Sea Surface Temperature Trends Research Articles

Regional Responses of the Northern Hemisphere Subtropical Jet Stream to Reduced Arctic Sea Ice Extent

The effect of Arctic sea ice loss on the boreal winter regional trends of wind speed and latitudinal position of the Northern Hemisphere subtropical jet stream (STJ) in 1980–2012 is investigated. Two sets of global simulations with reduced Arctic sea ice extent are analyzed: simulations that, south of 70 N, use a climatological annual cycle of the sea surface temperature (SST) and a second set that uses full SST variability. Results with the climatological SST have a significant but weak response of the STJ wind speed and latitudinal position to the warmer Arctic: the wind speed generally decreases and the jet core is displaced equatorward. However, in the realistic SST simulations, the effect of Arctic warming is only slightly evident in a small equatorward shift of the jet over the Atlantic basin. Over the Pacific basin the STJ is mostly driven by tropical and mid-latitude SST variability, with little influence from the Arctic region. A weakening and poleward shift of the STJ that is observed in the realistic SST simulations over the Pacific basin is attributed to negative SST trends in the tropical Pacific and the consequent weakening of the mid-latitude meridional gradient of geopotential height in the upper troposphere.

Persistent Discrepancies between Observed and Modeled Trends in the Tropical Pacific Ocean

Abstract The trends over recent decades in tropical Pacific sea surface and upper ocean temperature are examined in observations-based products, an ocean reanalysis and the latest models from the Coupled Model Intercomparison Project phase six and the Multimodel Large Ensembles Archive. Comparison is made using three metrics of sea surface temperature (SST) trend—the east–west and north–south SST gradients and a pattern correlation for the equatorial region—as well as change in thermocline depth. It is shown that the latest generation of models persist in not reproducing the observations-based SST trends as a response to radiative forcing and that the latter are at the far edge or beyond the range of modeled internal variability. The observed combination of thermocline shoaling and lack of warming in the equatorial cold tongue upwelling region is similarly at the extreme limit of modeled behavior. The persistence over the last century and a half of the observed trend toward an enhanced east–west SST gradient and, in four of five observed gridded datasets, to an enhanced equatorial north–south SST gradient, is also at the limit of model behavior. It is concluded that it is extremely unlikely that the observed trends are consistent with modeled internal variability. Instead, the results support the argument that the observed trends are a response to radiative forcing in which an enhanced east–west SST gradient and thermocline shoaling are key and that the latest generation of climate models continue to be unable to simulate this aspect of climate change.

Detection of mucilage phenomenon in the Sea of Marmara by using multi-scale satellite data

Marine mucilage outbreaks occurred in the Sea of Marmara in 2021 which severely affected the marine ecosystem. The thick mucilage blankets with different colors became a public concern due to the toxicity potential related to pathogens that accumulate in prolonged presence of mucilage. The mucilage-covered areas in the Sea of Marmara detected by remote sensing data acquired in 2021 were previously reported. However, the areal extents and spectral characteristics of the different colored mucilage types remain unknown. This study presents the spectral characteristics of different types of mucilage in the İzmit Bay in the Sea of Marmara by using medium- (Sentinel-2) and high-spatial resolution (Worldview-3) satellite images. Also, the sea surface temperatures (SST) were studied in relation with the mucilage formation from January 2015 to August 2021 by using NOAA data. Two multispectral satellite sensors Sentinel-2 and Worldview-3 were studied for their potential for mucilage mapping and characterization in the sub-region İzmit Bay. Support vector machine (SVM) classifier was used to detect three different types of mucilage with distinguishable spectral differences in infrared region ranging from 725 to 950nm. Three different types of mucilage were characterized based on color and texture including (a) the white mucilage aggregates with dispersed patterns which are likely freshly formed, (b) the yellow mucilage accumulations in the coasts that are wind/current transported, and (c) the brown mucilage accumulations that are probably the most-aged. Our results showed that brown mucilage and white mucilage showed similar reflectance values between 425 and 545nm region, while yellow mucilage showed higher and more distinctive spectral reflectance than white and brown mucilages. The NOAA data showed that average surface water temperature has been increased over the years from 2015 (16.1°C) to 2021 (17.6°C). This increase trend in SSTs points out a likely relation with the mucilage formation and hence may suggest a potential of repeating mucilage events in the near future. This study provides a practical methodology for monitoring, classification, and efficient site selection for mucilage cleaning areas in the Sea of Marmara.

Suggestions for marine protected area management in Australia: a review of temperature trends and management plans

Climate change and related ocean warming have affected marine ecological and socioeconomic systems worldwide. Therefore, it is critically important to assess the performance of conservation mechanisms, particularly marine protected areas (MPAs) to moderate the risks of climate-related impacts. In this study, sea surface temperature trends of Australian Commonwealth MPAs are assessed against climate change management criteria, as defined in Adapting to Climate Change: Guidance for Protected Area Managers and Planners. Monthly sea surface temperature trends between 1993 and 2017 were statistically assessed using the Mann–Kendall trend test and management plans were subject to a thematic analysis. Temperature trends showed variable SST changes among the regions, with the northern reserves all showing statistically significant increases in temperature, and the Southwest Network having the least number of reserves with statistically significant increases in temperature. The thematic analysis shows that management plans address approximately half of the climate change adaptation criteria. Several management strategies, such as dynamic MPAs, replication, and translocations, are currently absent and have been suggested as necessary tools in supporting the climate readiness of Australian MPAs. This study is significant because it helps to identify and synthesize regions most vulnerable to the impacts of ocean warming and provides management suggestions make MPAs “climate ready.”

Prediction of Sea Surface Temperature in the East China Sea Based on LSTM Neural Network

Sea surface temperature (SST) is an important physical factor in the interaction between the ocean and the atmosphere. Accurate monitoring and prediction of the temporal and spatial distribution of SST are of great significance in dealing with climate change, disaster prevention, disaster reduction, and marine ecological protection. This study establishes a prediction model of sea surface temperature for the next five days in the East China Sea using long-term and short-term memory neural networks (LSTM). It investigates the influence of different parameters on prediction accuracy. The sensitivity experiment results show that, based on the same training data, the length of the input data of the LSTM model can improve the model’s prediction performance to a certain extent. However, no obvious positive correlation is observed between the increase in the input data length and the improvement of the model’s prediction accuracy. On the contrary, the LSTM model’s performance decreases with the prediction length increase. Furthermore, the single-point prediction results of the LSTM model for the estuary of the Yangtze River, Kuroshio, and the Pacific Ocean are accurate. In particular, the prediction results of the point in the Pacific Ocean are the most accurate at the selected four points, with an RMSE of 0.0698 °C and an R2 of 99.95%. At the same time, the model in the Pacific region is migrated to the East China Sea. The model was found to have good mobility and can well represent the long-term and seasonal trends of SST in the East China Sea.

2021 Texas cold snap: Manifestation of natural variability and a recent warming trend

In this paper, we demonstrate that the extreme cold snap in Texas in February 2021 resulted from a large-scale background circulation anomaly over the North Pacific and North America that was a manifestation of both natural variability (namely, a negative Pacific–North American pattern, PNA) and a warming trend that began in the late 1990s. Numerical experiments revealed that the negative PNA pattern could be driven by negative (La Niña-like) sea surface temperature (SST) anomalies in the equatorial eastern Pacific on an interannual–decadal timescale and the SST warming trend in the subtropical North Atlantic on a longer timescale. We propose that the excitation of the most unstable mode of the Northern Hemisphere winter, which exhibits a combined negative PNA and positive East Atlantic pattern resulting from SST anomalies and trends, leads to the dominance of the large-scale circulation anomaly observed in February 2021 and over the last few decades.Our study demonstrated the key role of extratropical wave activity and the intrinsic mode in causing the extreme cold in North America. The arguments favoring polar or tropical influences may partially explain the source of variability, considering that extratropical weather and climate variability could be modulated by not only polar or tropical perturbations but also the enhanced tropical–extratropical interaction and mid-latitude instability. A systematic approach involving both empirical diagnostics and a suite of carefully designed numerical experiments is required to determine the relative influence of various sources of variability.Regarding future changes, models of the Coupled Model Intercomparison Project Phase 6 project a weakening, rather than an enhancement, of the negative PNA pattern that favors the occurrence of cold snaps despite failing to simulate the observed enhanced trend since the late 1990s.

Local ocean–atmosphere interaction in Indian summer monsoon multi-decadal variability

The significant multi-decadal mode (MDM) of the Indian summer monsoon rainfall (ISMR) during the past two millennia provides a basis for decadal predictability of the ISMR and has a strong association with the North-Atlantic (NA) variability with the Atlantic Multi-decadal Oscillation (AMO) as a potential external driver. It is also known that the annual cycles and interannual variability of ISMR and sea surface temperatures (SST) over the tropical Indian Ocean (IO) are strongly coupled. However, the role of local air–sea interactions in maintaining or modifying the ISMR MDM remains unknown. A related puzzle we identify is that the IO SST has an increasing trend during two opposite phases of the ISMR MDM, namely during an increasing phase of ISMR (1901–1957) as well as a decreasing phase of ISMR (1958–2007). Here, using a twentieth-century reanalysis (20CR), we examine the role of air-sea interactions in maintaining two opposite phases of the ISMR MDM and unravel that the Bjerknes feedback is at the heart of maintaining the ISMR MDM but cannot explain the increasing trend of SST in the tropical IO during the opposite phases. Large-scale low-level vorticity influence on SST and net heat flux changes through circulation and cloudiness changes associated with the two phases of the ISMR MDM together contribute to the SST trends. The decreasing trend of low-level wind convergence during the period between 1958 and 2007 is a determining factor for the decreasing trend of ISMR in the backdrop of an increasing trend of atmospheric moisture content. Consistent with the lead of the AMO with respect to ISMR by about a decade, the AMO drives the transition from one phase of ISMR MDM to another by changing its phase first and setting up low-level equatorial zonal winds conducive for the transition.

Unprecedented early-summer heat stress and forecast of coral bleaching on the Great Barrier Reef, 2021-2022.

The Great Barrier Reef (GBR) is predicted to undergo its sixth mass coral bleaching event during the Southern Hemisphere summer of 2021-2022. Coral bleaching-level heat stress over the GBR is forecast to start earlier than any previous year in the satellite record (1985-present). The National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW) near real-time satellite-based heat stress products were used to investigate early-summer sea surface temperature (SST) and heat stress conditionson the GBR during late 2021. As of 14 December 2021, values of instantaneous heat stress (Coral Bleaching HotSpots) and accumulated heat stress over a 12-week running window (Degree Heating Weeks) on the GBR were unprecedented in the satellite record. Further, 89% of GBR satellite reef pixels for this date in 2021 had a positive seven-day SST trend of greater than 0.2 degrees Celsius/week. Background temperatures (the minimum temperature over the previous 29 days) were alarmingly high, with 87% of GBR reef pixels on 14 December 2021 being greater than the maximum SST over that same 29-day period for any year from 1985-2020. The GBR is starting the 2021-2022 summer season with more accumulated heat than ever before, which could have disastrous consequences for the health, recovery, and future of this critical reef system.

CMIP6 model simulation of concurrent continental warming holes in Eurasia and North America since 1990 and their relation to the Indo-Pacific SST warming

Observations during 1990–2014 depict concurrent cooling trends in land surface air temperature (LSAT) over central-eastern Eurasia (CEE) and northwestern North America (NWNA), while significant warming trends are observed in other areas across the Northern Hemisphere (NH). This lack of surface warming of the continental CEE and NWNA is termed continental warming holes (CWH) here. The ability of the 6th phase of the Coupled Model Intercomparison Project (CMIP6) to reproduce the LSAT trends during 1990–2014 over the continental NH is evaluated, and the evaluation includes all CMIP6 historical simulations from 32 unique models and their multi-model ensemble mean (MMEM). The results show that the performances of the different models vary greatly. GISS-E2–1-G-CC model performs best among the 32 models, considering reproducing the correct sign of the LSAT trends as well as reproducing the trend magnitude. However, the MMEM simulates uniformly significant warming trends in NH and fails to capture the continental warming holes, indicating a role of internal variability in the CWH. The mechanisms of the continental warming holes are further investigated using reanalysis datasets, CMIP6 models and AGCM simulations. GISS-E2–1-G-CC also shows a better simulation ability, including the trends in NH sea level pressure and tropical sea surface temperature than other models. Both reanalysis data and GISS-E2–1-G-CC model show high-pressure trends over mid-high latitudes, which corresponded to enhanced Siberia High and weakened Aleutian Low. These atmospheric circulation changes result in cold advection over the CEE and NWNA regions, offsetting anthropogenic warming and leading to the emergence of the warming holes. Further analysis and AGCM simulations link these atmospheric circulation trends to Indo-Pacific SST warming. In response to the Indo-Pacific SST warming, tropical tropospheric warming leads to the equatorward shift of the mid-latitude jet stream, and subsequently, anomalous easterly and high pressure over mid-high latitudes tend to influence the Siberia High and Aleutian low, resulting in the LSAT cooling over the CEE and NWNA.

Unprecedented early-summer heat stress and forecast of coral bleaching on the Great Barrier Reef, 2021-2022

The Great Barrier Reef (GBR) is predicted to undergo its sixth mass coral bleaching event during the Southern Hemisphere summer of 2021-2022. Coral bleaching-level heat stress over the GBR is forecast to start earlier than any previous year in the satellite record (1985-present). The National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW) near real-time satellite-based heat stress products were used to investigate early-summer sea surface temperature (SST) and heat stress conditionson the GBR during late 2021. As of 14 December 2021, values of instantaneous heat stress (Coral Bleaching HotSpots) and accumulated heat stress over a 12-week running window (Degree Heating Weeks) on the GBR were unprecedented in the satellite record. Further, 89% of GBR satellite reef pixels for this date in 2021 had a positive seven-day SST trend of greater than 0.2 degrees Celsius/week. Background temperatures (the minimum temperature over the previous 29 days) were alarmingly high, with 87% of GBR reef pixels on 14 December 2021 being greater than the maximum SST over that same 29-day period for any year from 1985-2020. The GBR is starting the 2021-2022 summer season with more accumulated heat than ever before, which could have disastrous consequences for the health, recovery, and future of this critical reef system.

Sea Surface Temperature Variability and Marine Heatwaves in the Black Sea

Marine heatwaves (MHWs) have recently been at the forefront of climate research due to their devastating impacts on the marine environment. In this study, we have evaluated the spatiotemporal variability and trends of sea surface temperature (SST) and MHWs in the Black Sea. Furthermore, we investigated the relationship between the El Niño–Southern Oscillation (ENSO) and MHW frequency. This is the first attempt to investigate MHWs and their characteristics in the Black Sea using high-resolution remote-sensing daily satellite SST data (0.05° × 0.05°) from 1982 to 2020. The results showed that the spatial average of the SST warming rate over the entire basin was about 0.65 ± 0.07 °C/decade. Empirical orthogonal function (EOF) analysis revealed that SST in the Black Sea exhibited inter-annual spatiotemporal coherent variability. The maximum spatial SST variability was discovered in the central Black Sea, whereas the lowest variability was in the Batumi and Caucasus anti-cyclonic eddies in the eastern Black Sea. The highest SST temporal variability was found in 1994. More than two-thirds of all MHW events were recorded in the last decade (2010–2020). The highest annual MHW durations were reported in 1994 and 2020. The highest MHW frequency was detected in 2018 (7 waves). Over the whole study period (1982–2020), a statistically significant increase in annual MHW frequency and duration was detected, with trends of 1.4 ± 0.3 waves/decade and 2.8 ± 1.3 days/decade, respectively. A high number of MHW events coincided with El Niño (e.g., 1996, 1999, 2007, 2010, 2018, and 2020). A strong correlation (R = 0.90) was observed between the annual mean SST and the annual MHW frequency, indicating that more MHWs can be expected in the Black Sea, with serious consequences for the marine ecosystem.

Global warming and decadal trends of sea surface temperature in Hurghada, Red Sea, Egypt

Global warming and decadal trends of sea surface temperature in Hurghada, Red Sea, Egypt

Sea Surface Temperature (SST) and Rainfall Trends in the Singapore Strait from 2002 to 2019

Studying Singapore Strait waters condition as a form of maritime mitigation is necessary because it is an international shipping lane. The dominant weather changes include rainfall, wind flows, and sea surface temperature (SST). This study aims to reveal the relationship between rainfall and SST activity in the Singapore Strait for over 18 years, from 2002 to 2019. The results showed a negative correlation, where the SST decreases as rainfall increases and vice versa. In addition, the high rainfall and low SST distribution occur in the Western season (December–February). The low rainfall intensity and high (warm) SST distribution occur yearly in the transition from West to East (March–August). Also, the distribution pattern is influenced by rainfall intensity and the water mass from the South China Sea and the Malacca Strait, where the strait is a mixture of these masses. The neural network model confirmed the negative correlation. Hence a small change in SST causes rainfall if it is cooler, and less precipitation if warmer.

Extreme value distributions describe interannual variability in the seasonal North Atlantic phytoplankton bloom

AbstractThe North Atlantic phytoplankton bloom depends on a confluence of environmental factors that drive transient periods of exponential phytoplankton growth and interannual variability in bloom magnitude. I analyze interannual bloom variability in the North Atlantic via extreme value theory where the generalized extreme value distribution (GEVD) is fitted spatially to annual maxima of satellite‐measured surface chlorophyll. I find excellent agreement between the observed distribution of interannual bloom maxima and those predicted from the GEVD. The spatial distribution of fitted GEVD parameters closely follows basin bathymetry where the largest extremes and heaviest distribution tails are found on the continental shelves and slopes. Trend analyses suggest weak evidence for changes in GEVD parameters, despite regional trends in mean chlorophyll levels and sea surface temperature. These results provide a framework to quantify interannual bloom variability and call for further work examining how extreme blooms propagate through food webs and contribute to carbon export.

Extreme Atlantic hurricane seasons made twice as likely by ocean warming

Abstract. Tropical cyclones are among the most damaging extreme weather events. An increase in Atlantic tropical cyclone activity has been observed, but attribution to global warming remains challenging due to large inter-annual variability and modeling challenges. Here we show that the increase in Atlantic tropical cyclone activity since the 1980s can be robustly ascribed to variations in atmospheric circulation as well as sea surface temperature (SST) increase. Based on a novel weather-pattern-based statistical model, we find that the forced warming trend in Atlantic SSTs over the 1982–2020 period has doubled the probability of extremely active tropical cyclone seasons. For the year 2020, our results suggest that such an exceptionally intense season might have been made twice as likely by ocean surface warming. In our statistical model, seasonal atmospheric circulation remains the dominant factor explaining the inter-annual variability and the occurrence of very active seasons. However, our study underscores the importance of rising SSTs that lead to more extreme outcomes in terms of cyclone intensity for the same seasonal atmospheric patterns. Our findings provide a new perspective on the contribution of ocean warming to the increase in recent hurricane activity and illustrate how anthropogenic climate change has contributed to a decisive increase in Atlantic tropical cyclone season activity over the observational period.

Paleoclimate Records of the Middle Okinawa Trough Since the Middle Holocene: Modulation of the Low-Latitude Climate

The ubiquity of glycerol dibiphytanyl glycerol tetraethers (GDGTs) and their temperature sensitivity make them one of the most effective tools for paleoclimate reconstruction. High- and low-latitude climates influence the Okinawa Trough (OT). It receives diverse inputs from the East China Sea, the western Pacific, and the Kuroshio Current, providing good conditions for paleoclimate studies. Here, isoprenoid GDGTs (isoGDGTs), branched GDGTs, and hydroxylated GDGTs (OH-GDGTs) were studied to reconstruct the sea surface temperature (SST) of the central OT for the past 8.2 kyr using the tetraether index of 86 carbon atoms at low latitudes (TEXH86) and the ring index of OH-GDGTs (RI-OH). The GDGT-0/crenarchaeol ratios ranged from 0.39 to 0.98. The branched and isoprenoid tetraether index and the methane index values were lower than 0.1 and 0.5, respectively, indicating that the isoGDGTs were mainly derived from marine Thaumarchaeota and that TEXH86 could be used to reconstruct the paleotemperatures. The TEXH86 SSTs ranged from 21.6 to 27.2°C during 8.2 kyr. The overall range of TEXH86 SSTs is close to the UK’37 SST of the middle OT and reflects the mean annual SST. In contrast, RI-OH temperatures varied from 17.4 to 26.0°C, showing a lower trend than TEXH86 SSTs. The core top RI-OH temperature is 24.1°C, in line with the mean annual seawater temperature at 40 m (24.2°C) in the study area, which likely reflects the subsurface temperature in this case. The small overall warming trend of TEXH86 SSTs agrees with the increasing intensity of the Kuroshio Current during the last 8.2 kyr, indicating that the SST evolution is governed by the Kuroshio Current that transports heat from the western tropical Pacific. The decreasing temperature differences between TEXH86 and RI-OH and between UK’37 and RI-OH showed increased mixing of the upper water column, which was in good accordance with the increasing low-latitude winter insolation decoupling from the East Asian summer monsoon. The cold event that occurred at 7.4–6.6 kyr was magnified (∼5°C) at the TEXH86 and RI-OH temperatures and possibly caused by tephra’s significant input (∼7.3 kyr).

Satellite-Observed Chlorophyll-a Concentration Variability in the East Sea (Japan Sea): Seasonal Cycle, Long-Term Trend, and Response to Climate Index

In this study, to determine the spatiotemporal variability of satellite-observed chlorophyll-a(Chl-a) concentrations in the East Sea (Japan Sea, EJS), monthly composite images were generated via noise processing using Level-2 MODIS Chl-adata from 2003 to 2020. Harmonic analysis was performed on time-series Chl-adata to present the spatial distribution of seasonal and intraseasonal variability with 1–4 cycles per year. In the EJS, seasonal cycles contributed less than approximately 30% to the total variance in Chl-avariability, indicating the existence of dominant interannual variability. Analysis of the temporal trend in Chl-aconcentrations showed that they increased (< 0.06 mg m–3yr–1) in most of the EJS over almost two decades (2003–2020). In recent years, in the areas showing positive trends in Chl-a, it tended to increase with time, especially in the northern part of the EJS. As a result of examining the trend associated with the physical environment that affects the long-term trend in Chl-aconcentrations, sea surface temperature (SST) trends were mostly increased. The wind speeds showed a characteristic strengthening trend in the northeastern part of the EJS and the North Korean coast. Long-term changes in wind direction indicated strengthening of the northerly wind components on the Russian coast and the westerly components on the eastern coast of the Korean Peninsula. These wind changes were closely related to the Arctic Oscillation (AO) index variability in relation to the recent warming of the Arctic Ocean. When the AO index was greater than 1, the wind speed tended to be weakened and the SSTs showed a tendency to increase. This led to general increasing responses in Chl-aconcentrations during positive AO. The summer SST anomaly revealed an inverse relationship between higher positive values during the La Niña period and lower ones during the El Niño period. When the amplitude of MEI (Multi-variate ENSO Index) was high (| MEI| > 1), the SST anomaly indicated an inverse correlation with the Chl-aconcentration anomaly in the EJS. This study demonstrated the regional effects of climate change on Chl-avariability in the EJS in response to tropical–subtropical and arctic–subarctic interactions between ocean and atmospheric variations.

Prediction Challenges From Errors in Tropical Pacific Sea Surface Temperature Trends

Models in the North American Multi-Model Ensemble (NMME) predict sea surface temperature (SST) trends in the central and eastern equatorial Pacific Ocean which are more positive than those observed over the period 1982–2020. These trend errors are accompanied by linear trends in the squared error of SST forecasts whose sign is determined by the mean model bias (cold equatorial bias is linked to negative trends in squared error and vice versa). The reason for this behavior is that the overly positive trend reduces the bias of models that are too cold and increases the bias of models that are too warm. The excessive positive SST trends in the models are also linked with overly positive trends in tropical precipitation anomalies. Larger (smaller) SST trend errors are associated with lower (higher) skill in predicting precipitation anomalies over the central Pacific Ocean. Errors in the linear SST trend do not explain a large percentage of variability in precipitation anomaly errors, but do account for large errors in amplitude. The predictions toward a too warm and wet tropical Pacific, especially since 2000, are strongly correlated with an increase in El Niño false alarms. These results may be relevant for interpreting the behavior of uninitialized CMIP5/6 models, which project SST trends that resemble the NMME trend errors.

Marine Heatwaves Characteristics in the Barents Sea Based on High Resolution Satellite Data (1982–2020)

Marine heatwaves (MHWs) can potentially alter ocean ecosystems with far-reaching ecological and socio-economic consequences. This study investigates the spatiotemporal evolution of the main MHW characteristics in the Barents Sea using high-resolution (0.25° × 0.25°) daily Sea Surface Temperature (SST) data from 1982 to 2020. The results reveal that the Barents Sea has experienced accelerated warming and several more MHWs in recent decades. Since 2004, an amplified increasing SST trend was observed across the entire Barents Sea, with a spatially averaged SST trend of 0.25 ± 0.18°C/decade and 0.58 ± 0.21°C/decade for the northern and southern Barents Sea, respectively. The annual mean MHW frequency, days, and duration over the entire Barents Sea increased by, respectively, 62, 73, and 31% from the pre- to the post-2004 period. More than half of all MHW days occurred in the last decade (2011–2020). The most intense MHW event occurred in summer 2016, which was also the warmest year during the study period. In general, the annual mean MHW frequency was relatively high in the northern Barents Sea, while the intensity and duration were higher in the southern Barents Sea. The highest annual MHW intensity and duration were observed in 2016, 2013, and 2020, respectively, while the highest annual MHW frequency was found in 2016. For the entire Barents Sea, the annual MHW frequency and duration increased significantly (p < 0.05) over the whole study period, with a trend of, respectively, 1.0 ± 0.4 events/decade, which is a doubling of the global average, and 2.4 ± 1.3 days/decade. In terms of the influence of climate variability on MHW characteristics, our findings revealed that the Eastern Atlantic Pattern (EAP) plays a significant role in controlling MHW characteristics, whereas the North Atlantic Oscillation (NAO) has no significant relationship. Sea ice concentrations were found to have a significant negative correlation with MHW characteristics. Strong positive correlations were observed between SST, surface air temperature, and MHW frequency, implying that as global warming continues, we can expect continued rising in MHW frequencies and days in the Barents Sea with huge implications for the ocean ecosystem.

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.