Application of a Sequential Data Assimilation Technique to Improve Modeling of Surface Currents Using Radar Data at a Coastal Domain

6 pages•Published: September 20, 2018

Abstract

Numerical model is generally to simulate hydrodynamic parameters such as surface currents. However, it has limits such as difficulty in definition of initial and boundary conditions. As remote sensing such as satellite and radars advances and is applied in practice. Data assimilation technique has becoming a promising means to improve modeling performance through taking advantages of available observations. In this paper, surface currents hourly monitored by a radar system were assimilated into a 3D numerical model to improve modeling performance using a sequential data assimilation algorithm. Results indicated that application proposed data assimilation approach not only improved hindcasting of surface flow fields, but also improved its forecasting.

Keyphrases: data assimilation, efdc, galway bay, radar, surface currents

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1752-1757.

Links:	https://easychair.org/publications/paper/x9g6
	https://doi.org/10.29007/w7nn

BibTeX entry

@inproceedings{HIC2018:Application_Sequential_Data_Assimilation,
  author    = {Lei Ren and Michael Hartnett},
  title     = {Application of a Sequential Data Assimilation Technique to Improve Modeling of Surface Currents Using Radar Data at a Coastal Domain},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/x9g6},
  doi       = {10.29007/w7nn},
  pages     = {1752-1757},
  year      = {2018}}

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