scholarly journals SPATIO-TEMPORAL CHARACTERISTICS OF SEA LEVEL ANOMALY IN THE INDONESIAN WATER

GEOMATIKA ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 103
Author(s):  
Dina Anggreni Sarsito ◽  
Dudy Darmawan Wijaya ◽  
Nur Fajar Trihantoro ◽  
Muhammad Syahrullah Fathulhuda ◽  
Dhota Pradipta
Keyword(s):  
Sea Level ◽  
Geographical Location ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Sea Level Anomaly ◽  
Level Data ◽  
Mean Sea Surface ◽  
Spatio Temporal ◽  
East Asia Region ◽  
The Impact

<p>Indonesia is an archipelago state lies between Indian and Pacific Oceans at the South East Asia region. Its unique geomorphological and geographical setting affect variabilities of instantaneous sea surface height (ISSH) concering to one of the sea reference surface i.e mean sea surface height (MSSH). The differences between both heights, known as sea level anomaly (SLA), can be recognized as one of the parameter that describes the dynamic phenomena of the ocean. We investigated the Spatiotemporal characteristics of long-term SLA in this research based on 30 years of sea-level data derived from the multi-mission of satellite Altimetry (Topex/Poseidon, Jason-1, Jason-2 and Jason-3). The Spatiotemporal of SLA characteristics in Indonesian waters indicate substantial variations due to the influences of geographical location, bathymetric depth, and seasonal patterns. The SLA rate in the Indonesian region provides values that vary between 3.4 mm/yr to 5.3 mm/yr that higher than 3.2 mm/yr global SLA rate. The impact caused by the phenomenon needs to be taken into account given the vulnerability and disaster that could endanger the islands and coastal area in Indonesia. <strong></strong></p>

scholarly journals Arctic sea surface height maps from multi-altimeter combination

2021 ◽  
Author(s):  
Pierre Prandi ◽  
Jean-Christophe Poisson ◽  
Yannice Faugère ◽  
Amandine Guillot ◽  
Gérald Dibarboure
Keyword(s):  
Sea Level ◽  
Sea Surface Height ◽  
Open Ocean ◽  
Sea Surface ◽  
Optimal Interpolation ◽  
Independent Data ◽  
Interpolation Scheme ◽  
Sea Level Anomaly ◽  
Arctic Sea ◽  
The Cross

Abstract. We present a new Arctic sea level anomaly dataset, based on the combination of three altimeter missions using an optimal interpolation scheme. Measurements from SARAL/AltiKa, CryoSat-2 and Sentinel-3A are blended together providing an unprecedented resolution for this type of products. The final gridded fields cover all latitudes north of 50° N, on a 25 km EASE2 grid, with one grid every three days over three years from July 2016 to April 2019. We use the Adaptive retracker to process both open ocean and lead echoes on SARAL/AltiKa thus removing the need to estimate a bias between open ocean an ice covered areas. SARAL/AltiKa also provides the baseline for the cross-calibation of CryoSat-2 and Sentinel-3A data. When compared to independent data, the combined product exhibits a much better performance than previously available datasets based on the analysis of a single mission.

The new Black Sea Reanalysis System within CMEMS

2021 ◽  
Author(s):  
Leonardo Lima ◽  
Stefania Angela Ciliberti ◽  
Ali Aydogdu ◽  
Romain Escudier ◽  
Simona Masina ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Black Sea ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface Height ◽  
Sea Surface ◽  
The Black Sea ◽  
Freshwater Flux ◽  
Sea Level Anomaly

&lt;p&gt;Ocean reanalyses are becoming increasingly important to reconstruct and provide an overview of the ocean state from the past to the present-day. These products require advanced scientific methods and techniques to produce a more accurate ocean representation. In the scope of the Copernicus Marine Environment Monitoring Service (CMEMS), a new Black Sea (BS) reanalysis, BS-REA (BSE3R1 system), has been produced by using an advanced variational data assimilation method to combine the best available observations with a state-of-the-art ocean general circulation model. The hydrodynamical model is based on Nucleus for European Modeling of the Ocean (NEMO, v3.6), implemented for the BS domain with horizontal resolution of 1/27&amp;#176; x 1/36&amp;#176;, and 31 unevenly distributed vertical levels. NEMO is forced by atmospheric surface fluxes computed via bulk formulation and forced by ECMWF ERA5 atmospheric reanalysis product. At the surface, the model temperature is relaxed to daily objective analysis fields of sea surface temperature from CMEMS SST TAC. The exchange with Mediterranean Sea is simulated through relaxation of the temperature and salinity near Bosporus toward a monthly climatology computed from a high-resolution multi-year simulation, and the barotropic Bosporus Strait transport is corrected to balance the variations of the freshwater flux and the sea surface height measured by multi-satellite altimetry observations. A 3D-Var ocean data assimilation scheme (OceanVar) is used to assimilate sea level anomaly along-track observations from CMEMS SL TAC and available in situ vertical profiles of temperature and salinity from both SeaDataNet and CMEMS INS TAC products. Comparisons against the previous Black Sea reanalysis (BSE2R2 system) show important improvements for temperature and salinity, such that errors have significantly decreased (about 50%). Temperature fields present a continuous warming in the layer between 25-150 m, within which there is the presence of the Black Sea Cold Intermediate Layer (CIL). SST exhibits a positive bias and relatively higher root mean square error (RMSE) values are present in the summer season. Spatial maps of sea level anomaly reveal the largest RMSE close to the shelf areas, which are related to the mesoscale activity along the Rim current. The BS-REA catalogue includes daily and monthly means for 3D temperature, salinity, and currents and 2D sea surface height, bottom temperature, mixed layer fields, from Jan 1993 to Dec 2019.&amp;#160; The BSE3R1 system has produced very accurate estimates which makes it very suitable for assessing more realistic climate trends and indicators for important ocean properties.&lt;/p&gt;

Assimilating Along-Track Altimetric Observations through Local Hydrostatic Adjustment in a Global Ocean Variational Assimilation System

2011 ◽  
Vol 139 (3) ◽  
pp. 738-754 ◽  
Author(s):  
Andrea Storto ◽  
Srdjan Dobricic ◽  
Simona Masina ◽  
Pierluigi Di Pietro
Keyword(s):  
Sea Level ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Global Ocean ◽  
Dynamic Topography ◽  
Sea Level Anomaly ◽  
Mean Dynamic Topography ◽  
Skill Scores ◽  
The Mean ◽  
Along Track

Abstract A global ocean three-dimensional variational data assimilation system was developed with the aim of assimilating along-track sea level anomaly observations, along with in situ observations from bathythermographs and conventional sea stations. All the available altimetric data within the period October 1992–January 2006 were used in this study. The sea level corrections were covariated with vertical profiles of temperature and salinity according to the bivariate definition of the background-error vertical covariances. Sea level anomaly observational error variance was carefully defined as a sum of instrumental, representativeness, observation operator, and mean dynamic topography error variances. The mean dynamic topography was computed from the model long-term mean sea surface height and adjusted through an optimal interpolation scheme to account for observation minus first-guess biases. Results show that the assimilation of sea level anomaly observations improves the model sea surface height skill scores as well as the subsurface temperature and salinity fields. Furthermore, the estimate of the tropical and subtropical surface circulation is clearly improved after assimilating altimetric data. Nonnegligible impacts of the mean dynamic topography used have also been found: compared to a gravimeter-based mean dynamic topography the use of the mean dynamic topography discussed in this paper improves both the consistency with sea level anomaly observations and the verification skill scores of temperature and salinity in the tropical regions. Furthermore, the use of a mean dynamic topography computed from the model long-term sea surface height mean without observation adjustments results in worsened verification skill scores and highlights the benefits of the current approach for deriving the mean dynamic topography.

scholarly journals Measurement of the Sea Surface Height with Airborne GNSS Reflectometry and Delay Bias Calibration

2021 ◽  
Vol 13 (15) ◽  
pp. 3014
Author(s):  
Feng Wang ◽  
Dongkai Yang ◽  
Guodong Zhang ◽  
Jin Xing ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Arrival Time ◽  
Elevation Angle ◽  
Satellite System ◽  
Sea Surface Height ◽  
Antenna Pattern ◽  
Sea Surface ◽  
Observation Method ◽  
Global Navigation Satellite ◽  
The Impact

Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.

Contributions of Wind Forcing and Surface Heating to Interannual Sea Level Variations in the Atlantic Ocean

2006 ◽  
Vol 36 (9) ◽  
pp. 1739-1750 ◽  
Author(s):  
Cécile Cabanes ◽  
Thierry Huck ◽  
Alain Colin de Verdière
Keyword(s):  
Atlantic Ocean ◽  
Sea Level ◽  
Wind Stress ◽  
Large Scale ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Altimeter Data ◽  
Local Response ◽  
Sea Level Variability ◽  
Sea Level Variations

Abstract Interannual sea surface height variations in the Atlantic Ocean are examined from 10 years of high-precision altimeter data in light of simple mechanisms that describe the ocean response to atmospheric forcing: 1) local steric changes due to surface buoyancy forcing and a local response to wind stress via Ekman pumping and 2) baroclinic and barotropic oceanic adjustment via propagating Rossby waves and quasi-steady Sverdrup balance, respectively. The relevance of these simple mechanisms in explaining interannual sea level variability in the whole Atlantic Ocean is investigated. It is shown that, in various regions, a large part of the interannual sea level variability is related to local response to heat flux changes (more than 50% in the eastern North Atlantic). Except in a few places, a local response to wind stress forcing is less successful in explaining sea surface height observations. In this case, it is necessary to consider large-scale oceanic adjustments: the first baroclinic mode forced by wind stress explains about 70% of interannual sea level variations in the latitude band 18°–20°N. A quasi-steady barotropic Sverdrup response is observed between 40° and 50°N.

Seasonal Variation of Surface Circulation Along Peninsular Malaysia' East Coast

2014 ◽  
Vol 71 (4) ◽  
Author(s):  
Muhammad Faiz Pa'suya ◽  
Kamaludin Mohd Omar ◽  
Benny N. Peter ◽  
Ami Hassan Md Din ◽  
Mohd Fadzil Mohd Akhir
Keyword(s):  
Sea Level ◽  
East Coast ◽  
Peninsular Malaysia ◽  
Environmental Data ◽  
Sea Surface ◽  
Northeast Monsoon ◽  
Radar Altimeter ◽  
Sea Level Anomaly ◽  
Surface Circulation ◽  
Altimetric Data

The sea surface circulation pattern over the coast of Peninsula Malaysia's East Coast during Northeast Monsoon (NE) and Southwest Monsoon (SW) are derived using the seasonally averaged sea level anomaly (SLA) data from altimetric data and 1992-2002 Mean Dynamic Ocean Topography. This altimetric data has been derived from multi-mission satellite altimeter TOPEX, ERS-1, ERS-2, JASON-1, and ENVISAT for the period of nineteen years (1993 to 2011) using the Radar Altimeter Database System (RADS). The estimated sea level anomaly (SLA) have shown similarity in the pattern of sea level variations observed by four tide gauges. Overall, the sea surface circulations during the NE and SW monsoons shows opposite patterns, northward and southward respectively. During the SW monsoon, an anti-cyclonic circulation has been detected around the Terengganu coastal area centred at (about 5.5° N 103.5° E) and nearly consistent with previous study using numerical modelling. The estimated geostrophic current field from the altimeter is consistent with the trajectories of Argos-tracked Drifting Buoys provided by the Marine Environmental Data Services (MEDS) in Canada.

scholarly journals Denoising Effect of Jason-1 Altimeter Waveforms with Singular Spectrum Analysis: A Case Study of Modelling Mean Sea Surface Height over South China Sea

2020 ◽  
Vol 8 (6) ◽  
pp. 426 ◽  
Author(s):  
Jiajia Yuan ◽  
Jinyun Guo ◽  
Yupeng Niu ◽  
Chengcheng Zhu ◽  
Zhen Li ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Spectrum Analysis ◽  
Noise Level ◽  
Singular Spectrum Analysis ◽  
Sea Surface Height ◽  
Sea Surface ◽  
China Sea ◽  
Singular Spectrum ◽  
Mean Sea Surface

Altimeter waveforms are usually contaminated due to nonmarine surfaces or inhomogeneous sea state conditions. The present work aimed to present how the singular spectrum analysis (SSA) can be used to reduce the noise level in Jason-1 altimeter waveforms to obtain SSA-denoised waveforms, improving the accuracy of a mean sea surface height (MSSH) model. Comparing the retracked sea surface heights (SSHs) by a 50% threshold retracker for the SSA-denoised waveforms with those for the raw waveforms, the results indicated that SSA allowed a noise reduction on Jason-1 waveforms, improving the accuracy of retracked SSHs. The MSSH model (called Model 1) over the South China Sea with a grid of 2′ × 2′ was established from the retracked SSHs of Jason-1 by the 50% threshold retracker for the SSA-denoised waveforms. Comparing Model 1 and Model 2 (established from the retracked SSHs by the 50% threshold retracker for the raw waveforms) with the CLS15 and DTU18 models in the South China Sea, it was found that the accuracy of Model 1 was higher than that of Model 2, which indicates that using SSA to reduce noise level in Jason-1 waveforms can effectively improve the accuracy of the MSSH model.

scholarly journals Global Mean Sea Surface Height Estimated from Spaceborne Cyclone-GNSS Reflectometry

2020 ◽  
Vol 12 (3) ◽  
pp. 356 ◽  
Author(s):  
Hui Qiu ◽  
Shuanggen Jin
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Correlation Coefficient ◽  
Root Mean Square ◽  
Absolute Error ◽  
Satellite System ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Mean Square ◽  
Mean Sea Surface

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 ( RMSE ) of 3.56 m and, a correlation coefficient ( R ) of 0.95.

scholarly journals Adjusting altimetric sea surface height observations in coastal regions. Case study in the Greek Seas

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Ioannis Mintourakis
Keyword(s):  
Satellite Altimetry ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Altimetry Data ◽  
Geoid Model ◽  
Sea Surface Topography ◽  
Marine Gravity ◽  
Mean Sea Surface ◽  
Process Strategy ◽  
Satellite Altimetry Data

AbstractWhen processing satellite altimetry data for Mean Sea Surface (MSS) modelling in coastal environments many problems arise. The degradation of the accuracy of the Sea Surface Height (SSH) observations close to the coastline and the usually irregular pattern and variability of the sea surface topography are the two dominant factors which have to be addressed. In the present paper, we study the statistical behavior of the SSH observations in relation to the range from the coastline for many satellite altimetry missions and we make an effort to minimize the effects of the ocean variability. Based on the above concepts we present a process strategy for the homogenization of multi satellite altimetry data that takes advantage ofweighted SSH observations and applies high degree polynomials for the adjustment and their uniffcation at a common epoch. At each step we present the contribution of each concept to MSS modelling and then we develop a MSS, a marine geoid model and a grid of gravity Free Air Anomalies (FAA) for the area under study. Finally, we evaluate the accuracy of the resulting models by comparisons to state of the art global models and other available data such as GPS/leveling points, marine GPS SSH’s and marine gravity FAA’s, in order to investigate any progress achieved by the presented strategy

Regional Mean Sea Surface Model over the Eastern Mediterranean Sea

2020 ◽  
Author(s):  
Milaa Murshan ◽  
Balaji Devaraju ◽  
Nagarajan Balasubramanium ◽  
Onkar Dikshit
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Sea Level ◽  
Tide Gauge ◽  
Eastern Mediterranean ◽  
Sea Surface ◽  
Surface Model ◽  
Eastern Mediterranean Sea ◽  
Mean Sea Level ◽  
Mean Sea Surface

&lt;p&gt;The Mean Sea Level is not an equipotential surface because it is subject to several variations, e.g., the tides, currents, winds, etc. Mean Sea Level can be measured either by tide gauges near to coastlines relative to local datum or by satellite altimeter above the reference ellipsoid. From this observable quantity, one can derive a non-observable quantity at which the potential is constant called geoid and differs from mean sea surface by amount of &amp;#177;1 m. This separation is called Sea Surface Topography. In this research, the data of nine altimetric Exact Repeat Missions (Envisat, ERS_1 of 35 days (phase C and G), ERS_2, GFO, Jason_1, Jason_2, Jason_3, Topex/Poseidon and SARAL) were used for computing the regional mean sea surface model over the eastern Mediterranean Sea. The data of all missions together span approximately 25 years from September -1992 to January-2017 and referenced to Topex ellipsoid.&amp;#160; Which is later transformed to WGS84 ellipsoid, as it is chosen to be a unified datum in this study. Prior to computing the altimetric MSS,&amp;#160; altimetric sea surface height measurements were validated&amp;#160; by comparing&amp;#160; time series of altimetric-MSL with mean sea level time series calculated from three in-situ tide gauge measurements.&amp;#160; The sea surface heights values of the derived MSS model is between 15.6 and 26.7 m. And the linear trend slope is between -3.02 to 6.53 mm/year.&lt;/p&gt;&lt;p&gt;Keywords: Mean Sea Level, Satellite Altimetry, Tide Gauge, Exact Repeat Missions&lt;/p&gt;

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