Average Sea Surface Temperature Research Articles

Predicting the Fishery Ground of Jumbo Flying Squid (Dosidicus gigas) off Peru by Extracting Features of the Ocean Environment

We introduce a novel method that combines satellite data, advanced clustering techniques, machine learning feature extraction, and statistical models to enhance fishery forecasting accuracy. Focusing on jumbo flying squid in the southeast Pacific Ocean near Peru, we utilize MODIS-Aqua and MODIS-Terra satellite data on sea surface temperature (SST) to construct a deep convolutional embedded clustering (DCEC) model and extract the monthly SST features (FM) based on an optimized number of clusters determined by the Davies–Bouldi index (DBI). We use the extracted FM to construct a series of Generalized Additive Models (GAM) to forecast the catch per unit effort (CPUE) of jumbo flying squid within a spatial resolution of 0.5° × 0.5°. Our results demonstrate the following findings: (1) The SST feature clusters obtained through the DCEC model could capture the SST monthly variations; (2) The GAM models with FM outperform the models with the traditional monthly average SST in terms of predictive accuracy; (3) Using both FM and average SST together can further improve model performance. This study demonstrates the effectiveness of the DCEC combined with DBI in extracting marine environmental features and highlights the ocean environment feature extraction method to enhance the precision and reliability of fishery forecasting models.

Moisture sources and pathways during an extreme rainfall event over South Korea and the role of sea surface temperature anomalies in the Yellow Sea and East China Sea

AbstractOn August 8th, 2022, an extreme rainfall event (the 88ER) occurred over South Korea's metropolitan area and resulted in immense losses of human lives and properties. Previous study has attributed the rainfall event to the intersection of warm and cold air induced by a Northeast China Cold Vortex (NCCV) and the persistently northward displacement of the West Pacific Subtropical High (WPSH). However, in addition to dynamic drivers, understanding the moisture transport of the 88ER is likewise crucial for developing effective strategies to prevent rainstorm disasters. In this study, based on the output from a WRF model, the primary moisture sources and transport pathways of the 88ER are investigated in a Lagrangian view. The Yellow Sea and East China Sea (YSECS) are identified as the most significant moisture source region (84.42%), followed by South Korea (KR), the eastern China (EC) and Democratic People's Republic of Korea (DPRK), which contribute 12.52%, 1.52% and 1.43% of the released moisture, respectively. Furthermore, to assess the sensitivity of moisture fluxes and heavy rainfall to the sea surface temperature (SST) anomalies in the YSECS, an additional WRF model experiment is conducted in which the SST anomalies are replaced by the average SST over the past 30 years. It is found that the SST anomalies in the YSECS cause differences in atmospheric circulation, and therefore exert a strong influence on moisture transport. The SST anomalies finally enhance the moisture contribution of the YSECS by 1.72%, but decrease that over KR, EC and DPRK by 1.03%, 0.35% and 0.33%, respectively.

A Cold Lid on a Warm Ocean: Indian Ocean Surface Rain Layers and Their Feedbacks to the Atmosphere

AbstractOcean surface rain layers (RLs) form when relatively colder, fresher, less dense rain water stably stratifies the upper ocean. RLs cool sea surface temperature (SST) by confining surface evaporative cooling to a thin near‐surface layer, and generate sharp SST gradients between the cool RL and the surrounding ocean. In this study, ocean‐atmosphere coupled simulations of the November 2011 Madden‐Julian Oscillation (MJO) event are conducted with and without RLs to evaluate two pathways for RLs to influence the atmosphere. The first, termed the “SST gradient effect,” arises from the hydrostatic adjustment of the boundary layer to RL‐enhanced SST gradients. The second, termed the “SST effect,” arises from RL‐induced SST reductions impeding the development of deep atmospheric convection. RLs are found to sharpen SST gradients throughout the MJO suppressed and suppressed‐to‐enhanced convection transition phases, but their effect on convection is only detected during the MJO suppressed phase when RL‐induced SST gradients enhance low‐level convergence/divergence and broaden the atmospheric vertical velocity probability distribution below 5 km. The SST effect is more evident than the SST gradient effect during the MJO transition phase, as RLs reduce domain average SST by 0.03 K and narrow vertical velocity distribution, thus delaying onset of deep convection. A delayed SST effect is also identified, wherein frequent RLs during the MJO transition phase isolate accumulated subsurface ocean heat from the atmosphere. The arrival of strong winds at the onset of the MJO active phase erodes RLs and releases subsurface ocean heat to the atmosphere, supporting the development of deep convection.

MODEL OF ECONOMIC DECARBONIZATION IN THE CONTEXT OF CLIMATE CHANGE: ISSUES OF MANAGEMENT AND INNOVATION

The issues of the influence of human economic activity on natural conditions are analyzed. Record parameters for climate change on the planet have been noted in recent years: 2023 is recognized as the warmest year, according to global temperature observations, since 1850. It shows that 2023 was 0.60°C warmer than the 1991-2020 average and 1.48°C warmer than pre-industrial levels 1850-1900. An analysis of data from authoritative international climate organizations also showed that the global average sea surface temperature in 2023 remained persistently and unusually high. To achieve climate neutrality in the global economy, a comprehensive development model has been proposed, which combines the management of the formation of environmental thinking among the general public, the creation of environmental energy capacities and its rational use in the context of decarbonization.

Environmental drivers of persistent humpback whale Megaptera novaeangliae feeding events in a Mexican breeding area

Humpback whales Megaptera novaeangliae typically fast for several months in low-latitude breeding areas. Here we report on persistent feeding events during 5 wintering seasons between 2013 and 2020 in a known upwelling region of Banderas Bay of the mainland Mexico breeding area. In total, there were 76 unique feeding events documented (group size = 1 to ~100 individuals), involving 201 photo-identified whales, of which 18 were documented feeding in multiple years. The most prolific years of documented feeding in 2017 and 2018 (based on number of reports/individuals photo-identified feeding) followed the strongest marine heatwave ever recorded in the North Pacific. Whales documented feeding in Banderas Bay had significantly shorter mean sighting histories (2.3 yr) than a non-feeding sample (8.7 yr) and were reported to be of small size, suggesting they were predominantly younger whales. Most high-latitude recaptures of Banderas Bay feeding whales were in more northern North Pacific feeding grounds (50.8% were resighted in Russia, Alaska, and northern British Colombia, Canada). A binomial general linear model revealed a significant relationship between the probability of whales feeding in Banderas Bay and sea surface temperature (SST). Specifically, feeding consistently occurred in years of lower than average winter SST (<25°C), associated with La Niña years of the El Niño Southern Oscillation (ENSO). We conclude that feeding of humpback whales is now a predictable occurrence in the upwelling region of Banderas Bay in years that ENSO fluctuations lead to lower regional SST. The magnitude of several years of low-latitude feeding events reported here was likely influenced by climate change induced marine heatwaves that occurred during the study period.

The Rising Concern for Sea Level Rise: Altimeter Record and Geo-Engineering Debate

The Oceans from Space V Symposium, held in Venice, Italy, on 24–27 October 2022, devoted special sessions to sea level rise, as described by a series of satellite altimeters, and to remediations of consequent calamities in vulnerable mediterranean seas. It emerged that various aspects of climate change can be modelled in time as a Single Exponential Event (SEE), with a similar trend (a 54–year e–folding time) for CO2 concentration in the Earth’s atmosphere, global average sea surface temperature, and global average sea level. The sea level rise record, combining tide gauges data starting in 1850, as well as more recent altimeter data, for the last 30 years, is already 25 cm above historical values. If the curve continues to follow the exponential growth of the simple SEE model, it will reach about 40 cm by the year 2050, 1 m by 2100, and 2.5 m by 2150. As a result, dramatic impacts would be expected for most coastal areas in the next century. Decisive remediations, based on geo-engineering at the basin scale, are possible for semi-enclosed seas, such as the Mediterranean and Black Seas. Damming the Strait of Gibraltar would provide an alternative to the conclusion that coastal sites such as the City of Venice are inevitably doomed.

Thermal bleaching in the northern South China Sea: impact of abnormal environment and climate on high-latitude coral reefs.

Extensive coral bleaching events can result in catastrophic degradation of coral reefs and reorganization of coral communities. In the present study, we analyzed the spatial differences in coral bleaching and possible reasons of large-scale coral bleaching, based on the results of a survey carried out in the northern South China Sea in 2020. In addition, we have continuously monitored the sea surface temperature (SST) of the northernmost Weizhou Island for more than six years. The living coral cover at Weizhou Island (W), Xuwen Nature Reserve (X), and Haihua Island (H) was relatively high at 24.6% ± 4.8%, 12.1% ± 3.8%, and 8.1% ± 2.6%, respectively, whereas their bleaching rates were 9.7% ± 2.6%, 9.7% ± 3.3%, and 6.9% ± 2.1%, respectively. Among them, the living coral cover of W was significantly different from those of X and H, whereas the bleaching rate was not significantly different among the three areas. In all three areas, the massive and encrusting corals predominate and exhibit relatively high bleaching rates, with Porites lutea and Bernardpora stutchburyi being the dominant species. In addition, the temperature monitoring results of Weizhou Island for six consecutive years showed that the critical SST of coral bleaching was 31.5 ℃. The monitoring results also showed that the average SST of Weizhou Island was 32.1 ℃, exceeding 32 ℃ in July 2020 for up to 533h. The longest continuous time when the SST exceeded 32 ℃ was 97h. These findings indicated that the coral bleaching event that occurred in the Beibu Gulf during 2020 was a large-scale and high-temperature transient event that presented a relatively homogeneous threat to the coral communities. We inferred that this sudden heat stress event was caused by the enclosed tidal current in the Beibu Gulf, which prevented the southern upwelling from reaching the north, as well as by the inability of the SST to decrease without rainfall caused by typhoon cyclones. Our findings suggested that abnormal heat waves can result in coral bleaching at high latitudes and even coral reef degradation. Furthermore, our study provides a new perspective for investigating the self-recovery and reorganization of coral communities following accumulated coral bleaching.

The Gulf Stream Front Amplifies Large-Scale SST Feedback to the Atmosphere in North Atlantic Winter

The Gulf Stream (GS) ocean front releases intense moisture and heat to the atmosphere and regulates storm tracks and zonal jets in winter. The large-scale sea surface temperature (SST) anomaly in the central North Atlantic provides important feedback to the atmosphere in winter, but the role played in this feedback by the GS front inside the SST anomaly has not been extensively studied. In this study, two sets of ensemble experiments were conducted using a global community atmosphere model forced by SST in boreal winters from 2000 to 2013. The regional averaged SST and its variation in the experiments were identical, with the only difference being the strength of the SST front in the GS region. The large-scale SST anomaly in the central North Atlantic in our model provides feedback to the atmosphere and excites a wave train that extends across Eurasia. With the inclusion of the strong GS front, the first center of the wave train in the North Atlantic is strengthened by approximately 40%, and the wave activity flux toward downstream is highly intensified. When the large-scale SST anomaly is combined with a strong GS front, greatly increased water vapor is released from the GS region, resulting in a 50% increase in moisture transport toward Western Europe. In this scenario, precipitation and diabatic heating both increase greatly on the western Scandinavian Peninsula. With the release of deep diabatic heating, a strong upward wave activity flux is triggered, and the wave train excited by the large-scale SST variation is significantly intensified. These findings suggest that the strong SST front in the large-scale SST anomaly in the central North Atlantic significantly amplifies its feedback to the atmosphere in winter.

Tropical Cyclone-Induced Sea Surface Temperature Responses in the Northern Indian Ocean

Tropical cyclones (TCs) exert a significant influence on the upper ocean, leading to sea surface temperature (SST) changes on a global scale. However, TC-induced SST responses exhibit considerable variability in the northern Indian Ocean (NIO), and the general understanding of these responses remains limited. This paper investigates the SST changes caused by 96 TCs over an 18-year period in the NIO. Through a composite analysis utilizing satellite SST data, a comprehensive study is conducted to examine the relationship between TC characteristics, including wind speed and translation speed, and the associated SST changes. The overall findings reveal that within a radius of 300 km from the TC center, SST decreases were observed at 1702 (86%) locations, with an average SST response to TC of −0.46 °C and a maximum decrease of −2.07 °C. The most significant reduction in SST typically occurred two days after the passage of TCs, followed by a gradual recovery period exceeding 15 days for the SSTs to return to their initial values. Consistent with findings in other ocean basins, stronger and slower-moving TCs induced more substantial cooling effects. Conversely, at 279 (14%) locations, particularly associated with TCs of weaker intensities, SST increases were observed following the TC passage. Notably, 140 of these locations were situated at low latitudes, specifically between 8° N and 15° N. This study provides a quantitative analysis of the comprehensive SST response to TCs in the NIO.

Evaluating robustness of harvest control rules to climate-driven variability in Pacific sardine recruitment

Climate-driven changes in ocean temperatures, currents, or plankton dynamics may disrupt pelagic forage fish recruitment. Being responsive to such impacts enables fisheries management to ensure continued sustainable harvest of forage species. We conducted a management strategy evaluation to assess the robustness of current and alternative Pacific sardine harvest control rules under a variety of recruitment scenarios representing potential projections of future climate conditions in the California Current. The current environmentally informed control rule modifies the harvest rate for the northern sardine subpopulation based on average sea surface temperatures measured during California Cooperative Oceanic Fisheries Investigations field cruises. This rule prioritizes catch at intermediate biomass levels but may increase variability in catch and closure frequency compared to alternative control rules, especially if recruitment is unrelated to ocean temperatures. Fishing at maximum sustainable yield and using dynamically estimated reference points reduced the frequency of biomass falling below 150 000 mt by up to 17%, while using survey index-based biomass estimates resulted in a 14% higher risk of delayed fishery closure during stock declines than when using assessment-based estimates.

Deriving fine-scale patterns of sea surface temperature in coral reef habitats using the Landsat 8 thermal infrared sensor

The available sea surface temperature (SST) products are too coarse to assess the fine-scale (<1 km) SST variations related to coral bleaching. In this study, we proposed an optimal SST inversion model using Landsat 8 thermal infrared sensor (TIRS) images to derive fine-scale SST patterns in the coral reef habitats of the Xisha Islands, South China Sea. Our study included two parts: 1) six SST inversion models were developed using the radiative transfer method and the split window (SW) algorithm in the hot season and cool season, from which the optimal SST inversion model was determined; and 2) the optimal model was applied to 47 Landsat 8 TIRS images to derive the SST spatial and temporal pattern among the geomorphic zones of six reefs in hot and cool season conditions. Compared with the measured sea temperature data and the verified MODIS SST products, the SST6 model using the SW algorithm was optimal, with an RMSE of approximately 0.64°C in the hot season. The average SST results usually had a pattern of reef flat > lagoon > reef slope/offshore sea. The reef flat was usually approximately 0.05°C–0.2°C hotter than the lagoon in the hot season. The SST in the lagoon also increased from south to north and the shallow lagoon was usually warmer than the deep lagoon in the hot season. Our results suggested that scleractinian corals in the reef flat and the lagoon were more susceptible to bleaching-level thermal stress than other geomorphic zones. During the cool season, the SST fluctuated markedly among coral reefs and geomorphic zones.

Tissue-specific transcriptional response of post-larval clownfish to ocean warming

Anthropogenically driven climate change is predicted to increase average sea surface temperatures, as well as the frequency and intensity of marine heatwaves in the future. This increasing temperature is predicted to have a range of negative physiological impacts on multiple life-stages of coral reef fish. Nevertheless, studies of early-life stages remain limited, and tissue-specific transcriptomic studies of post-larval coral reef fish are yet to be conducted. Here, in an aquaria-based study we investigate the tissue-specific (brain, liver, muscle, and digestive tract) transcriptomic response of post-larval (20 dph) Amphiprion ocellaris to temperatures associated with future climate change (+3 °C). Additionally, we utilized metatranscriptomic sequencing to investigate how the microbiome of the digestive tract changes at +3 °C. Our results show that the transcriptional response to elevated temperatures is highly tissue-specific, as the number of differentially expressed genes (DEGs) and gene functions varied amongst the brain (102), liver (1785), digestive tract (380), and muscle (447). All tissues displayed DEGs associated with thermal stress, as 23 heat-shock protein genes were upregulated in all tissues. Our results indicate that post-larval clownfish may experience liver fibrosis-like symptoms at +3 °C as genes associated with extracellular matrix structure, oxidative stress, inflammation, glucose transport, and metabolism were all upregulated. We also observe a shift in the digestive tract microbiome community structure, as Vibrio sp. replace Escherichia coli as the dominant bacteria. This shift is coupled with the dysregulation of various genes involved in immune response in the digestive tract. Overall, this study highlights post-larval clownfish will display tissue-specific transcriptomic responses to future increases in temperature, with many potentially harmful pathways activated at +3 °C.

Turbidity buffers coral bleaching under extreme wind and rainfall conditions

Coral reefs in turbid waters have been hypothesized to be a refuge from climate change. These naturally occurring communities were brought into the spotlight because some of their species exhibited record levels of resistance to marine heatwaves (MHWs) by disturbance-tolerant corals. However, long-term monitoring data on the drivers of coral bleaching in these extreme reef habitats are scarce. Here, we describe the population structure and bleaching rates of a widespread and resilient coral (Siderastrea stellata). We examine the links between environmental factors, namely, rainfall, wind speed, turbidity, solar irradiance, sea surface temperature, MHWs, and coral bleaching status under the worst recorded drought cycle in the Tropical South Atlantic (2013–2015). We examined 2880 colonies, most of which (∼93%) fit in the size group of 2–10 cm, with a small number (∼1%) of larger and older colonies (>20 cm). The results indicated the absence of MHWs and normal sea surface temperature variations (between 26.6 °C and 29.3 °C), however, we detected an extreme rainfall deficit (30–40% less annual volume precipitation). In general, a high proportion (44–84%) of bleached colonies was found throughout the months when turbidity decreased. Siderastrea is the only reef-building coral that comprises this seascape with encrusting and low-relief colonies. During drought periods, cloudiness is reduced, turbidity and wind speed are reduced, and solar irradiance increase, driving coral bleaching in turbid reefs. However, episodic rainfall and higher wind speeds increase turbidity and decrease coral bleaching. Our hypothesis is that turbidity decreases during drought periods which increases bleaching risk to corals even without thermal stress. Our results suggest that turbidity may have related to wind and rainfall to provoke the coral bleaching phenomenon.

Implications of Warming on the Morphometric and Reproductive Traits of the Green Crab, Carcinus maenas

Understanding the relationship between environmental temperature and the biological traits of organisms is fundamental to inferring the potential impacts of climate change. In the case of marine poikilotherm species, seawater temperature is one of the main driving forces of biological processes, with consequences at higher levels of organization such as population and ecosystem. In this study, we analysed differences in maximum carapace width (CWmax), size at maturation, relative size at maturation, and duration of the reproductive season for the green crab (Carcinus maenas) along a temperature gradient. An extensive review of bibliographic data was performed on studies published between 1962 and 2020, gathering C. maenas data from 55 different populations, spread over 20 degrees of latitude and 14.2 °C of sea surface temperature (SST). In addition, green crab data were collected at five different lagoons and estuaries along the continental Portuguese coast. The relationship between average SST and CWmax, age of maturation, reduction of size at maturation, and duration of egg bearing was analysed to understand the role of SST in driving variation in these C. maenas characteristics across a latitudinal gradient. There was a significant relationship between SST and CWmax for males and SST and CW of females at maturation, respectively. The results extrapolate for each local projected temperature increase caused by climate change and suggest an effect on the morphometric and reproductive traits of C. maenas across regions. These changes comprise an overall reduction in C. maenas body size, an enlargement of the reproductive season, a shortening in the duration of larval developmental time, and a decrease in the relative size of crabs at maturation. Secondary consequences on the fecundity and connectivity of populations are discussed.

Data Reconstruction of Sea Surface Temperature in Indonesia’s Fish Management Area 713 (IFMA-713) Using Machine Learning

The IFMA-713 in Indonesia is water that has dynamic of temperature changes due to interactions with the Pacific Ocean and the surrounding. Sea surface temperature data can be obtained by measuring with satellite imagery. However, satellite imagery measurements of sea surface temperature can be incomplete due to cloud cover. In this study, a machine learning method was used to reconstruct sea surface temperature data using a backpropagation neural network algorithm. The data used in this research is data captured with MODIS Satellite. Then, the reconstruction of sea surface temperature data is carried with four scenarios with missing data percentages: empty data, zero values, average values at the point of data collection, and Indonesia’s average sea surface temperature. Accurate results were obtained in reconstructing sea surface temperature where the scenarios had a positive correlation. The most accurate scenarios for reconstructing sea surface temperature data with missing data were those in which the empty data was filled with average values at the point of data collection or Indonesia’s average sea surface temperature.

Recent Variations in the Size and Age Structure of the Population of Horse Mackerel <i>Trachurus mediterraneus</i> (Steindachner, 1868) on the South-Western Shelf of Crimea

The influence of the average annual sea surface temperature (SST) on the development of horse mackerel Trachurus mediterraneus on the south-western Crimean shelf has been shown. The changes in the main indicators of the population and their relationship with the change in the average annual SST (0.055°C/year) in 2000–2020 have been identified. Against the background of the observed increase in SST in recent years, the state of the horse mackerel population has improved: there has been an increase in the average age and, accordingly, the proportion of larger, well-fed individuals, and, in general, the average size and weight of fish. It has been shown that according to the nature of the change in the average annual SST, three periods can be distinguished: 2000−2007, 2008−2013 and 2014−2020.

Histopathological changes in the greenshell mussel, Perna canaliculus, in response to chronic thermal stress

Climate change associated temperature challenges pose a serious threat to the marine environment. Elevations in average sea surface temperatures are occurring and increasing frequency of marine heatwaves resulting in mortalities of organisms are being reported. In recent years, marine farmers have reported summer mass mortality events of the New Zealand Greenshell mussel, Perna canaliculus, during the summer months; however, the etiological agents have yet to be determined. To elucidate the role of thermal stress, adult P. canaliculus were exposed to three chronic temperature treatments: a benign control of 17 °C and stressful elevations of 21 °C and 24 °C. Eight mussels per treatment were collected each month throughout a 14-month challenge period to identify and investigate histopathological differences among P. canaliculus populations exposed to the three temperatures. Histopathology revealed several significant deleterious alterations to tissues associated with temperature and exposure time. Increasing temperature and progression of time resulted in 1) an increase in the number of focal lipofuscin-ceroid aggregations, 2) an increase in focal hemocytosis, 3) an increase in the thickness of the sub-epithelial layer of the intestinal tract and 4) a decreased energy reserve cell (glycogen) coverage in the mantle. Prolonged exposure, irrespective of temperature, impacted gametogenesis, which was effectively arrested. Furthermore, increased levels of the heat shock protein 70 kDa (HSP 70) were seen in gill and gonad from thermally challenged mussels. The occurrence of the parasite Perkinsus olseni at month 5 in the 24 °C treatment, and month 7 at 21 °C was unexpected and may have exacerbated the fore-mentioned tissue conditions. Prolonged exposure to stable thermal conditions therefore appears to impact P. canaliculus, tissues with implications for broodstock captivity. Mussels experiencing elevated, temperatures of 21 and 24 °C demonstrated more rapid pathological signs. This research provides further insight into the complex host-pathogen-environment interactions for P. canaliculus in response to prolonged elevated temperature.

Pendugaan Sebaran Klorofil-A dan Suhu Permukaan Air Laut untuk Menentukan Fishing Ground dengan Menggunakan Teknologi Pengindraan Jauh di Perairan Pantai Barat Sulawesi Selatan

Estimation of Chlorophyll-A Distribution and Sea Surface Temperature to Determine Fishing Ground Areas Using Remote Sensing Technology in West Coast Waters of South Sulawesi. The aim of this research is to study the distribution patterns of Chlorophyll-a and Sea Surface Temperature, and their relationship with potential fishing ground areas in the waters. West coast of South Sulawesi by utilizing Remote Sensing technology. The methodology used includes several stages, namely data collection of fashionable oceancolor 8 Day Chlorophyill Concentration and 8 Day Surface Temperature level 3 satellite imagery data with a resolution of 9 km, which is then carried out further processing using mapping software. The implementation of this research took place on May 1, 2015 until June 30 2015. The results of the study showed that in May - June 2015 there was a decrease in sea surface temperature of 1.35°C where the monthly average sea surface temperature ranged from 26.72° - 31.16°C. Sea Surface Temperature was relatively high in the first week of May 2015 compared to the following weeks during May – June. Chlorophyll-a concentration in the study area ranged from 0.06 – 3.34 mg/m³ based on the average. The relatively high concentration of Chlorophyll-a occurred on the second week of June 2015. The most potential Fishing Ground area was in June 2015 with the coordinates of 117° West – 119.5° East with a temperature range ranging from 27.06° – 29.04° C and 0.2 – 0.28 mg/m³ for the range of Chlorophyll-a concentrations.

Interannual variability of sea surface temperature at the polar latitudes of the Atlantic Ocean

The general regularities and regional differences in the interannual variability of the sea surface temperature in the polar latitudes of the Atlantic Ocean are revealed according to the OI SST reanalysis data for period 1982—2017. The reanalysis contains daily average sea surface temperature values at the nodes of a regular grid 0,25°×0,25°. In this work, areas where the ice concentration did not exceed
 90 % were analyzed. In both polar basins, the position of areas with a high level of sea surface temperature
 interannual variability qualitatively coincides with the position of intense currents. The maximum values of
 linear sea surface temperature trends are observed in areas of the maximum level of interannual variability,
 while the trends in long-term sea surface temperature variability in the Arctic and Antarctic are noticeably
 different. Significant positive sea surface temperature trends prevail in the Atlantic sector of the Arctic.
 Significant negative trends have been identified only off the northeastern coast of Greenland and north of the Arctic Current. The sea surface temperature decrease on a long-term scale in this area is associated with an increase of cold water transport by the East Greenland and Arctic currents, which are formed as a result
 of the intensive melting of Arctic ice observed in recent decades. In the Atlantic sector of the Antarctic, on the contrary, significant negative sea surface temperature trends prevail. In the Arctic, the maximum values of positive sea surface temperature trends are observed in August—September during the period of maximum warming of surface waters and minimum concentration of drifting ice. In the Antarctic, the maximum negative sea surface temperature trends in absolute value are observed from August to October, during the period of surface water cooling and maximum ice concentration.

Impact of changes in sea surface temperature due to climate change on hurricane wind and storm surge hazards across US Atlantic and Gulf coast regions

Communities in US coastal regions are threatened by hurricanes more than ever, and the effect of climate change may further aggravate the risk and corresponding losses in the future. This paper investigates the potential impact of changes in sea surface temperature (SST) on hurricane wind and storm surge hazards for the Atlantic and Gulf coast regions. An empirical track model that uses SST as an input is used to account for the effect of temperature variations on hurricane intensity. The storm surge hazard is modeled using Sea, Lake, and Overland Surges from Hurricanes (SLOSH). Four projected future climate conditions based on the Intergovernmental Panel on Climate Change (IPCC) emission scenarios are adopted to capture the effect of changes in SST on future hurricane intensity. The impacts of changes in hurricane frequency and sea-level rise are also considered. The results show that the projected increase in the average SST will lead to more intense hurricanes by the end of the twenty-first century. An increase in wind speed for all the studied sites with varying degrees is observed. The most significant increase in wind speeds is observed on the northeast Atlantic coast, with some areas showing an increase of more than 60% for high return period winds under the most extreme future climate scenario. This is because a higher increase in SST is observed in such areas, which will lead to more intense hurricanes in the future. An increasing trend is also observed for the storm surge for all the study sites in the future. However, the largest increase in predicted surge heights is mainly seen in the Gulf Coast locations.