Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.102
IF3.102
IF 5-year value: 3.284
IF 5-year
3.284
CiteScore value: 5.1
CiteScore
5.1
SNIP value: 1.37
SNIP1.37
IPP value: 3.21
IPP3.21
SJR value: 1.005
SJR1.005
Scimago H <br class='widget-line-break'>index value: 90
Scimago H
index
90
h5-index value: 42
h5-index42
Preprints
https://doi.org/10.5194/nhess-2020-340
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-340
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Oct 2020

30 Oct 2020

Review status
This preprint is currently under review for the journal NHESS.

Towards an efficient storm surge and inundation forecasting system over the Bengal delta: Chasing the super-cyclone Amphan

Md Jamal Uddin Khan1, Fabien Durand1,2, Xavier Bertin3, Laurent Testut1,3, Yann Krien3, A. K. M. Saiful Islam4, Marc Pezerat3, and Sazzad Hossain5,6 Md Jamal Uddin Khan et al.
  • 1LEGOS UMR5566, CNRS/CNES/IRD/UPS, 31400 Toulouse, France
  • 2Laboratório de Geoquímica, Instituto de Geociencias, Universidade de Brasilia, Brazil
  • 3UMR 7266 LIENSs, CNRS- La Rochelle University, 17000 La Rochelle, France
  • 4IWFM, BUET, Dhaka 1000, Bangladesh
  • 5Flood Forecasting and Warning Centre, BWDB, Dhaka, Bangladesh
  • 6Department of Geography and Environmental Science, University of Reading, UK

Abstract. The Bay of Bengal is a well-known breeding ground to some of the deadliest cyclones in history. Despite recent advancements, the complex morphology and hydrodynamics of this large delta and the associated modelling computational costs impede the storm surge forecasting in this highly vulnerable region. Here we present a proof of concept of a physically consistent and computationally efficient storm surge forecasting system tractable in real-time with limited resources. With a state-of-the-art wave-coupled hydrodynamic numerical modelling system, we forecast the recent super cyclone Amphan in real-time. From the available observations, we assessed the quality of our modelling framework. We affirmed the evidence of the key ingredients needed for an efficient, real-time surge and inundation forecast along this active and complex coastal region. This article shows the proof of the maturity of our framework for operational implementation, which can particularly improve the quality of localized forecast for effective decision-making.

Md Jamal Uddin Khan et al.

Interactive discussion

Status: open (until 22 Dec 2020)
Status: open (until 22 Dec 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Md Jamal Uddin Khan et al.

Data sets

Digitized flood location dataset during cyclone Amphan from newspaper survey Md Jamal Uddin Khan https://doi.org/10.5281/zenodo.4086102

Md Jamal Uddin Khan et al.

Viewed

Total article views: 264 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
202 59 3 264 6 3
  • HTML: 202
  • PDF: 59
  • XML: 3
  • Total: 264
  • BibTeX: 6
  • EndNote: 3
Views and downloads (calculated since 30 Oct 2020)
Cumulative views and downloads (calculated since 30 Oct 2020)

Viewed (geographical distribution)

Total article views: 211 (including HTML, PDF, and XML) Thereof 206 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 02 Dec 2020
Publications Copernicus
Download
Short summary
The Bay of Bengal is well-known for some of the deadliest cyclones in history. At the same time, storm surge forecasting in this region is physically involved, and computationally costly. Here we show a proof-of-concept of a real-time, computationally-efficient, and physically-consistent forecasting system with an application to a recent super cyclone Amphan. While challenges remain, our study paves the path forward to the improvement of the quality of localized forecast and disaster management.
The Bay of Bengal is well-known for some of the deadliest cyclones in history. At the same time,...
Citation
Altmetrics