Search Results (14)

Measurements of temperature, salinity, and currents in the Amazon River plume over a section in the open ocean of the western tropical North Atlantic (38°48′ W) are considered. The measurements were carried out using an AML Base X CTD probe in the upper layer and a flow-through system that measures salinity, turbidity, and chlorophyll-a content in seawater while a vessel is on the way. The measurements were supplemented by velocity profiling using shipborne SADCP. Additionally, archived oceanographic data from the World Ocean Database (WOD18), data on satellite altimetry measurements (AVISO), and satellite salinity data from Aquarius and SMOS were used. It is shown that the width of the Amazon River plume is about 170–400 km and the depth of desalination is from 50 to 100 m. Surface salinity decreases compared to the background (36.1) by 0.25 in February and by more than 3.0 in September during the period of maximum development of the plume, which was determined from satellite measurements of surface salinity. Lagrangian modeling of the back-in-time advection of passive markers simulating freshwater particles was carried out. It was shown that the source of freshwater in the measurement area is discharge from the Amazon River. Amazon River freshwater covered a distance of 3300 km in 60–80 days. The estimate of freshwater transport in the plume was 0.02 Sv, which is one order of magnitude smaller than the mean river discharge. Full article

The strong wind-induced current and sea level have influences on the wave distribution in a tropical cyclone (TC). In particular, the wave–current interaction is significant in the period in which the TC passed the mesoscale eddy. In this study, the wave fields of Typhoon Chan-hom (2015) are hindcastly simulated using a coupled oceanic model that utilizes a nested triangle grid, i.e., the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE) model. The forcing wind field is composited from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the simulation using a parametric Holland model, denoted as H-E. The open boundary fields include tide data from TPOX.5 and the hybrid coordinate ocean model (HYCOM) global datasets, including sea surface temperature (SST), sea surface salinity, sea surface current, and sea level data. The simulated oceanic parameters (e.g., the significant wave height, SWH) are validated against the measurements from the Jason-2 altimeter, yielding a root mean square error (RMSE) of 0.58 m for the SWH, a correlation (COR) coefficient of 0.94, and a scatter index (SI) of 0.23. Similarly, the simulated SSTs are compared with the remote sensing products of the remote sensing system (REMSS) and the measurements from Argos, yielding an RMSE of <0.8 °C, a COR of >0.95, and an SI of <0.04. The significant zonal asymmetry of the wave distribution along the typhoon track is observed. The Stokes drift is calculated from the FVCOM-SWAVE simulation results, and then the contribution of the Stokes transport is estimated using the Ekman–Stokes numbers. It is found that the ratio of the Stokes transport to the total net transport can reach >80% near the typhoon center, and the ratio is reduced to approximately <20% away from the typhoon center, indicating that Stokes transport is an essential aspect in the water mixing during a TC. The mesoscale eddies are detected by the sea level anomalies (SLA) fusion data from AVISO. It is found that the significant wave heights, Stokes drift, and Stokes transport inside the eddy area were higher than those outside the eddy area. These parameters inside the cold mesoscale eddies were higher than t inside the warm mesoscale eddies. Otherwise, the SST mainly increased within the cold mesoscale eddies area, while decreased within the warm mesoscale eddies area. The influence of mesoscale eddies on the SST was in proportion to the eddy radius and eddy EKE. Full article

The main aim of this work is to study the spatial–temporal variability of the model’s physical and spectral characteristics in the process of assimilation of observed ocean surface height data from the AVISO (Archiving, Validating and Interpolation Satellite Observation) archive in combination with the NEMO (Nucleus for European Modeling of the Ocean) ocean circulation model for a period of two months. For data assimilation, the GKF (Generalized Kalman filter) method, previously developed by the authors, is used. The purpose of this work is to study the spatial–temporal structure of the simulated characteristics using decomposition into eigenvalues and eigenvectors (Karhunen–Loeve decomposition method). The feature of the GKF method is the fact that the constructed Kalman weight matrix multiplied by the vector of observational data can be represented as a weighted sum of eigenvectors and eigenvalues (spectral characteristics of the matrix), which describe the spatial and temporal structure of corrections to the model. The main investigations are focused on the North Atlantic. Their variability in time and space is estimated in this study. Calculations of the main ocean characteristics, such as the surface height, temperature, salinity, and the current velocities on the surface and in the depths, both with and without assimilation of observational data, over a time interval of 60 days, were performed by using a high-performance computing system. The calculation results have shown that the main spatial variability of characteristics after data assimilation is consistent with the localization of the currents in the North Atlantic. Full article

Sea level rise will significantly impact coastal areas around the world. As a coastal country, Malaysia’s rising sea levels are a significant concern because they would affect 70% of its population. The study of sea level rise is important in order to implement effective mitigation and adaptation strategies. This study investigates the performance of CMIP6 Global Climate Models (GCMs) in simulating sea level rise in the Malaysian seas using various statistical methods. The models’ performances were evaluated by comparing historic CMIP6 GCM runs from 1993 to 2010 with sea level measurements from the satellite altimetry AVISO+ using the Taylor diagram. The SCS (SCSPM and SCSEM) had a higher sea level range and trend in both selected areas than the SM and SS. With 1.5 °C warmings, the multi-model ensemble means predicted that the SCS would rise by 16 mm near the Peninsular, with sea levels increasing by 0.908 m at a rate of 1.5 mm/year, and by 14.5 mm near East Malaysia, with sea levels increasing by 0.895 m at a rate of 1.1 mm/year. In contrast, 2.0 °C warmings project that SCSPM and SCSEM would cause sea levels to rise by 20.2 mm and 21.5 mm, respectively, at a rate of 0.6 mm/year and 0.7 mm/year. This information will provide an insight into Malaysian sea levels between now and the end of the twenty-first century, which will be beneficial for government agencies, academics, and relevant stakeholders. Full article

The oceanic Kármán vortex street is an important hydrokinetic phenomenon caused by the unsteady separation of sea currents in the wake of an obstacle. This study quantitatively analyzed the characteristics of the small-scale vortex street of Didicas Island in the Luzon Strait based on multimission satellite data. Five groups of vortex streets were captured, and each group was observed by two satellite images within one hour. Based on the displacement and change in the vortex street within one hour, we found that the formation time of a single vortex is longer than 40 min. The vortex propagation speed behind the island is approximately 0.98 m s⁻¹ (ranging from 0.66–1.22 m s⁻¹). The incoming velocity was calculated using the vortex propagation speed and the aspect ratio based on a vortex propagation model, which ranges from 0.72 to 1.47 m s⁻¹ The incoming speed is 1.6–2.3 times the geostrophic speed extracted from AVISO data, implying that the contribution of non-geostrophic flow to the total flow field is comparable to that of geostrophic flow in this region. Full article

Marine aquaculture has proliferated over the past decade, expanding into new, untapped open-water cultivation areas, such as lakes, rivers and deeper offshore environments, in response to increasing demand for seafood by consumers. However, to ensure sustainable development, it is necessary to minimize the impact of other ocean activities and the environment through science-based spatial planning. The choice of the primary site (physical carrying capacity) depends mainly on the aquaculture system, which varies around the world. However, the site is considered one of the factors (production, ecological and social) keys to any aquaculture operation, especially in the African continent. This choice affects both the success and sustainability of the products cultivated and the resolution of conflicts between different activities as well as the rational use of space. This study aims to identify suitable areas (primary site selection) for aquaculture in the Moroccan Atlantic continental shelf focused on the sub-area located between Cap Ghir 31.25° and Tarfaya 27.47°, based on the assessment of the dominant wave energy by implementing the hydrodynamical SWAN (Simulating Waves Nearshore) model dedicated for this kind of study. We derived the inputs for the SWAN model from WW3 (WAVEWATCH III model), which the AVISO data-products have extensively validated. The results show that, even if the Atlantic area is known for the agitation of its seas, there is the possibility of having adequate areas for aquaculture with an overall capacity that could extinguish the 389 ha in the study area if aquatic cultivation manages to exploit the offshore areas. At the level of the sub-zone belonging to the sous-Massa region (zone 1), the results show a strong coherence between the values of the surfaces estimated by the study and the actual values resulting from the development plan, with a value of 69 Ha for the first and 75 for the second, i.e., equal to 6 Ha, due to the geomorphology of the coast and natural coastal shelters, which play favorably on the environment for aquaculture development. These areas may attract the greed of investors, although they are in the process of being the subject of an aquaculture development plan. Full article

In this paper, we consider a recently developed data assimilation method, the Generalized Kalman Filter (GKF), which is a generalization of the widely-used Ensemble Optimal Interpolation (EnOI) method. Both methods are applied for modeling the Atlantic Ocean circulation using the known Hybrid Coordinate Ocean Model. The along-track altimetry data taken from the Archiving, Validating and Interpolating Satellite Oceanography Data (AVISO) were used for data assimilation and other data from independent archives of observations; particularly, the temperature and salinity data from the Pilot Research Array in the Tropical Atlantic were used for independent comparison. Several numerical experiments were performed with their results discussed and analyzed. It is shown that values of the ocean state variables obtained in the calculations using the GKF method are closer to the observations in terms of standard metrics in comparison with the calculations using the standard data assimilation method EnOI. Furthermore, the GKF method requires less computational effort compared to the EnOI method. Full article

The significant wave height (SWH) of oceans is the main parameter in describing the sea state, which has been widely used in the establishment of ocean process models and the field of navigation and transportation. However, traditional methods such as satellite radar altimeters and buoys cannot achieve SWH estimations with high spatial and temporal resolution. Recently, the spaceborne Global Navigation Satellite System reflectometry (GNSS-R) has provided an opportunity to estimate SWH with a rapid global coverage and high temporal resolution observations, particularly with the Cyclone Global Navigation Satellite System (CYGNSS) mission. In this paper, SWH was estimated using the polynomial function relationship between SWH from ERA5 and Delay-Doppler Map Average (DDMA) as well as Leading Edge Slope (LES) from CYGNSS data. Then, the SWH estimated from CYGNSS data was validated by ERA-Interim data, AVISO data, and buoy data. The results showed that the average correlation coefficient of CYGNSS SWH was 0.945, and the average RMSE was 0.257 m when compared to the ERA-Interim SWH data. The RMSE was 0.423 m and the correlation coefficient was 0.849 when compared with the AVISO SWH. The correlation coefficient with the buoy data was 0.907, and the RMSE was 0.247 m. This method can provide suitable SWH estimation data for ocean dynamics research and ocean environment prediction. Full article

The spatial–temporal variability of the calculated characteristics of the ocean in the Arctic zone of Russia is studied. In this study, the known hydrodynamic model of the ocean Nucleus for European Modelling of the Ocean (NEMO) is used with assimilation of observation data on the sea surface height taken from the Archiving, Validating and Interpolation Satellite Observation (AVISO) archive. We use the Generalized Kalman filter (GKF) method, developed earlier by the authors of this study, in conjunction with the method of decomposition of symmetric matrices into empirical orthogonal functions (EOF, Karhunen–Loeve decomposition). The investigations are focused mostly on the northern seas of Russia. The main characteristics of the ocean, such as the current velocity, sea surface height, and sea surface temperature are calculated with data assimilation (DA) and without DA (the control calculation). The calculation results are analyzed and their spatial–temporal variability over a time period of 14 days is studied. It is shown that the main spatial variability of characteristics after DA is in good agreement with the localization of currents in the North Atlantic and in the Arctic zone of Russia. The contribution of each of the eigenvectors and eigenvalues of the covariation matrix to the spatial–temporal variability of the calculated characteristics is shown by using the EOF analysis. Full article

An improved Fourier series model (FSM01) method is used in geophysical and environmental corrections to enhance the final product of the along-track Jason-2 sea level anomaly (SLA) data and extend it near the Red Sea borders. In this study, the ionospheric correction range, wet tropospheric correction range, sea state bias correction range, and dry tropospheric correction range are enhanced and improved using FSM01, which helped to retrieve three more tracks (106, 170, and 234) earlier neglected by the distribution centers and extend the tracks toward the coast. The FSM01 SLA is compared with Jason-2 SLA and Archiving Validation and Interpretation of Satellite Oceanographic (AVISO) SLA for the available five tracks, in which the FSM01 SLA shows a good agreement and higher correlation with the Jason-2 SLA compared with that of AVISO, in addition to filling the gaps in the times series of all tracks. The newly retrieved tracks are also compared with those retrieved by AVISO, and both data points show similar variability, with FSM01 SLA showing no gaps in the time series. The FSM01 SLA was also extended toward the coast and showed high correlation with the coastal tide measurements. Full article

Mean sea surface height (MSSH) is an important parameter, which plays an important role in the analysis of the geoid gap and the prediction of ocean dynamics. Traditional measurement methods, such as the buoy and ship survey, have a small cover area, sparse data, and high cost. Recently, the Global Navigation Satellite System-Reflectometry (GNSS-R) and the spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission, which were launched on 15 December 2016, have provided a new opportunity to estimate MSSH with all-weather, global coverage, high spatial-temporal resolution, rich signal sources, and strong concealability. In this paper, the global MSSH was estimated by using the relationship between the waveform characteristics of the delay waveform (DM) obtained by the delay Doppler map (DDM) of CYGNSS data, which was validated by satellite altimetry. Compared with the altimetry CNES_CLS2015 product provided by AVISO, the mean absolute error was 1.33 m, the root mean square error was 2.26 m, and the correlation coefficient was 0.97. Compared with the sea surface height model DTU10, the mean absolute error was 1.20 m, the root mean square error was 2.15 m, and the correlation coefficient was 0.97. Furthermore, the sea surface height obtained from CYGNSS was consistent with Jason-2′s results by the average absolute error of 2.63 m, a root mean square error ( $\mathrm{RMSE}$ ) of 3.56 m and, a correlation coefficient ( $R$ ) of 0.95. Full article

Eddies can be identified and tracked based on satellite altimeter data. However, few studies have focused on nowcasting the evolution of eddies using remote sensing data. In this paper, an improved Convolutional Long Short-Term Memory (Conv-LSTM) network named Prednet is used for eddy nowcasting. Prednet, which uses a deep, recurrent convolutional network with both bottom-up and top-down connects, has the ability to learn the temporal and spatial relationships associated with time series data. The network can effectively simulate and reconstruct the spatiotemporal characteristics of the future sea level anomaly (SLA) data. Based on the SLA data products provided by Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) from 1993 to 2018, combined with an SLA-based eddy detection algorithm, seven-day eddy nowcasting experiments are conducted on the eddies in South China Sea. The matching ratio is defined as the percentage of true eddies that can be successfully predicted by Conv-LSTM network. On the first day of the nowcasting, matching ratio for eddies with diameters greater than 100 km is 95%, and the average matching ratio of the seven-day nowcasting is approximately 60%. In order to verify the performance of nowcasting method, two experiments were set up. A typical anticyclonic eddy shedding from Kuroshio in January 2017 was used to verify this nowcasting algorithm’s performance on single eddy, with the mean eddy center error is 11.2 km. Moreover, compared with the eddies detected in the Hybrid Coordinate Ocean Model data set (HYCOM), the eddies predicted with Conv-LSTM networks are closer to the eddies detected in the AVISO SLA data set, indicating that deep learning method can effectively nowcast eddies. Full article

In recent years, two drought monitoring systems have been developed in the Czech Republic based on the SoilClim and AVISO soil moisture models. The former is run by Mendel University and Global Change Research Institute (CAS), while the latter, by the Czech Hydrometeorological Institute. SoilClim is based more on real soil properties and aimed primarily at agriculture, while AVISO complements the system with more theoretical presumptions about soil, showing, rather, climatological potential. Both soil moisture models were complemented by forecasts on a daily basis, taking meteorological inputs from NWP (Numerical Weather Prediction) models and thus giving short- to mid-range outlooks up to 9 days ahead. Validation of the soil moisture and drought intensity prediction was performed and is presented in this article showing its prediction reliability and potential. In the analysis, we focus mainly on the past year, 2017. The tool has strong predictive power for soil moisture and drought intensity so it is suitable for farmers who need to make decisions about irrigation and production activities. The presented system is fully functional and can be applied in the coming years. Full article

This study addresses the impact of satellite altimetry data processing on sea levelstudies at regional scale, with emphasis on the influence of various geophysical correctionsand satellite orbit on the structure of the derived interannual signal and sea level trend. Thework focuses on the analysis of TOPEX data for a period of over twelve years, for threeregions in the North Atlantic: Tropical (0^o≤φ≤25^o), Sub-Tropical (25^o≤φ≤50^o) and Sub-Arctic (50^o≤φ≤65^o). For this analysis corrected sea level anomalies with respect to a meansea surface model have been derived from the GDR-Ms provided by AVISO by applyingvarious state-of-the-art models for the geophysical corrections. Results show that sea leveltrend determined from TOPEX altimetry is dependent on the adopted models for the majorgeophysical corrections. The main effects come from the sea state bias (SSB), and from theapplication or not of the inverse barometer (IB) correction. After an appropriate modellingof the TOPEX A/B bias, the two analysed SSB models induce small variations in sea leveltrend, from 0.0 to 0.2 mm/yr, with a small latitude dependence. The difference in sea leveltrend determined by a non IB-corrected series and an IB-corrected one has a strong regionaldependence with large differences in the shape of the interannual signals and in the derivedlinear trends. The use of two different drift models for the TOPEX Microwave Radiometer(TMR) has a small but non negligible effect on the North Atlantic sea level trend of about0.1 mm/yr. The interannual signals of sea level time series derived with the NASA and theCNES orbits respectively, show a small departure in the middle of the series, which has noimpact on the derived sea level trend. These results strike the need for a continuousimprovement in the modelling of the various effects that influence the altimetermeasurement. Full article