scholarly journals Using global tide gauge data to validate and improve the representation of extreme sea levels in flood impact studies

2017 ◽  
Vol 156 ◽  
pp. 34-45 ◽  
Author(s):  
J.R. Hunter ◽  
P.L. Woodworth ◽  
T. Wahl ◽  
R.J. Nicholls
Keyword(s):  
Tide Gauge ◽  
Tide Gauge Data ◽  
Sea Levels ◽  
Impact Studies ◽  
Extreme Sea Levels ◽  
Gauge Data ◽  
Flood Impact

scholarly journals Complex Extreme Sea Levels Prediction Analysis: Karachi Coast Case Study

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 549
Author(s):  
Faisal Ahmed Khan ◽  
Tariq Masood Ali Khan ◽  
Ali Najah Ahmed ◽  
Haitham Abdulmohsin Afan ◽  
Mohsen Sherif ◽  
...  
Keyword(s):  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Probability Method ◽  
Annual Maximum ◽  
Tide Gauge Data ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Gauge Data ◽  
Pakistan Coast

In this study, the analysis of the extreme sea level was carried out by using 10 years (2007–2016) of hourly tide gauge data of Karachi port station along the Pakistan coast. Observations revealed that the magnitudes of the tides usually exceeded the storm surges at this station. The main observation for this duration and the subsequent analysis showed that in June 2007 a tropical Cyclone “Yemyin” hit the Pakistan coast. The joint probability method (JPM) and the annual maximum method (AMM) were used for statistical analysis to find out the return periods of different extreme sea levels. According to the achieved results, the AMM and JPM methods erre compatible with each other for the Karachi coast and remained well within the range of 95% confidence. For the JPM method, the highest astronomical tide (HAT) of the Karachi coast was considered as the threshold and the sea levels above it were considered extreme sea levels. The 10 annual observed sea level maxima, in the recent past, showed an increasing trend for extreme sea levels. In the study period, the increment rates of 3.6 mm/year and 2.1 mm/year were observed for mean sea level and extreme sea level, respectively, along the Karachi coast. Tidal analysis, for the Karachi tide gauge data, showed less dependency of the extreme sea levels on the non-tidal residuals. By applying the Merrifield criteria of mean annual maximum water level ratio, it was found that the Karachi coast was tidally dominated and the non-tidal residual contribution was just 10%. The examination of the highest water level event (13 June 2014) during the study period, further favored the tidal dominance as compared to the non-tidal component along the Karachi coast.

scholarly journals Sea Level Fusion of Satellite Altimetry and Tide Gauge Data by Deep Learning in the Mediterranean Sea

2021 ◽  
Vol 13 (5) ◽  
pp. 908
Author(s):  
Lianjun Yang ◽  
Taoyong Jin ◽  
Xianwen Gao ◽  
Hanjiang Wen ◽  
Tilo Schöne ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
The Other ◽  
Tide Gauge Data ◽  
Sea Levels ◽  
Sea Level Anomalies ◽  
Gauge Data ◽  
The Mediterranean

Satellite altimetry and tide gauges are the two main techniques used to measure sea level. Due to the limitations of satellite altimetry, a high-quality unified sea level model from coast to open ocean has traditionally been difficult to achieve. This study proposes a fusion approach of altimetry and tide gauge data based on a deep belief network (DBN) method. Taking the Mediterranean Sea as the case study area, a progressive three-step experiment was designed to compare the fused sea level anomalies from the DBN method with those from the inverse distance weighted (IDW) method, the kriging (KRG) method and the curvature continuous splines in tension (CCS) method for different cases. The results show that the fusion precision varies with the methods and the input measurements. The precision of the DBN method is better than that of the other three methods in most schemes and is reduced by approximately 20% when the limited altimetry along-track data and in-situ tide gauge data are used. In addition, the distribution of satellite altimetry data and tide gauge data has a large effect on the other three methods but less impact on the DBN model. Furthermore, the sea level anomalies in the Mediterranean Sea with a spatial resolution of 0.25° × 0.25° generated by the DBN model contain more spatial distribution information than others, which means the DBN can be applied as a more feasible and robust way to fuse these two kinds of sea levels.

Past, Present and Future Sea Levels in Singapore 

2021 ◽  
Author(s):  
Timothy Shaw ◽  
Stephen Chua ◽  
Jedrzej Majewski ◽  
Li Tanghua ◽  
Dhrubajyoti Samanta ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Land Surface ◽  
Tide Gauge ◽  
Ocean Dynamics ◽  
Tide Gauge Data ◽  
Sea Levels ◽  
Vertical Land Motion ◽  
Gauge Data ◽  
Probabilistic Projections

<p>Singapore is a small (728 km<sup>2</sup>) island nation that is vulnerable to rising sea levels with 30% of its land surface area less than 5 m above present sea level. Rising relative sea level (RSL), however, is not uniform with regional RSL changes differing from the global mean due to processes associated with vertical land motion (e.g., glacial-isostatic adjustment) and atmospheric and ocean dynamics. Understanding magnitudes, rates, and driving processes on past and present-day sea level are therefore important to provide greater confidence in accurately quantifying future sea-level rise projections and their uncertainty. Here, we present a synopsis of Singapore’s past and present RSL history using newly developed proxy RSL reconstructions from mangrove peats, coral microatolls and tide gauge data and conclude with probabilistic projections of future RSL change.</p><p>Past RSL is characterized by rapid rise during the early Holocene driven primarily by deglaciation of northern hemisphere ice sheets. Sea-level index points (SLIPs) from mangrove peats show sea levels rose rapidly from -20.7 m at 9.5 ka BP to -0.6 m at 7 ka BP at rates of 6-12 mm/yr. This is substantially greater than predicted magnitudes of RSL change from the ICE-6G_C GIA model which shows RSL increasing from -6.4 m at 9.5 ka BP to a ~2.8 m highstand at ~7 ka BP. SLIPs show the mid-Holocene highstand of ~4 ± 3.6 m at 5.2 ka BP before falling towards present at rates up to -2 mm/yr driven by hydro-isostatic processes. The nature of RSL changes during the mid- to late-Holocene transition remains poorly resolved with evidence of sea levels falling below present level to -2.2 ± 2.0 m at 1.2 ka BP. Present RSL reconstructions from coral microatolls coupled with tide-gauge data extend the limited instrumental period in this region beyond ~50 years. They show RSL rose ~0.03 m from 1915 to 1990 at 0.7 ± 1.4 mm/yr before increasing to 1.5 ± 2.1 mm/yr after 1990 to 2019. Future RSL change from probabilistic projections to 2100 under low (RCP 2.6) and high (RCP 8.5) emission scenarios show sea levels rising 0.43 m (50<sup>th</sup> percentile) (0.06 – 0.96 m; 95% credible interval) and 0.74 m (0.28 – 1.4 m), respectively. However, projected magnitudes of sea-level rise driven by rapid ice sheet dynamics and the unknown contribution of atmospheric and ocean dynamics in Southeast Asia have the potential to exacerbate projection magnitudes.</p>

Estimating contribution of high-frequency sea-level oscillations to the extreme sea levels in the Adriatic Sea

2021 ◽  
Author(s):  
Krešimir Ruić ◽  
Jadranka Šepić ◽  
Maja Karlović ◽  
Iva Međugorac
Keyword(s):  
Time Series ◽  
Sea Level ◽  
High Frequency ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Data Series ◽  
Sea Levels ◽  
Short Period ◽  
Extreme Sea Levels ◽  
Sea Level Oscillations

<p>Extreme sea levels are known to hit the Adriatic Sea and to occasionally cause floods that produce severe material damage. Whereas the contribution of longer-period (T > 2 h) sea-level oscillations to the phenomena has been well researched, the contribution of the shorter period (T < 2 h) oscillations is yet to be determined. With this aim, data of 1-min sampling resolution were collected for 20 tide gauges, 10 located at the Italian (north and west) and 10 at the Croatian (east) Adriatic coast. Analyses were done on time series of 3 to 15 years length, with the latest data coming from 2020, and with longer data series available for the Croatian coast. Sea level data were thoroughly checked, and spurious data were removed. </p><p>For each station, extreme sea levels were defined as events during which sea level surpasses its 99.9 percentile value. The contribution of short-period oscillations to extremes was then estimated from corresponding high-frequency (T < 2 h) series. Additionally, for four Croatian tide gauge stations (Rovinj, Bakar, Split, and Dubrovnik), for period of 1956-2004, extreme sea levels were also determined from the hourly sea level time series, with the contribution of short-period oscillations visually estimated from the original tide gauge charts.  </p><p>Spatial and temporal distribution of contribution of short-period sea-level oscillations to the extreme sea level in the Adriatic were estimated. It was shown that short-period sea-level oscillation can significantly contribute to the overall extremes and should be considered when estimating flooding levels. </p>

scholarly journals A 10-Year Comparison of Water Levels Measured with a Geodetic GPS Receiver versus a Conventional Tide Gauge

2017 ◽  
Vol 34 (2) ◽  
pp. 295-307 ◽  
Author(s):  
Kristine M. Larson ◽  
Richard D. Ray ◽  
Simon D. P. Williams
Keyword(s):  
Tide Gauge ◽  
Signal Propagation ◽  
Propagation Delay ◽  
Terrestrial Reference Frame ◽  
Water Levels ◽  
Sea Surface ◽  
Ocean Tide ◽  
Gps Receiver ◽  
Tide Gauge Data ◽  
Gauge Data

AbstractA standard geodetic GPS receiver and a conventional Aquatrak tide gauge, collocated at Friday Harbor, Washington, are used to assess the quality of 10 years of water levels estimated from GPS sea surface reflections. The GPS results are improved by accounting for (tidal) motion of the reflecting sea surface and for signal propagation delay by the troposphere. The RMS error of individual GPS water level estimates is about 12 cm. Lower water levels are measured slightly more accurately than higher water levels. Forming daily mean sea levels reduces the RMS difference with the tide gauge data to approximately 2 cm. For monthly means, the RMS difference is 1.3 cm. The GPS elevations, of course, can be automatically placed into a well-defined terrestrial reference frame. Ocean tide coefficients, determined from both the GPS and tide gauge data, are in good agreement, with absolute differences below 1 cm for all constituents save K1 and S1. The latter constituent is especially anomalous, probably owing to daily temperature-induced errors in the Aquatrak tide gauge.

Sign in / Sign up

Export Citation Format

Share Document