Sea Surface Temperature Values Research Articles

Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea

Sea surface temperature (SST) is a key hydrological variable which can be monitored via satellite. One source of thermal data with a spatial resolution high enough to study sub-mesoscale processes in coastal waters may be the Landsat mission. The Thermal Infrared Sensor on board Landsat 8 collects data in two bands, which allows for the use of the well-known nonlinear split-window formula to estimate SST (NLSST) using top-of-the-atmosphere (TOA) brightness temperature. To calibrate its coefficients a significant number of matchup points are required, representing a wide range of atmospheric conditions. In this study over 1200 granules of satellite data and 12 time series of in situ measurements from buoys and platforms operating in the Baltic Sea over a period of more than 6 years were used to select matchup points, derive NLSST coefficients and evaluate the results. To filter out pixels contaminated by clouds, ice or land influences, the IdePix algorithm was used with Quality Assessment Band and additional test of the adjacent pixels. Various combinations of flags were tested. The results show that the NLSST coefficients derived previously for coastal areas, characterised by a more humid atmosphere, might overestimate low SST values. Formulas derived for the Baltic Sea produced biases close to 0 °C and RMSEs in the range of 0.49–0.52 °C.

Time series and neural network to forecast water quality parameters using satellite data

Complex and highly variable parameters of water quality are difficult to predict over time and space. In most cases, predictions of surface chlorophyll-a (Chl-a) and sea surface temperature (SST) are based on coupled ecological-hydrodynamic modeling, which is driven by oceanic and climatic conditions. Since these models are complex, simpler and efficient methods of predictions are required. The objective of this study is to evaluate the performance of stochastic time series models - Seasonal Auto Regressive Integrated Moving Average (SARIMA) and nonlinear neural network (NN) - to predict Chl-a and SST in coastal areas. Additionally, this study examines the sensitivity of the aforementioned models with respect to variation in depth and changes in turbidity. The data used in this study are satellite-derived Chl-a and SST collected for the Arabian Gulf region for a period of 10 years. This region has been selected for the study due to pronounced variability in depth and changes in turbidity in its waters. As a result of this study, it has been shown that SARIMA and NN are able to forecast Chl-a and SST. In the deep & less turbid water, SARIMA and NN models (SARIMA/NN) produced Chl-a R2:RMSE values of (0.5:0.6)/(0.37:0.53) and SST R2:RMSE (0.9:1.36)/(0.8:1.43). However, the NN has performed better than SARIMA in predicting Chl-a in turbid & shallow waters, especially when Chl-a concentrations are high (>2 mgm−3). Based on our analysis, we conclude that SARIMA and NN are capable of forecasting the future values of Chl-a and SST in regions with pre-existing knowledge of the water depth and turbidity.

Presence of whale sharks based on oceanographic variations in Cenderawasih Bay National Park, Papua, Indonesia

Abstract. Manuhutu JF, Wiadnya DGR, Sambah AB, Herawati EY. 2021. The presence of whale sharks based on oceanographic variations in Cenderawasih Bay National Park, Papua, Indonesia. Biodiversitas 22: 4948-4955. Oceanographic factors have an important role in the study of estimating the distribution of fish resource habitats. Sea Surface Temperature (SST), Sea Surface Chlorophyll (SSC), Current Speed, Sea Surface Height (SSH), and bathymetry are important parameters that have been used in estimating the habitat of certain species. Through analyzing these environmental factors, research on the appearance and distribution of whale shark habitats in the Cenderawasih Bay National Park in Papua, Indonesia, utilized field observation data and satellite imagery. This study applied data on the presence of whale sharks and oceanographic parameter data from satellite recordings during 2019 – 2020. Analysis of the relationship and habitat modeling between the monthly presence of whale sharks and environmental parameters was carried out through the Generalized Additive Model (GAM) statistical approach and spatial analysis through the Geographic Information System approach. In the GAM analysis, data on the presence of whale sharks was used as a response variable. In contrast, the predictor variables consisted of SST, SSC, current speed, SSH, and bathymetric data. The results showed that the highest frequency of whale shark presence occurred in the transitional monsoon, with an average presence of 31.77 ± 4.00 %. The study also showed that all predictors showed a highly significant relationship (P < 0.001) to the number of whale sharks present. SST values range from 30.3 – 31.3 °C, SSC of 0.39 – 0.86 mg/L, the current speed of 0.46 – 0.65 m/s, SSH showed 0.63 to 1.00 cm, and bathymetry between 40 – 50 m . In the GAM model, the SST and SSC parameters were the two most important parameters that affect the presence of whale sharks, followed by SSHD, depth (bathymetry), and current parameters.

High-resolution marine heatwave mapping in Australasian waters using Himawari-8 SST and SSTAARS data

Marine heatwaves (MHWs) have significant ecological and economic impact at local and regional scales. Consequently, there is a pressing need to map the fine-scale temporal and spatial patterns of MHWs, for both historical and near real-time events. Satellite remote sensing of Sea Surface Temperature (SST) provides fundamental data for the mapping of MHWs. This study used high-resolution Himawari-8 SST and the Sea Surface Temperature Atlas of the Australian Regional Seas (SSTAARS) data, which have a spatial resolution of ~2 km, to map recent and near real-time MHW events in waters around Australasia. The high-resolution MHWs mapping identified two broad areas of MHW hotspots that occurred between August 2015 and February 2019. The Tropical Warm Pool region (including the Great Barrier Reef and part of the Coral Sea) was affected by strong and prolonged MHW conditions for the greater part of 2016. The unusually strong 2015–16 El Niño event was believed to be the primary underlying driver for the MHWs, and the air-sea heat flux was likely the key local process controlling the heat budget. The south-east of the study area (including Australia's south-east coast, the Tasman Sea and New Zealand's east coast) suffered severe MHWs in 2015–16, 2017–18 and 2018–19. The 2015–16 summer Bass Strait and East Tasmania MHW event was likely due to the anomalous heat transported by the East Australia Current. The air-sea heat flux, however, was likely an important local driver for the MHW events in the Tasman Sea during the 2016 autumn, the 2017–18 summer and the 2018–19 summer. The anomalous heat flux into ocean was attributed to potential underlying climate drivers including ENSO teleconnections, positive SAM and their interaction. This mapping has not only enhanced our understanding of the spatio-temporal characteristics of several previously documented MHWs, but also identified and mapped several previously undocumented MHWs. Two case studies in the Beagle Marine Park located in north-eastern Bass Strait and the Elizabeth and Middleton Reefs situated ~550 km east of the Australian coast within the Lord Howe Marine Park proved the value of Himawari-8 SST and SSTAARS data in mapping fine details of MHWs in a small area, which could not be captured by the broad-scale DOISST data. During the 2017–18 summer event, the case studies revealed much stronger MHW influence in the shallow waters east of the Beagle Marine Park where most of the important rocky reef habitats exist. During the same event, the case studies also confirmed more severe MHW impact on the Elizabeth Reef than the Middleton Reef which resulted in bleaching to selective coral species on the Elizabeth Reef. The near-real time MHWs mapping showed that both the GBR and the Coral Sea marine parks were experiencing MHW conditions in early March 2020, with most affected areas having strong MHW class.

Warming of the Indian Ocean and its impact on temporal and spatial dynamics of primary production

The Indian Ocean, the third largest among the world’s oceans, is experiencing unprecedented changes in sea surface temperature (SST). We present temporal and spatial dynamics of phytoplankton and their response to warming in the Indian Ocean (∼25°N to 30°S) during 1998–2019 using remote sensing data. Our study revealed that the area of the Indian Ocean Warm Pool (IOWP), defined as waters with SST values >28 °C, is significantly expanding in most regions, particularly in the most recent decade. The increase in IOWP area was greatest (∼74%) in the south-central basin. Furthermore, SST increased significantly in most areas of the Indian Ocean (10 out of 11 regions explored) over the 22-year study period with the highest increase of 0.7 °C observed in the south-central regions. Most other regions showed an average increase in temperature of 0.4–0.5 °C. At the same time, net primary production (NPP) showed large interannual variability in northern and central regions of the Indian Ocean, with slightly decreasing trends in a few northern regions. Overall, years of the first decade (1998–2008) showed more often cooler temperatures and higher productivity, except for a few years, whereas years of the last decade (2009–2019) showed more often warmer temperature and lower productivity, except in very recent years (2017–2019) when productivity was high. Mean Chl a concentrations increased in the last decade during the northeast monsoon period in the northwestern regions, suggesting increased NPP in December to March period as a future scenario in this highly productive area of the Indian Ocean. We also observed increasing SST in several major upwelling areas during the study period, whereas Chl a showed high interannual variability with no marked significant trends in most areas. Results from this study corroborate the importance of the southwest monsoon as a key driver of seasonal patterns in Chl a in major upwelling areas of the Indian Ocean.

Warming trend during millennial-scale cold events in the northern Indian Ocean and potential atmospheric CO2 forcing during the past 40 kyr

• Millennial-scale climate variability in the Bay of Bengal is reconstructed by TEX 86 . • Warming trend during millennial-scale cold events is revealed in the northern Indian Ocean. • Atmospheric CO 2 force SST change during the millennial-scale cold events over the past 40 kyr. To better understand the process of hydrographic and temperature changes in the Indian Ocean, we present Glycerol dialkyl glycerol tetraether data on core BoB-56 from the Bay of Bengal to reconstruct the sea surface temperature (SST) variability during the last glaciation. The results indicate that the TEX 86 -derived SST ranged from 22.00 to 28.30 °C with several fluctuations since 40 ka BP and that the evolution pattern matched well with the marine isotope stage (MIS). During MIS 3, the SST kept around 24.60 °C with some small amplitudes. The SST showed more significant fluctuations during MIS 2 and increased gradually with a ~3 °C cooling during the Last Glacial Maximum (LGM). After the Younger Dryas (YD) stage, Holocene SST values exhibited miniscule variations. During the last glaciation climate variability process, the cold signals of the YD and Heinrich events were recorded well in our core SST series, revealing a regional response to global climate changes. The warming trend during these millennial-scale cold events in the northern Indian Ocean was also identified, and SST increased in the range of 2 °C. A comparison of SST records and atmospheric CO 2 concentration shows that the warming process during the YD, LGM, and Heinrich (1–4) events matched the gradual increase in atmospheric CO 2 concentration in the northern Indian Ocean. Hence, this study implies millennial-scale hydroclimate change linked with atmospheric CO 2 forcing that could improve our knowledge of the role of atmospheric CO 2 in triggering abrupt Indian Ocean climate changes.

Meridional migration of Indian Ocean Monsoon precipitation during the early Holocene: Evidence from the Andaman Sea

The Holocene evolution of the Indian Ocean Monsoon (IOM), especially the spatiotemporal nature of its maximum precipitation period, remains controversial. Here we reconstruct high-resolution local δ18Osw and sea surface temperature (SST) values by pairing Mg/Ca values and the δ18O data from planktonic foraminifera Globigerinoides ruber (white) in the southern Andaman Sea in order to understand IOM rainfall variability during the Holocene. Local δ18Osw values show that local maximum rainfall occurred between 10.6 ka and 8.6 ka in the southern Andaman Sea, before declining markedly during the 8.6–5.0 ka period, and then decreasing slightly after 5.0 ka. The Mg/Ca-SST was relatively low during the 10.3–8.6 ka period, before increasing slightly between 8.6 ka and 4.0 ka; it declined thereafter. But the sedimentation rate at the site of Core ADM-C1 relating to monsoonal precipitation of the source region of sediments exhibited its highest value during the 8.6–5.5 ka period. After making further comparisons with other published records for this region, we would propose that maximum IOM precipitation during the early Holocene has exhibited a clearly meridional migration: it was located in the tropics around 7°N during the 10.6–8.6 ka period, migrated northward to the subtropics during the 8.6–5.5 ka period, before migrating southward again after 5.0 ka. We would suggest that the northward shift of maximum precipitation during the Early Holocene in the IOM region was in response to the progressively northward migration of the Intertropical Convergence Zone (ITCZ) and the change of El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) activities.

A remote sensing approach to ascertain spatial and temporal variations of seawater quality parameters in the coastal area of Bay of Bengal, Bangladesh

Sea surface temperature (SST), surface chlorophyll (SChl), Sea surface salinity (SSS), and total suspended solids (TSS) are some critical seawater quality parameters (SWQP) in the Bay of Bengal (BoB) of Bangladesh. The research objectives were to investigate the distribution of SST, SChl, SSS, and TSS in the Summer and Winter seasons of 2014, 2018, and 2020 and denominate the spatial and temporal variation of these parameters in the BoB. The MODIS-Aqua, VIIRS-SNPP level-3 ocean color, and Landsat 8 OLI-TIRS multitemporal images were used and the Geographical Information System (GIS), and Remote Sensing (RS) techniques were applied for interpreting and mapping the output. The results asserted that temporally in the Summer season SChl and SSS increased by 11.02% and 7.96% respectively and TSS decreased by 14.25% from 2014 to 2020. On the other hand, in the Winter season, SST and SSS decreased by 3.37% and 3.38% respectively and SChl and TSS increased by 2.32% and 70.95% respectively from 2014 to 2020. Besides, in the Summer season, the maximum values of SST, SChl, and TSS were 30.16 °C, 2.61 mg/m3, 268.45 mg/l respectively and in the Winter season, the maximum values were 25.06 °C, 2.93 mg/m3, 192.31 mg/l respectively. Spatially, all the maximum values of SST, SChl, and TSS were concentrated in areas near the coastline. Contrary, the maximum values of SSS were 29.01 ppt and 31.21 ppt in the Summer and Winter seasons respectively and both values were coagulated in the open sea area. Seasonally, The SST and TSS were higher in the Summer season and SChl and SSS were higher in the Winter season for all the years in the BoB.

General description of some meteo-marine variables of surface waters adjacent to the Palmer Archipelago, Antarctic Peninsula, during 1979-2018 based on Era5 data

Aspatial and temporal description of meteo-marine parameters for 1979-2018 period of the marine region surrounding the Palmer Archipelago, located West of the Antarctic Peninsula (WAP), is presented. The used information was extracted from the ERA5 reanalysis. Air Temperature (Ta), Total Precipitation (TP) and Sea Surface Temperature (SST) showed a general increase over the last 40 years in the study region. The highest increase of Ta, TP and SST values were recorded north of Gerlache Strait, followed by Bismarck Strait. It was evidenced that Sea Ice Cover (SIC) has decreased mostly north of Palmer Archipelago. The existence of a local differentiation of meteo-marine conditions around the Palmer Archipelago was identified. The climatology of five reference points in the region showed more visible differences during the austral winter in Ta and SIC, these were appreciated during the austral summer in SST and a bimodal behavior was recorded in Pr. The rate of change during the 1979-2018 period for Ta was 0.011 ºC/year, for Pr it was 0.008 mm/year, for SST it was 0.004 ºC/year and for SIC it was -0.003 fraction/year.

Influence of Spawning Ground Dynamics on the Long-Term Abundance of Japanese Flying Squid (Todarodes pacificus) Winter Cohort

Japanese flying squid (Todarodes pacificus) is one of the most commercially important resources in the Pacific Ocean and its abundance is largely affected by environmental conditions. We examined the influence of environmental factors in potential spawning grounds of the winter cohort, approximated from Japanese and South Korean catch and catch per unit effort (CPUE) data of Japanese flying squid. Annual spawning ground dynamics were constructed using sea surface temperature (SST), submarine elevation and mean Kuroshio axis data from 1979 to 2018. Based on these information, we generated a suite of spawning ground indices including suitability SST-weighted area of potential spawning ground (SSWA), mean values (January–April) of suitable SST (MVSS), and the meridional position (MP) of SST isolines (18–24°C). Comparable interannual-decadal variability patterns were detected between the squid abundance and spawning ground indices, with abrupt shifts around 1990/1991 and in recent decades. In particular, the Pacific Decadal Oscillation is negatively correlated with spawning ground indices, suggesting its role in regulating the environmental dynamics in the area. Further, the gradient forest model underpinned the importance of SSWA, SSWA_Lag1 and MVSS_Lag1 on squid abundance. The CPUE is also shown to be a better abundance index than the annual catch in modeling the species’ response to environmental variability in its spawning grounds. Our findings suggest that it is imperative to pay more and timely attention to the relationship between the abundance of Japanese flying squid and environmental changes, especially under adverse environmental conditions.

Commentary: Early Diagenetic Imprint on Temperature Proxies in Holocene Corals: A Case Study From French Polynesia

Coral-based reconstructions of sea surface temperatures (SSTs) using Sr/Ca, U/Ca and δ 18 O are important tools for quantitative analysis of past climate variabilities. However, post-depositional alteration of coral aragonite, particularly early diagenesis, restrict the accuracy of calibrated proxies even on young corals. Considering the diagenetic effects, we present new Mid to Late Holocene SST reconstructions on well-dated (U/Th: ∼70 yr to 5.4 ka) fossil Porites sp. collected from the Society Islands, French Polynesia. For few corals, quality pre-screening routines revealed the presence of secondary aragonite needles inside primary pore space, resulting in a mean increase in Sr/Ca ratios between 5-30%, in contrast to the massive skeletal parts. Characterized by a Sr/Ca above 10 mmol/mol, we interpret this value as the threshold between diagenetically altered and unaltered coral material. At a high-resolution, observed intra-skeletal variability of 5.4 to 9.9 mmol/mol probably reflects the physiological control of corals over their trace metal uptake, and individual variations controlled by CaCO 3 − precipitation rates. Overall, the Sr/Ca, U/Ca and δ 18 O trends are well correlated, but we observed a significant offset up to ± 7 • C among the proxies on derived palaeo-SST estimates. It appears that the related alteration process tends to amplify temperature extremes, resulting in increased SST-U/Ca and SST-Sr/Ca gradients, and consequently their apparent temperature sensitivities. A relative SST reconstruction is still feasible by normalizing our records to their individual mean value defined as SST. This approach shows that SST records derived from different proxies agree with an amplitudinal variability of up to ± 2 • C with respect to their Holocene mean value. Higher SST values than the mean SSTs (Holocene warm periods) were recorded from ∼1.8 to ∼2.8 ka (Interval I), ∼3.7 to 4.0 ka (Interval III) and before ∼5 ka, while lower SST values (Holocene cold periods, Interval II and IV) were recorded in between. The ensuing SST periodicity of ∼1.5 ka in the Society Islands record is in line with the solar activity reconstructed from 10 Be and 14 C production (Vonmoos et al., 2006), emphasizing the role of solar activity on climate variability during the Late Holocene.

An Innovative Method for the Spatial Sampling Analysis of Sea Surface Temperature in the Pacific-Indian Oceans

Zhu, Y.; Zhang, J., and Tang, Q., 2021. An innovative method for the spatial sampling analysis of sea surface temperature in the Pacific-Indian Oceans. Journal of Coastal Research, 37(5), 1053–1062. Coconut Creek (Florida), ISSN 0749-0208. In this study, a pragmatic approach is presented for evaluating the spatial representativeness of the point-scale drifting buoy sea-surface temperature (SST) over the joined area of Asia and the Pacific-Indian Ocean with that help of the high-resolution satellite-derived SST at multipixel scales. The relative spatial sampling error (RSSE) and coefficient of sill (CS) are selected to investigate consistency between the drifting buoy SST and pixel mean value of satellite-derived SST and representativeness of drifting buoy SST at pixel scales of 25 km, 50 km, and 100 km, respectively. The results show that at the 25-km scale, the consistency between the drifting buoy SST and the satellite-derived SST is high, and the spatial heterogeneity within the pixel scale is not obvious, i.e. only two measurements with RSSE are larger than the critical value of all 43,748 measurements. But with the increase in the scale, the number of the drifting buoy SST, which is inconsistent with the satellite-derived SST, is obviously increased (the number of the inconsistent point measurement at the scale of 50 km increased to 42, and at the scale of 100 km it is 59), and the spatial heterogeneity is enhanced. This spatial variation along the direction of latitude change is more obvious. Combining spatial consistency and spatial heterogeneity, no point-scale measurements of the worst spatial representativeness occur at the 25-km pixel scale, in which RSSE and CS are above the critical value. Although drifting buoy SST keeps a high consistency with satellite-derived SST, there are measurements of obvious local variation within pixel scales, and this variation is more obvious along the direction of latitude change. The spatial representativeness of the drifting buoy SST is unstable. This method is helpful to remove the poor-quality reference points during the validation of satellite-derived products, taking point-scale measurements as reference.

Assessing Summertime Primary Production Required in Changed Marine Environments in Upwelling Ecosystems Around the Taiwan Bank

The Taiwan Bank (TB) is located in the southern Taiwan Strait, where the marine environments are affected by South China Sea Warm Current and Kuroshio Branch Current in summer. The bottom water flows upward along the edge of the continental shelf, forming an upwelling region that is an essential high-productivity fishing ground. Using trophic dynamic theory, fishery resources can be converted into primary production required (PPR) by primary production, which indicates the environmental tolerance of marine ecosystems. This study calculated the PPR of benthic and pelagic species, sea surface temperature (SST), upwelling size, and net primary production (NPP) to analyze fishery resource structure and the spatial distribution of PPR in upwelling, non-upwelling, and thermal front (frontal) areas of the TB in summer. Pelagic species, predominated by those in the Scombridae, Carangidae families and Trachurus japonicus, accounted for 77% of PPR (67% of the total catch). The benthic species were dominated by Mene maculata and members of the Loliginidae family. The upwelling intensity was the strongest in June and weakest in August. Generalized additive models revealed that the benthic species PPR in frontal habitats had the highest deviance explained (28.5%). Moreover, frontal habitats were influenced by NPP, which was also the main factor affecting the PPR of benthic species in all three habitats. Pelagic species were affected by high NPP, as well as low SST and negative values of the multivariate El Niño–Southern Oscillation (ENSO) index in upwelling habitats (16.9%) and non-upwelling habitats (11.5%). The composition of pelagic species varied by habitat; this variation can be ascribed to impacts from the ENSO. No significant differences were noted in benthic species composition. Overall, pelagic species resources are susceptible to climate change, whereas benthic species are mostly insensitive to climatic factors and are more affected by NPP.

Effect of environmental variables on the number of births at California sea lion (Zalophus californianus) rookeries throughout the Gulf of California, Mexico

Abstract The 13 California sea lion breeding colonies in the Gulf of California (GoC), Mexico are each characterized by different population growth trends, including a variable number of births. Despite being located in a highly productive marine area, both the species’ population and the number of births have declined significantly over the past few decades. The goal of this study was to assess the effects of certain environmental variables on the number of births at colonies in three regions (northern, central and southern) of the GoC (1995–2018). Data on diet, small pelagic fish catches by fisheries, the density of small pelagic fish schools, remotely sampled values of sea surface temperature and chlorophyll‐a concentration and El Niño Southern Oscillation events were collected in order to evaluate whether these variables had an effect on the number of births using correlations and generalized linear models. No significant relationships were found between the environmental variables and the number of births. However, the number of births decreased when the sea surface temperature anomalies exceeded 1°C in the northern and central regions of the GoC. Although no significant relationships were found between the small pelagic fish catches and the number of births, positive trends were observed between sardine catches and the number of births during certain periods in the central region. A positive correlation between the density of small pelagic fish schools and the number of births suggests a possible relationship between prey availability and reproductive success in the central region. A Programme of Action for the Conservation of the Species should be promoted by the Federal Government and carried out in order to implement specific management actions. Specifically, surveillance efforts should increase, fishing gear conversion plans should be established and sea lion exclusion devices should be introduced, among other measures.

The impact of Cirebon coal-fired power plants on water quality in Mundu Bay, Cirebon Regency

The presence of Cirebon coal-fired power plant I and II caused negative effects to coastal morphology and the quality of marine waters. This also have negative impacts to the fisherman around that sea. This study aims to examine the impact of the Cirebon coal-fired power plant on the water quality of Mundu Bay, Cirebon Regency. Water quality is determined based on total suspended solids (TSS), sea surface temperatures (SST), chlorophyll-A, and salinity in the range 1999 – 2019. Data collection was carried out using satellite imagery of Landsat-5 TM, Landsat- 7 ETM+, and Landsat-8 OLI verified with in-situ field measurements, Sentinel-2 A MSI, and MODIS Aqua imageries. Changes in water quality due to the infrastructure of the two power plants are known through the Mann-Whitney U-Test and Spearman’s correlation analysis. This research shows that two Cirebon coal-fired power plant has a significant effect on changes in the quality of Mundu Bay waters. Changes in water quality are shown by a significant increase in TSS concentrations and SST values ​​accompanied by a decrease in chlorophyll-A levels and salinity levels. Changes in the quality of these waters also disrupt marine biota habitat and cause fishermen in around are difficult to get the ideal catchment yield.

Estimating the spawning ground of Pacific saury Cololabis saira by using the distribution and geographical variation in maturation status of adult fish during the main spawning season

AbstractWe analyzed distribution and differences in body length, age, and maturation rate of Pacific saury Cololabis saira in the western North Pacific Ocean, during the main spawning season (winter), to locate its spawning ground. Sampling was conducted in the coastal area north of the Kuroshio axis (CA), the offshore area of the southern Japanese archipelago (SA), and the area east of the Honshu Island (EA) from 1996 to 2017. Higher densities of Pacific saury were widely observed on or just north (within 100–200 km) of the axis of the Kuroshio and the Kuroshio Extension currents. Body length, age composition, and sea‐surface temperature (SST) differed across the studied areas, with larger fish (>250 mm knob length, mainly age‐1) dominating at higher SST (16–21°C) in the SA and smaller fish (<250 mm knob length, age‐0) dominating at lower SST (14–16°C) in the EA. In the CA, both SST and body length values were in between those in the SA and EA. The area where matured Pacific saury were collected was broadly distributed in the study area, except for the CA and a part of the Transition zone where the SST was low and mean body length was short. This study suggests that the main spawning ground during winter, where the area of high density and high maturation rate overlap, is formed on or just north of the Kuroshio and the Kuroshio Extension axis.

Application of satellite observations to study the changes of hypoxic conditions in near-bottom water in the western part of Peter the Great Bay (the Sea of Japan)

In this paper we explore the possibilities of applying satellite ocean colour (OC) observations and SST to study the changes in the conditions of hypoxia in the near-bottom water in the western part of Peter the Great Bay. Near-bottom water hypoxia occurs in water bodies with increased organic matter influx when the dissolved oxygen (DO) consumed at its oxidation is not restored. Consumption of most DO is usually attributed to the oxidation of organic matter formed as a result of increased algae growth during water eutrophication. Satellite data on indicators of phytoplankton (chlorophyll-a concentration (Chl) and fluorescence (FLH)) allow to analyze the spatial-temporal changes of this substation. Coloured dissolved organic matter (CDOM), non-algal particles (NAP) influence on satellite Chl estimates and also on near-bottom water hypoxia formation. This study analyzes daily, seasonal, and inter-annual changes in the distributions of indicators (Chl, FLH, the coefficients of light absorption by coloured detrital matter (aCDM) and light backscattering by suspended particles (bbp)), based on the instant satellite OC data from MODIS-Aqua. Data on the Chl, the sea surface temperature (SST) from the MODIS-Aqua, the precipitation from the TRMM satellite and the hydrometeorological stations (HMSs), the wind speed and direction from HMS “Vladivostok” are used to study the influence of hydrometeorological conditions on the Chl values. These distributions were compared with the literary information based on field observations of the hypoxia cases in the same area and with the changes in the vertical DO, Chl, temperature, salinity distribution obtained by coastal expeditions in October-November 2010 and February-March 2011. Significant interrelations within 95% confidence level between the satellite Chl, FLH values calculated at the MUMM atmospheric correction and in situ Chl values obtained in the autumn of 2010 were reached separately for the cases with winds of northern and southern directions with the correlation coefficients of 0.71, 0.48 and 0.49, 0.71, respectively. Significant dependences of Chl on SST and Chl on wind speed explained by the influence of continental runoff and water ventilation were obtained. Therefore, the changes of Chl reflect the changes of hypoxic conditions in the near-bottom water. In Amursky Bay the onset of hypoxia was at the Chl and SST values equal to 4 mg m−3 and 13 °C (↑ – at increasing SST); near Furugelm Island it was at 1.6 mg m−3 and 25 °C (↑), 1 mg m−3 and 21 °C (↓). The difference in the Chl values was reflected in the hypoxia onset timings that were the beginning of June (2011), August (2013), and September (2014), respectively. The water flow from the eastern coast of Amursky Bay in early August of 2013 recorded from the OC and SST satellite imagers appeared in an additional hypoxic zone. Decreased OC characteristics in the runoff of the Razdolnaya River in August-September of 2014 were a sign of hypoxia at its mouth. Near Furugelm Island the hypoxia destruction (increase in the DO level from 1 to 4.5 ml L−1) was observed at the Chl of 0.9 mg m−3 and SST = 18 °C (↓). At the autumn maximum of Chl equal to 1.7 mg m−3 and SST = 4 °C (↓) in mid-November the DO level here increased to 8 ml L−1. In Amursky Bay, short-term destructions/weakening of hypoxia manifested themselves in sharp increases of Chl. At that, the ratio between the Chl value and the approximation level was equal to 2 and higher for SST equal to 22–25 °C (↑), to 0.9 and higher for SST equal to 5–13 °C (↓). With the water stratification destruction in temperature and the noticeable weakening of the stratification in salinity (mid-November), the hypoxia destructed (the DO level increased from 2 to 6 ml L−1). In this case, Chl and SST were about 3 mg m−3 and 5 °C (↓).

ANALYZING THE EFFECT OF INDIAN OCEAN DIPOLE PHENOMENON TO THE ANOMALIES DISTRIBUTION OF SEA SURFACE TEMPERATURE IN WEST SUMATERA

The waters of West Sumatera that face directly into Indian Ocean is strongly influenced by Indian Ocean Dipole (IOD) phenomenon which caused an anomaly of sea surface temperature (SST) and affect rainfall intensity in the West Sumatera Province. This research was aimed to know the effect of IOD on the distribution and anomaly of SST and rainfall intensity in West Sumatera. Data processing methods in this research is using statistical and descriptive. The data used in this research are NOAA OI-SST, Dipole Mode Index (DMI), and rainfall data from BKMG. The results showed that IOD positive occured in October 2018 and the IOD negative occured in July 2016. During the positive IOD, SST distribution values were 28 ˚C – 28,8 ˚C and SST anomaly values were ​​-1,2 to -0,4, in the negative phase the distribution of SST values were 29,8 ˚C – 30,35 ˚C and the SST anomaly values were 0,15 to 0,7. The rainfall intensity during positive IOD phase is 157 mm/month and during negative IOD phase is 525 mm/month.

Development of an adaptive neuro-fuzzy inference system (ANFIS) model to predict sea surface temperature (SST)

Abstract An accurate estimation of the sea surface temperature (SST) is of great importance. Therefore, the objective of this work was to develop an adaptive neuro-fuzzy inference system (ANFIS) model to predict SST in the Çanakkale Strait. The observed monthly air temperature, evaporation and precipitation data from the Çanakkale meteorological observation station were used as input data. The Takagi–Sugeno fuzzy inference system was applied. The grid partition method (ANFIS-GP) and the subtractive clustering partitioning method (ANFIS-SC) were used with Gaussian membership functions to generate the fuzzy inference system. Six performance evaluation criteria were used to evaluate the developed SST prediction models, including mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE) and correlation of determination (R2). The dataset was randomly divided into training and testing datasets for the machine learning process. Training data accounted for 75% of the dataset, while 25% of the dataset was allocated for testing in ANFIS. The hybrid algorithm was selected as a training algorithm for the ANFIS. Simulation results revealed that the ANFIS-SC4 model provided a higher correlation coefficient of 0.96 between the observed and predicted SST values. The results of this study suggest that the developed ANFIS model can be applied for predicting sea surface temperature around the world.

Loggerhead marine turtle (Caretta caretta) ecological facts from a trophic relationship model in a hot spot fishery area: Gulf of Ulloa, Mexico

The oceanographic conditions in the Gulf of Ulloa (GU) region make a distinctive faunal assemblage, allowing the presence of species both ecologically and economically important. Constant interaction of emblematic species with the fishing activity has brought social and conservation problems due to the lack of ecological information and/or management tools. For the loggerhead turtle (Caretta caretta), the GU is an important feeding area, so the interaction with anglers is frequent. In this sense, some events of high loggerhead mortality have resulted in restrictive fishing measures; nevertheless, alternative hypotheses should be explored to explain this fact better. With the purpose of not only knowing the ecosystem ecological attributes but also obtaining specific ecological facts of the loggerhead turtle – as instantaneous total mortality – this study proposes Ecopath with Ecosim (EwE) model by calculating Allen's approximation of production to biomass ratio (P/B). Using the thermoregulation theory of ectotherms and this baseline model, the scenarios were run in Ecosim combining two forcing factors (FF): sea surface temperature (SST) and different fishing effort (F) values. All Ecosim scenarios were run over 30 simulated years taking the (P/B) values of the loggerhead turtle. According to the results in this study, the model allowed us to obtain specific ecological attributes for C. caretta, particularly for the P/B estimates in different simulation scenarios, which showed that colder sea surface temperature increases loggerhead mortality. All the information combined provided a better panorama to understand the role this turtle has within the Biological Action Center of the GU system and its interaction with other activities developed on site, such as fishing.