Persian gulf and Oman sea tide modeling using satellite altimetry and tide gauge data (TM-IR01)

Soltanpour, A.; Pirooznia, Mahmoud; Aminjafari, Saeid; Zareian, P.

doi:10.1080/1064119x.2017.1366608

Cited by 9 publications

(6 citation statements)

References 20 publications

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“…1), is not known to be exceptionally sensitive to extreme sea level hazards and meteotsunamis. Indeed, under normal conditions, the Persian Gulf is characterized by (1) tides ranging from 1 to 2 metres (Akbari et al 2016;Soltanpour et al 2018), (2) storms generally not associated with coastal flooding, as mostly connected to the so-called winter Shamal winds driving negative surges of approximately 0.25-0.4 m in the northernmost coastal regions (Thoppil and Hogan 2010) and (3) very rare or, more appropriately, tsunami occurrences from either local origin or propagating from the Indian Ocean are non-existent (Jordan 2008;Heidarzadeh et al 2008). Consequently, waves of 2 to 3 metres hitting the south-eastern Bushehr (Fig.…”

Section: Introductionmentioning

confidence: 99%

Weather radar and ancillary observations of the convective system causing the northern Persian Gulf meteotsunami on 19 March 2017

et al. 2020

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This study documents the atmospheric system driving the observed meteotsunami waves that hit the northern Persian Gulf on 19 March 2017 during high tide. This destructive meteotsunami event resulted in coastal inundations that reached several hundred metres inland along the 100-km coastline between the cities of Dayyer and Asaluyeh and caused the death or injury of 27 persons. Based on previously published research, eyewitness reports, oceanic and atmospheric observations, including synoptic station and weather radar data, and available reanalysis ERA5 products, this study provides new insights into destructive events, particularly mesoscale atmospheric systems conjoined with observed meteotsunami waves. Precipitation intensity, maximum reflectivity and echo top height images provided by the weather radar covering the affected area and the area over which the meteotsunamigenic disturbance travelled revealed that a strong convective system that encompassed the mid-and upper troposphere entered the northern Persian Gulf approximately 4 h before the event and moved eastward. Two hours before reaching the affected coastline, this convective system was reshaped to an elongated and narrow squall line varying between 70 and 130 km in length with a width of less than 10 km and travelled at an average speed of approximately 24 m/s over the sea. The peak maximum reflectivity of the squall line always surpassed 40 dBZ, while it increased to 60 dBZ near the Dayyer area. As such, intense atmospheric disturbances are known to be associated with sharp air pressure increases, and these disturbances were found to resonantly pump energy to the ocean through Proudman resonance for over 12 or more disturbance wavelengths (i.e. up to 120 km in this study). A half-metre meteotsunami wave was presumably created in the open sea and then amplified while travelling towards the shore where it broke as a meteotsunami bore and inundated the coastal areas. Further research on the physical mechanisms driving the interactions between meteotsunamigenic disturbances and ocean responses, the recurrence of such events and meteotsunami hazard assessments along the affected coastline is envisaged.

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Section: Introductionmentioning

confidence: 99%

Weather radar and ancillary observations of the convective system causing the northern Persian Gulf meteotsunami on 19 March 2017

et al. 2020

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“…To address this issue, a waveform retracking method known as the adaptive leading edge sub-waveform (ALES) is applied to correct the range observations [16]. Additionally, inherent uncertainties exist in satellite altimetry measurements, including errors introduced by geophysical and environmental factors, which are typically addressed through global or local modeling techniques [23,24]. Moreover, the systematic errors, such as radial error [24], present in the satellite altimeter datasets require calibration, which is considered as described in [25].…”

Section: Data Descriptionmentioning

confidence: 99%

“…Additionally, inherent uncertainties exist in satellite altimetry measurements, including errors introduced by geophysical and environmental factors, which are typically addressed through global or local modeling techniques [23,24]. Moreover, the systematic errors, such as radial error [24], present in the satellite altimeter datasets require calibration, which is considered as described in [25]. Given the limited spatial resolution of satellite altimetry in the crosstrack direction, despite the utilization of multiple repeat-track or multi-mission data, there is a chance that certain regions may still be overlooked or not adequately captured in satellite altimetry measurements [26].…”

Section: Data Descriptionmentioning

confidence: 99%

Integrating Hydrography Observations and Geodetic Data for Enhanced Dynamic Topography Estimation

Pirooznia,

Voosoghi,

Poreh

et al. 2024

Remote Sensing

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Dynamic topography (DT) refers to the time-varying component of the sea surface height influenced by factors like ocean currents, temperature, and salinity gradients. Accurate estimation of DT is crucial for comprehending oceanic circulation patterns and their impact on climate. This study introduces two approaches to estimating DT: (1) utilizing satellite altimetry to directly observe sea surface height and (2) considering the steric and non-steric components of sea level anomalies. The steric term is calculated using salinity and temperature data obtained from local buoy data, Argo observations, and the World Ocean Atlas model. The non-steric term is calculated using GRACE Satellite gravimetry data. To estimate the assimilated DT, four methods are utilized, including variance component estimation (VCE), Bayesian theory, Kalman filter, and 3D variational (3DVAR). These methods assimilate the two aforementioned schemes. The validity of the estimated DT is assessed by comparing the calculated sea surface current, derived from the obtained DT, with observations from local current meter stations. The results indicate that the VCE method outperforms other methods in determining the final DT. Furthermore, incorporating the steric and non-steric terms of sea level in determining DT in coastal areas enhances the accuracy of estimating sea surface currents.

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“…The range observation is contaminated by some source of errors which must be corrected via global or local modeling and can be summarized as follows: wet troposphere correction, dry troposphere correction, ionosphere correction, electromagnetic bias correction, ocean tide correction, inverse barometer correction, pole tide correction and center of gravity movement. They are better known as "geophysical corrections" [Benada, 1997;Pirooznia et al, 2016a;Soltanpour et al 2017]. Also the re-tracking correction is used to correct range observation.…”

Section: Re-tracking Of Sa Observationsmentioning

confidence: 99%

Point wise Determination of Vertical Deformation at southern Coastal Areas of Caspian Sea by Combination of Satellite Altimetry and Tide Gauge Observations

Pirooznia

Naeeni

Yousefzadeh

2020

Annals of Geophysics

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In this paper, a combination of satellite altimetry (SA) and tide-gauge (TG) observations is used to determine the pattern of vertical deformation at southern coasts of Caspian Sea. Satellite altimetry measures the variations of sea water surface with a respect to a reference ellipsoid, while tide gauge data gives the sea level relative to a particular ground station; consequently, the difference between these two observations will give the vertical motion at the ground station. However, altimeter satellites still have problems at shallow waters or coastal areas which leads to inaccurate and corrupted sea surface height at tide gauge stations. To minimize this imprecision, two strategies are applied for the selection of the suitable SA points near the TG stations. The First one is to choose those close passes to the TG stations, provided that the SA data is not corrupted (range observation is available). The second strategy is to extrapolate the SA points at TG stations using Spatio- Temporal Kriging method. In both point of views, use is made of re-tracking methods to improve the ranges of SA observations near the coast. Amplitudes of tidal components are removed from both SA and TG observations to derive the residual tide free signals. Afterward, a linear trend is fitted to the residual signals in the sense of least square; the difference between these two, supplies the vertical deformation of the ground station. The results illustrate that the average vertical crustal motion at Anzali, Noshahr and Neka are -1.387, -1.903 and -3.14 mm/year, respectively.

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Persian gulf and Oman sea tide modeling using satellite altimetry and tide gauge data (TM-IR01)

Cited by 9 publications

References 20 publications

Weather radar and ancillary observations of the convective system causing the northern Persian Gulf meteotsunami on 19 March 2017

Weather radar and ancillary observations of the convective system causing the northern Persian Gulf meteotsunami on 19 March 2017

Integrating Hydrography Observations and Geodetic Data for Enhanced Dynamic Topography Estimation

Point wise Determination of Vertical Deformation at southern Coastal Areas of Caspian Sea by Combination of Satellite Altimetry and Tide Gauge Observations

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