Search

Eddies are structures of recognized physical and biogeochemical relevance. Because of their small space and time scales, submesoscale eddy detection is a challenge, and detection methods for these structures are scarce. In this study, we detect submesoscale eddies (SME) by means of a method implemented on satellite chlorophyll-a (CSAT) and sea surface temperature (SST) data from Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. The performance of this method is shown through the characterization of the shape and size of the detected eddies. The trajectory and characteristics of one particular eddy could be observed for 6 days over the Argentine continental shelf. The eddy reached the highest CSAT concentration (1.52 mg m−3, decreasing to less than 0.8 mg m−3 in about 3.5 km), and the lowest SST on the same day it developed its largest size. All SME detected within the study period are in agreement with cyclonic eddies and have a radius smaller than the baroclinic Rossby radius of deformation. This paper presents a workflow for the automated recognition of SME that could be applied to other regions with similar characteristics, or different ones with previous changes in the parameters. [ABSTRACT FROM AUTHOR]

During 2015, sea surface temperature (SST) in the central tropical Pacific (TP) was warmer than normal, what indicated about the potential for the development of El Niño Southern Oscillation (ENSO). By December 2015, El Niño intensified when SST anomaly in the Niño-3.4 tropical Pacific area reached +2.9 °C, which indicated about the strongest event of the past 36 years. El Niño normally impacts weather, ecosystems, and socioeconomics (agriculture, fisheries, energy, human health, water resource etc.) on all continents. However, the current El Niño is much stronger than the recent strong 1997–1998 event. Therefore, this paper investigates how the strength of El Niño impacts world ecosystems and which areas are affected. The vegetation health (VH) method and 36-year of its data have been used as the criteria of the impact. Specifically, the paper investigates VH-ENSO teleconnection, focusing on estimation of vegetation response to El Niño intensity and transition of the impact from boreal winter to spring and summer. Two types of ecosystem response were identified. In boreal winter, ecosystems of northern South America, southern Africa, eastern Australia, and Southeast Asia experienced strong vegetation stress, which will negatively affect agriculture, energy, and water resources. In Argentina, southeastern USA and the Horn of Africa ecosystem response is opposite. One of the worst disasters associated with ENSO is drought. The advantages of this study are in derivation of vegetation response to moisture, thermal, and combined conditions including an early detection of drought-related stress. For the first time, ENSO impact was evaluated based on all events with |SSTa|> 0.5 ºC and >2.0 ºC. The current strong El Niño has already triggered drought in Brazil, southern Africa, southeastern Asia, and eastern Australia during December–February. Such conditions will be transitioned from boreal winter to spring but not to summer 2016, except for two regions: northern Brazil and southeastern Asia. [ABSTRACT FROM PUBLISHER]

We investigate the spatial and temporal variability of the net ocean–atmosphere heat flux (Qnet) over the Indian Ocean (north of 30 S) for the period 2005–2008, as estimated from remotely sensed observations. Net heat flux data are based on turbulent fluxes from the Institut Français pour la Recherche et l'Exploitation de la MER (IFREMER) and radiative fluxes, both shortwave (SW) and longwave (LW) as produced at the University of Maryland (UMD). Special attention is given to the Arabian Sea (AS) and the Bay of Bengal (BoB). The estimates are evaluated against the Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA). Results are also compared to several widely used atmospheric re-analyses products such as the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-I), the ERA5, the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), and the Climate Forecast System Reanalysis (CFSR). It is demonstrated that satellite-based estimates of heat flux components are in better agreement with in-situ buoy observations than re-analysis-based products. As such, the satellite products can be instrumental in diagnosing model performance and utilized for addressing research issues related to atmospheric and oceanic dynamics in the Indian Monsoon. It was found that the mean Qnet is higher in the AS than in the BoB, yet the phase of their monthly time series is well correlated with ocean heat gain/loss extremes. We have also investigated the relationship between Qnet and Sea Surface Temperature (SST) (mixed layer temperature proxy) with respect to their consistency. It was found that over most of the open Indian Ocean, at least half of the seasonal SST magnitude is explained by the seasonal Qnet. Given the small ( ≤ 1 month) delay between an annual maximum of the seasonal mixed layer heat content rate of change and the seasonal Qnet, it is concluded that Qnet data presented in this paper are generally consistent with independently observed SST. [ABSTRACT FROM AUTHOR]

Near-ship wakes approximately form a triangle region on the sea surface, and they differ from the background sea in a wave pattern, wave propagation direction and velocity, and fluid particle orbital motion. The differences are observed by along-track interferometric synthetic aperture radar (ATI-SAR) systems, and can be properly measured by the ATI techniques. In this paper, a detection method for near-ship wakes based on interferometric magnitude, phase and physical shape in ATI-SAR systems is proposed. The complex multi-look interferometric information for near-ship wakes is first utilized to detect potential pixels. Then, a cluster algorithm is designed based on the interferometric phase and spatial position characteristics of near-ship wakes. After clustering the detected pixels and performing image close operation, the near-ship wakes, which is the triangular region with a much larger physical area than those of common ships or other false alarms, can be identified. Finally, simulation results validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the increasing demands of large maritime scene scattering prediction and also its high-resolution imaging simulation, the traditional two-scale scattering models, such as capillary wave modified facet scattering model (CWMFSM), appear to be inefficient and laborious when encountering scattering simulation of large maritime scene or long-time case. This paper proposes an effective and efficient approach, i.e. a statistical realisation of CWMFSM, for scattering simulation of space-time varying sea surface. Namely, this approach can give a fast and accurate simulation of large scene and long-time space-time varying sea surface scattering results using the memoryless non-linear transform method together with the statistic characteristics of results calculated by CWMFSM method. From the comparisons of texture feature, statistical characteristics and Doppler spectrum between the results derived from CWMFSM method and the statistical realisation, it is demonstrated that the proposed approach can give a pretty efficient simulation of space-time varying sea surface scattering with almost the same accuracy as the CWMFSM method itself. Similar with CWMFSM, the proposed approach can be applied to fields of sea surface scattering intensity distribution simulation, Doppler spectrum investigation of dynamic sea surface, composite scattering prediction of sea surface with multiple targets, SAR remote-sensing simulation of maritime scene, etc. [ABSTRACT FROM AUTHOR]

This paper presents the Global Atmospheric Profiles derived from Reanalysis Information (GAPRI) database, which was designed for earth surface temperature retrieval. GAPRI is a comprehensive compilation of selected atmospheric vertical profiles at global scale which can be used for radiative transfer simulation in order to obtain generalized algorithms to estimate land surface temperature (LST). GAPRI includes information on geopotential height, atmospheric pressure, air temperature, and relative humidity derived from the European Centre for Medium-Range Weather Forecasts Re-Analysis data from year 2011. The atmospheric profiles are structured for 29 vertical levels and extracted from a global spatial grid of about 0.75° × 0.75° latitude–longitude with a temporal resolution of 6 hours. The selection method is based in the extraction of clear sky profiles over different atmospheric weather conditions such as tropical, mid-latitude summer, subarctic, and arctic, while also considering sea and land areas and day- and night-time conditions. The GAPRI database was validated by comparing land and sea surface temperature values derived from it to those obtained using other existing atmospheric profile databases andin situmeasurements. Moreover, GAPRI was also compared to previous radiosonde atmospheric profiles using simulated split-window algorithms. Results show good agreement between GAPRI and previous atmospheric databases, thus demonstrating the potential of GAPRI for studies related to forward simulations in the thermal infrared range. GAPRI is a freely available database that can be modified according to the user’s needs and local atmospheric conditions. [ABSTRACT FROM PUBLISHER]

The Coral Triangle (CT) and the South China Sea (SCS) are the world's great tropical seas, located in the Indo-Pacific (IP) region. It is home to the richest marine ecosystem on Earth, with a total of 76% reef-building coral species as well as 37% coral reef fish species. Unfortunately, this sensitive area is now vulnerable to Sea Surface Temperature (SST) warming. This research explored the possible consequences of SST warming on the rich ecosystems of the IP region, specifically on bleaching of its coral reefs. Reefbase provided coral bleaching records together with the daily NOAA AVHRR Optimum Interpolation (OI) SST V2 dataset (OISSTv2) were used to explore the relationship between coral bleaching and SST in the IP region. Three different categories of monthly mean SST were tested as potential covariates: minimum SST, mean SST and maximum SST, obtained from the OISSTv2. The fitted logistic regression (LR) model revealed a significant and large correlation between coral bleaching and annual maximum monthly mean SST in the study area using the bleaching data from an online database and the time-series of AVHRR images. Predicted maps of coral bleaching based on the LR model were highly consistent with NOAA Coral Reef Watch (CRW) Degree heating Weeks (DHW) maps. However, some important discrepancies resulted from the more specific local fitting used in the LR model. The maximum SST was forecasted from 2020 to 2100 based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset under the Representative Concentration Pathways (RCP2.6) scenario. The fitted logistic regression model was employed to transform the forecasted maximum SST values into maps of the probability of coral bleaching from 2020 to 2100. The results provide considerable cause for concern, including the likelihood of widespread coral bleaching in many places in the IP region over the next 30 years. [ABSTRACT FROM AUTHOR]

The previous studies of upwelling within the Indonesian seas only focused on the Southeast Monsoon (SEM) season. The western coast of Sumatra Island; the southern coast of Java Island, Sunda Islands, and Sulawesi Island; the Banda Sea, the Maluku Sea, and the Arafura Sea are well-known SEM upwelling areas. However, the upwelling events during Northwest monsoon (NWM) have never been investigated. The investigation of NWM upwelling is challenging due to the broad cloud coverage, limiting the observation of infrared and visible sensors of the satellites. This study used the blended products of the satellite-based sea surface temperature (SST), chlorophyll-a (chl-a), sea level anomaly (SLA), surface wind, and rainfall to identify the NWM upwelling occurrences. Remote sensing reflectances 443 nm and 555 nm were also used to examine the influence of suspended sediment and organic matter which may bias the chl-a concentration. Along the northern coast of the Lesser Sunda Islands, the north coast of Papua Island and the Malacca Strait are the areas of NWM upwelling as denoted by the positive anomaly of chl-a, the negative anomaly of SST, and the negative anomaly of SLA. Focusing on the area along the northern coast of the Lesser Sunda Islands, the NWM upwelling is generated by offshore Ekman Mass Transport that reduces SST and increases chl-a. From 2010 onwards, El Niňo Southern Oscillation has a more consistent effect on the NWM upwelling than Indian Ocean Dipole. El Niňo (La Niňa) tends to weaken (strengthen) upwelling. The magnitude of NWM upwelling is weaker than SEM upwelling. [ABSTRACT FROM AUTHOR]

Ribbonfish (Trichiurus lepturus) is one of the major fishery resources of the north-eastern Arabian Sea having significance from commercial as well as ecological point of view. Information on habitat of the resource and its spatio-temporal variations is sparse limiting precise prediction of the grounds for efficient harvest and management of the resource. Habitat suitability modelling was applied to the ribbonfish presence/absence data from commercial trawlers using Generalized Additive Model (GAM) and Boosted Regression Tree (BRT) model along with environmental variables (euphotic depth (Zeu), Sea Surface Temperature (SST), bathymetry and Sea Surface Height anomaly (SSHa) to understand the influence of these on the spatio-temporal variation of ribbonfish in the north-eastern Arabian Sea. The model predictive performances of the models were compared with Area Under the Curve (AUC) and maximum kappa shows BRT model performed slightly better in predicting ability than GAM. Euphotic depth (28.5%) was observed to be the most significant contributor to the spatio-temporal distribution of ribbonfish followed by SST (24.3%), bathymetry (23.8%), and SSHa (23.5%) in the BRT model. Spatial variation of ribbonfish over the months modelled from BRT model indicated fish was strongly linked with bio-physical environment and the potential fishing grounds occurred along off Maharashtra coast during post-monsoon season. Field demonstration of the model was carried out by comparing the daily fish catch locations with weekly prediction maps. Analysis indicated the model to be in good agreement with the catch data and reliable for prediction of spatio-temporal variation in potential fishing grounds of ribbonfish in the north-eastern Arabian Sea. [ABSTRACT FROM AUTHOR]

The Argentine shortfin squid (Illex argentinus) in the Southwest Atlantic Ocean is an economically important cephalopod. Catch per unit effort (CPUE) of species, a critical proxy for fish abundance, affected by many factors, including environmental variables. Given the importance and less considering of multiple environmental factors in the CPUE standardization for I. argentinus, this study provided an accurate standardized CPUE based on the habitat-based model incorporating the effect of environmental variables including sea surface temperature (SST), sea surface height (SSH), and chlorophyll a concentration (Chl-a). The results showed that the trends of yearly and monthly nominal CPUE were consistent with the standardized CPUE. As the highly concentrated fishing operations, the effective fishing effort was always lower than nominal fishing effort, subsequently, the standardized CPUE was found to be higher than nominal CPUE. Among the environmental factors, SSH and Chl-a are the primary environmental variables when standardizing I. argentinus CPUE revealed by habitat-based model. The precision of CPUE standardization could be improved by our methods. The findings will help to grasp the dynamics in the abundance and provide a basic information for the I. argentines stock assessment in the Southwest Atlantic Ocean. [ABSTRACT FROM AUTHOR]

Tropical Cyclone Heat Potential (TCHP) is the heat content relative to 26°C isotherm, which is important in the development of cyclone. Cyclonic events last for few weeks and become intensified within few days or in some cases few hours. To study such low pressure systems, daily TCHP is required which is created in our study using Two Layer Gravity Model (TLGM) using monthly climatologies of temperature and salinity profiles, daily Sea Surface Height Anomaly (SSHA) and daily Sea Surface Temperature (SST). This satellite-based data of SSHA and SST are used to create daily TCHP fields which are validated using collocated ARGO in-situ data. ARGO derived TCHP and TLGM TCHP showed correlation coefficient r = 0.92 , which indicates that TLGM can be used for near real time TCHP calculation for cyclone studies. Analysis done on 92 non-developing and 93 developing systems shows that, on the day of formation of depression, average TCHP is 89.3 kJ cm − 2 for developing systems while average TCHP is 78.3 kJ cm − 2 for non-developing systems in North Indian Ocean (NIO). Minimum TCHP was found to be 27.2 kJ cm − 2 and 28.6 kJ cm − 2 for developing and non developing systems out of 93 and 92 cases, respectively. Further, Genesis Potential Parameter (GPP) using low-level relative vorticity, middle troposphere relative humidity, middle troposphere temperature instability and vertical wind shear is created based on past similar studies, but with six hourly as well as daily resolution (1993 to 2017) and 0.125° × 0.125° spatial resolution. Using daily TCHP, another index called Genesis Potential Index (GPI) is created and then both the GPP and GPI are analysed for 93 developing and 92 non-developing systems in north Indian ocean from the year 1993 to 2017. Our study shows that both are good predictors for the lead periods of less than 2 days, while for the lead periods of more than 2 days, the distinction becomes difficult between developing and non-developing systems. Abbreviations: TLGM - Two Layer Gravity Model; TCHP - Tropical Cyclone Heat Potential; D 26 - Depth of 26°C isotherm; D 20 - Depth of 20°C isotherm; NIO - North Indian Ocean; AS - Arabian Sea; India Meteorological Department - IMD; BOB - Bay of Bengal [ABSTRACT FROM AUTHOR]

The development of remote sensing (RS) technology has enabled the dynamics of various vegetation biophysical parameters to be monitored, such as the water content of vegetation, fraction of green vegetation, and fluorescence relating to photosynthesis. This study aims to estimate and compare the influence of climate and sea surface temperature (SST) variabilities on vegetation dynamics in Australia and parts of Southeast Asia by conducting lagged Pearson's correlation coefficient (r), multilinear regression, and teleconnection analyses using the Empirical Orthogonal Teleconnection (EOT). The monthly vegetation anomalies from January 2013 to September 2018 (69 months) from several RS-based proxies such as, Solar Induced Fluorescence (SIF) from the Global Ozone Monitoring Experiment (GOME)-2B, Moderate Resolution Imaging Spectroradiomater (MODIS) based-Normalized Differenced Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), and X-, C- and Ku-band microwave-based Vegetation Optical Depth Climate Archive (VODCA), were linked with precipitation and rainfall anomalies in Global Land Data Assimilation System (GLDAS) data and Optimum Interpolation Sea Surface Temperature (OISST) anomalies from National Oceanic and Atmospheric Administration (NOAA). The results showed the correlation strengths between vegetation dynamics and precipitation and rainfall were −0.23 (X- and Ku-band VOD) to 0.35 (SIF) and −0.41 (NDVI) to 0.39 (SIF), respectively. The climate variabilities can explain 22% to 37% ( R a d j 2 of 19% to 35%) of the variance in vegetation dynamics in the study area. In addition, the two modes generated from EOT analysis formed spatial patterns relating to El Nino Southern Oscillation (ENSO) events that can explain 18% (SIF) to 62% (Ku-band VOD) of the variance in vegetation dynamics. These results highlight the influence of climate variabilities and ENSO on various vegetation biophysical properties. [ABSTRACT FROM AUTHOR]

It has been widely known that the coastal upwelling along the southern coast of Java is generated by southeasterly wind which induces offshore Ekman Mass Transport (EMT) during southeast monsoon. However, the variability of EMT has not been fully described in previous studies. The present study investigated the variability of Ekman dynamics which consist of EMT and Ekman Pumping Velocity (EPV) along the southern coast of Java, based on remotely sensed data. We demonstrated the incongruity between the distribution of southeasterly wind speed and sea surface temperature (SST) during southeast monsoon which is related to the distribution of Ekman dynamics. Offshore EMT at the western region of the southern coast of Java is stronger than offshore EMT at the eastern region. However, stronger offshore EMT at the western part is inhibited by downwelling EPV while weaker offshore EMT at the eastern part is accelerated by upwelling EPV. Consequently, SSTs at the eastern parts are lower than those at the western parts. Thus, the changes of offshore EMT intensity from eastern to western parts are balanced by their EPV distributions which explain the incongruity between the distribution of wind speed and SST during southeast monsoon. On an interannual timescale, the combination of La Niña and negative Indian Ocean Dipole (IOD) events tends to weaken offshore EMT and EPV which reduce the intensity of Chl-a bloom and SST cooling during southeast monsoon season. Furthermore, ENSO has a less significant impact on the Ekman dynamics variability than IOD. [ABSTRACT FROM AUTHOR]

The level of quasi-stationary planetary wave (QSW) activity in the Antarctic winter stratosphere provides insights into the likely behaviour of the ozone hole in the following spring months. Observation of anomalously large amplitude of the QSW in winter stratospheric temperatures is an indicator that strong disturbances to the polar vortex are likely to occur, and may lead to large reductions in both the area of the Antarctic ozone hole and the overall amount of stratospheric ozone that is depleted. In the sudden stratospheric warming (SSW) preconditions in 2019, the maximum QSW amplitude over Antarctica in August was approximately 12 K, which was only 2 K less than conditions prior to the unprecedented major SSW in 2002. The additional factors disturbing the Antarctic stratosphere in austral winter 2019 were anomalously warm sea surface temperatures in the central tropical Pacific Ocean and the western Indian Ocean, and the descending easterly phase of the Quasi-Biennial Oscillation. Under these preconditions, the Antarctic ozone hole in 2019 had the potential to demonstrate the early disruption and reduced level of the ozone depletion that has been confirmed by the satellite ozone observations. The anomalous ozone hole may also have important regional consequences for weather conditions in the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

The spatial and temporal changes of phytoplankton biomass in the Arabian Sea (AS), though a well-researched topic, its variability according to the phytoplankton size classes (PSCs) were less analysed and explored. Concisely, the chlorophyll-a (chl-a) concentration is not only considered as a proxy of phytoplankton biomass but also an essential factor for identifying phytoplankton community structure. Hence, the synoptic relationship between chl-a concentration and phytoplankton size classes (PSCs) (micro- >20 μm, nano-2 – 20 μm and picoplankton – < 2 μm) provides the better understanding of phytoplankton communities at regional and global scales. In this study, Data INterpolating Empirical Orthogonal Function (DINEOF) is applied on the 16 years Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua Level-3 chl-a concentration of the AS. The spatial reconstruction is performed on eight-day composite time resolution to achieve considerably accurate gap-free chl-a data. Further ocean colour phytoplankton functional types (OCPFT) model is applied on gap-filled chl-a data of the time series 2003–2018 to study the spatial and temporal distribution of PSCs. The results show that microplankton is found highly distributed in north-west and north-east AS and south-west AS during summer monsoon (June–September) and winter monsoon (December–March), respectively, due to nutrient and light availability, constituting only 16.60% of the entire phytoplankton biomass in the mean-field of 2003–2018. Conversely, nanoplankton encounters ubiquitous nature throughout the AS, constituting 51.80% of chl-a. Whereas picoplankton appeared to be dominant in lower latitudes of AS (i.e., south-east AS) because of their survival capability (nutrient and light-independent) in oligotrophic conditions, but constitute only 31.6% in the AS. Moreover, comparing sea surface temperature (SST) and photosynthetically active radiation (PAR) with the PSCs shows the relationship and distribution of PSCs towards favourable environmental conditions. Thus, PSCs estimation using reconstructed gap-free chlorophyll-a concentration provides a better understanding of PSCs shift and their dynamics on seasonal and temporal scales in the AS. [ABSTRACT FROM AUTHOR]

The duration of a single satellite deployment is insufficient to detect long-term trends in phytoplankton biomass. By integrating data from different platforms, we quantified the phytoplankton trends in the South China Sea (SCS) from the early-to-mid 1980s to the present. We focused on winter data because the sea surface temperature (SST) in winter has been increasing over the past three decades. We included data from three different eras: (1) the Coastal Zone Colour Scanner (CZCS) period (1979–1983), (2) the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) period (1998–2002), and (3) the Moderate Resolution Imaging Spectroradiometer (MODIS) period (2010–2014). There was a decline in phytoplankton (approximately 0.15 mg m−3) over the entire SCS from the CZCS period to the SeaWiFS period. The largest reduction (over 0.3 mg m−3) occurred in the northern and western SCS. After the SeaWiFS period, the phytoplankton increased by approximately 0.05 mg m−3. The largest increase was observed to the west of Luzon Strait, extending towards the east coast of Hainan Island. The fluctuations in phytoplankton from the early-to-mid 1980s to the present were consistent with the variation in the wind field rather than with the continued increase in SST. The wind speed decreased from the CZCS period to the SeaWiFS period and increased from the SeaWiFS period to the MODIS period. Moreover, the nutrient variations induced by the mixed-layer depth also contributed to the fluctuations in phytoplankton. [ABSTRACT FROM AUTHOR]

Yellowfin tuna (Thunnus albacares, Bonnaterre, 1788; YFT) face extensive exploitation pressure worldwide owing to the attractive economics of these fisheries. A better understanding of how oceanography influences the distribution of YFT (or highly migratory species more generally) will improve the ability for fisheries management policies to achieve conservation (e.g., maintain a stocks reproductive capacity), economic (e.g., maximize gross domestic product), and social (e.g., optimize successful fishing opportunities) objectives. Such ecosystem-based linkages, when combined with real-time remote sensing data, provide the predictive framework for enhancing favourable fishing opportunities and limiting excessive harvest. We examined factors influencing YFT distribution and behaviour using pop-up satellite archival tags and remotely sensed oceanographic data from two regions in the northern Indian Ocean. Tagged individuals did not exhibit significant deep diving or diurnal behaviour, and preferred ambient temperatures of 26–30°C and 25–29°C in the Arabian Sea (AS) and the Bay of Bengal (BoB), respectively. In general, tagged YFT were found to be in waters with sea surface temperatures of 26–29°C, 60% of the time and within a sea surface height-anomaly of ±6 cm 70% of the time. YFT avoided moving below the relatively shallow oxycline depth, which is indicative of the stratified waters of the AS and the BoB. Low dissolved oxygen levels are likely a limiting factor for tuna movement given their high oxygen demand. The northern Indian Ocean provides an opportunity to study climate impacts on fish distribution and movement, and our findings provide a basis for understanding how habitat and migratory patterns may be altered under climate change. [ABSTRACT FROM AUTHOR]

The hybrid sea surface temperature (SST) algorithm derives coefficients for SST estimation based on the regression procedure of incremental values between the satellite-observed brightness temperature (BT) minus the first-guess BT and the in-situ temperature minus the first-guess SST. In this study, the hybrid SST algorithm was applied to retrieve the SST coefficients of which the results were compared with extensively used regression algorithms of Multi-Channel SST (MCSST) and Non-Linear SST (NLSST) using data obtained by the Meteorological Imager of the first Korean geostationary satellite, the Communication, Ocean and Meteorological Satellite, in the Northwest Pacific Ocean in May 2014. The empirical regression SSTs and hybrid SSTs exhibited similar root-mean-squared errors in the range of 0.61–0.84°C. Although the SST errors were quite similar to each other, the comparison of the hybrid SSTs with the in-situ SSTs indicated a slightly higher accuracy of approximately 0.2°C compared with that of the empirically derived SSTs. SST retrieval using the hybrid algorithm reduced the errors near the cloud edges. The differences between the hybrid SST and regression SST tended to be greater when the distance to the nearest cloudy pixel was less than 0.2°. This study discusses the potential causes of the differences between the SST errors of the algorithms and addresses a few constraints in the execution of the hybrid algorithm related to the numerical model. [ABSTRACT FROM AUTHOR]

For high wind speeds (7–22 m s−1), a semi-theoretical model for retrieving sea surface salinity (SSS) is derived from the version V3.0 of Aquarius data. In the model, the sea surface brightness temperature is the sum of the brightness temperatures of foam-covered sea surface and rough sea surface, which is weighted by the foam coverage. The emissivity of foam layer is dealt with the effective permittivity of foam composites and the wave approach theory, where the air volume fraction and thickness of the foam layer are optimized with Aquarius data. Due to the influence of foam coverage, the foam contribution to the sea surface emissivity is smaller than that of the rough sea surface, only about 20% at 22 m s−1. Furthermore, the model is applied to retrieve Aquarius SSS for the wind speeds larger than 7 m s−1. The inverse accuracy is assessed by comparison with ARGO monthly gridded salinity products. The average root mean square error (RMSE) between the retrieved SSS and Argo SSS are about 0.20 and 0.30 psu for the latitude within 40° S–40° N and 70° S–70 N, respectively. The model improves the retrieval accuracy of SSS for high wind speeds. [ABSTRACT FROM AUTHOR]

Change detection within non-stationary and unequally spaced remote sensing time series has become a key methodology for a broad range of environmental applications. A new method of analysing vegetation variation over lands is proposed. Four regions in northern Tunisia with various characteristics are selected, and a non-stationary and unequally spaced Normalized Difference Vegetation Index (NDVI) time series is obtained for each region since 2000. The Landsat 7 remote sensing satellite imagery with insignificant cloud-shadow coverage is used to calculate the NDVI after atmospheric correction. The Least-Squares Wavelet (LSWAVE) software is implemented to rigorously analyse each NDVI time series and study the relationship between the vegetation of olive trees and temperature/precipitation in one of the regions. To investigate possible effects of temperature on the green cover caused by increasing water salinity, the coherency between the NDVI and sea surface temperature time series is also shown in the region of Lake Ichkeul in Tunisia. [ABSTRACT FROM AUTHOR]

Traditionally, moving ship detection by Synthetic Aperture Radar (SAR) image is primarily based on the ship wake feature. However, many ship wakes cannot be imaged by SAR owing to changes in imaging conditions, such as the SAR band, polarisation, incident angle, and sea state. In this study, we discovered a unique phenomenon called 'azimuth tail' from Radarsat-2 SAR images. Following research and analysis, we determined that the azimuth tail is not manifested as a visible disturbance on sea surface waves. Instead, it is an observation enabled by certain SAR imaging principles. Consequently, we propose a new method for extracting information on moving vessels after a preliminary analysis of the principle of the azimuth tail. The results of experimental analysis of the correctness of the method indicate that the error of the vessel's velocity from its azimuth tail is less than 20%, and the azimuth tail can be applied to the detection of moving vessels in oceans using Radarsat-2 SAR imagery. [ABSTRACT FROM AUTHOR]

The primary energy supply for tropical cyclones is the upward latent heat fluxes that are directly related to Sea Surface Temperatures (SST). The strong winds induce a negative SST anomaly in the tropical cyclone wake. This is usually referred to as the 'cold wake'. Many studies have suggested that the cold wake results in a significant reduction of upward latent heat fluxes that supply energy to the tropical cyclone, and hence provides a negative feedback on its intensity. The cold-wake feedback on the intensity of tropical cyclones is a strong motivation to understand the oceanic response to tropical cyclones. A recent study of re-examining the mechanisms controlling the cold wake has shown the importance of vertical Ekman pumping. Under the core of tropical cyclones (typically over a disk of 100 km radius), vertical pumping is responsible for a cooling of the entire water column, while surface heat fluxes and vertical mixing both contribute to the surface cooling during the cyclone passage. Farther away from the cyclone core, vertical mixing generally overwhelms the effect of vertical pumping, and also the effect of heat fluxes in the case of strong tropical cyclones. The study examines the Ekman pumping during the passage of few cyclonic storms in the Arabian Sea (AS) and Bay of Bengal (BOB) during last decade using different datasets such as Satellite (QuikScat) and reanalysis (ERA-Interim) data and calls up the value for satellite deliverables. Surface currents and subsurface temperature structure is examined further and for different Ekman pumping velocity (EPV), variable subsurface response is illustrated. The changes in ocean surface temperature, sea level and heat content obtained from the remote sensing data products, in the wake of cyclone are also reported and thus the usefulness of satellite products to study the coupled tropical system is demonstrated. [ABSTRACT FROM AUTHOR]

An efficient unsupervised method is developed for automatic segmentation of the area covered by upwelling waters in the coastal ocean of Morocco using the Sea Surface Temperature (SST) satellite images. The proposed approach first uses the two popular unsupervised clustering techniques, k-means and fuzzy c-means (FCM), to provide different possible classifications to each SST image. Then several cluster validity indices are combined in order to determine the optimal number of clusters, followed by a cluster fusion scheme, which merges consecutive clusters to produce a first segmentation of upwelling area. The region-growing algorithm is then used to filter noisy residuals and to extract the final upwelling region. The performance of our algorithm is compared to a popular algorithm used to detect upwelling regions and is validated by an oceanographer over a database of 92 SST images covering each week of the years 2006 and 2007. The results show that our proposed method outperforms the latter algorithm, in terms of segmentation accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

The summer upwelling of the Eastern Aegean Sea is investigated by daily night-time MODerate resolution Imaging Spectroradiometer Sea Surface Temperature scenes in the periods from June to November (extended summer) 2003-2015. The analysis is supported by wind data downloaded from the European Centre for Medium-Range Weather Forecasts Re-Analysis archive. On average over these summers, upwelling and Etesian wind occurred 69% and 78% of time, respectively. The highest correlation between upwelling and wind was found from June to September, with the beginning of the upwelling events shifted between 24 and 48 h after the start of the Etesian wind. The upwelling always begins in the same areas of the Eastern Aegean coast with the only differences that these areas tesian wind pattern. The largest upwelling events occurred in summers 2003-2009 and not in the following years of the study period. The upwelled cold surface water, still pushed by the persistent Etesian wind, fills part of South-Eastern Aegean and eventually outflows the Aegean Sea through Kassos and Karpathos Straits of the eastern Cretan Arc. [ABSTRACT FROM AUTHOR]

Sea-surface salinity (SSS) can be measured from space using a microwave sensor. However, achieving the desired accuracy in SSS retrieval is challenging due to the lower sensitivity of the brightness temperature to SSS especially at low sea-surface temperature conditions. The retrieval accuracy can be further degraded due to the atmospheric and sea-surface effects (including emission and reflection), which require more accurate correction methods based on the radiative transfer model. In this article, a vector radiative transfer model (VRTM) was developed based on a matrix operator method that considers the ocean-atmosphere system under non-raining conditions. The results from this model were compared with measurement data provided by the Soil Moisture and Ocean Salinity (SMOS) satellite sensor and the results from two other RT models (RT4 model and a forward model of the European Space Agency, ESA). Statistical evaluation of these results revealed that estimation errors of top of atmosphere (TOA) radiance by the VRTM model was less than 0.3% as compared to the RT4 model results. The difference of the brightness temperatures predicted by the VRTM model and measured by the SMOS was within 1.5 K which was better than the ESA's forward model predictions. These results suggest that the VRTM is relatively more accurate and has high computational efficiency for simulating the TOA brightness temperature for various scientific research and remote-sensing applications. [ABSTRACT FROM AUTHOR]

In this article, daily fields of sea surface temperature (SST) and sea level anomaly (SLA) of the Western Mediterranean Sea obtained in 2011-2013 are being co-analysed. The study is aimed at assessing potentials of the fields of SLA for manifestation of mesoscale eddies in the region of interest. First, the SST imagery was inspected visually and locations of mesoscale eddies noticed in the images were detected. After that, closed contours were extracted in the fields of SLA and their locations were compared with locations of eddies directly seen in the SST images. Such a comparison showed that among anticyclonic eddies found in SST, about 56.3% had corresponding closed contours of SLA; the percentage was increasing with increasing eddy diameter. For cyclonic eddies, supposedly due to their smaller spatial and time scales, such percentage was only about 20.2%. During the warm season, when the mixed layer is particularly shallow and the turbulence is closer to the two-dimensional model, the correspondence between eddies seen in SST and closed contours of SLA was higher than during the cold period. [ABSTRACT FROM AUTHOR]

The wintertime variations and distributions of sea surface temperature (SST) and thermal fronts associated with the spatial distribution of ichthyoplankton were investigated in the continental shelf waters of the southern East China Sea (ECS) by using 10 year (2005-2015) satellite SST images with an entropy-based edge detection method. The Mainland China Coastal Front and Kuroshio Front (KF) in winter (December to March) were examined with SST gradient magnitudes (GMs) of 0.20-0.40 and 0.30-0.45°C Km−1, respectively, along the 50 m and 100-200 m isobaths in the southern ECS. These two fronts coincided with isotherms of 14-16°C and 21-22°C, respectively. The Mainland China Coastal Front pattern remained fairly stable along the 50 m isobaths, and the coexisting SST front and upwelling were shifted seaward or shoreward with the recession or intrusion of the KF during the winters. Notably, the SST GMs of the KF showed a significant strengthening that was higher than those of the past two decades. Moreover, the total abundance of the nearshore waters of the KF (which was occupied by approximately 75% neritic species) was 23 times higher than that of the offshore waters (which was occupied by approximately 63.60% oceanic species). We suggest that the generation of the KF in winter may act as the biological barrier of oceanic organisms and larval fishes in the study area. [ABSTRACT FROM AUTHOR]

This study investigates the processes of occasional sea surface temperature (SST) fronts and their impacts on chlorophyll-a concentration (chl-a) in the South China Sea (SCS), based on satellite remote sensing and in situ observations in 2009-2013. The SST fronts were detected by an entropy-based edge detection algorithm method from satellite-derived SST images with a 0.011° grid size. Three offshore SST front case studies (S1, S2 and S3) at the peripheries of eddies in the northern SCS were studied. In case S1 in September 2013, two SST fronts were detected with gradient magnitudes (GMs) greater than 0.06°C km-1 in the cyclonic eddy and 0.08°C km-1 in the periphery waters, and the fronts only existed for one and two days, respectively. After three and seven days, the high chl-a was found in the strong SST front waters which were about 51 and 54% higher than the concentration in the surrounding waters. The depth of the maximum chl-a elevated from the subsurface (50 m) to the surface. In case S2 in August 2013, two SST fronts were detected at the periphery of an anti-cyclonic eddy with GM stronger than 0.06°C km-1 and only existed for one day. After two days, the chl-a in the SST front waters was about 40% higher than the levels in the surrounding waters. In case S3 in June 2009, the GM of the eddy-feature SST front was stronger than 0.12°C km-1 and existed for three days, which was generated by tropical cyclone Linfa. The chl-a in the eddy-feature phytoplankton bloom was 6 times higher than in the surrounding waters. The results show that, in general, occasional offshore SST fronts at peripheries of eddies have stronger influence on surface chl-a, comparing to those seasonal coastal and permanent offshore SST fronts, via ‘Wind Pump’ effects. [ABSTRACT FROM AUTHOR]

Whiting events, or waters with high concentrations of fine-grained calcium carbonate, have been previously reported in southwest Florida using three years of observations from the Moderate Resolution Imaging Spectroradiometer. Here, the initial case study has been expanded to 13 years (2003–2015) with a statistical analysis that includes environmental data to document and understand longer term temporal and spatial variability of whiting occurrence in the same region. Annual mean whiting coverage (km2) peaked in 2011 and 2012, with the highest daily coverage in 2008 (126.0 km2). Over the time series, whiting events showed spatial variability based on distance from shore. Whiting seasonality also varied within the extended time series. Multivariate linear and non-linear regressions between mean whiting coverage (km2) and several environmental variables (wind speed, sea surface temperature, precipitation, and nearby river discharge) were performed over the entire study region as well as subregions based on spatial division from the coast line. Statistically significant correlations have been found with sea surface temperature and river discharge in subregions. These findings suggest that although observing spatial and temporal patterns of whiting events is possible with modern satellites, understanding the mechanisms regulating their initiation and maintenance is more difficult. [ABSTRACT FROM AUTHOR]

The Cariaco Basin, located on the continental margin of the southeastern Caribbean Sea, has been a site of extensive oceanographic research since the early 1950s. Here we examined the seasonal and spatial variability in satellite wind, sea surface temperature (SST), surface chlorophyll (CHL), and primary production (PP) within the Cariaco Basin (1994-2009). This variability has implications in modulating the vertical flux of particulate material to the bottom of the basin. While cross-shore Ekman Transport was positive (upwelling inducing) year-round, it showed 20-60% higher values (stronger upwelling) in the eastern sub-basin, compared to the western sub-basin 1.35-2.77 m2 s-1 and 1.06-1.73 m2 s-1, respectively; p < 0.01). This translated into differences in CHL concentration and PP rates between the eastern and western Cariaco sub-basins. Long-term seasonal means of SST, CHL, and PP showed significant inter-basin differences (p < 0.01) between December and July; during that period the eastern basin was cooler (24.86 ± 1.03°C vs. 25.56 ± 0.80°C, p < 0.01), with higher CHL (0.50 mg m-3 vs. 0.35 mg m-3; p < 0.01) and PP (1763 ± 994 vs. 782 ± 129 mg C m-2 day-1, p < 0.01) than the western sub-basin. The eastern Cariaco sub-basin had larger seasonal amplitude and variability in oceanographic characteristics than the western sub-basin, while the western sub-basin had slightly higher and more variable seasonal riverine run-off inputs. These differences have implications for the interpretation of the paleoclimate sediment record stored in different sectors of the Cariaco Basin. [ABSTRACT FROM AUTHOR]

The daily sea surface temperatures (SSTs) derived from the visible and infrared scanning radiometer (VIRR) and microwave radiation imager (MWRI) aboard the Fengyun-3C (FY-3C) satellite are evaluated against the measurements ofin-situSST and Reynolds optimum interpolation daily 0.25° SST (OISST) products. Statistical results for 2015 reveal a mean bias ± standard deviation of error () for the daytime VIRR SST, night-time VIRR SST, daytime MWRI SST (MWRID), and night-time MWRI SST (MWRIN) of 0.5877 ± 1.3279°C, −0.4801 ± 1.2588°C, 0.6044 ± 3.9064°C, and 0.7653 ± 3.7307°C, respectively. According to the SST bias performance of each product for different periods and latitudes, it is clear that the SST biases of the VIRR products are the largest at low latitudes and are relatively lower at mid-high latitudes and that negative SST biases in the VIRR increase with varying time. Large abnormal SST biases from MWRI products occur in Time III (the 211th to 319th day of 2015), and the average values of the SST biases are 3.6010°C and 3.7822°C for the MWRID and MWRIN, respectively. We expect that our validation results for VIRR and MWRI products can help algorithm developers further enhance the accuracy of SST retrievals while also helping sensor designers improve the performance of sensors for the next generation of FY satellites. [ABSTRACT FROM AUTHOR]

A step by step algorithm for air–sea CO2 flux (F(CO2)) calculation from satellite parameters is presented in this study. Parameters used for F(CO2) calculation are: (1) sea surface temperature (SST) and chlorophyll-a (chl-a) from Moderate Resolution Imaging Spectroradiometer Aqua (MODIS Aqua), (2) sea surface salinity (SSS) estimated from MODIS Aqua SST using multiple linear regression, (3) seawater CO2 fugacity (f(CO)) estimated by MODIS Aqua SST and chl-a using feedforward neural networks, (4) atmospheric CO2 fugacity (f(CO)) from the Cape Grim station, and (5) wind speed from the Quick and Advanced Scatterometer (QSCAT and ASCAT). In situ data provided by (1) the Surveillance de l'Océan Austral – Monitoring the Southern Ocean (SURVOSTRAL) project, (2) the Integrated Marine Observed System (IMOS) project, and (3) Mesures à l'INterface Eau-aiR de la Variabilité des échanges de CO2 (MINERVE) project collected on the research vessel L'Astrolabe, are used to establish and validate the models. These models are then tested using remote sensing data. This work focus on the southern ocean from the south of Australia to the Antarctica coasts (between 43.5° S and 67° S), on the period of spring and Austral summer (from October to March, between 2002/2003 and 2014/2015). In each step, the result's precision of experiments was determined by the root mean square error (RMSE). Results show (1) an improvement of satellite SSS estimation with a precision of ±0.16 using SST and latitude, (2) an estimation of f(CO) by satellite data with a good accuracy of ±9.45 µatm (0.96 Pa), and (3) a calculation of F(CO2) using satellite data with a global RMSE of about ±3 mmol CO2 m–2 day–1. The interpolated F(CO2) shows that, in the period of austral spring and summer, this region absorbs the atmospheric CO2, and becomes a stronger sink of CO2 throughout the years (from an overall average absorption of about 2 mmol CO2 m–2 day–1 in 2002/2003 to about 7 mmol CO2 m–2 day–1 in 2014/2015). [ABSTRACT FROM AUTHOR]

Remotely derived environmental variables, including sea surface height anomaly (SSHA), sea surface temperature (SST), chlorophyll-a (chl-a), eddy kinetic energy (EKE), mixed layer data set of argo float (MLD), Niño 3.4 index, and bigeye tuna catch data for the period 1997-2008, were used to analyse ocean climate variability and how they relate to the hotspots of bigeye tuna catch in the eastern Indian Ocean off Java. The empirical orthogonal function (EOF) was performed to obtain a more detailed structure of the spatio-temporal ocean variability in the region. The results showed that the first EOF modes of chl-a, SSHA, and SST accounted for 42.8%, 36.5%, and 27.4% of total variance, respectively, and these corresponded to the interannual signal. The maps of spatial patterns of the first EOF modes of SSHA, SST, and chl-a gave very typical values for cold-water SSHA, low SST, and high chl-a concentration along the southern coast of the Indonesian archipelago; and warm-water SSHA, high SST, and low chl-a concentration in the offshore region to make frontal areas along the latitudinal line around 10-12° S. The EOF analysis further revealed a strong relationship between the El Niño event and favourable oceanographic conditions, resulting in a significant increase in bigeye tuna catch. The average hook rate of 0.71 (0.43) was recorded during El Niño (La Niña). Major hotspots were located away from the confluence region and frontal areas around 11-16° S and 110-118° E and were thus demonstrated as the most favourable oceanographic conditions for bigeye tuna fishing in the eastern Indian Ocean off Java. [ABSTRACT FROM AUTHOR]

The decadal variability of sea surface temperature (SST) and sea level pressure (SLP) anomalies, as well as the response of global land vegetation and marine fisheries, are investigated for three periods: 1982–1988, 1989–1998, and 1999–2008, separated by the 1988–89 and 1998–99 regime shifts. The goal is to develop a global-scale ecosystem concept to support an improved understanding of the corresponding changes in atmospheric, oceanic, and biological responses. The analysis is based on global SST, SLP, precipitable water content (PWC), land vegetation condition index (VCI), and the United Nations Food and Agriculture Organization’s (FAO) fish capture data. The results show that SST and SLP displayed significant decadal variability. The decadal variability of sea surface temperature anomalies (SSTA) associated with sea level pressure anomalies (SLPA) has an influence on the land vegetation moisture condition (VCI). Positive SSTA tends to be associated with negative SLPA, and vice versa, in the corresponding ocean areas and most land areas. Consequently, clearly opposing distributions of SSTA and SLPA are observed in the periods 1982–1988 and 1999–2008. With positive SSTA and negative SLPA, VCI tends to increase in value representing more favourable vegetation conditions. Negative SSTA and positive SLPA is generally unfavourable for global vegetation development. The decadal variability of SSTA is closely related to the number of fish species (NFS) doing better or worse based on normalized fish landing data. However, the fishery responses show different yet consistent trends in the three ocean basins. When SSTA is negative, it appears more beneficial for the number of fish species with improved landings in the Atlantic Ocean. However, positive SSTA leads to more fish species with improved landings in the Indian and Pacific Oceans. [ABSTRACT FROM PUBLISHER]

Ommastrephes bartramiiis a short-lived species of squid and reacts rapidly to changes in the regional environmental conditions of the fishing ground. Understanding the preferred range of key environmental variables and predicting potential resource distributions are critical to conserve and manage its resources. Commercial fishery data for the western winter–spring cohort ofO. bartramiifrom Chinese squid-jigging vessels during 2003–2013 were used to evaluate a suitable range of three key environmental variables, sea surface temperature (SST), sea surface height (SSH), and chlorophyll-a(chl-a) concentration, and to explore potential fishing zones (PFZs) using an artificial neural network. The neural interpretation diagram and independent variable relevance analysis indicate that month, latitude, and SST had significant influences on the PFZ distribution ofO. bartramii, yielding 21.78%, 23.91%, and 26.04% of contribution rates, respectively. Based on the sensitivity analyses, a high abundance ofO. bartramiimainly occurred in the waters between 150°–165° E and 37°–42° N during July to August. Suitable ranges of environmental variables forO. bartramiiwere 11–18°C for SST, −10 to 60 cm for SSH, and 0.1–1.7 mg/m3for chl-aconcentration, respectively. The back-propagation network model was well developed and could be used to predict the PFZ with 80% accuracy. The actual fishing grounds coincided with the predicted PFZ, suggesting that the established model of PFZ is effective in forecasting the potential habitat ofO. bartramiiin the Northwest Pacific Ocean. [ABSTRACT FROM PUBLISHER]

A main objective of the Global Space-Based Inter-Calibration System (GSICS) is to ensure consistent accuracy of thermal infrared (IR) channels of satellite measurements. In this article, IR channels observed by the Communication, Ocean, and Meteorological Satellite (COMS) were corrected using observations by the Infrared Atmospheric Sounding Interferometer (IASI) on board Meteorological Operation (MetOp) satellites as a reference. We then produced sea surface temperature (SST) products using GSICS-corrected COMS/Meteorological Imager (MI) IR data and evaluated the accuracies of the SST data by comparing with buoy data. Our results showed that SST produced from GSICS-corrected IR data was more accurate than that from original IR data, with a difference of 0.01–0.2ºC. Differences in SST between the original and GSICS-corrected IR showed a linear proportional relationship around IR2(12.0 μm) during the day and IR1(10.8 μm) at night. In the IR1analysis, accuracies of daytime SST were improved significantly when the GSICS correction was applied to COMS IR data; also, the mean and median values of SST discrepancies (between the original and GSICS-corrected IR) according to changes in brightness temperature difference (BTD) were close to 0ºC. We found that the accuracies of SST estimation from satellite IR bands were greatly improved by applying the GSICS correction. [ABSTRACT FROM AUTHOR]