Impact of using scatterometer and altimeter data on storm surge forecasting

Bajo, Marco; Biasio, Francesco De; Umgiesser, Georg; Vignudelli, Stefano; Zecchetto, S.

doi:10.1016/j.ocemod.2017.03.014

Cited by 33 publications

(34 citation statements)

References 32 publications

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“…Two simulations, forced with the 2008 and 2009 cut‐off winds, have been run with each grid, for a total of six simulations. For these simulations, the model has been used in the configuration described in Section 2.2 and the bottom stress has the following quadratic formulation:

{bold-italicτ}_{normalb} = ρ_{w} C_{d} false| u false| boldu,

where u is the vertically averaged current velocity and C d is set to 0.0025 (Bajo et al ). The modelled water level was extracted at 12 stations (the same stations where observations are available) and compared for 20 days after the main sea level peak (when the wind stops).…”

Section: Resultsmentioning

confidence: 99%

“…Usually, during Sirocco episodes, at the eastern side of the Adriatic Sea, only the northernmost cities are endangered, but on this occasion the whole of Dalmatia (the central and southern part of the Croatian coast) was flooded as well. For further details on the 2008 flood, refer to Bertotti et al (), Med‐ugorac et al () and Bajo et al ().…”

Section: Resultsmentioning

confidence: 99%

“…Of course, the forecast can be improved using better atmospheric forcing but sometimes it is difficult to obtain such a forcing. Atmospheric models have higher errors in extreme events than under calm conditions (De Biasio et al ; Bajo et al ), while a correct set‐up of a data assimilation system should always improve the results, as we will show in the next section.…”

Section: Resultsmentioning

confidence: 99%

“…Without data assimilation, the model strongly underestimates the maxima, despite the correct model tuning that results from the first part of the paper. As was outlined also in other work (Zecchetto and Accadia, ; Bajo et al ), the underestimation of the wind forcing is the main issue. However, even with an underestimated wind, the forecast can improve considerably with a correct assimilation of residual sea level from coastal stations.…”

Section: Discussionmentioning

confidence: 99%

“…where u is the vertically averaged current velocity and is set to 0.0025 (Bajo et al, 2017). The modelled water level was extracted at 12 stations (the same stations where observations are available) and compared for 20 days after the main sea level peak (when the wind stops).…”

Section: Influence Of the Spatial Resolutionmentioning

confidence: 99%

See 4 more Smart Citations

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Bajo

Međugorac

Umgiesser

et al. 2019

Quart J Royal Meteoro Soc

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In this research we present a modelling study of storm surges influenced by pre‐existing seiches in the Adriatic Sea. The natural oscillation modes – seiches – of the Adriatic Sea can be easily excited by wind, due to the particular marine bathymetry and coastal orography. Moreover, such oscillations can interact with newer wind‐induced storm surges or with other sea‐level components. This paper first considers modelling issues in the seiche reproduction, using a simplified approach, and then analyses the reproduction with the model of two extreme storm surge events, influenced by pre‐existing seiches. In order to investigate the impact of assimilating sea level data, these events are simulated without and with a data assimilation system, based on an Ensemble Kalman Filter. Results show that, while the formulation of the bottom shear stress does not influence the seiche period, the seiche decay time is correctly estimated with a hybrid linear‐quadratic formulation. We found also that non‐linear interactions of bottom currents, caused by different sea level components, can modify the decay time. However, the two events are poorly reproduced by the model, even with a correct modelling set‐up, because of wind deficiencies. Therefore we considered the issue and found that the assimilation of tide‐gauge residual sea level has a strong positive impact, lasting several days, despite the errors in the atmospheric forcing. This is mainly due to the persistence of the seiche oscillations in the Adriatic Sea.

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{bold-italicτ}_{normalb} = ρ_{w} C_{d} false| u false| boldu,

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Influence Of the Spatial Resolutionmentioning

confidence: 99%

See 3 more Smart Citations

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Bajo

Međugorac

Umgiesser

et al. 2019

Quart J Royal Meteoro Soc

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Observations to Underpin Policy

Smail¹,

Celliers²,

Costa³

et al. 2022

Earth Observation Applications and Global Policy Frameworks

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Improving the short‐range forecast of storm surges in the southwestern Atlantic continental shelf using 4DEnSRF data assimilation

Dinápoli

Ruiz

Simionato

et al. 2023

Quart J Royal Meteoro Soc

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In this study, the assimilation of tide gauge and altimetry data into a two‐dimensional barotropic numerical model for the southwestern Atlantic continental shelf (SWACS) was developed. To do this, the preoperative 4‐day storm surges ensemble prediction system developed by Dinápoli et al. (2021, Journal of the Royal Meteorological Society 147: 557–572) was implemented for the SWACS. This new configuration, called “Model for Storm Surge Simulations” (M3S), considers a curvilinear grid that covers the SWACS with higher resolution along the shoreline (from 2 to 10 km). M3S was forced with an ensemble of 60 members conformed by the combination of perturbations of the eight principal tidal constituents and of the atmospheric products derived from the Global Ensemble Forecast System. Tidal gauge and altimetry data were assimilated in an asynchronous mode using the four‐dimensional‐ensemble square‐root filter (4DEnSRF). The system was developed and validated forecasting two strong positive storm surges. Results show that 4DEnSRF's innovations produce a positive impact upon the forecast skill up to 2 days. Hence, the 4‐day forecast can be divided into two parts: the first 2 days with a stronger dependence on the initial conditions and the other 2 days purely driven by external forcing. It was found that a symmetric assimilation window of 12 hr length produces the best initial condition. Under this configuration, 4DEnSRF removes biases and improves the timing of the M3S forecasted solutions. The largest improvements were observed at the northern SWACS, where more chaotic processes, such as the atmospheric circulation, explain a large part of the sea‐surface height variability. No significant improvements were found at the southern SWACS, which can be attributed to the strong tidal dynamics that characterise the zone. Our results show that the incorporation of 4DEnSRF into M3S can significantly improve the forecast in the SWACS and also the accuracy of the short‐range detection of storm surges.

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Impact of using scatterometer and altimeter data on storm surge forecasting

Cited by 33 publications

References 32 publications

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Observations to Underpin Policy

Improving the short‐range forecast of storm surges in the southwestern Atlantic continental shelf using 4DEnSRF data assimilation

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