Sea Surface Temperature Fluctuations Research Articles

Relative Contributions of Atmospheric, Oceanic, and Coupled Processes to North Pacific and North Atlantic Variability

AbstractPatterns of sea surface temperature (SST) variability over the northern oceans arise from a combination of atmospheric, oceanic, and coupled processes. Here we use a novel methodology and a suite of observations to quantify the processes contributing to the dominant patterns of interannual SST variability over these regions. We decompose the upper ocean heat content tendency associated with such dominant patterns into contributions from different heat fluxes: (a) atmospherically driven, (b) surface feedbacks, and (c) oceanic. We find that in the subtropics, cloud radiative flux, turbulent heat flux, and residual oceanic processes each contributes substantially to North Pacific SST variability, whereas turbulent heat flux primarily induces North Atlantic SST variability. Cloud radiative fluxes therefore provide a major source of interannual SST variability in the North Pacific but not in the North Atlantic. In midlatitudes, SST fluctuations over the northern oceans are driven by the combination of turbulent and oceanic heat fluxes.

The long-term spatiotemporal variability of sea surface temperature in the northwest Pacific and China offshore

Abstract. The variability of the sea surface temperature (SST) in the northwest Pacific has been studied on seasonal, annual and interannual scales based on the monthly datasets of extended reconstructed sea surface temperature (ERSST) 3b (1854–2017, 164 years) and optimum interpolation sea surface temperature version 2 (OISST V2 (1988–2017, 30 years). The overall trends, spatial–temporal distribution characteristics, regional differences in seasonal trends and seasonal differences of SST in the northwest Pacific have been calculated over the past 164 years based on these datasets. In the past 164 years, the SST in the northwest Pacific has been increasing linearly year by year, with a trend of 0.033 ∘C/10 years. The SST during the period from 1870 to 1910 is slowly decreasing and staying in the range between 25.2 and 26.0 ∘C. During the period of 1910–1930, the SST as a whole maintained a low value, which is at the minimum of 164 years. After 1930, SST continued to increase until now. The increasing trend in the past 30 years has reached 0.132 ∘C/10 years, and the increasing trend in the past 10 years is 0.306 ∘C/10 years, which is around 10 times that of the past 164 years. The SST in most regions of the northwest Pacific showed a linear increasing trend year by year, and the increasing trend in the offshore region was stronger than that in the ocean and deep-sea region. The change in trend of the SST in the northwest Pacific shows a large seasonal difference, and the increasing trend in autumn and winter is larger than that in spring and summer. There are some correlations between the SST and some climate indices and atmospheric parameters; the correlations between the SST and some atmospheric parameters have been discussed, such as those of the North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI) anomaly, total column water (TCW), NINO3.4 index, sea level pressure (SLP), precipitation, temperature at 2 m (T2) and wind speed. The lowest SST in China offshore basically occurred in February and the highest in August. The SST fluctuation in the Bohai Sea and Yellow Sea (BYS) is the largest, with a range from 5 to 22 ∘C; the SST in the East China Sea (ECS) is from 18 to 27 ∘C; the smallest fluctuations occur in the South China Sea (SCS), maintained at range of 26 to 29 ∘C. There are large differences between the mean and standard deviation in different sea regions.

Atmospheric Mixed Layer Convergence from Observed MJO Sea Surface Temperature Anomalies

ABSTRACTThe Madden–Julian oscillation (MJO) dominates tropical weather on intraseasonal 30–90-day time scales, yet mechanisms for its generation, maintenance, and propagation remain unclear. Although surface moist static energy (MSE) flux is greatest under strong winds in the convective phase, sea surface temperature (SST) warms by ~0.3°C in the clear nonconvective phase of the MJO. Winds converging into the hydrostatic low pressure under warm air over the warm SST increase the vertically integrated MSE. We estimate column-integrated MSE convergence using a model of mixed layer (ML) winds balancing friction, planetary rotation, and hydrostatic pressure gradients. Small (0.3 K) SST anomalies associated with the MJO drive 7 W m−2net column MSE convergence averaged over the equatorial Indian Ocean ahead of MJO deep convection. The MSE convergence is in the right phase to contribute to MJO generation and propagation. It is on the order of the total MSE tendency previously assessed from reanalysis, and greater than surface heat flux anomalies driven by intraseasonal SST fluctuations.

Quantifying Tidal Fluctuations in Remote Sensing Infrared SST Observations

The expected amplitude of fixed-point sea surface temperature (SST) fluctuations induced by barotropic and baroclinic tidal flows is estimated from tidal current atlases and SST observations. The fluctuations considered are the result of the advection of pre-existing SST fronts by tidal currents. They are thus confined to front locations and exhibit fine-scale spatial structures. The amplitude of these tidally induced SST fluctuations is proportional to the scalar product of SST frontal gradients and tidal currents. Regional and global estimations of these expected amplitudes are presented. We predict barotropic tidal motions produce SST fluctuations that may reach amplitudes of 0.3 K. Baroclinic (internal) tides produce SST fluctuations that may reach values that are weaker than 0.1 K. The amplitudes and the detectability of tidally induced fluctuations of SST are discussed in the light of expected SST fluctuations due to other geophysical processes and instrumental (pixel) noise. We conclude that actual observations of tidally induced SST fluctuations are a challenge with present-day observing systems.

MJO Anomalies relationship with Volcanic Eruption in Indonesian Archipelago

Madden-Julian Oscillation (MJO) is a large-scale atmospheric phenomenon that crosses the equator with a propagation area ranging from 15° North to 15° South, and moves from west to east, precisely from the Indian Ocean to the Pacific. MJO propagation is usually characterized by the rising of Sea Surface Temperature (SST) in Indian Ocean respectively. MJO anomaly is closely related to the variability of weather in the area it passes, including the Indonesian Archipelago. The impact of MJO anomaly in Indonesian Archipelago itself is suspected to cause not only excessive rainfall, but also a very long consecutive No Rain Days (NRD), with in the end can also trigger massive crop failures. In addition to SST, there are also external events that can affect the duration of the MJO, i.e. volcanic eruptions. Therefore, the study aims to determine the effect of volcanic eruption events on MJO anomalies, through the SST variable as an MJO anomaly parameter and also the occurrence of volcanic eruptions in the same time span. Data from both variables were taken over a period of 35 years, from 1982 to 2016. The SST data is a daily average data, obtained from ESRL NOAA, which is then filtered by the Bandpass Filter method to reinforce the oscillation of data. The MJO anomaly that seen from the SST fluctuations is then matched with time data and the duration of volcanic eruption events over the same time span. It found out that there are three MJO anomalies occurred during the time span of 35 years, and it is hypothesized that they were clearly in correspondence between the duration of volcanic eruption events with the incidence of MJO anomalies in Indonesian Archipellago.

Spatial and temporal differences in the reproductive traits of skipjack tuna Katsuwonus pelamis between the subtropical and temperate western Pacific Ocean

The reproductive traits of skipjack tuna (Katsuwonus pelamis) in the subtropical (10–25°N) and temperate (25–42°N) western Pacific Ocean were investigated to examine the geographical differences in spawning potential. In total, 91% of spawning capable female specimens appeared in waters with sea surface temperatures (SSTs) of over 24 °C. The length of the spawning season for females varied among sampling areas according to the seasonal fluctuations in SSTs, with shorter spawning seasons in the high latitudinal areas (north of 25°N). Mature males were observed during almost all sampling months in all sampling areas. The total spawning fraction during the spawning season in each sampling area ranged from 0.23 to 0.46. Seasonal fluctuations in the spawning fraction were observed in the temperate western Pacific Ocean. The mean relative batch fecundity differed significantly between sampling areas (p < 0.05) and ranged from 67.2 to 106.1 oocytes per gram of body less the ovary weight. The estimated mean relative batch fecundity tended to be lower in the temperate western Pacific Ocean than in the subtropical western Pacific Ocean and the tropical western and central Pacific Ocean. The reproductive traits observed in the present study indicated that the spawning grounds of skipjack tuna in the western Pacific Ocean were expanded in the temperate western Pacific Ocean in the boreal summer, and that the spawning potential per individual in these areas was inferior to those in the subtropical western Pacific Ocean and tropical western and central Pacific Ocean.

Short and mid-term sea surface temperature prediction using time-series satellite data and LSTM-AdaBoost combination approach

Sea surface temperature (SST) is one of the most important parameters in the global ocean-atmospheric system, changes of which can have profound effects on the global climate and may lead to extreme weather events such as droughts and floods. Therefore, predicting the dynamics of future SSTs is of vital importance which can help identify these extreme events and alleviate the losses they cause. In this paper, a machine learning method combining the long short-term memory (LSTM) deep recurrent neural network model and the AdaBoost ensemble learning model (LSTM-AdaBoost) is proposed to predict the short and mid-term daily SST considering that LSTM is good at modelling long-term dependencies but suffers from overfitting, while AdaBoost has strong prediction capability and is not easily overfitted. By combining these two strong and heterogeneous models, the prediction errors related to variance may cancel out each other and the final results can be improved. In this method, the historical time-series satellite data of SST anomaly (SSTA) is used instead of SST itself considering that the fluctuations of SSTs are very small compared to their absolute magnitudes. The seasonality of the SSTA time series is first modelled using polynomial regression and then removed. Then, the deseasonalized time series are used to train the developed LSTM model and AdaBoost model independently. Daily SSTA predictions are made using these two models, and eventually, their predictions are combined as final predictions using the averaging strategy. A case study in the East China Sea that predicts the daily SSTA 10 days ahead shows that the proposed LSTM-AdaBoost combination model outperforms the LSTM and AdaBoost separately, as well as the optimized support vector regression (SVR) model, the optimized feedforward backpropagation neural network model (BPNN), and the stacking LSTM-AdaBoost model (S_LSTM-AdaBoost), when judged using multiple error statistics and from different perspectives. The results suggest that the LSTM-AdaBoost combination model using the averaging strategy is highly promising for short and mid-term daily SST predictions.

Multi-scale structure of tropical rainfall response to SST fluctuations

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 78:165-178 (2019) - DOI: https://doi.org/10.3354/cr01566 Multi-scale structure of tropical rainfall response to SST fluctuations Miguel Nogueira* Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisbon, Portugal *Corresponding author: mdnogueira@fc.ul.pt ABSTRACT: The sensitivity of tropical rainfall to sea surface temperature (SST) fluctuations was investigated using a multi-scale analysis framework, covering time scales between a few days and 1 decade. The analysis includes an intercomparison between a satellite-based observational dataset and two twentieth century general circulation model (GCM)-based products: the ERA-20CM ensemble of atmospheric simulations and the ERA-20C reanalysis. The results provide robust evidence for the physical linear response of regional rainfall to SST fluctuations at multi-year time scales. All datasets showed tight correlations between rainfall and local SST, the Niño 3.4 index and local surface downwelling longwave radiation (DLR) over wide tropical regions. Additionally, the rainfall-DLR correlation held under a clear sky approximation. These 3 correlations are tightly related since the Niño 3.4 index and clear sky DLR can be computed from SST alone. The latter requires a robust correlation between local precipitable water vapor (W) and SST (i.e. Clausius-Clapeyron relationship), which was confirmed at multi-year scales over large portions of the tropics. All datasets also showed a robust transition in all these correlations at faster time scales (below ~1 yr), suggesting a change in the physical mechanisms controlling rainfall (and W) variability. Based on the linear sensitivities, 3 simplified models were proposed to reconstruct 3-yearly tropical rainfall time series at 5° resolution, forced only by ERA-20CM’s prescribed SST fields. The simplified linear response models were shown to reproduce observations with similar accuracy to GCM-based products, despite having a (easily correctable) systematic bias. The good agreement between all datasets, including the simplified model, provides confidence to the representation of the tropical rainfall response to SST fluctuations in GCM-based and satellite-based products, at least at multi-year time scales. KEY WORDS: Tropical Rainfall · Multiscale Analysis · Rainfall sensitivity · Statistical modelling Full text in pdf format PreviousNextCite this article as: Nogueira M (2019) Multi-scale structure of tropical rainfall response to SST fluctuations. Clim Res 78:165-178. https://doi.org/10.3354/cr01566 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 78, No. 2. Online publication date: August 08, 2019 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2019 Inter-Research.

Recent changes (2013-2017) in scyphomedusan fauna in the Boka Kotorska Bay, Montenegro (Southeast Adriatic)

A semi- quantitative time series (2013-2017) was used to present the recent events of scyphomedusae appearance and abundance in the Boka Kotorska Bay, Montenegro, Southeast Adriatic. Six meroplanktonic species were recorded: Aurelia spp, Chrysaora hysoscella, Cotylorhiza tuberculata ̧ Discomedusa lobata, Drymonema dalmatinum and Rhizostoma pulmo. Among them, C. hysoscella and D. lobata dominated in the water column during winter and spring, forming dense aggregations in March and May, and February to May, respectively. Our description of the D. lobata blooms are actually the first known records of blooms for this species. C. tuberculata was observed in the Bay principally in August and September. The bloom was occurred only in 2017, being the first information of C. tuberculata mass appearance in this area. We hypothesized that global warming phenomena could trigger the observed changes, and in this respect, long-term trends of sea surface temperature (SST) fluctuations were analysed. The scyphomedusae blooms coincided with high positive SST anomalies, noted in the last seven years for this area. To better understand the mechanisms underlying changes in their phenology and abundance, detailed studies on benthic stages in the Bay are essential.

Seaweed Biodiversity and Temperature Fluctuations of Calatagan Bay, Verde Island Passage

Changes in seaweed biodiversity reflect ecological changes and management of coastal communities. Calatagan Bay is a tourism, agriculture and aquaculture hotspot fronting the Verde Island Passage, touted to be the global center of marine biodiversity. Detection of stressors through monitoring is the key in the proper management of the area. This study surveyed existing seaweed species of the coast, and contrasted it with reported species in the area together with fluctuations in sea surface temperatures for the past two decades, contrasted with the local knowledge and perspectives of local coast-dwellers. Seaweed along the coast were collected from a representative area of 50 km2 with species identification based on morphology and pigment. Ten species that were previously unreported were found while fourteen previously reported species were no longer observed. Caulerpa, Kappaphycus and Sargassum, all with known market demands, were the dominant genera. Sea surface temperature data from local weather stations and the NOMADs database indicate significant warming events from June 1998 to present, with peak sea surface temperature at 31.9oC. Focused group discussions with local communities indicate increased incidences of ice-ice disease, and issues with the uncontrolled use of fertilizers of neighboring farms contaminating their coastal fronts.

Seaweed biodiversity and temperature fluctuations of Calatagan bay, Verde Island passage

Changes in seaweed biodiversity reflect ecological changes and management of coastal communities. Calatagan Bay is a tourism, agriculture and aquaculture hotspot fronting the Verde Island Passage, touted to be the global center of marine biodiversity. Detection of stressors through monitoring is key in the proper management of the area. This study surveyed existing seaweed species of the coast, and contrasted it with reported species in the area together with fluctuations in sea surface temperatures for the past two decades, contrasted with the local knowledge and perspectives of local coast-dwellers. Seaweed along the coast were collected from a representative area of 50 km2 with species identification based on morphology and pigment. Nine species that were previously unreported were found while fourteen previously reported species were no longer observed. Caulerpa, Kappaphycus and Sargassum, all with known market demands, were the dominant genera. Sea surface temperature data from local weather stations and the NOMADs database indicate significant warming events from June 1998 to present, with peak sea surface temperature at 31.9oC. Focused group discussions with local communities indicate increased incidences of ice-ice disease, and issues with the uncontrolled use of fertilizers of neighboring farms contaminating their coastal fronts.

Correlation and coherence analysis between sea surface temperature (SST) and surface wind in the Equatorial Western Sumatra Waters

Equatorial Western Sumatra Waters have a tremendous dynamic in ocean characteristics. It directly faces the Indian Ocean exactly located below the equator. Consequently, Equatorial Western Sumatra waters are influenced by the tropical climatic factors such as monsoons and climate variabilities, such as Indian Ocean Dipole (IOD) and Madden Julian Oscillation (MJO) that control sea surface temperature (SST) fluctuation in the Indian Ocean regions. This study aimed to review the correlation and coherence of SST distributed by surface wind in the Equatorial Western Sumatra waters. Wavelet method (cross wavelet transforms and wavelet coherence) was used to analyze the correlation and coherency between SST and surface wind. The annual variation of SST for 365 days period is the strongest event throughout the year caused by either monsoon or the changes of wind speed in the surface. Otherwise, the strongest intra-seasonal SST variation of 35 - 60 days observed from December 2012 to March 2013. The highest surface wind speed occurs in the southern and western waters. The surface wind plays a role in evoking SST distribution of 35 - 60 days period (intra-seasonal variability). Besides, the surface wind with 6 months period (semi-annual variability) influences the SST distribution which is identified only in the southern waters and the Indian Ocean regions. These conditions are possibly predicted as the influence of monsoons.

Impacts of consecutive bleaching events and local algal abundance on transplanted coral colonies in the Florida Keys

Climate change threatens many marine ecosystems, including coral reefs and the thousands of organisms that inhabit these reefs. Fluctuations in sea surface temperatures trigger bleaching events in coral colonies that lead to increased coral mortality and reef degradation. To combat the decline in coral cover, many researchers have focused on transplanting coral colonies to better understand which species are best adapted to these environmental changes. This current study examined the impacts of two consecutive thermal stress events on transplanted coral colonies in the middle Florida Keys within the Florida Keys National Marine Sanctuary. Coral fragments of two species (Porites astreoides and Siderastrea siderea) were transplanted on seven reef sites. Transplanted colonies were monitored for evidence of coral bleaching during quarterly sampling trips from June 2013 through June 2017. Bleaching was only observed during the late summer of 2014 and 2015 when Degree Heating Weeks exceeded 4 °C-weeks. Results indicate that P. astreoides colonies had significantly higher bleaching than S. siderea colonies. Reefs differed in their proportion of bleached and unbleached corals for P. asteroides, but these reefs did not differ in their average daily maximum temperature or Degree Heating Weeks. However, individual corals that did bleach had a higher average fleshy algal abundance (Dictyota spp.) surrounding them than those corals that remained unbleached. Corals that bleached the first year and survived were no more or less likely to bleach the second year. These findings suggest that resilience to bleaching differs not only by coral species but may also be influenced by the local abundance of fleshy algal species.

The correlation between sea surface temperature and MJO incidence in Indonesian waters

Madden-Julian Oscillation (MJO) is a large-scale atmospheric phenomenon that crosses the equator within range of 15° North to 15° South and moves from West to East respectively. The MJO is closely related to weather anomalies (excess rainfall) that occur during the dry season in Indonesia and can make an unstable environment due to the sustainability of several staples plantation. This phenomenon is suspected to be related directly to the occurrence of sea surface temperature fluctuations in equatorial areas. This research aims to analyze the relation of sea surface temperature fluctuation in Indonesian waters with the MJO incidence, through the empirical method with statistical calculation, based on Sea Surface Temperature (SST) and Outgoing Longwave Radiation (OLR) which is representing the MJO incidence. The data of these two variables were obtained from ESRL NOAA, with a range of 35 years, from 1982 to 2016. With the hypothesis that the two data are directly correlated to each other, by using Bandpass filtering scheme, the filtering results then analyzed using simple linear regression method. It founded that the correlation between these two variables can reach up to 80.2%, and it means that the MJO incidence is directly correlated with SST in the Indonesian waters respectively.

Diagnosing Ocean Feedbacks to the BSISO: SST‐Modulated Surface Fluxes and the Moist Static Energy Budget

AbstractThe oceanic feedback to the atmospheric boreal summer intraseasonal oscillation (BSISO) is examined by diagnosing the sea surface temperature (SST) modification of surface fluxes and moist static energy on intraseasonal scales. SST variability affects intraseasonal surface latent heat (LH) and sensible heat (SH) fluxes, through its influence on air‐sea moisture and temperature gradients (∆q and ∆T, respectively). According to bulk formula decomposition, LH is mainly determined by wind‐driven flux perturbations, while SH is more sensitive to thermodynamic flux perturbations. SST fluctuations tend to increase the thermodynamic flux perturbations over active BSISO regions, but this is largely offset by the wind‐driven flux perturbations. Enhanced surface fluxes induced by intraseasonal SST anomalies are located ahead (north) of the convective center over both the Indian Ocean and the western Pacific, favoring BSISO northward propagation. Analysis of budgets of column‐integrated moist static energy (⟨m⟩) and its time rate of change (∂⟨m⟩/∂t) shows that SST‐modulated surface fluxes can influence the development and propagation of the BSISO, respectively. LH and SH variability induced by intraseasonal SSTs maintain 1–2% of ⟨m⟩ day−1 over the equatorial western Indian Ocean, Arabian Sea, and Bay of Bengal but damp about 1% of ⟨m⟩ day−1 over the western North Pacific. The contribution of intraseasonal SST variability to ∂⟨m⟩/∂t can reach 12–20% over active BSISO regions. These results suggest that SST variability is conducive, but perhaps not essential, for the propagation of convection during the BSISO life cycle.

Tropical Atlantic Response to Last Millennium Volcanic Forcing

Climate responses to volcanic eruptions include changes in the distribution of temperature and precipitation such as those associated with El Niño Southern Oscillation (ENSO). Recent studies suggest an ENSO-positive phase after a volcanic eruption. In the Atlantic Basin, a similar mode of variability is referred as the Atlantic Niño, which is related to precipitation variability in West Africa and South America. Both ENSO and Atlantic Niño are characterized in the tropics by conjoined fluctuations in sea surface temperature (SST), zonal winds, and thermocline depth. Here, we examine possible responses of the Tropical Atlantic to last millennium volcanic forcing via SST, zonal winds, and thermocline changes. We used simulation results from the National Center for Atmospheric Research Community Earth System Model Last Millennium Ensemble single-forcing experiment ranging from 850 to 1850 C.E. Our results show an SST cooling in the Tropical Atlantic during the post-eruption year accompanied by differences in the Atlantic Niño associated feedback. However, we found no significant deviations in zonal winds and thermocline depth related to the volcanic forcing in the first 10 years after the eruption. Changes in South America and Africa monsoon precipitation regimes related to the volcanic forcing were detected, as well as in the Intertropical Convergence Zone position and associated precipitation. These precipitation responses derive primarily from Southern and Tropical volcanic eruptions and occur predominantly during the austral summer and autumn of the post-eruption year.

Spatiotemporal variations in the distribution of round herring eggs in the East China and Japan Seas during 1997–2013

Spawning stock biomass (SSB) and environmental factors, such as water temperature, can affect the size and location of spawning grounds of small pelagic fishes. We examined the effects of SSB, water temperature, and day length on the probability of egg presence of the round herring Etrumeus teres to clarify spatiotemporal variation in its spawning grounds in the Tsushima Warm Current region off the west coast of Japan. Egg presence probability (EPP) was estimated from monthly egg surveys and annual stock assessments from 1997 to 2013. Our results indicated that EPP was positively correlated with sea surface temperature (SST), and increased between 12 and approximately 17 °C, where it became constant, and then decreased when SST exceeded 24 °C. From February to June, locations of the main spawning grounds gradually shifted northeast from the waters off western Kyushu to the Japan Sea as the areas with water temperatures suitable for successful egg development (≥17 °C) expanded. However, few eggs were observed during the season when day length shortened daily, even when SST was suitable. The main spawning grounds expanded more towards northern waters in warmer years than in cooler years. In addition, EPP was positively correlated with SSB, which resulted in an expansion of the spawning grounds into coastal regions in years with high SSB. These results indicate that spawning of the round herring responds to seasonal changes in SST and day length, and interannual fluctuations in SST and SSB in the Tsushima Warm Current region.

Sea surface temperature change in the Black Sea under climate change: A simulation of the sea surface temperature up to 2100

Surface temperature of the Black Sea increased due to climate change during the 20th century and continues to rise. Here we present by in situ data‐corrected remote‐sensed SST data covering a 34‐year period (1982–2015). Using a linear black box model, we predicted the Black Sea surface temperature (SST) up to 2100. During the 34‐year study period, we detected a 0.64 °C increase in SST per decade. The largest monthly fluctuations in SST were during late summer (August) and autumn (November). The rate of SST increase has almost caught up with the worst climate change scenario for the future. At the end of this century, the relative increase in average Black Sea SST is predicted to be 5.1 °C. In summary, our data show sea surface warming during recent decades, and we predict that this warming is likely to continue under the present environmental condition. The warming of the sea seems to also influence the amount of caught anchovies in the Black Sea. After 1993, the amount of captured anchovies in the southern Black Sea was drastically decreased with increased SST.

TENDENCIES OF CLIMATE CHANGES FOR THERMAL CONDITIONS IN THE COASTAL WATERS OF THE WESTERN BERING SEA AND ADJACENT AREAS IN THE LAST DECADES

The sea surface temperature (SST) variability in recent conditions of climate warming is analyzed for the coastal waters in the western Bering Sea and adjacent areas on the data of regular observations on coastal hydrometeorological stations in 1980–2016 and the data of NOAA_OI_SST_V2 reanalysis, taking into account the climate indices variations. The data series are analyzed using the methods of Empirical Orthogonal Functions, cluster analysis, and correlation analysis. Mean climatic trends are estimated for the air temperature as +0.27 о C/decade and for SST as +0.23 о C/decade; they explain 27 % and 35 % of the year-to-year variability, respectively. The warming patterns are not identical for all seasons and areas. The most rapid growth of the air temperature and SST is observed for warm season (on average +0.36 o C/decade and +0.49 o C/decade). Both year-to-year fluctuations of SST and its climatic trend increase from south to north, the SST trend has increased from 0.11 to 0.32 o C/decade. Statistically significant climatic trends are found also in the changes of zonal and meridional components of wind velocity and certain indices of atmosphere circulation.

Upper Ocean Response to the Atmospheric Cold Pools Associated With the Madden‐Julian Oscillation

AbstractAtmospheric cold pools are frequently observed during the Madden‐Julian Oscillation events and play an important role in the development and organization of large‐scale convection. They are generally associated with heavy precipitation and strong winds, inducing large air‐sea fluxes and significant sea surface temperature (SST) fluctuations. This study provides a first detailed investigation of the upper ocean response to the strong cold pools associated with the Madden‐Julian Oscillation, based on the analysis of in situ data collected during the Dynamics of the Madden‐Julian Oscillation (DYNAMO) field campaign and one‐dimensional ocean model simulations validated by the data. During strong cold pools, SST drops rapidly due to the atmospheric cooling in a shoaled mixed layer caused by the enhanced near‐surface salinity stratification generated by heavy precipitation. Significant contribution also comes from the component of surface heat flux produced by the cold rain temperature. After the period of heavy rain, while net surface cooling remains, SST gradually recovers due to the enhanced entrainment of warmer waters below the mixed layer.