Interannual Sea Surface Temperature Variability Research Articles

Karadeniz'de 2000-2022 Yılları Arasında Yüzey Sıcaklığının Mekansal ve Zamansal Değişimi

This study presents a comprehensive assessment of the spatio-temporal variability of Sea Surface Temperature (SST) in the Black Sea at monthly to interannual scales, with a focus on understanding its connection to major large-scale atmospheric forcing during the period 2000-2022. Monthly variations of SST in the Black Sea reveal distinct seasonal patterns. The study evaluates the potential impacts of large-scale atmospheric patterns on interannual SST variations using climate indices such as the North Atlantic Oscillation (NAO), East Atlantic/West Russia (EA-WR) and El Niño-Southern Oscillation (ENSO) during the winter months. The results indicated that these large-scale atmospheric oscillations played a substantial role in influencing SST anomalies, with the NAO and EA-WR indices particularly affecting the Black Sea's SST anomalies. The NAO index exhibited negative values during warm winters and positive values during cold winters, with extreme cold and warm winters corresponding to specific years, as observed in 2003, 2006, 2012, 2017 (cold) and 2018, 2020, 2021 (warm). Notably, the relationship between NAO and SST anomalies was not as dominant during 2000-2022. This difference might be explained by the combined influence of NAO and ENSO, which is beyond the scope of this study. The EA-WR pattern was identified as another significant large-scale atmospheric dynamic affecting the Black Sea's SST. Although it explains the cold SST anomalies in certain years, it cannot account for extreme warm SST years. While the influence of ENSO remains somewhat inconclusive for the extreme warm period, the SST pattern between 2016-2022 aligns closely with El Niño events, particularly in 2018 and 2021 when positive SOI index values coincide with warm SST years in the Black Sea.

Future weakening of southeastern tropical Atlantic Ocean interannual sea surface temperature variability in a global climate model

AbstractFuture changes in the southeastern tropical Atlantic interannual sea surface temperature (SST) variability in response to increasing greenhouse gas concentrations are investigated utilizing the global climate model FOCI. In that model, the Coastal Angola Benguela Area (CABA) is among the regions of the tropical Atlantic that exhibits the largest surface warming. Under the worst-case scenario of the Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5), the SST variability in the CABA decreases by about 19% in 2070–2099 relative to 1981–2010 during the model’s peak interannual variability season May–June–July (MJJ). The weakening of the MJJ interannual temperature variability spans the upper 40 m of the ocean along the Angolan and Namibian coasts. The reduction in variability appears to be related to a diminished surface-layer temperature response to thermocline-depth variations, i.e., a weaker thermocline feedback, which is linked to changes in the mean vertical temperature gradient. Despite improvements made by embedding a high-resolution nest in the ocean a significant SST bias remains, which might have implications for the results.

Varying Relationship between La Niña and SST Anomalies in the Kuroshio and Adjacent Regions during Boreal Winter: Role of the East Asian Winter Monsoon

Abstract The winter sea surface temperature (SST) anomalies in the Kuroshio and adjacent regions (KAR), which greatly influence the East Asian–North Pacific–North American climate, are closely related to El Niño–Southern Oscillation (ENSO). This SST relationship between the KAR and the equatorial eastern-central Pacific is widely assumed to be symmetric between El Niño and La Niña. Compared to previous studies indicating the significant and strong KAR warming during El Niño winters, this study indicates weakly negative KAR SST anomalies in the composite analysis for all La Niña events. Positive winter KAR SST anomalies unexpectedly appear in approximately half of La Niña events, which counteract negative SST anomalies in the rest of La Niña events. Further analysis suggests that the impact of La Niña on KAR SST anomalies is modulated by the East Asian winter monsoon (EAWM) during early winter. The weaker-than-normal EAWM offsets the anomalous northeasterly winds in the KAR induced by La Niña and then reinforces the KAR warming through warm oceanic advection. As for strong EAWM, it enhances the northeasterly winds to the west of an anomalous Philippine Sea cyclone associated with La Niña, leading to KAR cooling with more latent heat flux loss from the ocean and anomalous cold oceanic advection. Additionally, when the EAWM is independent of ENSO and is associated with the western Pacific pattern, it also can exhibit a pronounced influence on the KAR SST anomalies via the major processes of surface latent flux and horizontal heat advection in the ocean, accompanied by a change in Kuroshio transport. Significance Statement The interannual variability of SST from Philippine Sea to the Kuroshio and adjacent regions is considered an important forecast factor of the eastern China climate. Previous studies have reported a dipole SST pattern with Philippine Sea cooling and warming in the Kuroshio and adjacent regions during El Niño winter is dominant, and simply regarded that the effect of La Niña on western North Pacific SST anomalies was a mirror image of that of El Niño events. Here, we have found two distinctive SST patterns in the western North Pacific during La Niña winter. One type is the dipole SST pattern, characterized by Philippine Sea warming and by cooling in the Kuroshio and adjacent regions. The other type is the monopole SST pattern with uniform warming expanding from the Philippine Sea to the Kuroshio and adjacent regions. The dipole (monopole) SST pattern in western North Pacific is modulated by La Niña and a strong (weak) EAWM. Analysis shows that the above two SST patterns during La Niña winter are equally important during 1950–2021. This study has identified the influence of the EAWM independent of ENSO on the SST anomalies in the Kuroshio and adjacent regions.

Chasing Interannual Marine Paleovariability

AbstractSeveral modes of tropical sea‐surface temperature (SST) variability operate on year‐to‐year (interannual) timescales and profoundly shape seasonal precipitation patterns across adjacent landmasses. Substantial uncertainty remains in addressing how SST variability will become altered under sustained greenhouse warming. Paleoceanographic estimates of changes in variability under past climatic states have emerged as a powerful method to clarify the sensitivity of interannual variability to climate forcing. Several approaches have been developed to investigate interannual SST variability within and beyond the observational period, primarily using marine calcifiers that afford subannual‐resolution sampling plans. Amongst these approaches, geochemical variations in coral skeletons are particularly attractive for their near‐monthly, continuous sampling resolution, and capacity to focus on SST anomalies after removing an annual cycle calculated over many years (represented as geochemical oscillations). Here we briefly review the paleoceanographic pursuit of interannual variability. We additionally highlight recent research documented by Ong et al., (2022, https://doi.org/10.1029/2022PA004483) who demonstrate the utility of Sr/Ca variations in capturing SST variability using a difficult‐to‐sample meandroid coral species, Colpophyllia natans, which is widespread across the Caribbean region and can be used to generate records spanning multiple centuries.

CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment

The outputs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model for the decadal climate prediction project (DCPP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are described in this paper. The FGOALS-f3-L was initialized through the upgraded, weakly coupled data assimilation scheme, referred to as EnOI-IAU, which assimilates observational anomalies of sea surface temperature (SST) and upper-level (0–1000-m) ocean temperature and salinity profiles into the coupled model. Then, nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year over the period of 1960–2021, based on initial conditions produced by three initialization experiments. The hindcast and forecast experiments follow the experiment designs of the Component-A and Component-B of the DCPP, respectively. The decadal prediction output datasets contain a total of 44 monthly mean atmospheric and oceanic variables. The preliminary evaluation indicates that the hindcast experiments show significant predictive skill for the interannual variations of SST in the north Pacific and multi-year variations of SST in the subtropical Pacific and the southern Indian Ocean.

Tropical coral reefs in Sri Lanka are threatened due to the fluctuation of seasonal and interannual sea surface temperature.

The thermal stress of oceans causes coral bleaching, which induces loss of life in coral reefs and makes them exposed to other threats which directly and indirectly affect millions of other species that inhabit the reef. However, studies focusing on how those thermal stresses affect Sri Lankan fringing reef ecosystems are scarce. Hence, the patterns of long-term and short-term fluctuations of sea surface temperature (SST) over the shallow reefs around the country were studied by separating them into different zones as the eastern coast (Passikudha, Kayankerni, Adukkuparu, Parrot Rock, and Pigeon Island), the southern coast (Beruwala Barbarian, Hikkaduwa, Unawatuna, Ahangama, Mirissa, Madiha, Polhena, and Devundara), and northern-northwestern coasts (Valiththoondal, Palk Bay, Mannar, Kalpitiya, Thalwila, and Uswatakeiyawa). The 1km Multiscale Ultrahigh Resolution (MUR) Level 4 SST dataset was used to analyze seasonal and interannual SST variability from 2005 to 2021. The data were correlated with the Indian Ocean Dipole (IOD), Ekman velocity, and wind stress curl. The annual, seasonal, and monthly variability of SST on different coasts is significantly different. Higher increasing trends of SST from 0.0324 to 0.0411 ℃/year are observed on different coasts, and most of the time higher positive anomalies are recorded after 2014. The First Inter Monsoon (IM-1) and the month of April are more critical since they reach the maximum SST, and the minimum is in the North West Monsoon (NWM) and January. Significant positive relationships are recorded between the Indian Ocean Dipole (IOD) index and the monthly average SST on different coasts, which was robust on the southern coast. Therefore, tropical coral reefs in Sri Lanka are severely threatened due elevation of SST by global warming and climate variability.

The Role of Equatorially Forced Waves in Triggering Benguela Niño/Niña as Investigated by an Energy Flux Diagnosis

AbstractThe Benguela Niño/Niña events manifest the anomalous signals of sea surface temperature (SST) in the coastal region of the tropical Atlantic Ocean. These events are triggered by the interannual modulation of either equatorial waves or local atmospheric forcing. In the present study, the mechanism that equatorial waves induce the coastal SST anomaly is investigated in terms of the transfer episodes of wave energy. The analysis suggests that most of the coastal events can be reproduced by subseasonal wind forcing with an interannual modulation that excites oceanic waves of the first three baroclinic modes. The transfer routes of wave energy illustrate the role of wave dynamics that explains how the interannual variability of SST in the equatorial Atlantic is connected with that in coastal regions. The linearly superposed sign‐indefinite potential energy flux owing to waves manifests its capability of sufficiently displacing the thermocline so as to trigger the coastal events. The results suggest that the equatorial wave signal is able to provide credible predictions for remotely forced Benguela Niño/Niña events if a proper transection in central equatorial Atlantic with an appropriate threshold is selected for observing.

Variations of temperature, salinity and oxygen of the Baltic Sea for the period 1950 to 2020

Variations of temperature, salinity and oxygen of the Baltic Sea on interannual to decadal timescales were studied for the period from 1950 to 2020. Both observational data and the output of a numerical circulation model of the Baltic Sea were analyzed. In addition, we investigated the influence of atmospheric parameters and river runoff on the observed hydrographic variations. Variability of sea surface temperature (SST) closely follows that of air temperature in the Baltic on all timescales examined. Interannual variations of SST are significantly correlated with the North Atlantic Oscillation in most parts of the sea in winter. The entire water column of the Baltic Sea has warmed over the period 1950 to 2020. The trend is strongest in the surface layer, which has warmed by 0.3–0.4°C decade−1, noticeably stronger since the mid-1980s. In the remaining water column, characterized by permanent salinity stratification in the Baltic Sea, warming trends are slightly weaker. A decadal variability is striking in surface salinity, which is highly correlated with river runoff into the Baltic Sea. Long-term trends over the period 1950–2020 show a noticeable freshening of the upper layer in the whole Baltic Sea and a significant salinity increase below the halocline in some regions. A decadal variability was also identified in the deep layer of the Baltic Sea. This can be associated with variations in saltwater import from the North Sea, which in turn are influenced by river runoff: fewer strong saltwater inflows were observed in periods of enhanced river runoff. Furthermore, our results suggest that changes in wind speed have an impact on water exchange with the North Sea. Interannual variations of surface oxygen are strongly anti-correlated with those of SST. Likewise, the positive SST trends are accompanied by a decrease in surface oxygen. In greater depths of the Baltic Sea, oxygen decrease is stronger, which is partly related to the observed increase of the vertical salinity gradient.

Climatological diagnostics and subseasonal‐to‐seasonal predictions of Madden–Julian Oscillation events

AbstractThe Madden–Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability, which serves as a primary source of subseasonal‐to‐seasonal (S2S) predictability. Noticeably, MJO is not always a regularly recurring cycle but is characterized by discrete episodes. In this study, considering the quasi‐consecutive actives and eastward propagating features, a standard metric is proposed to identify MJO events based on the real‐time multivariate MJO (RMM) index. The re‐identification of historical MJO events reveals that there were 5.4 MJO events each year since 1981, and the average duration of each event is about 31.5 days. More MJO events tend to occur in the boreal winter and spring, with stronger intensity, longer duration and faster propagating speed than those in the boreal summer. Furthermore, MJO events are more likely to initiate in Phases 2 and 5, with a longer lifetime than those initiating in other phases. The amplitude and propagation characteristics of MJO events are strongly modulated by the dominant modes of sea surface temperature interannual variability with a strong regional dependence. Based on hindcast datasets of six S2S models, the prediction skill for the MJO is evaluated in the perspective of individual events. The longest leading time of the skilful prediction for individual MJO events ranges from 11 to 17 days, far below the traditional recognition. This result could be attributed to the apparent prediction barrier of MJO initiation, that is, a rapid decrease in prediction skill when predictions are carried out before the initiation of MJO events. In addition, the prediction skills of MJO events depends on interannual variabilities, with relatively higher skills under the conditions of the El Niño and Indian Ocean basin warming. These findings may shed light on the complexity and challenges of profoundly understanding and skilfully predicting MJO events.

Interannual changes of the summer circulation and hydrology in the East China Sea: A modeling study from 1981 to 2015

This study investigated long-term interannual changes in summer circulation and hydrology in the East China Sea (ECS) by performing 35-year high-resolution ocean model simulation from 1981 to 2015. The sea surface temperature (SST) warming trend was considerably weaker in summer than in winter. To the east of the Yangtze Estuary, the interannual variation of SST in summer was mainly dominated by horizontal advection associated with variations in the Taiwan warm current and heat flux in the offshore region north of the Yangtze Estuary. Baroclinic circulation during summer played a crucial role in subsurface mixing. Near the surface, the significant atmospheric wind mode (EOF1) and Kuroshio mode (EOF2) dominate interannual variations in ocean circulation. In the subsurface, local wind around the Tsushima Strait dominated the interannual ocean variation. Anomalous northeasterly winds induced a southwestward pressure gradient due to topographical confinement. These anomalies propagated to the south along the continental shelf through topographic Rossby waves. This study identified two types of anomalous features based on combinations of surface and subsurface EOFs. The combination represents an in-phase contribution between wind and Kuroshio forcings and between the surface and subsurface circulation that enhances the hydrological variability in the ECS. The implication on the relevant biogeochemical and ecological studies in the East China Sea is also very crucial at the interannual time scale.

Marine Heat Waves over Natural and Urban Coastal Environments of South Florida

Marine Heat Wave (MHW) events are increasingly recognized as an important factor in the sustainability of coastal environments (both natural and urban), in the context of climate change. They are related to increasing trends of Sea Surface Temperature (SST) at the adjacent ocean waters. SST is an important parameter of the earth’s climate and increasing SST trends have been associated with adverse effects on coastal ecosystems, with important environmental and socioeconomic implications. This study focuses on the SST interannual variability over the coastal marine environment of South Florida, which contains several fragile ecosystems, and draws associate effects with adjacent large urban coastal settlements. The methodology is based on high-resolution satellite-derived SST data during a 40-year period (1982–2021), augmented by recent high-resolution model simulations (2012–2020). A generally increasing trend has been detected in the observations over the entire region (0.19 °C/decade). The unusual temperature levels have been associated with the formation of extensive MHW events, which showed interannual positive trends (0.75 events/decade) during the 40-year study period. Specifically, the six most recent years (2015–2021) were characterized by the strongest formation of MHWs with a peak in 2015, 2019 and 2020, with more than 8 events/year and approximately 70 to 110 days/year duration in total. The Florida Keys, especially along the Straits of Florida (southern island coasts), revealed very strong increasing trends. Miami Beach is also characterized by strong interannual trends (1.1 events/decade and 10 days/decade) compared to the enclosed basin of Biscayne Bay. In addition to the influence of atmospheric conditions over all regions around South Florida, the formation of MHWs near the eastern Florida coasts was also controlled by ocean dynamics, related to the warm Florida Current (FC). The evolution of the FC close to the eastern coasts (e.g., Miami Beach) was found to be a pre-condition of MHW formation. Several disastrous events on the biotic environment of South Florida near large urban settlements have been related to the formation of MHWs. The detected positive trends, and especially the recent high peaks of MHW events, may enhance the loss of specific heat-sensitive species, damaging the biodiversity of this tropical coastal environment and weakening the natural coastal protection against tropical storms. Urban planning for sustainable development in South Florida’s coastal cities must take into account MHW trends.

Interannual and Decadal Variability of Sea Surface Temperature and Sea Ice Concentration in the Barents Sea

Sea ice loss and accelerated warming in the Barents Sea have recently been one of the main concerns of climate research. In this study, we investigated the trends and possible relationships between sea surface temperature (SST), sea ice concentration (SIC), and local and large-scale atmospheric parameters over the last 39 years (1982 to 2020). We examined the interannual and long-term spatiotemporal variability of SST and SIC by performing an empirical orthogonal function (EOF) analysis. The SST warming rate from 1982 through 2020 was 0.35 ± 0.04 °C/decade and 0.40 ± 0.04 °C/decade in the ice-covered and ice-free regions, respectively. This climate warming had a significant impact on sea-ice conditions in the Barents Sea, such as a strong decline in the SIC (−6.52 ± 0.78%/decade) and a shortening of the sea-ice season by about −26.1 ± 7.5 days/decade, resulting in a 3.4-month longer summer ice-free period over the last 39 years. On the interannual and longer-term scales, the Barents Sea has shown strong coherent spatiotemporal variability in both SST and SIC. The temporal evolution of SST and SIC are strongly correlated, whereas the Atlantic Multidecadal Oscillation (AMO) influences the spatiotemporal variability of SST and SIC. The highest spatial variability (i.e., the center of action of the first EOF mode) of SST was observed over the region bounded by the northern and southern polar fronts, which are influenced by both warm Atlantic and cold Arctic waters. The largest SIC variability was found over the northeastern Barents Sea and over the Storbanken and Olga Basin. The second EOF mode revealed a dipole structure with out-of-phase variability between the ice-covered and ice-free regions for the SST and between the Svalbard and Novaya Zemlya regions for SIC. In order to investigate the processes that generate these patterns, a correlation analysis was applied to a set of oceanic (SST) and atmospheric parameters (air temperature, zonal, and meridional wind components) and climate indices. This analysis showed that SST and SIC are highly correlated with air temperature and meridional winds and with two climate indices (AMO and East Atlantic Pattern (EAP)) on an interannual time scale. The North Atlantic Oscillation (NAO) only correlated with the second EOF mode of SST on a decadal time scale.

Predictability of sea surface temperature anomalies at the eastern pole of the Indian Ocean Dipole—using a convolutional neural network model

In this study, we train a convolutional neural network (CNN) model using a selection of Coupled Model Intercomparison Project (CMIP) phase 5 and 6 models to investigate the predictability of the sea surface temperature (SST) variability off the Sumatra-Java coast in the tropical southeast Indian Ocean, the eastern pole of the Indian Ocean Dipole (IOD). Results show that the CNN model can beat the persistence of the interannual SST variability, such that the eastern IOD (EIOD) SST variability can be forecast up to 6 months in advance. Visualizing the CNN model using a gradient weighted class activation map shows that the strong positive IOD events (cold EIOD SST anomalies) can stem from different processes: internal Indian Ocean dynamics were associated with the 1994 positive IOD, teleconnection from the equatorial Pacific was important in 1997, and cooling off the Australian coast in the southeast Indian Ocean contributed to the 2019 positive IOD. The CNN model overcomes the winter prediction barrier of the IOD, to a large extent due to the frequent transition from a warm state of the Indian Ocean to a negative IOD condition (warm EIOD SST anomalies) over the boreal winter to the following spring period. The forecasting skills of the CNN model are on par with predictions from a coupled seasonal forecasting model (ACCESS-S2), even outperforming this dynamic model in seasons leading to the IOD peaks. The ability of the CNN model to identify key dynamic drivers of the EIOD SST variability suggests that the CMIP models can capture the internal Indian Ocean variability and its teleconnection with the Pacific climate variability.

Interdecadal changes in SST variability drivers in the Senegalese-upwelling: the impact of ENSO

Sea surface temperature (SST) variability in the North Eastern Tropical Atlantic has its center of action in the Senegalese–Mauritanian upwelling system, where its drivers are wind-induced ocean dynamics and air–sea thermodynamic processes. Thus, a better understanding of the local wind variations, together with their predictability, contributes to a more comprehensive assessment of the SST variability in that region. In this study, we use monthly data from two ocean reanalyses, SODA and ORAS-5, and a regional forced-ocean simulation to characterize the interannual SST variability off the Senegalese Coast in the common period 1960–2008. Local indices of the mixed layer heat budget during the major upwelling season (February–March–April) exhibit pronounced interannual to decadal variability. We demonstrate that the local interannual SST variability undergoes inter-decadal fluctuation and concomitant changes in its local and remote drivers. Off-Senegal SST variability was largely controlled by wind-induced Ekman transport during the 1960s–1970s, acting under favorable thermocline and mixed layer conditions. However, from 1980s onwards, the drastically reduced Ekman impact observed on local SSTs is associated with a deeper thermocline. This shift in the effectiveness of the dynamic mechanisms coincides with a more active ENSO teleconnection with upwelling before the 1980s. An extended SODA record reveals that the multidecadal modulator of the ENSO impact on the North-eastern Tropical Atlantic resembles the negative phase of the Atlantic Multidecadal Variability. Our results bring to light the fundamental role played by the global decadal background state in the activation of the drivers and air-sea mechanisms responsible for generating the interannual off-Senegal SST variability.

Long-Term Trends and Interannual Variability of Wind Forcing, Surface Circulation, and Temperature around the Sub-Antarctic Prince Edward Islands

In the Southern Ocean, the sub-Antarctic Prince Edward Islands (PEIs) play a significant ecological role by hosting large populations of seasonally breeding marine mammals and seabirds, which are particularly sensitive to changes in the surrounding ocean environment. In order to better understand climate variability at the PEIs, this study used satellite and reanalysis data to examine the interannual variability and longer-term trends of Sea Surface Temperature (SST), wind forcing, and surface circulation. Long-term trends were mostly weak and statistically insignificant, possibly due to the restricted length of the data products. While seasonal fluctuations accounted for a substantial portion (50–70%) of SST variability, the strongest variance in wind speed, wind stress curl (WSC), and currents occurred at intra-annual time scales. At a period of about 1 year, SST and geostrophic current variability suggested some influence of the Southern Annular Mode, but correlations were weak and insignificant. Similarly, correlations with El Niño Southern Oscillation variability were also weak and mostly insignificant, probably due to strong local and regional modification of SST, wind, and current anomalies. Significant interannual and decadal-scale variability in SST, WSC, and geostrophic currents, strongest at periods of 3–4 and 7–8 years, corresponded with the variability of the Antarctic Circumpolar Wave. At decadal time scales, there was a strong inverse relationship between SST and geostrophic currents and between SST and wind speed. Warmer-than-usual SST between 1990–2001 and 2009–2020 was related to weaker currents and wind, while cooler-than-usual periods during 1982–1990 and 2001–2009 were associated with relatively stronger winds and currents. Positioned directly in the path of passing atmospheric low-pressure systems and the Antarctic Circumpolar Current, the PEIs experience substantial local and regional atmospheric and oceanic variability at shorter temporal scales, which likely mutes longer-term variations that have been observed elsewhere in the Southern Ocean.

Seasonality in the relationship between equatorial-mean heat content and interannual eastern equatorial Atlantic sea surface temperature variability

Interannual sea surface temperature (SST) variations in the tropical Atlantic Ocean lead to anomalous atmospheric circulation and precipitation patterns with important ecological and socioeconomic consequences for the semiarid regions of sub-Saharan Africa and northeast Brazil. This interannual SST variability is characterized by three modes: an Atlantic meridional mode featuring an anomalous cross-equatorial SST gradient that peaks in boreal spring; an Atlantic zonal mode (Atlantic Niño mode) with SST anomalies in the eastern equatorial Atlantic cold tongue region that peaks in boreal summer; and a second zonal mode of variability with eastern equatorial SST anomalies peaking in boreal winter. Here we investigate the extent to which there is any seasonality in the relationship between equatorial warm water recharge and the development of eastern equatorial Atlantic SST anomalies. Seasonally stratified cross-correlation analysis between eastern equatorial Atlantic SST anomalies and equatorial heat content anomalies (evaluated using warm water volume and sea surface height) indicate that while equatorial heat content changes do occasionally play a role in the development of boreal summer Atlantic zonal mode events, they contribute more consistently to Atlantic Niño II, boreal winter events. Event and composite analysis of ocean adjustment with a shallow water model suggest that the warm water volume anomalies originate mainly from the off-equatorial northwestern Atlantic, in agreement with previous studies linking them to anomalous wind stress curl associated with the Atlantic meridional mode.

Sea surface temperature trend analysis by Mann-Kendall test and sen’s slope estimator: a study of the Hai Phong coastal area (Vietnam) for the period 1995-2020

Based on the Mann-Kendall test and Sen’s slope method, this study investigates the monthly, seasonal, and annual sea surface temperature (SST) trends in the coastal area of Hai Phong (West of Tonkin Gulf) based on the measurements at Hon Dau Station from 1995 to 2020. The results show a sea surface warming trend of 0.02°C/year for the period 1995-2020 (significant level α = 0.1) and of 0.093°C/year for the period 2008-2020 (significant level α = 0.05). The monthly SSTs in June and September increased by 0.027°C/year and 0.036°C/year, respectively, for the period 1995-2020, and by 0.080°C/year and 0.047°C/year, respectively, for the period 2008-2020. SST trends in winter, summer, and other months were either different for the two periods or not significant enough. This may be due to the impact of ENSO, which caused interannual SST variability in the Hai Phong coastal with two intrinsic mode functions (IMF) signals a period of ~2 (IMF3) and ~5.2 years cycle (IMF4). A combination of these signals had a maximum correlation of 0.22 with ONI (Oceanic Niño Index) delayed by 8 months. ENSO events took ~8 months to affect SST at Hai Phong coastal area for 1995-2020 and caused a variation of SST within 1.2°C.

Sea Surface Temperature Variability and Marine Heat Waves over the Aegean, Ionian, and Cretan Seas from 2008–2021

The sea surface temperature (SST) is an important factor and indicator of the sea water quality, with various ecological and anthropogenic implications. We used high-resolution satellite-derived SST data, in tandem with field observations and long-term meteorological data, to investigate the spatial and interannual SST variability over the Aegean, Ionian, and Cretan (AIC) Seas during the recent 14-year period (2008–2021). Increasing trends were identified for most of the sub-basins of the AIC Seas. The numbers and durations (days) of the marine heat waves (MHWs) have significantly increased, especially during the last quadrennial period (2018–2021). Changes have been detected in both the maximum and minimum values; however, the trend of the mean annual values is mainly associated with the interannual increases in the lowest values (weaker minima during the cold seasons). The interannual variability and the increasing positive trends of the air temperature are very similar to the SST variations, showing a 5-to-10-day lag between the seasonal time series of the two parameters for all regions; however, extreme atmospheric events (e.g., cold fronts or heat waves) have a more direct impact on the SST variability (zero lag). MHWs were more frequent over the northern Aegean Sea, especially in Thermaikos Gulf, which is characterized as a “hot spot” for MHWs. MHWs were rarer over the southern regions, especially over the southeastern Aegean and Cretan Seas. A stratified upper ocean, controlled by buoyant brackish plumes, such as the Black Sea Waters (BSW) in the northern Aegean, may increase the heat storage capacity of the surface water masses, contributing to the further warming of the ocean. This was the case in the summer of 2021, which was a unique year for the AIC Seas, and especially for the northern Aegean, which revealed the highest SST values among all the study years. The satellite-derived observations of the 2008–2021 period showed increasing trends for all coastal waters, strong trend slopes for most of the coasts of the northern Aegean and central Ionian Seas, and milder trend slopes in the eastern Aegean.

Interaction between the Tropical Atlantic and Pacific Oceans on an Interannual Time Scale

ABSTRACT Based on the fifth-generation reanalysis of the European Centre for Medium-range Weather Forecasts (ECMWF), the Hadley Centre sea surface temperature (SST) data, and the Global Precipitation Climatology Project (GPCP) precipitation data, the interaction between the tropical Atlantic and Pacific Oceans on an interannual time scale is investigated using correlation, regression, and composite analyses, and the quantitative estimates of the relative and collective contribution of the tropical North Atlantic (NTA) and equatorial Atlantic (ETA) SST anomalies to the El Niño–Southern Oscillation (ENSO) are presented. An El Niño or La Niña event can cause a same-sign SST anomaly in the NTA in the following boreal spring, accounting for 33% of the interannual variability of the NTA SST. The NTA SST anomaly may excite a same-sign SST anomaly of the ETA in boreal summer with an ETA SST anomaly of 0.44°C per 1°C NTA SST anomaly. Moreover, an SST anomaly in the NTA and ETA can cause an opposite-sign SST anomaly in the equatorial Pacific during the following winter. The NTA SST anomaly influences the central equatorial Pacific with a Niño 3.4 SST anomaly of −0.85°C per 1°C NTA SST anomaly, while the ETA SST anomaly exerts an impact on the central-eastern equatorial Pacific with a Niño 3.4 SST anomaly of −1.85°C per 1°C ETA SST anomaly based on a multiple regression analysis. The composite analyses based on Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) hindcasts show that the ETA SST anomaly in summer acts as a primary contributor to the interaction between the tropical Atlantic and Pacific Oceans. The ETA impact can relay and amplify the NTA SST anomaly such that it affects the equatorial Pacific. The collective impact of spring NTA and summer ETA SST anomalies can explain 33% of the total variance of the winter Niño 3.4 index. This study deepens our understanding of the interannual interaction between the tropical Atlantic and Pacific Oceans and highlights the role of the tropical Atlantic Ocean, especially the ETA region, in the pan-tropical air–sea interaction.

Remote and Local Processes Controlling Decadal Sea Ice Variability in the Weddell Sea

AbstractSea ice in the Weddell Sea plays important roles in the albedo, air‐sea heat, freshwater, and gas exchanges and the formation of the Antarctic Bottom Water on the continental shelf that regulates global climate through deep thermohaline circulation. Sea ice extent (SIE) in the Weddell Sea does not show any significant trend in the four‐decade satellite observation period but does experience large interannual‐to‐decadal variability. Physical processes underlying this variability are difficult to examine because of a paucity of prolonged observations. Using a coupled general circulation model, we corroborate the observational finding that decadal increases in SIE are preceded by weakening of the mean westerly winds linked to the Southern Annular Mode. Weakening of the westerly winds over the Weddell Sea reduces the northward Ekman current and suppresses upwelling of warm water from the subsurface ocean; this lowers the upper‐ocean temperature, causing an increase in sea ice. In a sensitivity experiment where the interannual sea surface temperature variations are suppressed outside the South Atlantic and the Weddell Sea, decadal increase in the SIE over the Weddell Sea is induced by a decrease in the upper‐ocean temperature owing to enhanced horizontal advection by the Weddell Gyre. The strengthening of the Weddell Gyre increases the upper‐ocean salinity as a result of enhanced evaporation and brine rejection associated with the sea ice increase. These results demonstrate that both the remote atmospheric forcing and local ice‐ocean interaction are crucial for generation of decadal sea ice variability in the Weddell Sea.