scholarly journals Kinematics and source zone properties of the 2004 Sumatra-Andaman earthquake and tsunami: Nonlinear joint inversion of tide gauge, satellite altimetry, and GPS data

2010 ◽  
Vol 115 (B2) ◽  
Author(s):  
S. Lorito ◽  
A. Piatanesi ◽  
V. Cannelli ◽  
F. Romano ◽  
D. Melini
Keyword(s):  
Satellite Altimetry ◽  
Tide Gauge ◽  
Joint Inversion ◽  
Source Zone ◽  
Gps Data ◽  
Nonlinear Joint ◽  
Andaman Earthquake

Study of the tsunami source in the Palu Bay following the Mw7.5 2018 Sulawesi earthquake

2020 ◽  
Author(s):  
Fabrizio Romano ◽  
Haider Hasan ◽  
Stefano Lorito ◽  
Finn Løvholt ◽  
Beatriz Brizuela ◽  
...  
Keyword(s):  
Tide Gauge ◽  
Joint Inversion ◽  
Seismic Source ◽  
Strike Slip ◽  
Tsunami Source ◽  
Fault System ◽  
Tsunami Propagation ◽  
Slip Mechanism ◽  
Short Period ◽  
Nonlinear Joint

<p>On 28 September 2018 a Mw 7.5 strike-slip earthquake occurred on the Palu-Koro fault system in the Sulawesi Island. Immediately after the earthquake a powerful tsunami hit the Palu Bay causing large damages and numerous fatalities.</p><p>Several works, inverting seismic or geodetic data, clearly estimated the slip distribution of this event, but the causative source of the tsunami is still not completely understood; indeed, the strike-slip mechanism of the seismic source alone might not be sufficient to explain the large runups observed (> 6 m) along the coast of the Palu Bay, and thus one or more additional non-seismic sources like a landslide could have contributed to generate the big tsunami. An insight of that can be found in an extraordinary collection of amateur videos, and on the only available tide gauge in the Bay, at Pantoloan, that showed evidence for a short period wave of at least 2-3 minutes, compatible with a landslide.</p><p>In this study, we attempt to discriminate the contribution in the tsunami generation of both the seismic source and  some supposed landslides distributed along the coast of the Bay.</p><p>In particular, we attempt to estimate the causative source of the tsunami by means of a nonlinear joint inversion of geodetic (InSAR) and runup data. We use a fault geometry consistent with the Sentinel-2 optical analysis results and analytically compute the geodetic Green’s functions. The same fault model is used to compute the initial condition for the seismic tsunami Green’s functions, including the contribution of the horizontal deformation due to the gradient of the bathymetry (10 m spatial resolution); the landslide tsunami Green’s functions are computed the software BingClaw by placing several hypothetical sources in the Bay. In both the cases the tsunami propagation is modelled by numerically solving the nonlinear shallow water equations.</p><p>In this work we also attempt to address the validity of Green’s functions approach (linearity) for earthquake and landslide sources as well as the wave amplitude offshore as predictor of nearby runup.</p>

scholarly journals An Analysis of Vertical Crustal Movements along the European Coast from Satellite Altimetry, Tide Gauge, GNSS and Radar Interferometry

2021 ◽  
Vol 13 (11) ◽  
pp. 2173
Author(s):  
Kamil Kowalczyk ◽  
Katarzyna Pajak ◽  
Beata Wieczorek ◽  
Bartosz Naumowicz
Keyword(s):  
Time Series ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Measurement Techniques ◽  
Radar Interferometry ◽  
Vertical Movements ◽  
Persistent Scatterer ◽  
Gnss Time Series ◽  
Vertical Crustal Movements ◽  
European Coast

The main aim of the article was to analyse the actual accuracy of determining the vertical movements of the Earth’s crust (VMEC) based on time series made of four measurement techniques: satellite altimetry (SA), tide gauges (TG), fixed GNSS stations and radar interferometry. A relatively new issue is the use of the persistent scatterer InSAR (PSInSAR) time series to determine VMEC. To compare the PSInSAR results with GNSS, an innovative procedure was developed: the workflow of determining the value of VMEC velocities in GNSS stations based on InSAR data. In our article, we have compiled 110 interferograms for ascending satellites and 111 interferograms for descending satellites along the European coast for each of the selected 27 GNSS stations, which is over 5000 interferograms. This allowed us to create time series of unprecedented time, very similar to the time resolution of time series from GNSS stations. As a result, we found that the obtained accuracies of the VMEC determined from the PSInSAR are similar to those obtained from the GNSS time series. We have shown that the VMEC around GNSS stations determined by other techniques are not the same.

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>

scholarly journals Improving the Coastal Mean Dynamic Topography by Geodetic Combination of Tide Gauge and Satellite Altimetry

2018 ◽  
Vol 41 (6) ◽  
pp. 517-545 ◽  
Author(s):  
Ole Baltazar Andersen ◽  
Karina Nielsen ◽  
Per Knudsen ◽  
Chris W. Hughes ◽  
Rory Bingham ◽  
...  
Keyword(s):  
Satellite Altimetry ◽  
Tide Gauge ◽  
Dynamic Topography ◽  
Mean Dynamic Topography

Sea level variations in the coastal region from altimetry – Using optimal interpolation in the Baltic Sea for 3-day mean sea level from altimetry, tide gauge and model data

2021 ◽  
Author(s):  
Ida Margrethe Ringgaard ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Adili Abulaitijiang ◽  
Ole B. Andersen
Keyword(s):  
Baltic Sea ◽  
Sea Level ◽  
Temporal Resolution ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Coastal Region ◽  
Optimal Interpolation ◽  
The Baltic Sea ◽  
Spatial Coverage ◽  
The Baltic

<p>The rise and fall of the sea surface in the coastal region is observed closely by two different sources: tide gauges measure the relative sea level anomaly at the coast at high temporal resolution (minutes or hours) and satellite altimeters measure the absolute sea surface height of the open ocean along tracks multiple times a day. However, these daily tracks are scattered across the Baltic Sea with each track being repeated at a lower temporal resolution (days). Due to the inverse relationship between spatial and temporal coverage of the satellite altimetry data, gridded satellite altimetry products often prioritize spatial coverage over temporal resolution, thus filtering out the high sea level variability. In other words, the satellite data, and especially averaged products, often miss the daily sea level variability, such as storm surges, which is most important for all societies in the coastal region. To compensate for the sparse spatial coverage from satellite altimetry, we here present an experimental product developed as part of the ESA project Baltic+SEAL:  on a 3-day scale, the DMI Optimal Interpolation (DMI-OI) method is combined with error statistics from a storm surge model as well as 3-day averages from both tide gauge observations and satellite altimetry tracks to generate a gridded sea level anomaly product for the Baltic Sea for year 2017. The product captures the overall temporal evolution of the sea level changes well for most areas with an average RMSE wrt. tide gauge observations of 17.2 cm and a maximum of 34.2 cm. Thus, the 3-day mean gridded product shows potential as an alternative to monthly altimetry products, although further work is needed.</p>

scholarly journals Recent Sea Level Change in the Black Sea from Satellite Altimetry and Tide Gauge Observations

2020 ◽  
Vol 9 (3) ◽  
pp. 185 ◽  
Author(s):  
Nevin Avşar ◽  
Şenol Kutoğlu
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Black Sea ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
The Black Sea ◽  
Sea Level Changes ◽  
Early 19Th Century ◽  
Mean Sea Level ◽  
The Mean

Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, wetlands, ecosystems, and beaches. Sea level changes are not geographically uniform. This study focuses on present-day sea level changes in the Black Sea using satellite altimetry and tide gauge data. The multi-mission gridded satellite altimetry data from January 1993 to May 2017 indicated a mean rate of sea level rise of 2.5 ± 0.5 mm/year over the entire Black Sea. However, when considering the dominant cycles of the Black Sea level time series, an apparent (significant) variation was seen until 2014, and the rise in the mean sea level has been estimated at about 3.2 ± 0.6 mm/year. Coastal sea level, which was assessed using the available data from 12 tide gauge stations, has generally risen (except for the Bourgas Station). For instance, from the western coast to the southern coast of the Black Sea, in Constantza, Sevastopol, Tuapse, Batumi, Trabzon, Amasra, Sile, and Igneada, the relative rise was 3.02, 1.56, 2.92, 3.52, 2.33, 3.43, 5.03, and 6.94 mm/year, respectively, for varying periods over 1922–2014. The highest and lowest rises in the mean level of the Black Sea were in Poti (7.01 mm/year) and in Varna (1.53 mm/year), respectively. Measurements from six Global Navigation Satellite System (GNSS) stations, which are very close to the tide gauges, also suggest that there were significant vertical land movements at some tide gauge locations. This study confirmed that according to the obtained average annual phase value of sea level observations, seasonal sea level variations in the Black Sea reach their maximum annual amplitude in May–June.

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