Average Sea Surface Temperature Research Articles

First Analyses of the TIMELINE AVHRR SST Product: Long-Term Trends of Sea Surface Temperature at 1 km Resolution across European Coastal Zones

Coastal areas are among the most productive areas in the world, ecologically as well as economically. Sea Surface Temperature (SST) has evolved as the major essential climate variable (ECV) and ocean variable (EOV) to monitor land–ocean interactions and oceanic warming trends. SST monitoring can be achieved by means of remote sensing. The current relatively coarse spatial resolution of established SST products limits their potential in small-scale, coastal zones. This study presents the first analysis of the TIMELINE 1 km SST product from AVHRR in four key European regions: The Northern and Baltic Sea, the Adriatic Sea, the Aegean Sea, and the Balearic Sea. The analysis of monthly anomaly trends showed high positive SST trends in all study areas, exceeding the global average SST warming. Seasonal variations reveal peak warming during the spring, early summer, and early autumn, suggesting a potential seasonal shift. The spatial analysis of the monthly anomaly trends revealed significantly higher trends at near-coast areas, which were especially distinct in the Mediterranean study areas. The clearest pattern was visible in the Adriatic Sea in March and May, where the SST trends at the coast were twice as high as that observed at a 40 km distance to the coast. To validate our findings, we compared the TIMELINE monthly anomaly time series with monthly anomalies derived from the Level 4 CCI SST anomaly product. The comparison showed an overall good accordance with correlation coefficients of R > 0.82 for the Mediterranean study areas and R = 0.77 for the North and Baltic Seas. This study highlights the potential of AVHRR Local Area Coverage (LAC) data with 1 km spatial resolution for mapping long-term SST trends in areas with high spatial SST variability, such as coastal regions.

Asymmetry of hemispheric climate during MIS 16 versus MIS 12

Marine isotope stage (MIS) 16 (676-621 ka) and MIS 12 (478-424 ka) stand out as two significant glacial periods during the late Quaternary, demonstrating consistent continental ice volume or sea level, as discerned from benthic δ18O records. Intriguingly, the average sea surface temperature (SST) during MIS 16 surpasses that of MIS 12 by approximately 0.54–0.79 °C, while the atmospheric CO2 concentration during MIS 16 is approximately 16 ppmv lower than that of MIS 12. The underlying mechanism driving these discrepancies remains enigmatic. In this study, we present new high-resolution X-ray fluorescence (XRF) and grain size records covering the interval from 700 to 400 ka from Ocean Drilling Program (ODP) Site 1090 in the South Atlantic Ocean. We also integrated benthic δ13C, ice-rafted debris (IRD) and carbonate ion concentration ([CO32−]) records globally, to elucidate the distinct climate evolution during the MIS 16 versus MIS 12. Our findings suggest that MIS 12 is distinguished by a more substantial Antarctic ice-sheet, coupled with a weakened and/or equatorward displacement of southern westerly winds, and expansion of southern source water (SSW) alongside contractive northern source water (NSW). Conversely, the opposite climate state can be observed in MIS 16. The elevated atmospheric CO2 in MIS 12 and diminished atmospheric CO2 in MIS 16 may be attributed to reconfigurations in the ocean carbon reservoir regulated by the reorganization of deep-water masses and meridional ocean circulation, as a result of the divergent evolution of bipolar ice-sheets. Our study underscores the critical role of the interplay between the two polar regions in modulating deep-sea carbon storage on the orbital timescale and atmospheric CO2. This interplay is essential for a comprehensive understanding of past and future carbon cycle adjustments in response to climate change.

SST and ENSO activity 282,000 years ago reconstructed from Porites coral in the South China Sea

The El Niño-Southern Oscillation (ENSO) is the most influential climatic phenomenon on an interannual timescale. Studying the relationship between sea surface temperature (SST) and ENSO events during typical geological periods is helpful for understanding the trends of ENSO activities in the future, especially under the background of global warming. Here we quantitatively reconstructed a 115-year history of SST and ENSO activity around 282 ka during Marine Isotope Stage 8 (MIS8) by using the growth rate of Porites corals from Xisha Islands in the South China Sea. The results show that the average coral growth rate (6.0 ± 1.0 mm/yr (1σ)) around 282 ka was only 56.1% of the modern average value (10.7 ± 0.9 mm/yr; 1937–2014 CE), and the average SST (26.0 ± 0.3 °C (1σ)) was 0.7 ± 0.4 °C and 1.1 ± 0.4 °C lower than that in the Little Ice Age (LIA; 1520–1676 CE; 26.7 ± 0.2 °C) and the present (1937–2014; 27.1 ± 0.2 °C), respectively. The reconstructed results show that there was significant ENSO activity with moderate intensity or above at 282 ka, while the frequency of ENSO activity at that time was lower than that of the LIA and the present. This seems to indicate that the frequency of moderate intensity ENSO activity increases with rising SST. Given the current rapid warming, the future trend of ENSO activities deserves close attention.

Threats to a Temperate Kelp Forest Species, Ecklonia cava, through Tropical Fish Herbivory Associated with Sea Surface Warming in the East China Sea

Kelp forests in Korean waters, mainly consisting of Ecklonia cava, provide ecologically and economically important ecosystems. However, they are severely threatened by increasing sea surface temperature (SST). In 2023, an unusually high SST was observed in the northern East China Sea, where the average SST from August to November 2023 was found to be 1.1 °C higher than the average SST during the same period over the last two decades. Our photo images and videos reveal increasing feeding on E. cava populations by tropical herbivore rabbitfish (Siganus canaliculatus, Siganus fuscescens) associated with the impact of increasing SST. Given the fall reproductive peak of E. cava population, increased herbivory by tropical rabbitfish could have a significant adverse impact on the composition of temperate kelp forests.

Spatial structure of the temporary variability of the Arctic seas surface temperature

Interannual oscillations in the surface temperature of the Arctic Ocean and the North Atlantic with the southern boundary (instead “border”) at latitude 55° 25′ N between 1949 and 2007 are investigated based on the MPIOM (Max Planck Institute Ocean Model) solution. It is a free surface ocean model based on primitive equations in the Boussinesq and incompressibility approximations. High-resolution spectra were estimated via fast Fourier transform with a maximum resolution (Welch’s method). Factor analysis method, which makes it possible to identify areas with highly correlated oscillations and reduce the study of the characteristics in question to their analysis in local points, is used to minimize the significant amount of the initial information about monthly average sea surface temperature fields. Аnalysis of the main factors made it possible to identify 10 areas with quasi-synchronous variability of temperature anomalies by including the points correlated with relevant factors with correlation exceeding 0.6. Spectral structure compliance classification revealed that the areas of the Chukchi Sea, the Hudson Bay, the Irminger Sea, and the Labrador Sea have oscillation peak similarities for the periods of 5–6 years and 8–9 years. Central and western areas of the Norwegian Sea, the area affected by the North Atlantic Current, the eastern part of the Norwegian Sea, and some areas of the Kara Sea have similar spectral structure defined by the peaks at the 11-year and 6-year periods. The Baffin Bay with two main peaks at the 16-year and 5–6-year periods, and the central and the western parts of the Barents Sea, where oscillations are similar to the ones in the Chukchi Sea at short periods, and to the ones in the south-eastern part of the Barents Sea and in the eastern part of the Norwegian Sea at 7–8-year periods, stand out significantly. In some cases, spectrum peaks in different areas appear shifted and attenuated, so presumably the frequency characteristics of the temperature signal change as it moves across the water area.

Evolutionary trends and analysis of the driving factors of Ulva prolifera green tides: A study based on the random forest algorithm and multisource remote sensing images

Understanding the prolonged spatiotemporal evolution and identifying the underlying causes of Ulva prolifera green tides play pivotal roles in managing such occurrences, restoring water ecology, and fostering sustainable development in marine ecosystems. Satellite remote sensing represents the primary choice for monitoring Ulva prolifera green tides due to its capability for extensive, long-term ocean monitoring. Based on multi-source remote sensing images, ecological and environmental datasets, and machine learning algorithms, therefore, this study focused on "remote sensing modelling - evolution history - change trends - mechanism analysis" to elucidate both the remote sensing monitoring models and the underlying driving factors governing the spatiotemporal evolution of Ulva prolifera green tides in the highly impacted South Yellow Sea of China. With the use of GOCI Ⅰ/Ⅱ images, an hybrid remote sensing extraction model merging the robustness of the random forest (RF) model and the optical algae cloud index (ACI) was established to map Ulva prolifera distribution patterns. The ACI-RF method exhibited exceptional performance, with an F1 score surpassing 0.95, outperforming alternative methods such as the support vector machine (SVM) and K-nearest neighbour (KNN) methods. On the basis, we analysed the evolutionary trends and the driving factors determining these distribution patterns using meteorological data, runoff data, and data on various water quality parameters (SST, ocean current speed, wind speed, precipitation, DO, PAR, Si, NO3-, PO43-and N/P). Over the period from 2011 to 2022, excluding 2021, there was a notable decline in the area of Ulva prolifera green tides, varying between 397 and 2689.9 km2, with an average annual reduction rate of 3%. The maximum annual biomass varied between 0.12 and 15.9 kt. Notably, more than 75% of the area of Ulva prolifera green tides exhibited northward drift, which was significantly influenced by northern currents and wind fields. The analysis of driving factors indicates that factors such as average sea surface temperature, eastward wind speed, northward wind speed, precipitation, PO43- and N/P/Si significantly influence the biological growth rate of Ulva prolifera. Furthermore, coastal land use change and surface runoff, particularly surface runoff in June, significantly impacted the growth rate of Ulva prolifera, with Pearson correlation coefficients of 0.74 and 0.67, respectively. Against the background of global warming and severe deterioration in the marine environment, Ulva prolifera blooms persist. Consequently, two distinct management strategies were proposed based on the distribution patterns and cause analysis results for addressing Ulva prolifera green tides: establishing a continuous protection framework for rivers, lakes, and nearshore areas to mitigate pollutant inputs and implementing precise environmental monitoring measures in urban expansion areas and farmlands to combat overgrowth-induced green tides. This methodology could be applied in other regions affected by marine ecological disasters, and the criteria for selecting influencing factors offer a valuable reference for designing tailored and proactive measures aimed at controlling Ulva prolifera green tides.

Prediction on the changes in potential suitable areas for mangroves along the coast of Guangxi and the threat from Spartina alterniflora invasion.

As one of the important blue carbon pools in tropical and subtropical intertidal zones, mangroves are widely distributed along the coast of Guangxi in China. To deeply explore the variations of potential suitable habitats for mangroves in China under the background of climate change, based on remote sensing interpretation data of coastal wetlands in Guangxi, global marine environment and bioclimatic environment data in 2021, we constructed a maximum entropy habitat distribution model to simulate the spatial distribution of potential suitable areas for mangroves and the invasive species, Spartina alterniflora, along the coast of Guangxi, and predicted the patterns under extreme climate change scenarios (SSP5-8.5). The results showed that the interpreted area of mangrove forests along the coastline of Guangxi was 9136.7 hm2 in 2021, while the predicted area of potential suitable habitat area was 55955.9 hm2. Current distribution area of mangroves had basically covered its potential high suitability area and nearly 10% of the moderate suitability area. The current area of S. alterniflora was 1320.4 hm2, and the predicted area of potential high suitability area was twice of current area, indicating that there was still a large proportion of high suitability area that was not occupied by S. alterniflora. The most important environmental factors driving the distribution of potential habitats in mangroves were offshore Euclidean distance (62.2%), terrain deviation index (8.7%), average sea surface temperature in the hottest season (6.1%), and seabed terrain elevation (5.6%). The contribution of geographical conditions on mangrove distribution was predominant. Under the climate change scenario (SSP5-8.5), potential suitable area for mangroves would increase by 5.3%, while that for S. alterniflora would decrease by 3.1%. The overlapping proportion of the potential suitable area for mangroves and S. alterniflora was similar under current and SSP5-8.5 scenarios, being 15.2% and 14.5%, respectively. In the future, it is necessary to strengthen the protection and ecological restoration of mangroves along the coast of Guangxi and there is great challenge for preventing further invasion of S. alterniflora.

On the Estimation of the Interannual Variability of the Ocean Surface Temperature in the Area of the Peruvian Upwelling

The interannual variability of the ocean surface temperature in the area of the Peruvian upwelling for the period 1980–2022 is considered according to the satellite archive GODAS (Global Ocean Data Assimilation System) using the methods of multivariate statistical analysis. Local foci of significant trends, for average annual Sea Surface Temperature (SST) values, were identified near the Peruvian offshore. Four regions (clusters) were obtained, which describe the variability of SST in front off Peru, which could be used to pretend to develop a prognostic oceanographic model. Furthermore, coincidences of temperature fluctuations were found between the first cluster and the region N3+4

Quantifying the probability of a successful marine bioinvasion due to source-destination risk factors.

The increasing spread of marine non-indigenous species (NIS) due to the growth in global shipping traffic is causing widespread concern for the ecological and economic impacts of marine bioinvasions. Risk management authorities need tools to identify pathways and source regions of priority concern to better target efforts for preventing NIS introduction. The probability of a successful NIS introduction is affected by the likelihood that a marine species entrained in a transport vector will survive the voyage between origin and destination locations and establish an independently reproducing population at the destination. Three important risk factors are voyage duration, range of environmental conditions encountered during transit and environmental similarity between origin and destination. In this study, we aimed for a globally comprehensive approach to assembling quantifications of source-destination risk factors from every potential origin to every potential destination. To derive estimates of voyage-related marine biosecurity risk, we used computer-simulated vessel paths between pairs of ecoprovinces in the Marine Ecoregions Of the World biogeographic classification system. We used the physical length of each path to calculate voyage duration risk and the cross-latitudinal extent of the path to calculate voyage path risk. Environmental similarity risk was based on comparing annual average sea surface temperature and salinity within each ecoprovince to those of other ecoprovinces. We derived three separate sets of risk quantifications, one each for voyage duration, voyage path and environmental similarity. Our quantifications can be applied to studies that require source-destination risk estimates. They can be used separately or combined, depending on the importance of the types of source-destination risks that might be relevant to particular scientific or risk management questions or applications.

Pliocene Weakening of Gradients in Temperature but Not in Productivity in the Eastern Equatorial Pacific

AbstractThe modern eastern equatorial Pacific Ocean (EEP) exhibits strong upwelling, producing pronounced gradients in sea surface temperature (SST), nutrient concentration, and biological productivity between 80° and 140°W. During the globally warmer late Pliocene (3.0–3.6 Ma), the EEP may have experienced permanent El Niño‐like conditions, supported by a reduced SST gradient across the equatorial Pacific. However, the weakened east‐west SST gradient has been controversial, with disparate results depending on the proxy used to monitor Western Warm Pool SSTs. We present new Pliocene alkenone‐based SST and paleoproductivity records from four Ocean Drilling Program (ODP) cores spanning an east‐west transect across the EEP, which present an internally consistent picture of SST and productivity gradients in the modern cold tongue, resolved at orbital‐scale variability. Strong agreement between core top reconstructions and satellite estimates indicates that alkenone paleotemperature and paleoproductivity proxies are appropriate for reconstructing Pliocene EEP conditions. The average SST gradient between 90° and 120°W was reduced from the modern 1.8°C gradient to 0.9°C in the late Pliocene. Despite the weakened SST gradient, the surface productivity gradient was stronger during the late Pliocene compared to modern, based on calibrated X‐ray fluorescence biogenic opal and alkenone average accumulation rates. Contrary to modern El Niño SST and productivity patterns, reduced Pliocene surface productivity did not accompany the weakened SST gradient. Instead, strong Pliocene biogenic opal and alkenone concentration accumulation gradients in the eastern EEP suggest that subsurface tilting of the nutricline and thermocline persisted to supply vigorous upwelling of warm but nutrient‐rich subsurface waters in a warmer climate.

Marine Heat Waves in the Indian Ocean: A Major Climate Impact on Marine Microalgae

A clearly defined, lengthy (five days or longer) period of extraordinarily high ocean temperatures is known as Marine Heat Waves (MHWs) (above the e0th percentile). These events significantly impact the structure, abundance, cell size, metabolic functions, physico-chemical interactions between microalgae cells and their surroundings in the Indian Ocean. In the tropical Indian Ocean, the average sea surface temperature (SST) increased by 1.0°C (0.15°C/decade) on average between 1951 and 2015, while the global average SST warmed by roughly 0.7°C (0.11 °C/decade). This resulted from the incidence of Marine microalgal bloom MMBs (including Harmful Algal Bloom) and the number of causal taxa may grow as SST increases. Trichodesmium and Noctiluca contributed 34.4% and 31.8%, respectively, to the overall blooms. Such a heating phenomenon also triggers the dominance of small-sized algal cells, harmful diatoms and pico-plankton. The present paper reviews the Indian as well as global episodes of MHWs such as Western South Atlantic, North-East Pacific, Western Australia, Alaskan Sea etc. and their impact on phytoplankton. The combination of warming and heatwaves triggers blooms of buoyant cyanobacteria and its combined impacts of MHWs and ocean warming/acidification on phytoplankton community structure have not been fully studied in the Indian Ocean.

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.