Search

Large volumes of cool water are drawn up to the surface in the tropical oceans. A companion paper shows that the cool water reaches the surface in or near the upwelling zones off northern and southern Africa and Peru. The cool water has a subantarctic origin and spreads extensively across the Atlantic and Pacific basins after it reaches the surface. Here, we look at the spreading in two low‐resolution ocean general circulation models and find that the spreading in the models is much less extensive than observed. The problem seems to be the way the upwelling and the spreading are connected (or not connected) to the ocean's large‐scale overturning. As proposed here, the cool upwelling develops when warm buoyant water in the western tropics is drawn away to become deep water in the North Atlantic. The "drawing away" shoals the tropical thermocline in a way that allows cool subantarctic water to be drawn up to the surface along the eastern margins. The amounts of upwelling produced this way exceed the amounts generated by the winds in the upwelling zones by as much as 4 times. Flow restrictions make it difficult for the warm buoyant water in our models to be drawn away. Plain Language Summary: A companion paper uses the radioactive isotope carbon‐14 to map the upwelling in the ocean basins north of the Antarctic Circumpolar Current (ACC). It shows that deep water drawn up to the surface to the south of the ACC is drawn up to the surface a second time in a number of upwelling areas in the tropics. In this paper, we attempt to simulate the tropical upwelling in an ocean circulation model and find that it is largely missing. Other circulation features are missing as well. The other features operate on the opposite sides of the ocean basins from the upwelling areas and help carry warm water out of the tropics ("outflows"). The combination of missing elements leads to a hypothesis about the upwelling mechanism. Our hypothesis is that the tropical upwelling is driven by the outflows and the fact that the warm water being carried away ultimately becomes deep water again in the North Atlantic. Key Points: Cool subantarctic water is drawn up to the surface in the tropical oceansThe upwelling tends to be poorly expressed in ocean general circulation modelsA new mechanism is proposed to explain how the upwelling is tied into the ocean's large‐scale overturning [ABSTRACT FROM AUTHOR]

Consequences of the mesoscale Thermal FeedBack (TFB) on the ocean dynamics are studied in the South‐East Pacific (SEP) using a high‐resolution regional ocean–atmosphere coupled model. Three simulations are compared: the first one is a fully coupled simulation. In the second one, the TFB has been removed with an online smoothing of the Sea Surface Temperature (SST) conditions used by the atmosphere. In the third one, to disentangle the impact of the nearshore and the offshore TFB, the smoothing is only applied in the offshore region. In the SEP, the coastal upwelling cold tongue constitutes a permanent mesoscale SST pattern. We show that this SST pattern alters the coastal wind structure, reducing the coastal upwelling‐favorable wind intensity. So, the nearshore TFB reduces the coastal surface current and the vertical velocities. As a result, the Eddy Kinetic Energy (EKE) generation by baroclinic conversion is also weakened. In the offshore region, on the contrary, the oceanic mean state is not affected by the TFB and only the EKE is weakened. Composites above the coherent eddies show that the heat flux response to the mesoscale SST anomalies is responsible for the mesoscale activity weakening over the whole studied area. Although the wind response to the SST anomalies has a very weak mean impact on the EKE generation through wind work, we show that it strongly modifies the mean oceanic vertical velocity anomalies over the coherent eddies. Plain Language Summary: The ocean dynamics is usually seen as driven by the atmosphere. However, the influence between the ocean and the atmosphere is mutual and the oceanic surface conditions feedback on the atmosphere. In this paper, we focus on the response of the atmosphere to the sea surface temperature mesoscale structures (structures that ranges from a few tens of km to a few hundred km). This response, called Thermal Feedback (TFB), is modeled with a high‐resolution ocean‐atmosphere coupled model to investigate its consequences on the oceanic dynamics in the South‐East Pacific. This region is characterized by a wind‐driven upwelling of sub‐surface waters near the coast, forming a sea surface coastal cold tongue. We show that this structure alters in return the coastal wind structure, which contributes to reduce the upwelling and the surface current. The generation of mesoscale structures, such as coherent eddies and filaments, is also reduced. The mesoscale structures are also weakened in the offshore region. We analyze the atmospheric response above the coherent eddies and show that the heat flux response to the SST anomalies is responsible for the eddy damping. Vertical velocities are also created in the eddy by the wind response to the SST anomalies. Key Points: Mesoscale thermal feedback decreases the mean coastal upwelling‐favorable wind, surface current and nearshore eddy generationMesoscale thermal feedback on the heat fluxes decreases the coherent eddy intensity through baroclinic conversionCoherent eddy mean vertical velocity is strongly modified by the mesoscale thermal feedback [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) is the dominant interannual variability affecting global weather and climate. However, limited observational records hinder our understanding of the evolution of natural ENSO variability and its driving mechanisms. In this study, ENSO variations from 665 to 749 CE (Common Era) were investigated using monthly sea surface temperature (SST) records of the northern South China Sea derived from coral strontium to calcium ratios of sub‐fossil Porites obtained at the Xisha Islands. The results suggested the existence of cold conditions in this period relative to the twentieth century. No change in SST seasonality for the CE was found that is in agreement with the orbitally controlled insolation seasonality at that time. ENSO variability during 665–749 CE was enhanced by 39% than that during 1980–2014 CE and exhibited fluctuations. A persistent dampened ENSO variability with frequent El Niño events from 665 to 700 CE was followed by a rapid increase in variability to a level double that of the present. The frequency of La Niña events increased during this time. The abrupt transformation of ENSO activity at 700 CE was attributed to the increased natural radiative forcing induced by intense solar irradiance and weak volcanism. This paper demonstrates that ENSO variability can be influenced by external forcings, such as changes in solar and volcanic activity, and not only by the internal dynamics of the climate system. Plain Language Summary: Reconstructing the amplitude and frequency of historical El Niño and La Niña events will allow us to better understand the driving mechanisms of their evolution and improve predictions of ENSO under anthropogenic climate change. This study reconstructed monthly sea surface temperature (SST) from 665 to 749 CE using a continuous sub‐fossil coral Sr/Ca record from Xisha Islands. We demonstrated that the northern South China Sea and its adjacent area experienced cold conditions during this period, with no change in SST seasonality relative to the present. Our results also revealed that ENSO variability during 665–749 CE exhibited significant fluctuations from a state with dampened ENSO to one with amplified ENSO, accompanied by a transition from frequent El Niño to La Niña anomalies. The abrupt increase in ENSO variability after 700 CE was triggered by the increased solar irradiance and weak volcanic eruptions. This suggests that in addition to the internal dynamics of the climate system, ENSO variability is also influenced by external forcings. Key Points: Cooler conditions and similar sea surface temperature seasonality compared to the present characterized 665–749 CEEl Niño–Southern Oscillation (ENSO) variability during 665–749 CE was 39% higher than that during 1980–2014 CEEnhanced solar activity triggered an abrupt increase in ENSO variability at 700 CE [ABSTRACT FROM AUTHOR]

Infragravity waves have received the least study of any class of waves in the deep ocean. This paper analyzes a 389‐day‐long deep ocean pressure record from the Hawaii Ocean Mixing Experiment for the presence of narrowband (≲2 μHz) components and nonstationarity over 400–4,000 μHz using a combination of fitting a mixture noncentral/central χ2 model to spectral estimates, high‐resolution multitaper spectral estimation, and computation of the offset coherence between distinct frequencies for a given data segment. In the frequency band 400–1,000 μHz there is a noncentral fraction of 0.67 ± 0.07 that decreases with increasing frequency. Evidence is presented for the presence of tidal harmonics in the data over the 400‐ to 1,400‐μHz bands. Above ~2,000 μHz the noncentral fraction rises with frequency, comprising about one third of the spectral estimates over 3,000–4,000 μHz. The power spectrum exhibits frequent narrowband peaks at 6–11 standard deviations above the noise level. The widths of the peaks correspond to a Q of at least 1,000, vastly exceeding that of any oceanic or atmospheric process. The offset coherence shows that the spectral peaks have substantial (p = 0.99–0.9999) interfrequency correlation, both locally and between distinct peaks within a given analysis band. Many of the peak frequencies correspond to the known values for solar pressure modes that have previously been observed in solar wind and terrestrial data, while others are the result of nonstationarity that distributes power across frequency. Overall, this paper documents the existence of two previously unrecognized sources of infragravity wave variability in the deep ocean. Plain Language Summary: Infragravity waves (IGWs) have arguably received the least study of any class of waves in the deep ocean. This paper contains the analysis of a 389 day long deep ocean pressure record from northwest of Hawaii for the presence of narrowband (≲2 μHz) components and nonstationarity over 400‐4000 μHz. Evidence is presented for the presence of tidal harmonics in the data over the 400‐1400 μHz band, possibly originating in the Gulf of Alaska. The power spectral density exhibits frequent narrowband peaks at 6‐11 standard deviations above the noise level. Some of the peak frequencies correspond to the known values for solar normal modes that have previously been observed in solar wind, seismic, geomagnetic, barometric and ionospheric data, while others are the result of nonstationarity that distributes power across frequency. Overall, this paper documents the existence of two heretofore unrecognized sources of IGW variability in the deep ocean. Key Points: Tidal harmonics comprise about half of the power in the deep ocean pressure field over 400–1,000 μHzSolar pressure or p‐modes are readily identified throughout the 400‐ to 4,000‐μHz bands, both by their characteristic frequencies and through their pervasive nonstationarityTwo previously unrecognized sources of infragravity wave variability have been characterized, indicating the complexity of the arguably least studied class of waves in the deep ocean [ABSTRACT FROM AUTHOR]

This study used the ERA‐5 40‐year reanalysis data set from the European Centre for Medium‐Range Weather Forecasts to analyze the spatial characteristics of wind waves and swells in the Indian Ocean. Although swells from the Southern Ocean can propagate into the Bay of Bengal, the zonal surface Stokes drift has been shown to correlate well with wind waves. Investigation of the relationship between the Indian Ocean Dipole (IOD) and the surface Stokes drift revealed strong correlation in the tropical Indian Ocean. The surface Stokes drift plays a positive role in maintaining sea surface temperature stability by transporting more (less) abnormally cold water during periods of positive (negative) IOD events. The depth‐integrated wave transport is quantified by the spectra and bulk parameters, respectively. Although two methods provide estimates of the same order of magnitude, the transport value is larger when wave spectra are used. With this approach, the estimated wave transport is comparable to the Ekman transport and its zonal component is even greater for more than 80% of the sea areas in the Indian Ocean; thus, it would have substantial effect on sea surface temperature. This paper proposes a new idea for studying this climatic phenomenon by considering the large‐scale wave effect, which builds a bridge for energy transport between the eastern and western boundaries of the Indian Ocean. Plain Language Summary: The Indian Ocean is closed on three sides and open only to the Southern Ocean. Swells from the Southern Ocean can propagate to the northern Indian Ocean, but the spatial distribution of the surface Stokes drift (i.e., wave‐induced current) is related to that of wind waves. The Indian Ocean Dipole (IOD) describes an irregular variation in sea surface temperature in which western parts of the Indian Ocean become alternately abnormal warming and cooling comparing with southeastern parts. In the tropical Indian Ocean, the abnormal surface Stokes drift has strong correlation with the IOD. During IOD events, the depth‐integrated Stokes drift can transport abnormally cold water to the area where sea surface temperature decreases anomalously, promoting stability of the tropical sea surface temperature. In quantifying the magnitude of wave transport, we found that it was comparable to the Ekman transport and its zonal component was even larger in the Indian Ocean. Because Ekman transport is one of the main processes of water transport in the upper ocean, we suggest that wave transport cannot be ignored when interpreting corresponding physical processes in the upper Indian Ocean. Key Points: Although swells from the Southern Ocean propagate northward for a long distance, the zonal surface Stokes drift is related to the wind wavesStokes drift plays a positive role in maintaining the zonal stability of sea surface temperature at low latitudes in the Indian OceanWave transport is of the same order of magnitude as Ekman transport and its zonal component is greater for more than 80% of the sea areas [ABSTRACT FROM AUTHOR]

Sea surface roughness is affected by surface current gradients, which provides a means of monitoring from satellite sharp oceanic fronts. This paper is the second report of an experiment designed to compare observations of sea surface roughness and surface currents at an unprecedented accuracy, owing to the conjunction of numerous deployed drifters and roughness instruments. About 200 drifters sampled a thin 10 km elongated submesoscale front, also monitored by a high density of roughness instruments: satellite synthetic aperture radar, satellite, and airborne multiangle sunglint radiometers. The first paper focused on the retrieval of the current gradient direction (convergence and cyclonic vorticity) at the front, using roughness observations at multiple angle from airplane. This second paper focuses on the retrieval of the current gradient magnitude and scale, using roughness observations at different scales, from airplane and from satellite. Two main results are obtained: (i) Trajectories of selected drifters show that the front is only 50 m wide and unambiguously exhibits convergence and cyclonic vorticity up to 100f (with f the Coriolis frequency). This far exceeds previously documented values for submesoscale deep ocean fronts. (ii) Correct estimation of such extreme current gradients using surface roughness hinges on instruments with sufficiently high spatial resolution. Lower‐resolution roughness sensors can still detect the front, as demonstrated from observations and a simplified model, but cannot properly estimate the current gradient magnitude and the frontal width. Those results provide guidelines for monitoring intense current gradients from space using sea surface roughness. Plain Language Summary: Ocean surface currents are not uniform horizontally but involve structures of many different sizes. After focusing on large‐scale currents (about 1,000 km) and eddies (about 100 km), attention is nowadays turning toward fine‐scale (about 1 km) fronts and filaments. Those fine structures are indeed particularly important for the exchanges between ocean surface and deeper ocean, for the accumulation of drifting pollution, and for the concentration of biological production and marine predators. Fishermen well know that oceanic fronts can be revealed by visual inspection of the ocean surface roughness. Exploring this idea, this paper investigates how oceanic fronts can be monitored using images of sea surface roughness. Images from satellites and airplanes were taken during an experiment where hundreds of surface drifters were released and got caught within an intense front. Two new lessons are learned from those observations: (1) The front was only 50 m wide, which is much sharper than commonly assumed for fronts of this type. (2) The front is thus associated with extreme current shear, which can only be detected by roughness sensors with sufficiently high spatial resolution. Those are important findings to improve monitoring of intense oceanic fronts from satellite. Key Points: Sea surface roughness induced by a submesoscale oceanic front is measured from satellite and airplane during a drifter release experimentDrifters unambiguously show extreme frontal sharpness with extreme current gradients, including both convergence and cyclonic vorticityAccurate monitoring of such sharp front using surface roughness is demonstrated and hinges on the availability of high‐resolution sensors [ABSTRACT FROM AUTHOR]

Anticyclonic mesoscale eddies are often observed in the Balearic Sea (BS) toward the end of summer and autumn. In some years, these eddies become strong and persistent, modifying the local water mass properties. In this study, we analyze two of the most significant recent long‐lived anticyclonic eddies, occurring in 2010 and 2017, using data from a high‐resolution circulation model, altimetry and satellite‐borne sea surface temperature observations. These eddies lasted around 2 and 4 months, respectively, with a radius varying between 40 and 75 km. The generation and intensification mechanisms of these long‐lived anticyclonic eddies are studied by means of (a) energy conversion terms associated with eddy‐mean flow interaction and (b) model sensitivity tests. Results show that these eddies were formed and intensified through mixed barotropic and baroclinic instabilities. The former are produced under the action of intense northwesterly (NW) winds. The latter are related to the existence of an intense summer thermal front between the BS and the Gulf of Lion, and to northward inflows of relatively lower salinity waters. Both the wind events and the presence of the thermal front are necessary for the formation of the eddies. The intensification process varied between both events. While in 2010 it was driven by significant salinity gradients produced by northwards inflows, in 2017 it was produced by additional intense NW winds. Both long‐lived anticyclonic eddies created long‐lasting surface temperature anomalies up to 2.5°C, which have characteristics of local marine heatwaves. Plain Language Summary: Eddies are closed circular currents present in the oceans. They are important phenomena due to their capacity to isolate water masses, retain floating particles and modify ocean circulation. In the Western Mediterranean Sea there is a recognized area of anticyclonic eddy presence between Barcelona and the Balearic Islands, especially during late summer. Specifically, in 2010 and 2017 two such eddies were identified with lifetimes of 2 and 4 months, respectively. In this paper, we investigate why these eddies were so long and persistent in comparison with other years. Results confirm that these eddies are generated as a result of northwesterly (NW) winds events blowing over an area with two water masses of different temperature. In 2010, low salinity northward water inflows sustained this eddy during two months, while in 2017 the eddy remained active for a period of four months under the influence of additional intense NW winds. Both eddies created long‐lasting surface temperature anomalies, in particular in 2017, the sea surface temperature within the eddy influence area was 2.5°C warmer in comparison to other years. Key Points: Northwesterly (NW) wind events and the existence of the Pyrenees thermal front are both necessary for the formation of strong long‐lived Balearic Sea eddiesEddy intensification was driven by salinity gradients in 2010 and by additional NW wind events in 2017Both events created long‐lasting surface temperature anomalies that have the characteristics of local marine heatwaves [ABSTRACT FROM AUTHOR]

Buoyant marine plastic debris has become a serious problem affecting the marine environment. To fully understand the impact of this problem, it is important to understand the dynamics of buoyant debris in the ocean. Buoyant debris accumulates in "garbage patches" in each of the subtropical ocean basins because of Ekman convergence and associated downwelling at subtropical latitudes. However, the precise dynamics of the garbage patches are not well understood. This is especially true in the southern Indian Ocean (SIO), where observations are inconclusive about the existence and numerical models predict inconsistent locations of the SIO garbage patch. In addition, the oceanic and atmospheric dynamics in the SIO are very different from those in the other oceans. The aim of this paper is to determine the dynamics of the SIO garbage patch at different depths and under different transport mechanisms such as ocean surface currents, Stokes drift, and direct wind forcing. To achieve this, we use two types of ocean surface drifters as a proxy for buoyant debris. We derive transport matrices from observed drifter locations and simulate the global accumulation of buoyant debris. Our results indicate that the accumulation of buoyant debris in the SIO is much more sensitive to different transport mechanisms than in the other ocean basins. We relate this sensitivity to the unique oceanic and atmospheric dynamics of the SIO. Plain Language Summary: Plastic pollution of the oceans is a serious problem. To better understand how big the problem is, it is important to know how plastics move in the oceans and where they end up. Floating plastics move with ocean currents, waves, and wind. Because these interact with each other in complex ways, the exact movement of plastic in the ocean is hard to predict. From observations and computer simulations, it is known that plastic collects in subtropical "garbage patches" in the Pacific and Atlantic oceans, but it is not clear if this also happens in the Indian Ocean. The aim of this paper is to determine the different influences of ocean currents, waves, and wind on the development of a garbage patch in the Indian Ocean. Because we cannot track plastics, we use data from over 22,000 GPS‐tracked drifting buoys that have been released worldwide in the oceans since 1979 to simulate the movement of plastic. Our results show that waves and wind prevent a garbage patch forming in the Indian Ocean. Because large amounts of plastic waste probably enter the Indian Ocean, an important question for follow‐up research is what happens to these plastics if they do not collect in a garbage patch. Key Points: The subtropical Indian Ocean garbage patch is very sensitive to different transport mechanismsSensitivity to different transport mechanisms is likely a result of the unique Indian Ocean dynamicsThe surface Indian Ocean garbage patch is located to the west of the basin and is highly dispersive [ABSTRACT FROM AUTHOR]

Oxygen measurements by in situ sensors on remote platforms are used to determine net biological oxygen fluxes in the surface ocean. On an annual basis these fluxes are stoichiometrically related to the export of organic carbon from the upper ocean (the ocean's biological carbon pump). In situ measurements on remote platforms make it feasible to observe the annual biological oxygen flux globally, but the accuracy of these estimates during periods of high winds depends on model‐determined fluxes by bubble processes created by breaking waves. We verify the importance of bubble processes in the gas exchange model of Liang et al. (2013, https://doi.org/10.1002gbc.20080) using surface‐ocean N2 gas measurements determined from observations of dissolved gas pressure and oxygen concentrations every 3 hr on a mooring in the northeast subarctic Pacific at Ocean Station Papa. The changes in N2 concentration during 10 separate monthlong periods in the winters between 2007 and 2016 indicate that bubble processes in the gas exchange model are over predicted by about a factor of 3 at this location. (The bubble mass transfer coefficients must be multiplied by 0.37 ± 0.14 to match the observations.) These results can be used to adjust model‐determined bubble fluxes to yield more accurate measurements of net biological oxygen production until the next generation gas‐exchange models are developed. Plain Language Summary: The flux of oxygen from the ocean to the atmosphere is related to the net biological flux of carbon to the ocean's interior. The biological carbon flux is the key process that determines the concentration of CO2 in the atmosphere and the oxygen concentration of deep ocean water. The net biological oxygen flux at the ocean‐atmosphere interface can be determined by measuring the gradient of oxygen across the air‐water interface and using this value in models of air‐sea gas exchange rates. To determine the biological component of the oxygen flux, the models must be able to evaluate physical fluxes of gas transfer caused by bubbles that result from breaking waves at high wind speeds. Our paper uses measurements of nitrogen gas on a surface mooring in the northeast Pacific Ocean to evaluate the role of bubbles in air‐sea gas exchange. With the information provided here oceanographers can use the verified gas exchange models to accurately determine biologically produced air‐sea oxygen fluxes. This advance will make it possible to verify biological fluxes that are critical for determining the ocean's role in climate, predicted in global circulation models. Key Points: Bubble‐promoted, air‐sea gas transfer is an important part of the annual oxygen flux in regions with high windsTen monthlong periods of in situ N2 and O2 gas measurements in the subarctic Pacific are used to verify a recent bubble flux modelThe model overpredicts the bubble flux for N2 and by inference other insoluble gases; a correction factor of 0.37 ± 0.14 is proposed [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) are prolonged anomalous warm seawater events that can severely impact marine ecosystems and have never been studied previously in the South China Sea. Here, we combine satellite sea surface temperature and reanalysis products to provide a systematic analysis of variations in summer MHWs in the South China Sea and potential influencing factors. The MHW days and duration, calculated as multiyear average, are mainly concentrated near the Nansha Islands and Beibu Gulf. Additionally, we find significant increasing trends in MHW days, duration, and frequency in the South China Sea during 1982–2020. The first empirical orthogonal function mode accounts for 60% of the total variance and exhibits a general mono‐sign pattern over the entire South China Sea. Increased solar radiation and released latent heat during summer MHWs contribute to high pressure in the western North Pacific. The anticyclone induced by the anomalous intensification of the western North Pacific subtropical high and its westward extension bring easterly wind anomalies to low latitudes, weakening the summer southwest monsoon south of 12°N in the South China Sea. The midwestern South China Sea upwelling weakens or even disappears due to a negative wind stress curl, causing basin‐wide severe summer MHWs. The paper also points out that more attention should be given to inter‐ocean interactions when monitoring the risks of unprecedented MHW‐related coral bleaching and marine ranching in the South China Sea. Plain Language Summary: Marine heatwaves, known as prolonged extreme oceanic warm water events, can last from days to months and severely affect marine ecosystems. In the South China Sea, frequent occurrences of coral bleaching are often associated with marine heatwaves in summer. Satellite data reveal that summer upwellings have significant influences on marine heatwaves' variations in the South China Sea, which has been unprecedented in the past decade. Based on observations and reanalysis products, we systematically examine the summer spatiotemporal variations and the potential factors that influence marine heatwaves in the South China Sea. From 1982 to 2020, the average total summer marine heatwave days, duration, and frequency increased by nearly 3.0 days/decade, 1.0 days/time/decade, and 0.2 times/decade, respectively. The anomalous western North Pacific subtropical high weakens midwestern upwelling. Without the mid‐summer cooling effect of midwestern upwelling, severe basin‐wide marine heatwaves will occur, and the ecological risks due to coral bleaching and marine ranching will increase. This study can aid the fisheries and aquaculture industries to better understand climate change risks under global warming in the South China Sea by considering marine heatwaves. Key Points: Summer marine heatwaves are mainly concentrated on the Nansha Islands and Beibu Gulf, with significant trends in the South China SeaThe anomalous western North Pacific subtropical high weakens midwestern South China Sea upwelling and triggers severe marine heatwavesInter‐ocean interactions are also responsible for summer marine heatwaves in the South China Sea [ABSTRACT FROM AUTHOR]

The satellite-derived precipitation over central India (73-78°E, 20-25°N) during the 2019 southwest monsoon season reveals that high-amplitude 3-7-day synoptic oscillations dominated the other intraseasonal oscillations and contributed to the excess seasonal monsoon rainfall. In this paper, we address the contribution of 3-7-day synoptic oscillations in atmospheric and oceanic parameters during the 2019 southwest monsoon season over the Bay of Bengal (BoB). Our study reveals that both satellite observations and the Nucleus for European Modeling of the Ocean (NEMO) model simulations show high-amplitude 3-7-day synoptic scale events during the 2019 monsoon. The upper 300 m of the water column responds to the basin-scale 3-7-day synoptic oscillations as revealed in the vertical structures of NEMO model simulated temperature, salinity, and currents in the BoB. The synoptic scale wind stress drives strong currents in the shallow mixed layer due to salinity stratification in the northern BoB. The northward propagation of the synoptic scale oscillations is evident across the BoB but is capped to the base of the mixed layer, above which the propagation is affected by wind stress and the spread of freshwater flux. The 3-7-day synoptic scale oscillations in NEMO sea surface height appear to be related to synoptic scale wind-driven convergence and divergence of waters through mesoscale eddy circulations that in turn contribute to thermocline variability, rather than the temperature and salinity in the mixed layer. [ABSTRACT FROM AUTHOR]

The California Current System (CCS) is one of the four major Eastern Boundary Current Systems, where major coastal upwelling is observed in the ocean. Oceanic fronts are abundant in the CCS, and are known to be associated with coastal upwelling. Analyses of satellite observations (altimetry and sea surface temperature, SST) of the CCS highlight the presence of SST fronts in the southern part of the CCS outside of the coastal upwelling season, which will be investigated. The submesoscale‐permitting and tidal‐resolving LLC4320‐simulation was used to analyze the nature of these features, through the study of the surface density gradients, the vertical velocities and the horizontal strain. An algorithm was also developed to track SST fronts in the model. The classical scenario of coastal upwelling is confirmed in the central CCS (off California), with a strain field correlated to vertical velocities associated with the SST fronts, and collocated density fronts. In contrast, in the southern CCS (off Baja California), vertical velocities were much weaker and density gradients were not always observed where SST fronts were detected, leading to the assumption that the fronts there may be affected by thermohaline compensation occurring in the region. These findings confirm the existence of SST fronts in the CCS outside of the traditional coastal upwelling framework, with part of the fronts in the southern CCS being passive and advected by the background flow. Plain Language Summary: Oceanic fronts can be defined as narrow boundaries separating waters with distinct properties (such as temperature) and play a major role in fisheries and marine ecology. This is particularly true for some of the features observed in the California Current System, which spans the western coast of North America. Indeed, fronts off California are due to a process called coastal upwelling, resulting in the presence of fronts that act as oases for marine life. Combined satellite observations of the region highlight the presence of temperature fronts off Baja California, which appear to have different patterns than the fronts off California. The aim of this paper is to investigate the nature of the temperature fronts found off Baja California, and to understand their distinct dynamics. Because satellite observations are confined to the ocean surface, we rely on a high‐resolution numerical simulation to study the three‐dimensional dynamics of the fronts. Our results show that some of the temperature fronts observed off Baja California, behave in a passive manner, in contrast with the fronts off California: they are not associated with coastal upwelling and are mainly carried out by the background flow. The implications for the local marine ecosystem remained to be clarified. Key Points: Sea surface height and sea surface temperature data reveal two distinctive frontal patterns across the California Current SystemSimulations by an ocean model highlight various frontal patterns in the California Current SystemDynamically passive fronts dominate off Baja California, whereas dynamically active fronts dominate off California [ABSTRACT FROM AUTHOR]

This paper evaluates the intraseasonal variability of sea surface temperature (SST) along the Sumatra‐Java southern coast using available satellite‐derived oceanic and atmospheric data combined with output from a numerical model. The result reveals that the intraseasonal variability of SST is greater during boreal summer–fall (June–October) than during boreal winter–spring (November–May). Composite analysis shows a correlation between positive/negative intraseasonal SST variabilities and coastal downwelling/upwelling, as well as onshore/offshore Ekman transport during summer–fall. During this period, with the significantly increasing role of oceanic advection, oceanic processes are evidently enhanced and dominate the intraseasonal variability of SST. Meanwhile, the contribution of atmospheric processes drops by 67%. During winter–spring, the intraseasonal SST is primarily contributed by atmospheric processes but has a nonsignificant relationship with sea level anomalies. Intraseasonal SST anomalies vary out of phase with surface wind anomalies. The result also shows a relatively small contribution by vertical processes throughout the year, with the maximum in April and the minimum during August–September. Further analysis reveals that the alternating dominance of atmospheric and oceanic processes on intraseasonal variability of SST is responsible for the seasonality along the Sumatra‐Java southern coast. Moreover, the result indicates that the seasonality in intraseasonal SST is different in the eastern Indonesian Seas, which tends to be relatively strong in boreal winter. Distinct dominance of atmospheric and oceanic processes in intraseasonal SST is the main reason for these differences in seasonal variation characteristics. Plain Language Summary: Previous studies indicated energetic intraseasonal variability of sea surface temperature (SST) along the Sumatra‐Java southern coast. Using available satellite‐derived oceanic and atmospheric data combined with output from a numerical model, we found that the intraseasonal variability of SST is greater during June–October than during November–May; that is, seasonality occurs in the intraseasonal variability. Then, we focused on the potential factors responsible for this seasonality. Our additional analysis reveals that oceanic processes, especially horizontal advection, contribute most to intraseasonal variabilities during summer–fall. During winter–spring, atmospheric processes, especially shortwave and latent heat flux, contribute most to intraseasonal variabilities. The alternating dominance of atmospheric and oceanic processes on intraseasonal SST induces seasonality along the Sumatra‐Java southern coast. By revealing the seasonality and ascertaining the main physical processes of the intraseasonal variability of SST, we believe this work can also confer some insight into the ongoing study on regional oceanography and climate change. Key Points: Intraseasonal SST along the Sumatra‐Java southern coast shows a larger variation in boreal summer–fall than in boreal winter–springThe intraseasonal variability of SST is mainly attributed to oceanic/atmospheric processes during boreal summer–fall/winter–springDistinct dominance of atmospheric and oceanic processes in intraseasonal SST leads to differences in seasonality of intraseasonal SST along the Sumatra‐Java southern coast and those in the eastern Indonesian Seas [ABSTRACT FROM AUTHOR]

During the summer monsoon season from June through September, low‐level winds from the Findlater Jet induce strong mesoscale activity and seasonal deepening of the mixed layer. For the first time, we have investigated the impact of mesoscale features on the strong intraseasonal variability of the mixed layer depth in the Arabian Sea using simulations from a reanalysis version of the HYbrid Coordinate Ocean Model and the European Centre for Mid‐range Weather Forecasting ERA‐Interim product. We identify and track mesoscale eddies using an eddy‐tracking algorithm during strong and weak summer monsoon conditions to determine the importance of mesoscale features on mixed layer variability during strong and weak wind forcing. We identify frontal systems in the Arabian Sea and observe how they strengthen with depth throughout the summer monsoon season. To quantify the role of these features on mixed layer variability, we also explore the roles of wind forcing, evaporation, precipitation, significant wave heights, and surface heat fluxes on mixed layer variability. A mixed layer heat budget was computed in the Arabian Sea, finding a strong dominance of vertical advective entrainment followed by compensation by horizontal processes indicating strong mesoscale activity. Plain Language Summary: The uppermost layer of the ocean is full of dynamic features such as frontal systems and quasi‐circular circulations on the order of 10–100 km called eddies. These features actively redistribute waters throughout the oceanic surface layer in which temperature, salinity, and density is almost vertically uniform, referred to as the mixed layer. In the Arabian Sea, the mixed layer deepens twice seasonally: once in the boreal winter and once in the boreal summer. In the wintertime, cool air blows over the Arabian Sea and cools the surface, which then sinks and deepens the mixed layer. In the summer, strong southwesterly winds deepen the mixed layer and provide conditions conducive to strong eddying and frontal development. In this paper, we compare the distribution of these mesoscale features under strong (weak) wind forcing associated with heavy (scanty) rainfall conditions and referred to as strong (weak) monsoon conditions. We find through the application of an eddy‐tracking algorithm, a spatial and temporal analysis of a variety of factors that impact mixed layer variability, and a heat budget analysis that there is an overall dominance of larger features in strong monsoon conditions and a higher frequency of small features in weak monsoon conditions. Key Points: For the first time, we have investigated the impact of mesoscale features on mixed layer variability in the Arabian SeaThe eddy field in the strong (weak) monsoon seasons favors larger‐mesoscale (smaller‐mesoscale) activityAnticyclonic eddies in the Arabian Sea have larger radii and smaller amplitudes for much of the summer monsoon season [ABSTRACT FROM AUTHOR]

Harvey entered the Gulf of Mexico as a tropical depression on 23 August 2017; two days later it had strengthened to a category 1 hurricane. Over the following 30 hr Harvey rapidly intensified, reaching the Texas Bight as a category 3 storm. This intensification continued while Harvey crossed the shelf, making landfall as a category 4 storm 60 km east of Corpus Christi, TX on 26 August. A hydrographic survey two weeks prior to landfall shows that the tropical cyclone heat potential across the Texas Bight was approximately 35 kJ/cm2, which is 55 kJ/cm2 less than the amount of upper ocean heat normally associated with intensification. Combined with buoy, float, and satellite data, we use hydrographic surveys to study the conditions of the Texas Bight that contributed to Harvey's rapid intensification. We find that, at the time of landfall, the Texas Bight was well mixed with very warm water extending from the surface to bottom. As a consequence, mixing induced by Harvey had a small impact on surface temperatures which remained high and supported continued intensification. The results show that tropical cyclone heat potential is not an effective metric for hurricane intensity prediction in shallow water, and illustrate the need for continuous subsurface monitoring in order to improve hurricane forecasts. Plain Language Summary: Hurricanes rely on heat extracted from the upper ocean as their energy source. When the ocean is warm conditions are more favorable and hurricanes are often stronger. Hurricanes also mix the ocean which brings cold water from greater depth and can lead to intensity reduction. Tropical cyclone heat potential is a measure of heat in the upper ocean which is available as an energy source for hurricanes. In shallow water tropical cyclone heat potential is typically low because there is not as much water to store heat; therefore, hurricanes are not expected to intensify over shallow water. In this paper we show that hurricane Harvey did intensify over the shallow water off the Texas coast despite having low heat potential. Using ocean measurements, we found that the reason was because the ocean was very warm from the surface to the seabed. Therefore, when Harvey mixed the ocean very little cold water was brought up from below and the surface remained warm which allowed Harvey to continue to strengthen. Results suggest that tropical cyclone heat potential is ineffective for estimating hurricane strength in shallow water and demonstrates the importance of knowing subsurface temperatures if we want to improve hurricane forecasts. Key Points: Hurricane Harvey intensified over the shallow water of the Texas Bight despite being a region of low tropical cyclone heat potentialPeak season, warm, well‐mixed shelf water limits sea surface cooling and helps contribute to hurricane intensificationTropical cyclone heat potential has limited usefulness in shallow water; therefore, subsurface ocean observations are essential for increasing the accuracy of hurricane intensity forecasts [ABSTRACT FROM AUTHOR]

Global sea surface salinity (SSS) has been obtained from space since 2009 by the Soil Moisture and Ocean Salinity (SMOS) mission and has been further enhanced by Aquarius in 2011 and Soil Moisture Active‐Passive (SMAP) missions in 2015. Due to the differences between SMOS, Aquarius, and SMAP in the instruments used, retrieval algorithms, and error correction strategies, the quality of their gridded products are different. In this paper, we have assessed the accuracy of three satellite products using in situ gridded data and buoy data. Compared with gridded in situ salinity measurements, the monthly Aquarius data are of the best quality, reaching the mission target accuracy (0.2 PSU) in the open ocean. SMOS and SMAP agree well with in situ data in the open ocean between 40°S and 40°N (root‐mean‐square deviation [RMSD]: SMOS 0.211 PSU, SMAP 0.233 PSU). The RMSD of SMAP is lower than that of SMOS at high latitudes, which may due to the fact that the roughness correction of SMAP is based on the Aquarius geophysical model function. Meanwhile, time series comparison of salinity measured at 1 m by moored buoys indicates that satellite SSS captures variability of SSS at weekly time scales with reasonably good accuracy (RMSD: SMOS 0.25 PSU, SMAP 0.26 PSU), when excluding suspicious buoy data. Synergetic analysis of satellite SSS and Argo data indicates that satellite SSS can be applied as real‐time quality control of buoy 1‐m salinity data. Plain Language Summary: It is important to analyze salinity variations and understand their relationship with the global hydrological cycle and climate changes. The performance of different sea surface salinity products from three salinity satellites is evaluated based on in situ salinity measurements in this study. The results show that the satellite salinity products agree well with in situ data in the open ocean and can be used as real‐time quality control of buoy sea surface salinity data. However, large discrepancies can be found in high latitudes and in the regions along the coast. Key Points: Satellite‐derived sea surface salinity (SSS) products from SMOS, Aquarius, and SMAP are compared with in situ dataAquarius data are of best quality between 40°S–40°N, and the root‐mean‐square deviations of SMOS and SMAP are closeSatellite SSS can be applied as real‐time quality control (QC) of buoy data [ABSTRACT FROM AUTHOR]

Observational data covering currents and temperature through two contrasting autumn to spring periods (2010/2011 and 2013/2014) at the constricted entrance to the inner basin of the Hornsund fjord, Svalbard, are investigated. This fjord is presently undergoing significant changes, manifested by reduction of the seasonal sea ice cover and retreating tidewater glacier fronts. The data set presented here shows how local wind, tides, and longer period current fluctuations allow warm water of Atlantic origin to reach the innermost basin of the fjord. While the forcing factors of the exchange mechanisms are not seen to vary much between the two studied seasons, the effect of wind events on exchange is assumed to be modified by local stratification and sea ice concentration. The resulting heat transport depends on availability of heat in the central part of the fjord. The observations indicate that available heat in autumn and winter 2013/2014 effectively hindered formation of a stable sea ice cover. While the present data set does not enable direct quantification of the role of oceanic heat in tidewater glacier melting, we find that the net retreat of glacier fronts was 10 times larger in the warm (ocean) period 2013/2014 compared to the colder 2010/2011. Plain Language Summary: Many high‐latitude fjords are undergoing rapid changes including warming water, diminishing sea ice cover and retreating tidewater glaciers. This paper documents inflow of warm water into the interior part of Hornsund Fjord, Svalbard, and describes the physical mechanisms that facilitate such inflow. Two contrasting years are presented; one cold year when more sea ice was present and glacier fronts retreated modestly, and a more recent warm year when there was virtually no sea ice and glaciers retreated much more rapidly. Key Points: Local wind, tides, and coastal‐trapped waves facilitate subsurface offshore water crossing the interior sill and entering the innermost fjord basinThe observations indicate that available ocean heat in autumn and winter 2013/2014 effectively hindered formation of a stable sea ice cover [ABSTRACT FROM AUTHOR]

Space‐borne synthetic aperture radar (SAR) measurements have already been proven to be invaluable in detecting and quantifying properties of ocean swell systems. With the improved spatial resolution, Sentinel‐1 wave mode measurements can further be extended toward shorter‐scale waves, that is, within the surface wave equilibrium range. In this study, a new parameter is derived from filtering SAR image cross‐spectra around range‐traveling intermediate wind waves (wavelengths 15–20 m). This parameter captures both the radar cross‐section variability and its time evolution. Given the dependence of intermediate waves on local wind field, this parameter is statistically documented to confirm its sensitivity to both wind speed and wind direction. Comparable to Doppler estimate, the signed parameter can be used to reduce the wind direction ambiguity in the inversion of high‐resolution wind fields from SAR imagery. In addition, under complex environmental situations over a polar low event, this parameter is expected to better capture the dynamics of the surface wind. Globally, our analysis demonstrates regional and seasonal variations of this parameter, associated with those of wind/wave patterns. In particular, its directionality reveals the seasonal migration of intertropical convergence zone. This parameter is valuable to various further applications, for example, to help develop wind retrieval scheme from SAR measurements or to map space‐time variability of ocean waves at various wavelengths. Plain Language Summary: Our paper entitled "A New Ocean SAR Cross‐Spectral Parameter: Definition and Directional Property Using the Global Sentinel‐1 Wave Mode Measurements" defines a new radar parameter to highlight the properties of intermediate scale ocean waves (wavelength of 15 m) based on high‐resolution space‐borne synthetic aperture radar images. This new parameter is found to be a signed quantity, sensitive to both wind speed and direction. At global scale, we use a 1‐year data to demonstrate the distribution and variation of this parameter. It is found that this parameter not only provides directional information of global winds but also exhibits distinct seasonal signatures of regional wind/wave. A case study over a polar low event also proves the capability of our new parameter in carrying surface wind information. Key Points: Estimated spectral properties are signed quantities associated to both wind speed and directionDistinct sensitivity to wind direction can help to retrieve ocean surface wind vector from SAR measurementsGlobal mapping and analysis confirm capabilities to enforce wind and wave climate studies [ABSTRACT FROM AUTHOR]

Many air‐sea interaction processes are quantified in terms of whitecap fraction W because whitecaps are the most visible and direct way of observing breaking waves with air entrainment in the open ocean. Photographs or video images of the sea state collected from towers, ships, and aircrafts have been used over the years to obtain W. Satellite remote sensing of W is a recent development that allows long‐term, consistent observations of whitecapping on a global scale. The method for estimating W uses the variations of ocean surface emissivity at microwave frequencies (6 to 37 GHz) due to presence of sea foam on a rough sea surface. Satellite‐borne microwave radiometers detect these variations at the ocean surface as changes of the brightness temperature TB at the top of the atmosphere. We present the physical and parameterized models, as well as the input data, necessary to calculate W from WindSat TB observations with our W (TB) algorithm. We describe the implementation versions through which the W (TB) algorithm has developed. We show that satellite‐based W data vary with the frequency and polarization of the TB observations. The wind speed dependence of the W retrievals at horizontal and vertical polarizations shows different behavior and compares differently with in situ W data and existing wind speed parameterizations W(U10). We discuss the applicability of our methodology to other radiometric data. We indicate possible modifications and tuning of the models in the W (TB) algorithm that can help to further improve the accuracy of the satellite W retrievals. Plain Language Summary: When out in the open sea, we all fancy the bright, fleeting sea foam capping the waves. In addition to their beauty, these whitecaps also play a critical role in the interaction between the ocean and the atmosphere. Oceanic whitecaps form when waves break and entrain air in the water. The entrained air breaks up into bubbles, which then rise to the surface clustering into patches of sea foam. Whitecaps on the surface and bubbles in the water enhance the exchange of gases and particles across the air‐sea interface. Accurate modeling of these exchange processes is necessary for weather prediction and climate studies. Whitecaps are traditionally measured from photographs of the ocean surface. However, these measurements are difficult and only on a local scale. We developed a method to measure whitecaps from satellites. This method allows observations of oceanic whitecaps, and the processes associated with them, on a global scale. In this paper, we describe the models and the data, which we use to measure whitecaps from satellites. We show how these satellite measurements compare to the traditional photographic measurements of whitecaps. We discuss how this methodology can be improved and applied to sensors on different satellites. Key Points: Passive microwave remote sensing of whitecap fraction is presentedAlgorithm obtaining whitecap fraction from satellite observations is describedSatellite‐based retrievals of whitecap fraction are evaluated [ABSTRACT FROM AUTHOR]

This study presents a method for estimating secondary phytoplankton pigments from satellite ocean color observations. We first compiled a large training data set composed of 12,000 samples; each sample is composed of 10 in situ phytoplankton high‐performance liquid chromatography (HPLC)‐measured pigment concentrations, GlobColour products of chlorophyll‐a concentration, and remote sensing reflectance (Rrs(λ)) data at different wavelengths, in addition to advanced very high resolution radiometer sea surface temperature measurements. The resulting data set regroups a large variety of encountered situations between 1997 and 2014. The nonlinear relationship between the in situ and satellite components was identified using a self‐organizing map, which is a neural network classifier. As a major result, the self‐organizing map enabled reliable estimations of the concentration of chlorophyll‐a and of nine different pigments from satellite observations. A cross‐validation procedure showed that the estimations were robust for all pigments (R2 > 0.75 and an average root‐mean‐square error = 0.016 mg/m3). A consistent association of several phytoplankton pigments indicating phytoplankton group specific dynamic was shown at a global scale. We also showed the uncertainties for the estimation of each pigment. Plain Language Summary: The knowledge of phytoplankton variability is essential to the understanding of the marine ecosystem dynamics and its response to environmental changes. This paper presents a new approach to estimate phytoplankton pigment concentrations from satellite observations by using an artificial neural network, the so‐called self‐organizing map. This neural network was calibrated using a large data set of in situ pigment observations from oceanic cruises along with ocean color satellite data provided by the Globcolour project and advanced very high resolution radiometer sea surface temperature. This approach allows an accurate estimation of phytoplankton pigment concentrations and their related uncertainties. Moreover, the method allows to reproduce the spatio‐temporal variability of pigment concentration and the dynamics of phytoplankton groups. A particular attention is given to the Southern Ocean whose phytoplankton communities are specific. Key Points: The dynamic of phytoplankton communities can be observed while reconstructing accessory pigment variability from ocean color observationsSelf‐organizing maps allow an accurate retrieval of different phytoplankton pigment concentrations from satellite observationsA consistent global approach is established to estimate accessory pigment concentrations along with the uncertainties [ABSTRACT FROM AUTHOR]

This study analyzes sea surface responses to tropical cyclones (TCs), based on sea surface temperature (SST) and ocean surface current (VOS) data from 57 buoy drifters, together with satellite SST and sea surface height anomaly data, associated with nine TCs during the year of 2016 in order to validate the TC‐induced SST cooling (SSTC) parameterization scheme developed in Part 1. Results show that the drifters‐measured SSTs compare favorably to the satellite detected, except near the coastline and at high latitudes, and that SSTCs are negatively correlated with sea surface height anomaly. During TC passage, VOS usually rotate clockwise on the right‐hand side of TC tracks, but their rotating directions cannot be specified on their left‐hand side. After TC passage, most drifters, located on both sides, show clockwise rotation. These results help characterize the responses of SST and VOS to TCs into the following three modes: (i) significant increases in VOS during TC passage, followed by strong SSTC; (ii) decreases or little changes in VOS, followed by SSTC; and (iii) little changes in both VOS and SSTC. All the three response modes are reasonably included in the SSTC parameterization scheme. After optimizing three empirical constants, based on the drifters' data, the scheme's performance is evaluated by comparing the parameterized SSTC to the drifters‐measured SSTs, showing satisfactory results in terms of the starting time, duration, strength, and rate of SSTCs. An error analysis shows a mean value of about 20% of the observed SSTC with a small standard deviation, confirming the effectiveness of the SSTC parameterization scheme. Plain Language Summary: In this study, we examine sea surface responses to the passage of tropical cyclones (TCs), based on observational data taken from ocean buoy drifters, in order to validate the TC‐induced sea surface temperature (SST) cooling parameterization scheme presented in Part I of this series of papers. Results show some interesting features in ocean surface currents during TC passage. These features have been more or less included in our TC‐induced SST cooling theory. An error analysis shows a mean value of about 20% of the observed SST cooling with a small standard deviation, which confirms the effectiveness of the SST cooling parameterization scheme. Key Points: We analyzed sea surface responses to tropical cyclone passage using SST and ocean current data from 57 buoy drifters and satellite dataThree different sea surface responses in terms of the starting time, duration, strength, and rate of SST cooling and ocean currents are foundAll the three response modes are well parameterized by the SST cooling scheme, when verified against the drifters‐measured data [ABSTRACT FROM AUTHOR]

The Kuroshio Extension region is well known for its strong eddy activity. In this paper, using satellite altimetry‐measured sea surface height anomaly data from 1993 to 2012 in an extended Kuroshio Extension region (140–180°E, 25–45°N), we analyze eddy characteristics: eddy size, polarity, lifetime, intensity, trajectory, and spatial and temporal distributions. Using temperature and salinity vertical profiles measured by Argo floats, we examine the eddy impact on vertical stratification. During the 20‐year period, 7,574 eddies are identified (based on following complete eddy trajectories) with a lifetime equal to or longer than 4 weeks. The numbers of cyclonic and anticyclonic eddies are found to be approximately the same. The distribution of eddy sizes peaks at a radius of about 40 km. The radius at the peak is at the same order as the first baroclinic deformation radius or the horizontal shear scale of the Kuroshio flow. The normalized eddy statistical characteristics show that eddies have different characteristics at different stages of their lifetimes. Among eddies with lifetimes longer than 50 weeks, more anticyclonic (cyclonic) eddies are found north (south) of 35°N. In contrast, among eddies with lifetimes shorter than 20 weeks, more cyclonic (anticyclonic) eddies are found north (south) of 35°N. The asymmetric distribution of eddies suggests two different eddy generation mechanisms: (1) the development of meanders in the Kuroshio path leading to the pinch off of eddies with longer lifetime (larger size) and (2) horizontal shear instability (barotropic instability) leading to eddies of shorter life (smaller size). We further apply an eddy‐resolved numerical product to quantitatively investigate the eddy generation mechanisms. Plain Language Summary: We analyze eddy characteristics with 20‐year satellite data and examine the eddy impact on vertical stratification. Besides, through the statistic result, we propose two eddy generation mechanisms: flow horizontal shear‐induced eddy generation and the meander of flow path leading to the eddy generation. And then, we further apply an eddy‐resolved numerical product to quantitatively investigate the eddy generation mechanisms. Key Points: We analyze eddy characteristicsWe examine the eddy impact on vertical stratificationWe discuss two eddy generation mechanisms and apply an eddy‐resolved numerical product to quantitatively analyze eddy generation mechanisms [ABSTRACT FROM AUTHOR]

An overflow of dense cold water from the Faroese Channels across the Wyville Thomson Ridge (WTR) into the Rockall Trough was recorded during the 136th cruise of the RRS James Cook in June 2016. This event happened in the eastern part of the ridge. The remotely operated vehicle ISIS deployed for a collection of coral samples recorded an abrupt drop in temperature at 500‐m depth. Specifically, the water temperature decreased from 8.73 to 6.74 °C and salinity from 35.26 to 35.16. This rapid drop happened over 20 min, with the fastest rate of water temperature decrease of 1.10 °C occurring just over 1 min 50 s. The numerical modeling conducted to reproduce the event has shown that a massive overflow took place in the WTR section, which is close to the Darwin Mounds. The overflow has led to resuspension of bottom sediments; the remotely operated vehicle sampling program in the area of the Darwin Mounds terminated due to low visibility. The numerical experiments have shown that tidally induced overflows over the WTR can occur periodically under spring tidal conditions. The model allowed us to identify two places in the eastern part of the WTR where the tidally driven overflows more realistically can happen. Plain Language Summary: The paper concerns deep water circulation in Northern Atlantic. A rare event of the Faroe‐Shetland Bottom Waters overflow through the Wyville Thomson Ridge to the Darwin Mounds was registered during the 136th cruise of the Royal Research Ship James Cook in June 2016. The overflow was observed in the eastern segment of the Wyville Thomson Ridge. The reason for a spillage of the cold bottom waters from the Faroese Channels over the Wyville Thomson Ridge to the Darwin Mound is discussed in the paper based on the observational data and the results of numerical modeling. The Massachusetts Institute of Technology general circulation model reproduced the baroclinic tidal processes developed in the area. Numerical experiments confirmed a high probability of overflows induced by cross‐channel tidal oscillations during spring tidal conditions. Key Points: Observational evidence of the Faroese Channels Bottom Water into the Darwin Mounds area is reportedThe observed overflow in the eastern part of the Wyville Thomson Ridge is replicated numericallySpring tidal currents across the Faroese Channels are responsible for the overflow [ABSTRACT FROM AUTHOR]

Abstract: This paper uses Lagrangian statistics—absolute dispersion, pair dispersion, and particle forecasting—to compare four eddy‐permitting models of idealized mesoscale ocean dynamics. The baseline model uses scale‐selective biharmonic damping of momentum to keep the velocity field smooth at the grid scale without overly smearing the partially resolved eddies. The second model uses a nonlinear space‐ and time‐varying Leith viscosity to absorb enstrophy near the grid scale without dissipating too much energy. The last two models use a strong biharmonic damping of momentum to keep the velocity field smooth at the grid scale; this dissipates an unrealistically large amount of kinetic energy, and the models add either deterministic or stochastic forcing to reinject this energy at larger scales. These models are called Jansen and Held models after Jansen and Held (2014, https://doi.org/10.1016/j.ocemod.2014.06.002). All four models correctly model the diffusive transport of particles over time scales more than a few weeks, as measured by the Lagrangian absolute dispersion, showing that all models correctly reproduce the large scales of coherent eddies. The Lagrangian relative dispersion (or pair dispersion) is more sensitive to structure at smaller scales in the velocity field. The Leith model has the least‐accurate relative dispersion, while the two Jansen and Held models have the most accurate. In initialized forecast experiments, there is very little difference in performance between the models. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an assessment and comparison of recent mean sea surface (MSS) models. Using a new approach and independent altimeter data sets, we quantify the major improvement of the CNES_CLS15 and the DTU15 models. We observe a reduction in the amplitude of omission errors thanks to the use of new geodetic altimeter data sets (i.e., Cryosat‐2 and Jason‐1 geodetic): they are reduced by a factor of 2 compared with previous generations (CNES_CLS11). We also quantify commission errors resulting from the leakage of residual ocean variability and altimeter noise into the MSS models. For wavelengths shorter than 250 km, the error is of the order of 1–2 cm2, i.e., ∼10% to 20% of the sea level anomaly (SLA) variance. The global error of both 2015 models has similar orders of magnitude and spectral power densities, although the commission errors of the CNES_CLS15 model are about half as large as those of the DTU15 model. Its absolute error is also slightly smaller than for the DTU15 model in coastal regions and at high latitudes. Conversely, the DTU15 model produces smaller omission errors, especially in the open ocean over strong bathymetric features. More importantly, the MSS errors still have a substantial impact on altimetry products for wavelengths ranging from 30 to 100 km: the error explains ∼30% of the global SLA variance, and the error can be 2.5 times higher on uncharted ground tracks (e.g., Sentinel‐3) over rugged bathymetry. [ABSTRACT FROM AUTHOR]

Shortwave penetration (Qpen) through the bottom of the oceanic mixed layer (ML) profoundly affects the thermal structure in the upper ocean and consequently contributes to sea surface temperature (SST) change, which has not been adequately understood under global warming. Here, using ensemble earth system model simulations under a high‐emissions scenario (SSP5‐8.5), we investigate the Qpen change and related effects on some oceanic parameters, which are regionally dependent. It is found that globally averaged Qpen typically increased by 2.49 ± 0.83 W m−2 in the second half of the 21st century, which is comparable to an increase in the net surface heat flux (3.01 ± 0.31 W m−2), corresponding to an increase in SST by 3.07 ± 0.83°C. Although there exist substantial intermodel uncertainties in the projected chlorophyll change, the shoaled ML contributes the most of the increase in Qpen in the global ocean, whereas in the tropical ocean, the reduction in the chlorophyll concentration plays an equivalent role with the mixed layer depth in determining Qpen change. The ML heat budget indicates that the enhanced Qpen leads to surface cooling through a decrease in the surface net surface heat flux. However, the cooling is compensated for by a warming effect from ocean dynamical change due to more shortwave penetration into the subsurface layer, leading to a small net effect on the ML heat budget. It is suggested that the impact of Qpen on the global oceanic ML heat balance needs to be adequately recognized. Plain Language Summary: Understanding the mechanism for ocean warming induced by anthropogenic effects (e.g., global warming) is important to study global climate change. The accumulated heat into the ocean (heat gain) mainly consists of heat fluxes at the air–sea interface absorbed with the oceanic mixed layer (ML). Additionally, a small part of shortwave radiation (∼20 W m−2) can penetrate out of the bottom of the ML and enters the subsurface ocean, which is referred to as Qpen. As Qpen is instantaneously determined by the ML depth and chlorophyll concentration, it also reflects optical characteristics associated with the redistribution of net surface heat flux and biomass. However, the Qpen change characteristics and its climatic effect under anthropogenic warming have not been quantified yet. Here, we found that the globally averaged Qpen typically increased by 2.49 ± 0.83 W m−2 in the second half of the 21st century. Furthermore, the enhanced Qpen leads to less heat absorbed within the ML and consequently contributes to surface cooling. Meanwhile, the enhanced Qpen makes the subsurface gain more heat, which subsequently warms the ML by ocean dynamical change. Therefore, recognizing the role played by the enhanced penetration is essential to understanding the global oceanic ML heat balance. Key Points: Shortwave penetration (Qpen) through the oceanic mixed layer (ML) increases by 2.49 ± 0.83 W m−2 under a warmer climate, which is comparable to the change in surface heat fluxThe shoaling ML dominates the Qpen change, while the decreasing chlorophyll plays an equivalent role with the ML in the tropical oceanIncreasing Qpen contributes to surface cooling through decreasing net surface heat flux, which is compensated for by the dynamical processes [ABSTRACT FROM AUTHOR]

The strong interaction between the Brazil Current and the adjacent shelf is clearly visible in satellite‐derived products (sea surface temperature, salinity, and chlorophyll‐a concentration). Assessments of circulation features and cross‐shelf exchanges from these products are, however, limited to the surface layer. Here we analyze the regional circulation and dynamics using the results of a suite of process‐oriented, high‐resolution numerical experiments. Passive tracers and Lagrangian floats characterize the exchanges between the shelf and the open ocean, identifying regions of high variability, and assessing the contribution of small‐scale eddies to the cross‐shelf mass exchanges. We estimate that 0.2–0.4 Sv of the shelf transport variability between 34°S and 25°S comes from ocean internal variability which represents ∼50%–70% of the total variability. Between 25°S and 21°S, internal ocean variability represents more than 90% of the shelf transport variability. We find that generation of cyclonic eddies is more frequent (>15% of the time) at the shelfbreak bights. The core of these eddies contains fresher, colder, and more nutrient‐rich shelf waters. Maps of satellite chlorophyll‐a concentration suggest that the horizontal and vertical exchanges of mass associated with these eddies are a critical element of the primary production cycle. Plain Language Summary: We use the results of a suite of ocean model experiments to investigate the variability of the shelf circulation off southern Brazil and Uruguay and the exchange between the shelf and the open ocean. Ocean internal variability (e.g., from eddies) represents more than 50% of the total shelf transport variability and reaches values up to 90% in the northern shelf region. Supported by maps of satellite chlorophyll‐a and using model passive tracers and Lagrangian floats, we also find that eddies along the shelfbreak play an important role in the advection of colder, fresher, and more nutrient‐rich shelf water to the open‐ocean. This is particularly significant where the shelfbreak changes its orientation (shelfbreak bights) where cyclonic small‐scale eddies are detected more than 15% of the time. Key Points: The variability of the shelf circulation and cross‐shelf exchanges off Southern Brazil and Uruguay is investigated using model experimentsMore than 50% of the total shelf transport variability is explained by internal ocean variabilityEddies along the shelfbreak play an important role in the advection of colder, fresher, and nutrient‐rich shelf water to the open‐ocean [ABSTRACT FROM AUTHOR]

Oceanic fronts mark the boundary between two water masses and are often sites of complex bio‐physical processes and multi‐trophic level interactions, making them particularly important features in marine ecosystems. As global climate change induces multi‐scale shifts in the driving physical mechanisms of fronts, spatiotemporal tracking of frontal variability can aid in efforts to understand the downstream effects on marine biodiversity and ecosystem structure. Here we focus on fronts within the dynamic northern extent of the California Current System (NCC). We derived mesoscale sea surface temperature (SST) and chlorophyll‐a (chl‐a) fronts across the NCC region from 4‐km MODIS‐Aqua L3 daily fields over 2003–2019. Mesoscale physical (SST) and biological (chl‐a) fronts were often adjacent and coherent in their seasonal and interannual occurrence frequencies, but were spatially decoupled. SST fronts were most frequent and broadly distributed offshore while chl‐a fronts mostly occurred along the continental shelf break, particularly from Vancouver Island to central Oregon. Additionally, we employed a standardized multiple linear regression analysis to quantify the relative influence of local‐ and basin‐scale processes on frontal variability in the NCC. Local wind stress and wind stress curl variability were the most influential drivers of fronts over the shelf, while basin‐scale climate variability (i.e., climate oscillations) significantly drove frontal occurrences along the shelf break and offshore. Given predictions in the intensification of coastal upwelling in systems such as the NCC, our results indicate that oceanic response to climate change driven atmospheric variability will significantly impact the NCC marine ecosystem on the mesoscale. Plain Language Summary: The northern California Current is a complex and dynamic system where ecologically and economically significant fisheries are supported by the upwelling of deep, nutrient‐rich waters that stimulate phytoplankton production in the surface ocean. This primary production ultimately fuels the marine food web and is a key facilitator of carbon export to the deep ocean, especially within water mass boundary regions (i.e., fronts). The driving mechanisms (e.g., wind and climate oscillations), timing, and location of surface fronts can dictate the location, timing, and quality of food available across trophic levels. Therefore, assessing how fronts change through space and time can aid in predicting future shifts in ecosystem functioning and biodiversity driven by global climate change. Our study shows that physical and biological fronts had different spatial patterns in their responses to shifts in the driving physical mechanisms. While individual physical and biological fronts rarely co‐occurred, the frequencies at which they occurred in the northern California Current System were correlated on seasonal and interannual scales. As the ocean responds to global climate change, our study indicates that subsequent shifts in the location of fronts to more offshore regions have major implications for the structure and functioning of the northern California Current ecosystem. Key Points: Mesoscale biological and physical fronts were spatially decoupled, but their occurrences were correlated on seasonal to interannual scalesLocal winds and climatic oscillations are the primary drivers of frontal variability over the shelf and farther offshore, respectivelyClimate change driven spatial shifts in front location toward offshore will likely impact marine ecosystem structure and function [ABSTRACT FROM AUTHOR]

Oceanic primary production (OPP) is crucial for ecosystem services and global carbon cycle. However, sensitivity to geographic and environmental characteristics limits the application of semi‐empirical OPP estimate models, such as the vertically generalized productivity model (VGPM) and its modified version, particularly in coastal regions. In addition, the difficulty in collecting necessary parameters also hampers long‐term OPP estimates. Data‐driven machine learning (ML) methods can automatically capture the relationships between the input parameters and the objective; hence, they may become new methods for global OPP estimates. In this study, the effectiveness of ML methods to estimate OPP and the key attributes influencing ML performance in different regions and seasons are discussed. First, the ML models obtain a lower root mean square error than the VGPM and Eppley‐VGPM. In addition, the random forest (RF) model achieves the best performance among the four selected ML models. The enhancement in the accuracy of OPP estimates based on the RF model is more obvious in coastal regions than in the open ocean. In the four seasons, the RF model obtains better estimates of OPP than the Eppley‐VGPM, especially for summer. Moreover, input attributes, including sea surface temperature (SST), photosynthetic active radiation (PAR), and chlorophyll‐a concentration (Chlor‐a), achieve the best performance. The suitable alternative input attributes are SST/Chlor‐a in the coastal regions, and single Chlor‐a, SST/Chlor‐a, and PAR/Chlor‐a in the open ocean. Except for the SST/PAR/Chlor‐a combination, input with Chlor‐a, that is, SST/Chlor‐a and PAR/Chlor‐a, result a relatively acceptable performance in the four seasons. Plain Language Summary: Oceanic primary production (OPP) is often estimated by traditional semi‐empirical models which are sensitive to geographic and environmental characteristics. In addition, the difficulty in collecting necessary parameters of OPP estimate algorithms also hampers long‐term OPP estimates. With the development of big data techniques, data‐driven methods, such as machine learning (ML), have been increasingly applied in oceanic feature estimates. However, the effectiveness of ML to estimate OPP and the key attributes influencing ML performance are not fully discussed. Hence, in this study, the superiority of ML methods to estimate OPP is presented, especially in coastal regions and in summer. In addition, suitable alternative input attributes for ML methods for different regions and seasons are analyzed when necessary oceanic parameters cannot be acquired simultaneously. Key Points: The effectiveness of machine learning (ML) methods for oceanic primary production estimate in different regions and seasons is analyzedThe influences of input attributes on ML methods for different regions and seasons are analyzedThe corresponding alternative input attributes are determined [ABSTRACT FROM AUTHOR]

Satellite altimetry measurements of sea surface height provide near‐global ocean state observations on sub‐monthly time scales, which are not always utilized by seasonal climate forecasting systems. As early as the mid‐1990s, attempts were made to assimilate altimetry observations to initialize climate models. These experiments demonstrated improved ocean forecasting skill, especially compared to experiments that did not assimilate subsurface ocean temperature information. Nowadays, some operational climate forecasting models utilize altimetry in their assimilation systems, whereas others do not. Here, we assess the impact of altimetry assimilation on seasonal prediction skill of ocean variables in two climate forecasting systems that are from the European Centre for Medium‐Range Weather Forecasts (SEAS5) and the Australian Bureau of Meteorology (ACCESS‐S). We show that assimilating altimetry improves the initialization of subsurface ocean temperatures, as well as seasonal forecasts of monthly variability in upper‐ocean heat content and sea level. Skill improvements are largest in the subtropics, where there are typically less subsurface ocean observations available to initialize the forecasts. In the tropics, there are no noticeable improvements in forecast skill. The positive impact of altimetry assimilation on forecast skill related to the subsurface ocean does not seem to affect predictions of sea surface temperature. Whether this is because current forecasting systems are close to the potential predictability limit for the ocean surface, or perhaps altimetry observations are not fully exploited, remains a question. In summary, we find that utilizing altimetry observations improves the overall global ocean forecasting skill, at least for upper‐ocean heat content and sea level. Plain Language Summary: Sea surface heights have been nearly continuously and globally measured by satellite‐based altimeters for almost 30 years, yet not all climate models utilize these observations during their initialization phases of seasonal forecasting. Since the local sea surface height (SSH), or sea level, is mostly determined by the ocean temperature and salinity‐controlled subsurface density structure, the altimetry measurements contain a vast amount of integrated information about the ocean climate state. Climate forecasting systems are usually most skillful when they start from the most accurate initial conditions, including the state of the ocean density structure. Unfortunately, temperature and salinity observations are sparse in many parts of the world's oceans, which degrades the initialization of models and thus possibly diminishes forecast skill. Here, we quantify the benefits of using altimetry observations to initialize two state‐of‐the‐art climate forecasting systems by verifying seasonal forecasts using observational products of upper‐ocean temperature, sea surface temperature, and SSH. In the experiments that did not use altimetry data assimilation, we find an overall decrease of seasonal forecasting skill for the subsurface temperature and SSH, which is especially pronounced in the global subtropics, although we find no widespread change in skill for sea surface temperature. Thus, for predicting the subsurface ocean, climate forecasting systems may benefit from incorporating altimetry data assimilation into their ocean initial conditions. More work is needed to assess how much of the subsurface skill improvements can potentially affect the surface ocean. Key Points: Assimilating observations of sea surface height improves initialization of subsurface ocean temperatures in climate forecasting systemsBy including altimetry assimilation, monthly forecasts are improved of upper‐ocean heat content and sea levelSea surface temperature is only minimally affected by altimetry assimilation, at least in the seasonal forecasts assessed here [ABSTRACT FROM AUTHOR]

Marine heatwaves in the summertime when temperatures may exceed organisms' thermal thresholds ("warm‐season marine heatwaves (MHWs)") have huge impacts on the health and function of ecosystems like kelp forests and coral reefs. While previous studies showed that MHWs are likely to become more frequent and severe under future climate change, there has been less analysis of the thermal properties of warm‐season MHWs or on the effects of climate model biases on these projections. In this study, we examine CMIP6 model ability to simulate five key thermal properties of warm‐season MHWs, and evaluate the global pattern of future projections for coral reef and kelp systems. The results show that the duration, accumulated heat stress and peak intensity are projected to increase by >60 days, 160°C·day and 1°C, respectively, across most of the ocean by the end of the 21st century. In contrast, the duration of "priming" (a period of sub‐lethal heat stress prior to substantial MHW heat stress) is projected to decrease by >30 days in the tropics, potentially reducing organisms' ability to acclimate to heat stress. The projected increases in MHW duration and accumulated heat stress in some coral reef and kelp forest locations, however, are likely overestimated due to model limitations in simulating surface winds, deep convection and some other processes that influence MHW evolution. The findings point to some possible processes to target in model development and regional biases to be considered when projecting the impacts of MHWs on marine ecosystems. Plain Language Summary: Periods of extremely high ocean temperatures that persist for days to months, known as marine heatwaves (MHWs), can cause the loss of marine life and impact coastal communities and economies. Climate change is expected to drive substantial increases in the length, strength and frequency of MHWs this century. There has been less analysis, however, of the characteristics of individual MHWs, like the rate at which they develop. In this research, we examine how well climate models can simulate these characteristics and the implication for future projections. We find considerable biases in the simulation of some key MHW characteristics in parts of the ocean due to model limitations in capturing physical processes like surface winds along the equator. Most MHW characteristics like duration and total heat stress are projected to increase sharply this century, particularly for coral reefs and kelp forests, although the increases in some regions are likely overestimated due to model biases. Conversely, we project decreases in "priming"—periods of sub‐lethal heat stress that help marine life prepare for heatwaves. These findings identify regional errors to consider when interpreting MHW projections and can help researchers identify areas for improving model performance. Key Points: Examination of three CMIP6 models show considerable regional biases in the thermal properties of warm‐season marine heatwavesUnlike marine heatwave duration and peak intensity, periods of "priming" heat stress that could train ecosystems are projected to declineIn some coral reef and kelp locations, projected increases in marine heatwave duration and accumulated heat stress are likely overestimated [ABSTRACT FROM AUTHOR]

Ocean chlorophyll‐a concentration is a reliable indicator of phytoplankton biomass that plays an important role in controlling the marine ecosystem. Here, we investigated the interannual variations in sea surface chlorophyll‐a concentration (SSC) in the Yellow Sea and underlying mechanisms with 22 yr (1998–2019) of satellite ocean color observations. Results indicated that SSC showed a positive trend (0.039 mg m−3 yr−1 on average) during 1998–2010 and a negative trend (−0.058 mg m−3 yr−1 on average) during 2011–2019. Similar SSC trends occurred in the four seasons. These trends had larger magnitudes in inshore waters than in offshore waters. SSC variations were primarily driven by rainfall and anthropogenic nutrient emissions with a possibly secondary contribution from sea surface temperature (SST). During 1998–2010, increased rainfall and anthropogenic nutrient emissions largely enhanced the terrestrial nutrient inputs into the Bohai Sea and Yellow Sea. Coincidentally, decreased SST might have led to a weakened stratification in summer, favoring upward turbulent diffusion of deeper waters rich in nutrients and chlorophyll‐a. These processes resulted in significant increases of surface nutrient concentrations and SSC. During 2011–2019, the opposite processes occurred to generate decreased SSC. The current study highlights the change of SSC trends in the Yellow Sea in the first two decades of the 21st century and physical processes at work, enriching our understanding of ocean chlorophyll‐a dynamics in the global shelf seas. Plain Language Summary: The Yellow Sea is a shallow marginal sea of the western Pacific Ocean. Combined effects of the complicated hydrodynamic conditions and human activities make the Yellow Sea one of the important marine ecosystems in the world, which contributes greatly to the socioeconomic development of bordering coastal countries, namely China, North Korea and South Korea. Previous studies indicated that increased anthropogenic nutrient emissions have predominantly caused a positive trend in sea surface chlorophyll‐a concentration (which is usually used as a reliable indicator of phytoplankton biomass in the marine ecosystem) in the Yellow Sea. In the current study, based on satellite ocean color observations, we found that sea surface chlorophyll‐a concentration in the Yellow Sea showed a positive trend during 1998–2010 and a negative trend during 2011–2019. These variations were primarily driven by rainfall and anthropogenic nutrient emissions with a possibly secondary contribution from sea surface temperature. The current study highlights the important role of the natural factors (primarily rainfall) in causing the change of sea surface chlorophyll‐a concentration trends in the Yellow Sea in the first two decades of the 21st century. Key Points: Surface chlorophyll‐a concentration in the Yellow Sea had significant interannual variation during 1998–2019Surface chlorophyll‐a concentration showed a positive trend during 1998–2010 and a negative trend during 2011–2019The trends were primarily driven by rainfall and anthropogenic nutrient emissions with a possible contribution from surface temperature [ABSTRACT FROM AUTHOR]

The physical and biogeochemical performance of 16 CMIP5 and 16 CMIP6 Earth System models (ESM) are examined relative to present day (1976–2005) observational data sets for a Ross Sea Region (RSR) containing the Ross Gyre (RG) and the Ross Sea Continental Shelf. A relative ranking scheme using error metrics and published ESM properties (including climate sensitivity parameters and anomalous deep ocean convection statistics) enables identification of a "best" ensemble of models for the RSR. Over the RSR the CMIP6 models are generally found to have improved physical representations compared to the CMIP5 set (based on our metrics for sea ice concentration, sea surface temperature, salinity, and height, and mixed layer depth), but the CMIP5 and CMIP6 biogeochemical representations remain similar. Examination of mean properties for the period 2081 to 2100 for RCP8.5 and SSP585 for CMIP5 and CMIP6, respectively, shows significant surface temperature increases, with significant decreases in sea surface salinity, sea ice concentration, and mixed layer depth across the RSR. Biogeochemically, there are generally small increases in surface values for chlorophyll, integrated primary production, and zooplankton carbon concentrations. The projections also have robust reductions in surface nitrate, phosphate, and silicate across the RSR. For that part of the RG circulation to the east of 180°E—which we refer to as the "inner RG"—significant barotropic transport increases are found by the end of century. Plain Language Summary: Global climate simulation models have been tested to see how well they represent observations of the ocean in a region around Antarctica known as the Ross Sea. Here we are interested in both the physical (temperature, flows etc) and biogeochemical (chlorophyll, nutrients etc) properties of the models compared to the observations. This process allows us to identify the "best" models, or at least to rank them all from "best" to "worst." This then provides us with more confidence about their future predictions, the argument being that models that do well for our present ocean will do better into the future. By the end of the century we find that the predictions show the surface ocean is warmer and fresher than today, with much reduced sea ice, and surface nutrients are depleted but the surface chlorophyll not so. The large scale circulation is also increased. This shows that the Ross Sea is likely to experience significant physical and biological changes over the coming century relative to today's world. Key Points: CMIP models ranked for their representation of the Ross Sea Region marine environment, and a "best" ensemble has been definedEnd of century projections show a warmer, fresher Ross Sea, and reduced sea ice concentration and mixed layer depths compared to present daySurface nutrients reduced by end of century, smaller changes to surface chlorophyll and Net Primary production, with increased Ross Gyre transport [ABSTRACT FROM AUTHOR]

The Strait of Belle Isle (SBI) is an important pathway for water mass exchanges between the Labrador Shelf and the Gulf of St. Lawrence (GSL), particularly for transport toward the GSL. Seasonal and inter‐annual variability of transport in the SBI are examined using 15 years of moored acoustic Doppler current profiler data. Tidal currents are largely along strait and homogeneous with depth. Transports are toward the GSL on average, lowest (−1.0 ± 0.8 dSv) from April to July, and highest (−4.0 ± 1.1 dSv) from September to January. Averaged seasonal transports are usually within one standard deviation of previously published modeled values. The volume of winter Labrador Shelf water (LShW) entering the GSL is computed by transport integration and compares well with integrated volumes that meet LShW temperature‐salinity criteria during an annual March survey of the GSL. Integrating over the whole year showed that on average 649 ± 397 km3 enters the GSL after the March surveys are conducted, independently of the volume that has entered up to March; this addition represents on average about a third of the total volume. Annual volumes of LShW calculated from transport suggest that flow through the SBI accounts for 12%–18% of the GSL winter surface mixed layer. Cross‐strait current shear may affect transport integration values, but sea surface temperature data suggests this bias is limited to the summer. Corrections are empirically derived to account for cross‐strait shear in our transport calculation. The corrected time series suggests that the average transport may be flowing toward the Labrador Shelf in July (0.6 ± 1.0 CI [0.1 1.1] dSv). Plain Language Summary: The Strait of Belle Isle (SBI) is the waterway at the northeastern end of the Gulf of St. Lawrence (GSL) that connects it to the Labrador Shelf, and where water may move in both directions. Despite its importance, there are not many recent measurements of water movement across this strait. This is because the SBI is remote from most routine oceanographic operations, and strong currents, sea ice, and icebergs complicate mooring design and restrict study site selection. Our study presents 15 years of new measurements obtained using contemporary technologies allowing for a better assessment of the contribution of Labrador Shelf waters to the GSL. In the future, they may also contribute to improving ocean models of the Northwest Atlantic. Key Points: A 15‐year Strait of Belle Isle transport time series is calculated from mooring‐based acoustic Doppler current profiler dataTransport is used to estimate Labrador Shelf Water contribution to the Gulf of St. Lawrence winter cold layerCorrecting for cross‐strait shear suggests that dominant July transport is toward the Labrador Shelf [ABSTRACT FROM AUTHOR]

Estimating surface heat fluxes via direct covariance measurements or bulk formulae is observation‐intensive and costly. We present a methodology whereby we estimate net surface heat fluxes as the difference between the depth‐integrated heat tendencies and the depth‐integrated horizontal heat exchanges in a hydrodynamic model. We calibrate the model to achieve a good representation of mixing and advection and then assimilate satellite sea surface temperature (SST) observations into the model at an 8‐day scale. The SST data assimilation forces a good representation of observed temperatures and heat tendencies both at the surface and throughout the water column. We estimate the horizontal heat exchange directly from the model output and then infer the surface fluxes required to close the budget. When we apply this methodology to a model with prescribed surface heat fluxes and without data assimilation, we can recover the prescribed fluxes with an RMS error of ±10 W m−2 and an r2 of 0.998. When we compare our results to those estimated using Coupled Ocean‐Atmosphere Response Experiment bulk formulae with observations in western Long Island Sound, we find similarly good agreement. Plain Language Summary: We use satellite observations of sea surface temperatures in combination with a three‐dimensional simulation of the ocean to infer the air‐sea surface heat fluxes needed to create the observed surface temperatures. We use this methodology to quantify the annual cycle of warming and cooling fluxes in Long Island Sound (LIS). Our surface heat flux estimates compare well with estimates obtained from meteorological measurements in the western LIS. Key Points: We infer net air‐sea heat fluxes by assimilating satellite measurements of sea surface temperatures into a calibrated hydrodynamic modelWe estimate both surface heat fluxes and horizontal exchange fluxesWe describe the annual evolution of the heat budget in Long Island Sound, USA [ABSTRACT FROM AUTHOR]

Numerical experiments were conducted to evaluate the effects of surface heating on coastal upwelling intensity. Offshore transport, isopycnal slope, and the sea surface temperature (SST) difference between coastal and offshore regions, which represent the upwelling intensity, were estimated. Surface heating decreases Ekman transport but increases Ekman pumping by changing air‐sea stability conditions. However, offshore transport does not change significantly with surface heating. Our experimental results revealed that the increase in surface heating decreases the isopycnal slope but increases the SST difference. Both the isopycnal slope and SST difference are closely related to the change in the surface boundary layer (SBL). Strong surface heating thins the surface‐mixed layer, which decreases the vertical eddy viscosity. The decreased vertical eddy viscosity thins the SBL and enhances its offshore velocity. The isopycnal slope weakens because of the thin SBL, while the SST difference becomes stronger because of the enhanced offshore velocity despite the same offshore transport. The present study may be relevant to the change in upwelling systems as the increase in surface heating under future global warming. Plain Language Summary: Coastal upwelling that brings deep cold water to the surface significantly impacts the coastal environment. Hence, it is essential to quantitatively evaluate the coastal upwelling intensity. This study provides deeper insights into the process of how surface heating changes coastal upwelling intensity. Offshore transport, isopycnal slope, and the sea surface temperature (SST) difference between coastal and offshore regions were estimated. The results suggest that the isopycnal slope decreases but the SST difference increases as the surface heating increases, while the offshore transport changes little. These results highlight the importance of the change in upwelling intensity with the increase in surface heating under global warming. Key Points: Surface heating decreases Ekman transport, but increases Ekman pumpingWith surface heating, isopycnal slopes become gentle but sea surface temperature differences between coastal and offshore regions increaseThe increase in the cross‐shore temperature difference due to faster offshore velocity overwhelms the decrease by net surface heat flux [ABSTRACT FROM AUTHOR]

Increasing exposure to coastal flood hazards will potentially induce an enormous socio‐economic toll on vulnerable communities. To accurately characterize the hazard, we must consider both natural water level variability and climate change‐induced sea‐level rise. In this study, we develop a paleo‐proxy‐based reconstruction of coastal flood events over the last 500 yr to capture natural water level variability and superimpose that reconstruction onto expected sea‐level rise to explore interannual and multidecadal variability in plausible future coastal flood risk. We first develop reconstructions of leading principal components (PCs) of sea surface temperature anomalies from 1500 CE onwards, using tree‐ring, coral, and sclerosponge chronology‐based El Niño Southern Oscillation reconstructions as predictors in a wavelet autoregression model. These reconstructions of PCs are then used in a stochastic water level emulator to develop ensemble simulations of hourly still water levels (SWLs) in the San Francisco Bay. The emulator accounts for multiple relevant processes, including monthly mean sea level (MMSL) anomalies, storm surge, and tide, all varying at different timescales. Accounting for natural variability in water levels over 1500–2000 CE increases coastal flood risk beyond that suggested by instrumental records alone. When superimposed on 0.22 m of sea‐level rise (approximately the amount experienced over the previous century), the simulations show that while high tides and large storm surges cause the smaller extreme SWLs, the larger extreme SWLs occur during concurrent high MMSL, high tides, and significant storm surges. Our findings thus highlight the need to consider natural water level variability for coastal adaptation and planning. Plain Language Summary: Increasing exposure to coastal flood hazards will potentially induce an enormous socio‐economic toll on vulnerable communities. To accurately characterize the flood risk, we must consider both natural water level variability and climate change‐induced sea‐level rise. But we need long records of sea level conditions to quantify the natural variability and characterize the associated extreme flood levels. Paleo‐proxies, such as corals, sponges, and tree rings, capture these long‐term conditions during times when modern instrumental records were unavailable. Using this paleo‐proxy‐based data, we have developed 500 yr long simulations of coastal water levels using specialized computer models that account for several climate and weather patterns and estimates of sea surface temperature conditions from 1500 to 2000. We use these long simulations to quantify the natural fluctuations in coastal water levels at annual and decadal time scales. When we consider the full extent of such fluctuations, coastal flood risk increases beyond the current flooding thresholds in San Francisco Bay, our study site. Our findings suggest a strong need to account for natural water level fluctuations in addition to projections of sea‐level rise for any future coastal adaptation planning. Key Points: Paleo‐proxy based reconstructions of hourly coastal water level components are produced using a stochastic water level emulatorConsidering natural variability in water levels over 1500–2000 CE increases coastal flood risk beyond that suggested by instrumental recordsWhen superimposed on sea‐level rise, natural variability in coastal water level can significantly increase extreme coastal water levels [ABSTRACT FROM AUTHOR]

Sea surface temperatures (SSTs) simulated by almost all models in Coupled Model Inter‐comparison Project phase five are consistently colder (∼−1°C to −4°C) than the observation in the northern Arabian Sea (AS) during winter and spring. These biases significantly weaken the seasonal and extended summer monsoon prediction skills and climate change projection's reliability in this region. To understand the relative contribution of diapycnal heat flux (Jh) compared to other terms in the mixed layer (ML) temperature (MLT) budget during these two seasons, we use time series of vertical profiles of microstructure shear measurements collected in the northeastern AS (NEAS) at 18.4°N and 67.4°E during January 10–17, 2019 (W19) and May 7–21, 2019 (S19). It is found that the vertical processes term and net surface heat flux together determine the bulk of MLT tendency during S19 and W19, and the contribution of the horizontal advection and Jh is relatively smaller. The mean value of Jh (∼−2 W m−2) at the base of the ML shows a comparable magnitude during W19 and S19, and the median values of diapycnal diffusivity (Kρ) at the ML base are not significantly different between W19 (∼3.1 × 10−6 m2 s−1) and S19 (∼5.2 × 10−6 m2 s−1). Besides, Kρ and Jh values were estimated using different Kρ‐Richardson number (Ri) based interior ocean parameterization schemes at the ML base in the NEAS overestimated with respect to observation. The alleged role of overestimation of Kρ and Jh in parameterization schemes on model simulation of cold SST bias in the AS is also discussed. Plain Language Summary: Sea surface temperature (SST) in the Arabian Sea (AS) plays a significant role in regulating the Indian summer monsoon. However, the SST simulated by almost all models in Coupled Model Inter‐comparison Project phase five is consistently colder (∼−1°C to −4°C) than observations in the northern AS during winter and spring. In this study, the alleged role of inappropriate representation of diapycnal heat flux at the mixed‐layer base through parameterization scheme in ocean model is investigated using the microstructure data collected during two scientific cruises in the northeastern AS during winter and spring 2019. It is found that the contribution of diapycnal heat flux is negligibly small compared to atmospheric fluxes and vertical processes on the modulation of SST in the northeastern AS during winter and spring. Besides, the present study demonstrated that diapycnal heat flux estimated using different Richardson number‐based interior ocean parameterization schemes at the mixed‐layer base in the northeastern AS shows higher values than observation. These characteristics suggest that parameterized diapycnal heat flux at the mixed‐layer base may also act as a critical process to generate anomalous cold SST bias in the ocean model. Key Points: The importance of diapycnal heat flux compared to other terms in the mixed layer temperature budget in the Arabian Sea is examinedThe contribution of the diapycnal heat flux at the base of the mixed layer is relatively smaller and comparable during winter and springThe diapycnal heat flux estimated by Richardson number‐based interior ocean parameterization schemes shows higher values than observation [ABSTRACT FROM AUTHOR]

The sea surface temperature (SST) is one of the essential parameters needed to understand the climate change in the Arctic. Saildrone, an advanced autonomous surface vehicle, has proven to be a useful tool for providing accurate SST data at high latitudes. Here, data from two Saildrones, deployed in the Arctic in the summer of 2019, are used to investigate the diurnal variability of upper ocean thermal structure. An empirical cool skin effect model with dependence on the wind speed with new coefficients was generated. Several local large diurnal warming events were observed, the amplitudes of warming in the skin layer >5 K, rarely reported in previous studies. Furthermore, the warming signals could persist beyond 1 day. For those cases, it was found surface warm air suppressed the surface turbulent heat loss to maintain the persistence of diurnal warming under low wind conditions. Salinity also plays an important role in the formation of upper ocean density stratification during diurnal warming at high latitudes. A less salty and hence less dense surface layer was likely created by precipitation or melting sea ice, providing favorable conditions for the formation of upper ocean stratification. Comparisons with two prognostic diurnal warming models showed the simulations match reasonably well with Saildrone measurements for moderate wind speeds but exhibit large differences at low winds. Both schemes show significant negative biases in the early morning and late afternoon. It is necessary to improve the model schemes when applied at high latitudes. Plain Language Summary: At high latitudes, satellite remote sensing retrieval of sea surface temperature (SST) is challenging and the number of drifting buoys measuring in situ temperatures for atmospheric correction algorithm refinement and validation is sparser than elsewhere. Two Saildrone cruises in summer 2019, carrying a suite of scientific instruments onboard, can offer both accurate skin SST and subsurface SST measurements in the Pacific sector of Arctic. This study concentrates on those data along with associated atmospheric parameters to demonstrate the characteristics of diurnal variability of temperatures in the upper 2 m of the ocean. That the Arctic is warming much faster than elsewhere as a result of temperature‐dependent feedbacks, emphasizes the need for a better understanding of the thermal structure of the upper Arctic Ocean. Furthermore, comparisons with model simulations reveal that the diurnal warming schemes for high latitudes still need to be improved. Key Points: Using skin and subsurface ocean temperatures from two Saildrones to study the 2 m upper ocean thermal stratifications at high latitudesSeveral diurnal warming events with significantly large amplitudes, some even with long persistence, are documented and discussedModel schemes for diurnal warming applied at high latitudes necessarily need to be improved [ABSTRACT FROM AUTHOR]

Rainfall alters the physical and chemical properties of the surface ocean, and its effect on ocean skin temperature and surface heat fluxes is poorly represented in many air‐sea interaction models. We present radiometric observations of ocean skin temperature, near‐surface (5 cm) temperature from a towed thermistor, and bulk atmospheric and oceanic variables, for 69 rain events observed over the course of 4 months in the Indian Ocean as part of the DYNAMO project. We test a state‐of‐the‐art prognostic model developed by Bellenger et al. (2017, https://doi.org/10.1002/2016JC012429) to predict ocean skin temperature in the presence of rain, and demonstrate a physically motivated modification to the model that improves its performance with increasing rain rate. We characterize the vertical skin‐bulk temperature gradient induced by rain and find that it levels off at high rain rates, suggestive of a transition in skin‐layer physics that has been previously hypothesized in the literature. We also quantify the small bias that will be present in turbulent sensible heat fluxes parameterized from ocean temperature measurements made at typical "bulk" depths during a rain event. Finally, a wind threshold is observed above which the surface ocean remains well‐mixed during a rain event; however, the skin temperature is observed to decrease at all wind speeds in the presence of rain. Plain Language Summary: We measured the change in ocean surface temperature throughout 69 rain events over the course of 4 months in the Indian Ocean, and used these measurements to improve a model of how the surface ocean temperature changes with rainfall. We also found that rain lowers the temperature of the ocean's skin even in the presence of high winds, and that the difference between the ocean skin temperature and the temperature of water 5 m deep approaches a constant value at high rain rates. Key Points: We characterize the response of ocean skin temperature to rain using in situ observations of 69 rain eventsSkin temperature depresses in response to rain at all wind speeds, and the skin‐bulk temperature difference levels off in intense rainWe test a prognostic model for the influence of rain on ocean skin temperature and demonstrate a realistic modification to improve it [ABSTRACT FROM AUTHOR]

Ocean warming around Antarctica has the potential to trigger marine ice‐sheet instabilities. It has been suggested that abrupt and irreversible cold‐to‐warm ocean tipping points may exist, with possible domino effect from ocean to ice‐sheet tipping points. A 1/4° ocean model configuration of the Amundsen Sea sector is used to investigate the existence of ocean tipping points, their drivers, and their potential impact on ice‐shelf basal melting. We apply idealized atmospheric perturbations of either heat, freshwater, or momentum fluxes, and we characterize the key physical processes at play in warm‐to‐cold and cold‐to‐warm climate transitions. Relatively weak perturbations of any of these fluxes are able to switch the Amundsen Sea to an intermittent or permanent cold state, that is, with ocean temperatures close to the surface freezing point and very low ice‐shelf melt rate. The transitions are reversible, that is, canceling the atmospheric perturbation brings the ocean system back to its unperturbed state within a few decades. All the transitions are primarily driven by changes in surface buoyancy fluxes resulting from the freshwater flux perturbation or from modified net sea‐ice production due to either heat flux or sea‐ice advection anomalies. These changes affect the vertical ocean stratification over the continental shelf and thereby the eastward undercurrent at the shelf break, which both impact ice‐shelf melting. As sea‐ice induced deep convection is already quite limited in present‐day conditions, surface buoyancy gain in a warmer climate has relatively little effect on deep ocean properties compared to colder climate conditions. Plain Language Summary: The West Antarctic Ice Sheet is under the threat of a partial collapse, which would induce rapid global sea level rise. This threat is partly related to the thinning of floating ice shelves, and the consequent retreat of the grounding line, which is a self‐sustained ice dynamics process. It is triggered by increased basal melting of the ice shelves, which results from enhanced flow of relatively warm waters onto the continental shelf. It has been suggested that self‐sustained ocean processes may lead to abrupt changes in the flow of warm water into ice‐shelf cavities, which could facilitate the tipping to a marine ice‐sheet instability. Here, we analyze whether such abrupt ocean changes can occur under cold‐to‐warm or warm‐to‐cold transitions in the Amundsen Sea, West Antarctica. We use a regional ocean model with a set of idealized local atmospheric perturbations to characterize the thresholds and reversibility of ocean abrupt changes.We find that the currently warm Amundsen Sea could switch intermittently or permanently to a cold state for relatively weak atmospheric perturbations and could be slightly warmer in the future. All transitions are reversible. The main mechanism involved on decadal scale is related to a change in the surface buoyancy fluxes. Key Points: The currently warm ice‐shelf cavities of the Amundsen sector could become or have been cold for slightly colder climatic conditionsThe transitions are reversible: canceling the atmospheric perturbation brings the ocean back to its unperturbed state within a few decadesAll the transitions are primarily driven, at multi‐decadal scale, by changes in surface buoyancy fluxes over the continental shelf [ABSTRACT FROM AUTHOR]

Although numerous mesoscale eddies are observed in the South China Sea (SCS), a comprehensive study that focuses on periodic eddies has not yet been reported. Periodic eddies are a type of eddies that occur nearly annually in fixed time frames with similar patterns and trajectories. On the basis of in situ and satellite observations, this paper reports a periodic anticyclonic eddy in the western SCS (the Western SCS Anticyclonic Eddy, WAE) and elucidates the underlying processes responsible for its generation and evolution. The WAE is a seasonal phenomenon modulated by the Asian monsoon and basin‐scale circulation. Usually, the WAE generates around 112°E, 14°N in February–March, induced by the cyclonic gyre in the northern SCS associated with the winter monsoon. The WAE occupies the western SCS for 5 months and finally dissipates in July due to the reversal of the monsoon and thus the circulation transition. The WAE shows important interannual variations associated with large‐scale climate variation, and the Niño‐3.4 index could be a potential predictor for its interannual variation. Finally, we summarize 13 periodic eddies in the SCS, including those unreported by previous studies. The period eddies in the SCS exhibit an inverse "L" shape vortex train structure along the western boundary and around the 17°N section, with an anticyclonic "phase" in summer and a cyclonic "phase" in winter. This study provides new knowledge for periodic eddies in the SCS and will benefit targeted observations of periodic eddies. Plain Language Summary: Some mesoscale eddies in the ocean are observed to occur nearly annually, we here call them periodic eddies. Due to high occurrence rates, those periodic eddies have profound impacts on local physics, fishery, biology, and air‐sea interaction. This study first reports a periodic anticyclonic eddy in the western South China Sea from in situ and satellite observations. By eddy reoccurrence rate, we then summarized all periodic eddies in the SCS. These eddies form the mean state of the mesoscale eddy field in the SCS. This study provides new knowledge for periodic eddies in the SCS and it also carries implications for future studies of periodic eddies in other regions. Key Points: A periodic anticyclonic eddy in the western South China Sea was documented by in situ measurementsThere are 13 periodic mesoscale eddies and they form the mean state of the eddy field in the South China SeaThe period eddies in the SCS exhibit an inverse "L" shape vortex train structure in summer and winter [ABSTRACT FROM AUTHOR]

Based on the Argo and multi‐satellite observations, this study investigates the asymmetric response of sea surface salinity (SSS) to two extreme positive and negative Indian Ocean Dipole (IOD) events in the southern tropical Indian Ocean (TIO). During positive IOD events, the easterly wind anomalies trigger zonal freshwater advection along the equator, decreasing SSS, while cold sea surface temperature (SST) depress the convective precipitation in the southeastern TIO (SETIO), increasing the SSS. Contrast SSS anomalies along the equator and in the SETIO show opposite phases during positive and negative IOD events. These SSS anomalies have enhanced in recent years, reaching the strongest in the extreme negative IOD in 2016 and positive IOD in 2019. The case study shows that positive SSS anomalies occurred in the southern TIO during both positive and negative IOD events in 2016 and 2019, suggesting significant asymmetry in SSS. Analysis of the mixed layer salinity budget shows that the local precipitation and the entrainment associated with the upwelling Rossby waves played an essential role in the SSS increase in 2016, while the decreased precipitation and horizontal advection caused by the westward South Equatorial Current contributed to the SSS increase in 2019. Further analyses suggest that SSS response is more sensitive to thermocline shoaling than deepening, and SSS response to precipitation is greater at shallower mixed layer than at deeper ones, which is the main reason for the asymmetric response of the SSS to negative and positive IOD events. Plain Language Summary: Indian Ocean Dipole (IOD) is one of the leading climate modes in the Indian Ocean, which impacts changes in temperature, precipitation, and salinity. This study reveals significant asymmetric responses in SSS during the decay phase of positive and negative IOD events. During the mature phase of positive and negative IOD events, there are opposite changes in sea surface temperature, atmospheric circulation, rainfall, and SSS in the equatorial and southeastern tropical Indian Ocean (SETIO). However, SSS increases in the SETIO during the decay phase of both positive and negative IOD events, revealing an asymmetric feature. This asymmetric structure of SSS anomalies has strengthened recently and reached extremes in the 2016 negative IOD event and the 2019 positive IOD event. The upwelling (downwelling) Rossby waves play an important role in the asymmetric response of SSS anomalies in the southern TIO since the SSS response is more sensitive to thermocline shoaling than deepening, and the shallower mixed layer may imply the SSS response to precipitation anomaly. Key Points: Contrast sea surface salinity (SSS) anomalies occur in the equatorial and southeastern tropical Indian Ocean (TIO) during the mature phases of Indian Ocean Dipole (IOD)SSS anomalies are out of phase during positive and negative IOD events but show an asymmetric change in the southern TIOThe asymmetry is due to different SSS responses to precipitation and thermocline changes associated with the ocean Rossby waves [ABSTRACT FROM AUTHOR]

Filchner‐Ronne Ice Shelf (FRIS) is the world's largest ice shelf by volume. It helps regulate Antarctica's contribution to global sea level rise, and water mass transformations within the sub‐ice‐shelf cavity produce globally important dense water masses. Rates of ice shelf basal melting are relatively low, however, as the production of cold (−1.9°C) and dense High Salinity Shelf Water over the Weddell Sea continental shelf isolates the ice shelf from large‐scale inflow of warm water. Nevertheless, a narrow inflow of relatively warm (−1.4°C) Modified Warm Deep Water (MWDW) that hugs the western flank of Berkner Bank is observed to reach Ronne Ice Front, although the processes governing its circulation and fate remain uncertain. Here we present the first observations taken within the ice shelf cavity along this warm water inflow using the Autosub Long Range autonomous underwater vehicle. We observe a core of MWDW with a south‐westward velocity of 4 cm s−1 that reaches at least 18 km into the sub‐ice cavity. The hydrographic properties are spatially heterogeneous, giving rise to temporal variability that is driven by tidal advection. The highest rates of turbulent dissipation are associated with the warmest MWDW, with the vertical eddy diffusivity reaching 10−4 m2 s−1 where the water column is fully turbulent. Mixing efficiency is close to the canonical value of 0.2. Modeling studies suggest MWDW may become the dominant water mass beneath FRIS in our changing climate, providing strong motivation to understand more fully the dynamics of this MWDW inflow. Plain Language Summary: Filchner‐Ronne Ice Shelf is the largest floating extension of the Antarctic Ice Sheet by volume. The ocean beneath it is cold and dense, and thus little ocean‐driven melting occurs at its base. Climate models predict that a significant shift in ocean circulation within the sub‐ice‐shelf cavity may occur within the coming century, with large‐scale inflows of warm water, highly elevated basal melt rates, and significant consequences for global sea level rise. Understanding the complex ice‐ocean interactions that occur beneath Filchner‐Ronne Ice Shelf is therefore critical. At present, only a single, narrow inflow of warm water is observed along Ronne Ice Front. The processes controlling this warm inflow are poorly understood, and here we present the first observations from the inflow region obtained using the unique autonomous Autosub Long Range underwater vehicle. We observe that the flow of warm water into the cavity extends at least 18 km and is highly patchy in nature, with isolated maxima in ocean temperature that are moved around by the tides. Vertical mixing is strongest where the ocean is warmest, contributing to diffusing and eroding the warm water signature. Many questions remain, motivating further studies with both autonomous and traditional observing platforms. Key Points: First observations with an Autonomous Underwater Vehicle beneath Ronne Ice Shelf, Antarctica, along the Modified Warm Deep Water inflow pathThe inflow velocity averages 4 cm s−1, and the hydrographic properties show strong spatial variability that is subject to tidal advectionTurbulent mixing is elevated for the warmest Modified Warm Deep Water, with eddy diffusivity values reaching 10−4 m2 s−1 [ABSTRACT FROM AUTHOR]

The seasonal Predictability Barrier (PB) of Sea Surface Temperature Anomaly (SSTA) is characterized by a rapid loss of prediction skills at a particular season in dynamic models. Here, the connection between seasonal PB and the inherent nonlinearity of SSTA was investigated using a statistical method known as Sample Entropy (SamEn). When the SamEn value is large, the chaotic degree of SSTA is high. In the Niño 3 and Niño 3.4 regions, the chaotic degree of SSTA was high in the spring; in the Niño 4 region, it was high in the summer. This result was consistent with the known PB occurrence season in these regions. The month when the chaotic degree of SSTA peaked moved westward longitudinally from March to June. This spatial‐temporal variation of the chaotic degree was consistent with that of the low SSTA variance and PB occurrence timing. Specifically, when the variance of SSTA was low, the low‐amplitude background SSTA signal was more dominant than the El Niño/Southern Oscillation (ENSO)‐related signal, the chaotic degree of SSTA was high, and the PB phenomenon occurred. Hence, the results indicated that the background SSTA signal was more chaotic than the ENSO‐related signal and the seasonal PB may result from the inherent low predictability of the chaotic background SSTA signal. Furthermore, the correlation coefficient between SSTA and shortwave flux anomaly showed similar variation along the longitude compared with the chaotic degree, which suggested that the seasonal connection between SSTA and atmospheric forcing may be responsible for the spatial‐temporal variation of the chaotic degree. Plain Language Summary: Accurate predictions of Sea Surface Temperature Anomaly (SSTA) in the tropical Pacific are in high demand. However, dynamic models tend to lose their prediction skills of SSTA during a certain season, which is known as the seasonal Predictability Barrier (PB). Based on a nonlinear statistic method—SamEn, the chaotic degree of SSTA was investigated in the tropical Pacific to explore the nonlinear cause for the seasonal PB. The spatial‐temporal distribution of the chaotic degree was consistent with that of the PB occurrence timing and low‐amplitude background SSTA signal. Specifically, when the low‐amplitude background SSTA signal was dominant in SSTA data, the chaotic degree of SSTA was high, and the PB phenomenon occurred. Hence, this result suggests that the low‐amplitude background SSTA signal is chaotic and the seasonal PB results from the inherent low predictability of this chaotic background SSTA signal. Furthermore, the seasonal connection between SSTA and atmospheric forcing may be responsible for the spatial‐temporal variation of the chaotic degree. Key Points: Sample Entropy method is utilized to study the nonlinearity of the seasonal Predictability Barrier (PB) of Sea Surface Temperature Anomaly (SSTA) in the tropical PacificThe low‐amplitude background SSTA signal, which is more chaotic than the El Niño/Southern Oscillation‐related signal, potentially results in PBThe seasonal connection between SSTA and atmospheric forcing could lead to the spatial‐temporal variation of the chaotic signal [ABSTRACT FROM AUTHOR]

For over two decades, satellite ocean color missions have revealed spatio‐temporal variations in marine chlorophyll. Seasonal cycles and interannual changes of the physical environment drive the nutrient and chlorophyll variations. In order to identify contributions of seasonal and interannual components on chlorophyll, the present study investigates total chlorophyll variance (TCV) of a 24 year records (September 1997 to December 2021) across satellite generations. First‐order contributions of the seasonal cycle in the mid‐latitude (25°–35°) oceans in the Northern and Southern Hemispheres explain 59.5% and 69.9% of TCV, respectively. In contrast, the contribution of seasonal cycle only explain 30.9% in the tropical oceans (20°N–20°S). Both seasonal cycle‐ and climate‐driven variability (26.3%) explain 57.2% on TCV in the tropical oceans. A multiple linear regression model was forced by instantaneous and delayed effects of oceanic memory of eight climate indices based on sea surface temperature anomalies to reconstruct chlorophyll anomalies. Delayed climate effects generally boost the anomaly correlation coefficients (ACC) between the observed and reconstructed chlorophyll timeseries (ACC skills: 0.64 to 0.72 in the Indian Ocean, 0.74 to 0.82 in off‐equatorial Northern Pacific, and 0.58 to 0.71 in the off‐equatorial Southern Pacific). Such delayed climate effects provide a source of predicted chlorophyll ACC (ACC_predic) skills one season ahead in some ocean regions (ACC_predic skill: 0.63 in the overall tropical ocean, 0.67 in the tropical Pacific, and 0.60 in the Indian Ocean). The attribution of chlorophyll variability indicates promising avenues for improving marine ecosystem predictions with Earth system models by incorporating delayed climate effects. Plain Language Summary: Surface ocean color detected by satellites can be used to estimate the photosynthetic pigment chlorophyll used by phytoplankton at the base of ocean food chains. Satellites show that chlorophyll varies in space and time. In this study, we identify chlorophyll time variation as it is influenced by two components: (a) the seasonal cycle, (b) interannual variations. We find that the seasonal cycle dominates chlorophyll variance in the mid latitudes. However, the seasonal cycle explains less than a third of tropical chlorophyll variance. The addition of interannual climate‐driven changes explains over half of tropical chlorophyll variance. We used a statistical model of chlorophyll based on eight different indices of year‐to‐year climate fluctuations in sea surface temperature to further understand the influence of current and past conditions on its variance. Delayed effects of sea surface temperature from prior seasons improve model estimates of chlorophyll in the equatorial Pacific and Indian Oceans. Thus, ocean "memory" of sea surface temperature variability can be a source of substantial skill in tropical chlorophyll predictability for future seasons. Key Points: In the mid‐latitudes, the seasonal cycle (64.7%) and climate variability (9.6%) combine to explain 74.3% of satellite chlorophyll varianceIn the tropics, the seasonal cycle (30.9%) and climate variability (26.3%) combine to explain 57.2% of satellite chlorophyll varianceDelayed climate effects (a season ahead) provide a source of interannual chlorophyll predictability in the tropics (39.7%) [ABSTRACT FROM AUTHOR]

Accurate representation of air‐sea interaction is crucial to numerical prediction of the ocean, weather, and climate. Sea surface temperature (SST) gradients and surface currents in the oceanic mesoscale regime are known to have significant influence on air‐sea fluxes of momentum. Studies based on high‐resolution numerical models and observations reveal that SST gradients and surface currents in the submesoscale regime are much stronger than those in the mesoscale. However, the feedback between the submesoscale processes and the air‐sea turbulent fluxes is not well understood. To quantitatively assess the responses between air‐sea flux of momentum and submesoscale processes, a non‐hydrostatic ocean model is implemented in this study. The inclusion of SST gradients and surface currents in air‐sea bulk fluxes are argued to be significant for modeling accurate wind stress in the submesoscale regime. Taking both into account, this study shows that the linear relationship between wind stress curl/divergence and crosswind/downwind SST gradients existing in the mesoscale regime is not obvious in the submesoscale. Instead, a linear relationship between wind stress curl/divergence and surface current curl/divergence is revealed in the submesoscale. Furthermore, the magnitude of wind stress curl introduced by submesoscale processes is much greater than that presented by mesoscale processes. Another key finding is that tracer subduction and potential vorticity distribution in the submesoscale is susceptible to submesoscale‐modified air‐sea turbulent momentum flux. This study serves as a starting point in investigating the feedbacks between atmospheric and oceanic submesoscale processes. Plain Language Summary: Sea surface temperature (SST) gradients and surface currents can significantly influence air‐sea fluxes of momentum in the mesoscale regime. In the recent decade, high‐resolution numerical models and observations reveal that SST gradients and surface currents in the submesoscale regime (length scale of order 1 km) are much stronger than those in the mesoscale (length scale of order 10–100 km). But the feedback between the submesoscale processes and the air‐sea turbulent fluxes is not well understood. In this study, we quantitatively assessed the responses between the air‐sea flux of momentum and oceanic submesoscale processes and found the impact of including SST gradients and surface currents on air‐sea bulk fluxes is significant for accurately modeling wind stress in the submesoscale regime. We also found the linear relationship between wind stress curl/divergence and crosswind/downwind SST gradients existing in the mesoscale regime is not obvious in the submesoscale. Instead, a linear relationship between wind stress curl/divergence and surface current curl/divergence is found in the submesoscale. Furthermore, the submesoscale wind stress curl is found to be much stronger (of greater magnitude) than previously identified in mesoscale studies. The strong wind stress curl in submesoscale can significantly influence tracer subduction and potential vorticity distribution, which indicates that the wind stress coupling with currents is very important for submesoscale modeling air‐sea interactions and predicting the ocean, weather, and climate. Key Points: Strong reactions of wind stress and the oceanic submesoscale to each other were foundWind stress field is argued to be significantly affected by both submesoscale sea surface temperature gradients and surface currentsSubmesoscale‐modified wind stress has the potential to change the dynamics in the upper ocean by modifying the potential vorticity distribution [ABSTRACT FROM AUTHOR]

Eighteen years (2003–2020) of data on remotely‐sensed ocean color in high northern latitudes show a significant increase (0.56% yr−1) in double blooms of phytoplankton. Starting in 2015 the rate of increase rose to 1.10% yr−1. Double blooms have become especially prevalent in regions north of 50°N in the North Atlantic, Gulf of Alaska and southern Chukchi Sea. Our correlation analysis suggests that double bloom occurrences are dependent on latitude and seasonal changes in both sea surface temperature (SST) and mixed layer depth (MLD), particularly in the subpolar North Pacific (SNP) and polar oceans (65°–75°N), although we cannot attribute the increased double blooms to specific causes. Single blooms indicated by Chlorophyll a (Chl a) dominate in subpolar‐polar waters and occur close to the timing of the Particulate Inorganic Carbon (PIC) peak (i.e., June–August). In the SNP single bloom, Chl a peaks occur earlier than PIC peaks. This interval was shorter during 2016–2020, which is associated with warming anomalies. In the southern part of the Chukchi Sea, however, we found that PIC peaks occur earlier than Chl a peaks, suggesting a potentially different succession pattern between calcifiers and other functional groups. We speculate that in the near future double blooms of phytoplankton will become a prevalent feature in high‐latitude oceans with concurrent changes in the timing of blooms and seasonal phytoplankton succession in the surface ocean due to climate change. Plain Language Summary: The subpolar and polar oceans are characterized by seasonal phytoplankton blooms during spring–summer. Recently a second bloom attributed to climate change and mostly occurring in fall has been observed. Our study of satellite observations across 18 years (2003–2020) shows that double blooms have been increasing in oceans north of 50°N. The increase in double blooms is related to water temperature and mixed layer depth, but this relationship is dependent on seasons, latitudes and ocean basins. We also compared the timing between two satellite‐derived proxies for the abundance of noncalcifying and calcifying phytoplankton communities. In the subpolar North Pacific (50°–65°N) we found the interval between these two blooms was shorter during 2016–2020, a period associated with warming water. In the southern part of the Chukchi Sea (65°–70°N) we found that the first annual blooms are more likely dominated by calcifying phytoplankton (i.e., coccolithophores) followed by a second blooms with a peak of Chlorophyll a concentration. Our results suggest that with ongoing environmental change, double blooms could become a prevalent feature of the subpolar northern oceans and parts of the Arctic Ocean. Key Points: Satellite data show a significant increase in double blooms of phytoplankton north of 50°N, particularly from 2016 to 2020The correlation of double blooms with mixed layer depth and sea surface temperature is dependent on latitude and seasonFrom 2016 to 2020, the interval between peaks of single PIC and Chl a blooms shortened in the subpolar North Pacific Ocean [ABSTRACT FROM AUTHOR]

The spatio‐temporal characteristics of the interannual variability and long‐term trend of the marine heatwaves (MHWs) and related dynamic mechanisms in the western equatorial Indian Ocean (WEIO) are investigated using satellite observations. A prominent MHW hot spot is found in a region of the WEIO (48°E−54°E, 2°S–2°N), with a mean MHWs' intensity, duration, and frequency of 1.54°C, 13.33 days, and 1.97 times, respectively. MHWs in the hot spot region have significant interannual variability after removing the long‐term trend, associated with Indo‐Pacific major climate modes. In 1982/1983, 1983/1984, 1987/1988, 1997/1998, 2006/2007, 2009/2010, 2011/2012, 2012/2013, 2014/2015, 2015/2016, and 2019/2020, the MHWs occurred with longer duration, higher frequency, and more total days. These years correspond to a positive Indian Ocean Dipole, or an El Niño event, or both. The occurrence of MHWs accompanied by anomalous positive sea surface height suggests that oceanic planetary wave processes modulate MHWs in the WEIO. Westward‐propagating downwelling equatorial Rossby waves triggered by anomalous equatorial easterly winds drive the convergence of warm upper‐ocean water and weaken the upwelling of cool subsurface water, which favor anomalously warm sea surface temperature (SST) and the occurrence of MHWs. In addition, the westward‐propagating off‐equatorial downwelling Rossby waves in the southern tropical Indian Ocean also affect MHWs in the WEIO through the propagation and reflection of waves. The annual MHW frequency, duration, and total days in the hot spot region increase up to 1.56 times, 4.95 days, and 31.72 days per decade, respectively, related to the significant increase in mean SST under global warming. Plain Language Summary: Marine heatwaves (MHWs) are anomalous warming events in the ocean that can be disastrous for the global marine ecosystem and lead to local socioeconomic losses. The western equatorial Indian Ocean (WEIO), as the western pole of the Indian Ocean Dipole (IOD) and the upwelling region where the Indian Ocean monsoon prevails, experiences strong MHWs. This study shows the characteristics and dynamic mechanisms of MHWs in the WEIO. The MHWs had a significant interannual variability during 1982–2020, associated with the positive IOD and El Niño events. It was found that oceanic planetary wave processes cause the occurrence of MHWs in the WEIO. Westward‐propagating downwelling equatorial Rossby waves and off‐equatorial downwelling Rossby waves in the southern tropical Indian Ocean increase sea surface temperature in the WEIO by suppressing upwelling and entrainment. Under global warming, increasing frequency, duration, and annual days of MHWs are found in the WEIO. Global warming is consistently one of the main causes of extreme warm events. Understanding the characteristics and mechanisms that drive the occurrence of MHWs in the WEIO is a step toward predicting these extreme events. Key Points: Marine heatwaves in the western equatorial Indian Ocean (WEIO) have significant interannual variability related to the Indo‐Pacific climateMarine heatwaves in the WEIO are mainly driven by westward‐propagating downwelling equatorial Rossby waves and off‐equatorial Rossby wavesThe frequency and duration of marine heatwaves exhibited significant increasing trends in the WEIO from 1982 to 2020 [ABSTRACT FROM AUTHOR]

Observations from two autonomous Wave Gliders and six Lagrangian Surface Wave Instrument Float with Tracking drifters in the northwestern tropical Atlantic during the January–February 2020 NOAA Atlantic Tradewind Ocean‐atmosphere Mesoscale Interaction Campaign (ATOMIC) are used to evaluate the spatial variability of bulk air‐sea heat, moisture, and buoyancy fluxes. Sea surface temperature (SST) gradients up to 0.7°C across 10–100 km frequently persisted for several days. SST gradients were a leading cause of systematic spatial air‐sea sensible heat flux gradients, as variations over 5 Wm−2 across under 20 km were observed. Wind speed gradients played no significant role and air temperature adjustments to SST gradients sometimes acted to reduce spatial flux gradients. Wind speed, air temperature, and air humidity caused high‐frequency spatial and temporal flux variations on both sides of SST gradients. A synthesis of observations demonstrated that fluxes were usually enhanced on the warm SST side of gradients compared to the cold SST side, with variations up to 10 Wm−2 in sensible heat and upward buoyancy fluxes and 50 Wm−2 in latent heat flux. Persistent SST gradients and high‐frequency air temperature variations each contributed up to 5 Wm−2 variability in sensible heat flux. Latent heat flux was instead mostly driven by air humidity variability. Atmospheric gradients may result from convective structures or high‐frequency turbulent fluctuations. Comparisons with 0.05°‐resolution daily satellite SST observations demonstrate that remote sensing observations or lower‐resolution models may not capture the small‐scale spatial ocean variability present in the Atlantic trade wind region. Plain Language Summary: Two autonomously piloted Wave Gliders and six surface current‐following drifters were deployed in the northwestern tropical Atlantic during the January–February 2020 NOAA Atlantic Tradewind Ocean‐atmosphere Mesoscale Interaction Campaign to study how air‐sea interaction varies on small spatial scales. The observations show that sea surface temperature (SST) can vary by up to 0.7°C over tens of kilometers of distance and that these SST fronts often persisted for several days. Larger fluxes of heat, moisture, and buoyancy typically occurred between the atmosphere and the ocean on the warm sides of SST fronts. The spatial variations of air‐sea fluxes across tens of kilometers are important because these small scales are not resolved in many prediction models or satellite‐based products. Thus, this work emphasizes the physics of, and importance of considering, persistent small‐scale gradients in SST and air‐sea fluxes in regional and global analyses. Key Points: Autonomous piloted and Lagrangian drifting platforms measured air‐sea properties and fluxes in the northwestern tropical AtlanticSensible heat, latent heat, and upward buoyancy flux varied by as much as 10, 50, and 10 Wm−2 across 10–100 km sea surface temperature (SST) gradientsSpatial SST gradients were a leading cause of sensible heat flux variability, but humidity fluctuations largely modulated latent heat flux [ABSTRACT FROM AUTHOR]