet schemes in improving ocean reanalyzes and enhancing our understanding of ocean dynamics. Plain Language Summary Satellite altimetry provides a unique means for direct observation of sea surface currents, but it is confined to the geostrophic component, limiting the recovery of a substantial portion of mesoscale sea surface currents in operational products. To address this limitation, we present a novel deep learning framework, rooted in a variational data assimilation paradigm, that unlocks new avenues for leveraging the synergistic relationships between satellite‐derived sea surface observations, namely sea surface height and sea surface temperature. This innovative scheme demonstrates its remarkable potential to enhance sea surface current reconstruction and recover a substantial portion of the elusive ageostrophic dynamics. Numerical experiments, employing realistic simulations, in a case study area along the Gulf Stream, underscore the efficacy of our proposed approach. These findings support the pivotal role of physics‐informed deep learning in maximizing the utilization of available multimodal observation data sets and numerical simulations to elucidate partially observed sea surface dynamics. Key Points We present end‐to‐end deep learning schemes to improve the reconstruction of total sea surface currents from satellite‐derived observations Experiments in a region of the Gulf Stream support the synergistic analysis of sea surface temperature and sea surface height data The strain of sea surface dynamics is a proxy of the uncertainty of the retrieved estimation

The South Atlantic Convergence Zone (SACZ) is an atmospheric system occurring in austral summer on the South America continent and sometimes extending over the adjacent South Atlantic. It is characterized by a persistent and very large, northwest-southeast-oriented, cloud band. Its presence over the ocean causes sea surface cooling that some past studies indicated as being produced by a decrease of incoming solar heat flux induced by the extensive cloud cover. Here we investigate ocean–atmosphere interaction processes in the Southwestern Atlantic Ocean (SWA) during SACZ oceanic episodes, as well as the resulting modulations occurring in the oceanic mixed layer and their possible feedbacks on the marine atmospheric boundary layer. Our main interests and novel results are on verifying how the oceanic SACZ acts on dynamic and thermodynamic mechanisms and contributes to the sea surface thermal balance in that region. In our oceanic SACZ episodes simulations we confirm an ocean surface cooling. Model results indicate that surface atmospheric circulation and the presence of an extensive cloud cover band over the SWA promote sea surface cooling via a combined effect of dynamic and thermodynamic mechanisms, which are of the same order of magnitude. The sea surface temperature (SST) decreases in regions underneath oceanic SACZ positions, near Southeast Brazilian coast, in the South Brazil Bight (SBB) and offshore. This cooling is the result of a complex combination of factors caused by the decrease of solar shortwave radiation reaching the sea surface and the reduction of horizontal heat advection in the Brazil Current (BC) region. The weakened southward BC and adjacent offshore region heat advection seems to be associated with the surface atmospheric circulation caused by oceanic SACZ episodes, which rotate the surface wind and strengthen cyclonic oceanic mesoscale eddy. Another singular feature found in this study is the presence of an atmospheric cyclonic vortex Southwest of the SACZ (CVSS), both at the surface and aloft at 850 hPa near 24°S and 45°W. The CVSS induces an SST decrease southwestward from the SACZ position by inducing divergent Ekman transport and consequent offshore upwelling. This shows that the dynamical effects of atmospheric surface circulation associated with the oceanic SACZ are not restricted only to the region underneath the cloud band, but that they extend southwestward where the CVSS presence supports the oceanic SACZ convective activity and concomitantly modifies the ocean dynamics. Therefore, the changes produced in the oceanic dynamics by these SACZ events may be important to many areas of scientific and applied climate research. For example, episodes of oceanic SACZ may influence the pathways of pollutants as well as fish larvae dispersion in the region.

The study delves into the complexities of prolonged El Niño (PE) and La Niña (PL) events, examining their behaviour, dynamics, and representation in climate models participating in CMIP6. These events deviate from the typical cycles of the El Niño-Southern Oscillation (ENSO) system and significantly impact global weather patterns and socioeconomic systems. The study aims to enhance our understanding of these multi-year ENSO events through a comparative analysis of observational data and model simulations. Observational data reveal the distinct characteristics of PE and PL events, with prolonged warming or cooling anomalies persisting in the equatorial Pacific beyond the usual timeframe associated with canonical El Niño (CE) and La Niña (CL) events. However, while climate models generally capture the general trend of sustained warming or cooling, discrepancies exist in the magnitude and timing of SST anomalies, particularly during peak phases. The analysis highlights limitations in the ability of current climate models to simulate consecutive El Niño events following PE events and strong El Niño events preceding PL events accurately. Furthermore, discrepancies in the representation of subsurface oceanic dynamics and zonal wind stress patterns underscore challenges in capturing the intricate interactions driving ENSO variability. The study emphasizes the importance of refining climate models to capture better the intricacies of prolonged ENSO events, which have significant implications for future climate projections and adaptation strategies.

This study investigates the effect of ocean dynamics on the tropical climate response to localized radiative cooling over three northern extratropical land regions using hierarchical model simulations that vary in the degree of ocean coupling. Without ocean dynamics, the tropical climate response is independent of the extratropical forcing location, characterized by a southward tropical precipitation shift with a high degree of zonal symmetry, a reduced zonal sea surface temperature gradient along the equatorial Pacific, and the eastward-shifted Walker circulation. When ocean dynamical adjustments are allowed, the zonal-mean tropical precipitation shift is damped primarily via Eulerian-mean ocean heat transport. The oceanic damping effect is strongest (weakest) for North Asian (American) cooling, associated with the largest (smallest) Eulerian-mean ocean heat transport across the equatorial Pacific. The cross-equatorial ocean heat transport in the Pacific is anchored to the North Pacific subtropical high, the response of which can be inferred from the corresponding slab ocean simulations. Hence, the slab ocean simulations provide useful a priori prediction for oceanic damping efficiency. Ocean dynamics also modulates the spatial pattern of climate response in a distinct manner depending on the zonal distribution of imposed forcing. North Asian forcing induces a pronounced eastern equatorial Pacific cooling extending to the western basin, accompanying the westward shifted Walker circulation. European forcing causes cooling confined to the eastern equatorial Pacific and strengthens the Walker circulation. The tropical precipitation response in these two cases exhibits large zonal variations with a high degree of equatorial symmetry, being essentially uncorrelated with the corresponding slab ocean simulations. By contrast, North American forcing induces a sufficiently strong inter-hemispheric contrast in the tropical Pacific SST response, due to the relatively weak oceanic damping effect, producing a weaker but spatially similar tropical response to that in the slab ocean simulation. This study demonstrates that the effect of ocean dynamics in modulating the tropical climate response depends on the extratropical forcing location. The results are relevant for understanding the distinct climate response induced by aerosols from different continental sites.

The accurate estimation of the spatial and temporal distribution of chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is crucial for understanding marine ecosystem dynamics and water quality assessment. However, the challenge of missing values in satellite-derived Chl-a data has hindered obtaining complete spatiotemporal information. Traditional methods for deriving Chl-a are based on the modeling of measured sensor data and in situ measurements. Spatiotemporal imputation of Chl-a is difficult due to the inaccessibility of the measured Chl-a. In this study, we introduce an innovative approach that incorporates an ocean dynamics dataset and utilizes the random forest algorithm for predicting the Chl-a concentration in the SCS. The method combines the spatiotemporal feature pattern of Chl-a and the main influencing factors, and it introduces ocean dynamics data, which has a high correlation with the spatiotemporal distribution of Chl-a, as the input data through feature engineering. Also, we compared Random Forest (RF) with other Machine Learning (ML) methods. The results show that (1) ocean dynamics datasets can provide important data support for Chl-a imputation by capturing the impact of dynamical processes on ecological roles in the South China Sea. (2) The RF method is the superior imputation method for the reconstruction of Chl-a in the South China Sea, with better model performance and smaller errors. This study provides valuable insight for researchers and practitioners in choosing suitable machine learning methods for the imputation of the Chl-a concentration in the SCS, facilitating a better understanding of the region’s marine ecosystems and supporting effective environmental management.

For the primitive equations of large-scale atmosphere and ocean dynamics, we study the problem of determining by means of a variational data assimilation algorithm initial conditions that generate strong solutions which minimize the distance to a given set of time-distributed observations. We suggest a modification of the adjoint algorithm whose novel elements is to use norms in the variational cost functional that reflects the H 1 -regularity of strong solutions of the primitive equations. For such a cost functional, we prove the existence of minima and a first-order adjoint condition for strong solutions that provides the basis for computing these minima. We prove the local convergence of a gradient-based descent algorithm to optimal initial conditions using the second-order adjoint primitive equations. The algorithmic modifications due to the H 1 -norms are straightforwardly to implement into a variational algorithm that employs the standard L 2 -metrics.

The land, oceans, and atmosphere are tightly linked and form the most dynamic component of the climate system. Studies on terrestrial and ocean science enhance the understanding on the impacts of climate change. Across India and the world over, human-driven land use and climate changes are altering the structure, function, and extent of natural terrestrial ecosystems and in turn regional biogeochemical feedbacks. In this special issue, we present 29 manuscripts; those discuss wide-ranging aspects of terrestrial and oceanic characterization and dynamics. These contributions are based on selected presentations made at the 2nd International Workshop on Biodiversity and Climate Change (BDCC-2018) held on 24–27 February 2018 at the Indian Institute of Technology Kharagpur, India. The manuscripts are arranged in five sections such as Ecological Assessment, Plant Invasion, Carbon Dynamics, Ecosystem Characterization, and Ocean Dynamics. We realized that the utility of satellite remote sensing data has been emerging as a dominant trend in environmental monitoring and assessment studies in India.