Validation of sea surface heights from satellite altimetry along the Indian coast

2021 ◽  
Author(s):  
Milaa Murshan ◽  
Balaji Devaraju ◽  
Nagarajan Balasubramanian ◽  
Onkar Dikshit
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Atmospheric Correction ◽  
North Indian Ocean ◽  
Sea Surface ◽  
Indian Coast ◽  
Vertical Land Motion ◽  
And Performance

<p>Satellite altimetry provides measurements of sea surface height of centimeter-level accuracy over open oceans. However, its accuracy reduces when approaching the coastal areas and over land regions. Despite this downside, altimetric measurements are still applied successfully in these areas through altimeter retracking processes. This study aims to calibrate and validate retracted sea level data of Envisat, ERS-2, Topex/Poseidon, Jason-1, 2, SARAL/AltiKa, Cryosat-2 altimetric missions near the Indian coastline. We assessed the reliability, quality, and performance of these missions by comparing eight tide gauge (TG) stations along the Indian coast. These are Okha, Mumbai, Karwar, and Cochin stations in the Arabian Sea, and Nagapattinam, Chennai, Visakhapatnam, and Paradip in the Bay of Bengal. To compare the satellite altimetry and TG sea level time series, both datasets are transformed to the same reference datum. Before the calculation of the bias between the altimetry and TG sea level time series, TG data are corrected for Inverted Barometer (IB) and Dynamic Atmospheric Correction (DAC). Since there are no prior VLM measurements in our study area, VLM is calculated from TG records using the same procedure as in the Technical Report NOS organization CO-OPS 065. </p><p>Keywords— Tide gauge, Sea level, North Indian ocean, satellite altimetry, Vertical land motion</p>

Estimation of Vertical Land Motion at the Tide Gauges in Turkey

2020 ◽  
Author(s):  
Muharrem Hilmi Erkoç ◽  
Uğur Doğan ◽  
Seda Özarpacı ◽  
Hasan Yildiz ◽  
Erdinç Sezen
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Marmara Sea ◽  
Tide Gauges ◽  
Sea Level Changes ◽  
Coordinate Time ◽  
Coordinate Time Series ◽  
Vertical Land Motion

<p>This study aims to estimate vertical land motion (VLM) at tide gauges (TG), located in the Mediterranean, Aegean and the Marmara Sea coasts of Turkey, from differences of multimission satellite altimetry and TG sea level time series. Initially, relative sea level trends are estimated at 7 tide gauges stations operated by the Turkish General Directorate of Mapping over the period 2001-2019. Subsequently, absolute sea level trends independent from VLM are computed from multimission satellite altimetry data over the same period. We have computed estimates of linear trends of difference time series between altimetry and tide gauge sea level after removing seasonal signals by harmonic analysis from each time series to estimate the vertical land motion (VLM) at tide gauges. Traditional way of VLM determination at tide gauges is to use GPS@TG or preferably CGPS@TG data. We therefore, processed these GPS data, collected over the years by several TG-GPS campaigns and by continuous GPS stations close to the TG processed by GAMIT/GLOBK software. Subsequently, the GPS and CGPS vertical coordinate time series are used to estimate VLM. These two different VLM estimates, one from GPS and CGPS coordinate time series and other from altimetry-TG sea level time series differences are compared.</p><p> </p><p><strong>Keywords: Vertical land motion, Sea Level Changes, Tide gauge, Satellite altimetry, GPS, CGPS </strong></p>

Vertical land motion in the Iberian Atlantic coast and its implications for sea level change evaluation

2020 ◽  
Vol 14 (3) ◽  
pp. 361-378
Author(s):  
V. B. Mendes ◽  
S. M. Barbosa ◽  
D. Carinhas
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Atlantic Coast ◽  
Sea Level Change ◽  
Tide Gauges ◽  
Tide Gauge Records ◽  
Level Change ◽  
Vertical Land Motion

AbstractIn this study, we estimate vertical land motion for 35 stations primarily located along the coastline of Portugal and Spain, using GPS time series with at least eight years of observations. Based on this set of GPS stations, our results show that vertical land motion along the Iberian coastline is characterized, in general, by a low to moderate subsidence, ranging from −2.2 mm yr−1 to 0.4 mm yr−1, partially explained by the glacial isostatic adjustment geophysical signal. The estimates of vertical land motion are subsequently applied in the analysis of tide gauge records and compared with geocentric estimates of sea level change. Geocentric sea level for the Iberian Atlantic coast determined from satellite altimetry for the last three decades has a mean of 2.5 ± 0.6 mm yr−1, with a significant range, as seen for a subset of grid points located in the vicinity of tide gauge stations, which present trends varying from 1.5 mm yr−1 to 3.2 mm yr−1. Relative sea level determined from tide gauges for this region shows a high degree of spatial variability, that can be partially explained not only by the difference in length and quality of the time series, but also for possible undocumented datum shifts, turning some trends unreliable. In general, tide gauges corrected for vertical land motion produce smaller trends than satellite altimetry. Tide gauge trends for the last three decades not corrected for vertical land motion range from 0.3 mm yr−1 to 5.0 mm yr−1 with a mean of 2.6 ± 1.4 mm yr−1, similar to that obtained from satellite altimetry. When corrected for vertical land motion, we observe a reduction of the mean to ∼1.9 ± 1.4 mm yr−1. Actions to improve our knowledge of vertical land motion using space geodesy, such as establishing stations in co-location with tide gauges, will contribute to better evaluate sea level change and its impacts on coastal regions.

scholarly journals Revisiting Vertical Land Motion and Sea Level Trends in the Northeastern Adriatic Sea Using Satellite Altimetry and Tide Gauge Data

2020 ◽  
Vol 8 (11) ◽  
pp. 949 ◽  
Author(s):  
Francesco De Biasio ◽  
Giorgio Baldin ◽  
Stefano Vignudelli
Keyword(s):  
Inverse Problem ◽  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Sea Level Change ◽  
Linear Inverse Problem ◽  
Level Change ◽  
Vertical Land Motion

We propose a revisited approach to estimating sea level change trends based on the integration of two measuring systems: satellite altimetry and tide gauge (TG) time series of absolute and relative sea level height. Quantitative information on vertical crustal motion trends at six TG stations of the Adriatic Sea are derived by solving a constrained linear inverse problem. The results are verified against Global Positioning System (GPS) estimates at some locations. Constraints on the linear problem are represented by estimates of relative vertical land motion between TG couples. The solution of the linear inverse problem is valid as long as the same rates of absolute sea level rise are observed at the TG stations used to constrain the system. This requirement limits the applicability of the method with variable absolute sea level trends. The novelty of this study is that we tried to overcome such limitations, subtracting the absolute sea level change estimates observed by the altimeter from all relevant time series, but retaining the original short-term variability and associated errors. The vertical land motion (VLM) solution is compared to GPS estimates at three of the six TGs. The results show that there is reasonable agreement between the VLM rates derived from altimetry and TGs, and from GPS, considering the different periods used for the processing of VLM estimates from GPS. The solution found for the VLM rates is optimal in the least square sense, and no longer depends on the altimetric absolute sea level trend at the TGs. Values for the six TGs’ location in the Adriatic Sea during the period 1993–2018 vary from −1.41 ± 0.47 mm y−1 (National Research Council offshore oceanographic tower in Venice) to 0.93 ± 0.37 mm y−1 (Rovinj), while GPS solutions range from −1.59 ± 0.65 (Venice) to 0.10 ± 0.64 (Split) mm y−1. The absolute sea level rise, calculated as the sum of relative sea level change rate at the TGs and the VLM values estimated in this study, has a mean of 2.43 mm y−1 in the period 1974–2018 across the six TGs, a mean standard error of 0.80 mm y−1, and a sample dispersion of 0.18 mm y−1.

Performance Assessment of GNSS-R Polarimetric Observations for Sea Level Monitoring

2021 ◽  
Author(s):  
Mahmoud Rajabi ◽  
Mstafa Hoseini ◽  
Hossein Nahavandchi ◽  
Maximilian Semmling ◽  
Markus Ramatschi ◽  
...  
Keyword(s):  
Time Series ◽  
Circular Polarization ◽  
Sea Level ◽  
Tide Gauge ◽  
Satellite System ◽  
Sea Surface ◽  
Analysis Tool ◽  
Lower Accuracy ◽  
Coastal Sea ◽  
Global Navigation Satellite

<p>Determination and monitoring of the mean sea level especially in the coastal areas are essential, environmentally, and as a vertical datum. Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way which is becoming a reliable alternative for coastal sea-level altimetry. Comparing to traditional tide gauges, GNSS-R can offer different parameters of sea surface, one of which is the sea level. The measurements derived from this technique can cover wider areas of the sea surface in contrast to point-wise observations of a tide gauge.  </p><p>We use long-term ground-based GNSS-R observations to estimate sea level. The dataset includes one-year data from January to December 2016. The data was collected by a coastal GNSS-R experiment at the Onsala space observatory in Sweden. The experiment utilizes three antennas with different polarization designs and orientations. The setup has one up-looking, and two sea-looking antennas at about 3 meters above the sea surface level. The up-looking antenna is Right-Handed Circular Polarization (RHCP). The sea-looking antennas with RHCP and Left-Handed Circular Polarization (LHCP) are used for capturing sea reflected Global Positioning System (GPS) signals. A dedicated reflectometry receiver (GORS type) provides In-phase and Quadrature (I/Q) correlation sums for each antenna based on the captured interferometric signal. The generated time series of I/Q samples from different satellites are analyzed using the Least Squares Harmonic Estimation (LSHE) method. This method is a multivariate analysis tool which can flexibly retrieve the frequencies of a time series regardless of possible gaps or unevenly spaced sampling. The interferometric frequency, which is related to the reflection geometry and sea level, is obtained by LSHE with a temporal resolution of 15 minutes. The sea level is calculated based on this frequency in six modes from the three antennas in GPS L1 and L2 signals.</p><p>Our investigation shows that the sea-looking antennas perform better compared to the up-looking antenna. The highest accuracy is achieved using the sea-looking LHCP antenna and GPS L1 signal. The annual Root Mean Square Error (RMSE) of 15-min GNSS-R water level time series compared to tide gauge observations is 3.7 (L1) and 5.2 (L2) cm for sea-looking LHCP, 5.8 (L1) and 9.1 (L2) cm for sea-looking RHCP, 6.2 (L1) and 8.5 (L2) cm for up-looking RHCP. It is worth noting that the GPS IIR block satellites show lower accuracy due to the lack of L2C code. Therefore, the L2 observations from this block are eliminated.</p>

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

<p>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 ±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.  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,  altimetric sea surface height measurements were validated  by comparing  time series of altimetric-MSL with mean sea level time series calculated from three in-situ tide gauge measurements.  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.</p><p>Keywords: Mean Sea Level, Satellite Altimetry, Tide Gauge, Exact Repeat Missions</p>

scholarly journals Assessment of Sea Level Rise at West Coast of Portugal Mainland and Its Projection for the 21st Century

2019 ◽  
Author(s):  
Carlos Antunes
Keyword(s):  
Time Series ◽  
Sea Level Rise ◽  
Sea Level ◽  
21St Century ◽  
West Coast ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
The West ◽  
Relative Sea Level ◽  
Global Sea Level

Data collected at the Cascais tide gauge, located on the west coast of Portugal Mainland, have been analyzed and sea level rise rates have been updated. Based on a bootstrapping linear regression model and on polynomial adjustments, time series are used to calculate different empirical projections for the 21st century sea level rise, by estimating the initial velocity and its corresponding acceleration. The results are consistent to an accelerated sea level rise, showing evidence of a faster rise than previous century estimates. Based on different numerical methods of second order polynomial fitting, it is possible to build a set of projection models of relative sea level rise. Appling the same methods to regional sea level anomaly from satellite altimetry, additional projections are also built with good consistency. Both data sets, tide gauge and satellite altimetry data, enabled the development of an ensemble of projection models. The relative sea level rise projections are crucial for national coastal planning and management since extreme sea level scenarios can potentially cause erosion and flooding. Based on absolute vertical velocities obtained by integrating global sea level models, neo-tectonic studies and permanent Global Positioning System (GPS) station time series, it is possible to transform relative into absolute sea level rise scenarios, and vice-versa, allowing the generation of absolute sea level rise projection curves and its comparison with already established global projections. The sea level rise observed at the Cascais tide gauge has always shown a significant correlation with global sea level rise observations, evidencing relatively low rates of composed vertical land velocity from tectonic and post-glacial isostatic adjustment, and residual synoptic regional dynamic effects rather than a trend. An ensemble of sea level projection models for the 21st century is proposed with its corresponding probability density function, both for relative and absolute sea level rise for the west coast of Portugal Mainland.

scholarly journals A comparison of methods to estimate vertical land motion trends from GNSS and altimetry at tide gauge stations

Ocean Science ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 187-204 ◽  
Author(s):  
Marcel Kleinherenbrink ◽  
Riccardo Riva ◽  
Thomas Frederikse
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Tide Gauge ◽  
Satellite System ◽  
Vertical Land Motion ◽  
Correlation Threshold ◽  
The Mean ◽  
Highly Correlated ◽  
Global Navigation Satellite ◽  
Along Track

Abstract. Tide gauge (TG) records are affected by vertical land motion (VLM), causing them to observe relative instead of geocentric sea level. VLM can be estimated from global navigation satellite system (GNSS) time series, but only a few TGs are equipped with a GNSS receiver. Hence, (multiple) neighboring GNSS stations can be used to estimate VLM at the TG. This study compares eight approaches to estimate VLM trends at 570 TG stations using GNSS by taking into account all GNSS trends with an uncertainty smaller than 1 mm yr−1 within 50 km. The range between the methods is comparable with the formal uncertainties of the GNSS trends. Taking the median of the surrounding GNSS trends shows the best agreement with differenced altimetry–tide gauge (ALT–TG) trends. An attempt is also made to improve VLM trends from ALT–TG time series. Only using highly correlated along-track altimetry and TG time series reduces the SD of ALT–TG time series by up to 10 %. As a result, there are spatially coherent changes in the trends, but the reduction in the root mean square (RMS) of differences between ALT–TG and GNSS trends is insignificant. However, setting correlation thresholds also acts like a filter to remove problematic TG time series. This results in sets of ALT–TG VLM trends at 344–663 TG locations, depending on the correlation threshold. Compared to other studies, we decrease the RMS of differences between GNSS and ALT–TG trends (from 1.47 to 1.22 mm yr−1), while we increase the number of locations (from 109 to 155), Depending on the methods the mean of differences between ALT–TG and GNSS trends vary between 0.1 and 0.2 mm yr−1. We reduce the mean of the differences by taking into account the effect of elastic deformation due to present-day mass redistribution. At varying ALT–TG correlation thresholds, we provide new sets of trends for 759 to 939 different TG stations. If both GNSS and ALT–TG trend estimates are available, we recommend using the GNSS trend estimates because residual ocean signals might correlate over long distances. However, if large discrepancies ( > 3 mm yr−1) between the two methods are present, local VLM differences between the TG and the GNSS station are likely the culprit and therefore it is better to take the ALT–TG trend estimate. GNSS estimates for which only a single GNSS station and no ALT–TG estimate are available might still require some inspection before they are used in sea level studies.

Sea Surface Height Predictions from the Global Navy Coastal Ocean Model during 1998–2001*

2004 ◽  
Vol 21 (12) ◽  
pp. 1876-1893 ◽  
Author(s):  
Charlie N. Barron ◽  
A. Birol Kara ◽  
Harley E. Hurlburt ◽  
C. Rowley ◽  
Lucy F. Smedstad
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Tide Gauge ◽  
Ocean Model ◽  
Sea Surface ◽  
Tide Gauges ◽  
Model Data ◽  
Free Running ◽  
R Value ◽  
Coastal Ocean Model

Abstract A ⅛° global version of the Navy Coastal Ocean Model (NCOM), operational at the Naval Oceanographic Office (NAVOCEANO), is used for prediction of sea surface height (SSH) on daily and monthly time scales during 1998–2001. Model simulations that use 3-hourly wind and thermal forcing obtained from the Navy Operational Global Atmospheric Prediction System (NOGAPS) are performed with/without data assimilation to examine indirect/direct effects of atmospheric forcing in predicting SSH. Model–data evaluations are performed using the extensive database of daily averaged SSH values from tide gauges in the Atlantic, Pacific, and Indian Oceans obtained from the Joint Archive for Sea Level (JASL) center during 1998–2001. Model–data comparisons are based on observations from 282 tide gauge locations. An inverse barometer correction was applied to SSH time series from tide gauges for model–data comparisons, and a sensitivity study is undertaken to assess the impact of the inverse barometer correction on the SSH validation. A set of statistical metrics that includes conditional bias (Bcond), root-mean-square (rms) difference, correlation coefficient (R), and nondimensional skill score (SS) is used to evaluate the model performance. It is shown that global NCOM has skill in representing SSH even in a free-running simulation, with general improvement when SSH from satellite altimetry and sea surface temperature (SST) from satellite IR are assimilated via synthetic temperature and salinity profiles derived from climatological correlations. When the model was run from 1998 to 2001 with NOGAPS forcing, daily model SSH comparisons from 612 yearlong daily tide gauge time series gave a median rms difference of 5.98 cm (5.77 cm), an R value of 0.72 (0.76), and an SS value of 0.45 (0.51) for the ⅛° free-running (assimilative) NCOM. Similarly, error statistics based on the 30-day running averages of SSH time series for 591 yearlong daily tide gauge time series over the time frame 1998–2001 give a median rms difference of 3.63 cm (3.36 cm), an R value of 0.83 (0.85), and an SS value of 0.60 (0.64) for the ⅛° free-running (assimilated) NCOM. Model– data comparisons show that skill in 30-day running average SSH time series is as much as 30% higher than skill for daily SSH. Finally, SSH predictions from the free-running and assimilative ⅛° NCOM simulations are validated against sea level data from the tide gauges in two different ways: 1) using original detided sea level time series from tide gauges and 2) using the detided data with an inverse barometer correction derived using daily mean sea level pressure extracted from NOGAPS at each location. Based on comparisons with 612 yearlong daily tide gauge time series during 1998–2001, the inverse barometer correction lowered the median rms difference by about 1 cm (15%–20%). Results presented in this paper reveal that NCOM is able to predict SSH with reasonable accuracies, as evidenced by model simulations performed during 1998–2001. In an extension of the validation over broader ocean regions, the authors find good agreement in amplitude and distribution of SSH variability between NCOM and other operational model products.

scholarly journals Studying the Sensitivity of Satellite Altimetry, Tide Gauge and GNSS Observations to Changes in Vertical Displacements

2021 ◽  
Vol 15 (4) ◽  
pp. 45-58
Author(s):  
Katarzyna Pajak ◽  
Kamil Kowalczyk ◽  
Jānis Kaminskis ◽  
Magdalena Idzikowska
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Vertical Motion ◽  
Crustal Movement ◽  
Vertical Crustal Movement ◽  
Vertical Land Motion ◽  
Vertical Displacements ◽  
Sea Coast

Tide gauge observations provide sea level relative to the Earth’s crust, while satellite altimetry measures sea level variations relative to the centre of the Earth’s mass. Local vertical land motion can be a significant contribution to the measured sea level change.Satellite altimetry was traditionally used to study the open ocean, but this technology is now being used over inland seas too.The difference of both observations can be used to estimate vertical crustal movement velocities along the sea coast. In this paper, vertical crustal movement velocities were investigated at tide gauge sites along the Adriatic Sea coast by analyzing differences between Tide Gauge (TG) and Satellite Altimetry (SA) observations. Furthermore, the estimated vertical motion rates were compared with those from nearby GNSS measurements.The study determines the practical relationships between these vertical crustal movements and those determined from unrelated data acquired from the neighbouring GNSS stations. The results show general consistence with the present geodynamics in the Adriatic Sea coastal zone.

scholarly journals Monitoring the Vertical Land Motion of Tide Gauges and Its Impact on Relative Sea Level Changes in Korean Peninsula Using Sequential SBAS-InSAR Time-Series Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 18
Author(s):  
Suresh Krishnan Palanisamy Vadivel ◽  
Duk-jin Kim ◽  
Jungkyo Jung ◽  
Yang-Ki Cho ◽  
Ki-Jong Han
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Sea Level ◽  
Korean Peninsula ◽  
Tide Gauge ◽  
Synthetic Aperture ◽  
Tide Gauges ◽  
Sea Level Changes ◽  
Vertical Land Motion

The relative sea-level changes from tide gauges in the Korean peninsula provide essential information to understand the regional and global mean sea-level changes. Several corrections to raw tide gauge records are required to account for coastal vertical land motion (VLM), regional and local coastal variability. However, due to the lack of in-situ measurements such as leveling data and the Global Navigation Satellite System (GNSS), making precise assessments of VLM at the tide gauges is still challenging. This study aims to address the above limitation to assess the VLM in the Korean tide gauges using the time-series Interferometric Synthetic Aperture Radar (InSAR) technique. For 10 tide gauges selected in the Korean peninsula, we applied the Stanford Method for Persistent Scatterers (StaMPS)—Small Baseline Subset (SBAS) method to C-band Sentinel-1 A/B Synthetic Aperture Radar (SAR) data acquired during 2014/10–2020/05, with the novel sequential interferograms pair selection approach to increase the slowly decorrelating filtered phase (SDFP) pixels density near the tide gauges. Our findings show that overall the tide gauges in the Korean peninsula are stable, besides the largest VLM observed at Pohang tide gauge station (East Sea) of about −26.02 mm/year; also, higher rates of uplift (>1 mm/year) were observed along the coast of Yellow Sea (Incheon TG and Boryeong TG) and higher rates of subsidence (<−2 mm/year) were observed at Jeju TG and Seogwipo TG. Our approach estimates the rate of VLM at selected tide gauges with an unprecedented spatial and temporal resolution and is applicable when the in-situ and GNSS observations are not available.

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