The all-source Green's function (ASGF) and its applications to storm surge modeling, part I: from the governing equations to the ASGF convolution
Gespeichert in:
Verfasser / Beitragende:
[Zhigang Xu]
Ort, Verlag, Jahr:
2015
Enthalten in:
Ocean Dynamics, 65/12(2015-12-01), 1743-1760
Format:
Artikel (online)
Online Zugang:
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| 024 | 7 | 0 | |a 10.1007/s10236-015-0893-z |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10236-015-0893-z | ||
| 100 | 1 | |a Xu |D Zhigang |u Fisheries and Oceans Canada, Maurice Lamontagne Institute, Mont-Joli, Quebec, Canada |4 aut | |
| 245 | 1 | 4 | |a The all-source Green's function (ASGF) and its applications to storm surge modeling, part I: from the governing equations to the ASGF convolution |h [Elektronische Daten] |c [Zhigang Xu] |
| 520 | 3 | |a In this study, a new method of storm surge modeling is proposed. This method is orders of magnitude faster than the traditional method within the linear dynamics framework. The tremendous enhancement of the computational efficiency results from the use of a pre-calculated all-source Green's function (ASGF), which connects a point of interest (POI) to the rest of the world ocean. Once the ASGF has been pre-calculated, it can be repeatedly used to quickly produce a time series of a storm surge at the POI. Using the ASGF, storm surge modeling can be simplified as its convolution with an atmospheric forcing field. If the ASGF is prepared with the global ocean as the model domain, the output of the convolution is free of the effects of artificial open-water boundary conditions. Being the first part of this study, this paper presents mathematical derivations from the linearized and depth-averaged shallow-water equations to the ASGF convolution, establishes various auxiliary concepts that will be useful throughout the study, and interprets the meaning of the ASGF from different perspectives. This paves the way for the ASGF convolution to be further developed as a data-assimilative regression model in part II. Five Appendixes provide additional details about the algorithm and the MATLAB functions. | |
| 540 | |a The Author(s), 2015 | ||
| 690 | 7 | |a Shallow-water equations |2 nationallicence | |
| 690 | 7 | |a Storm surges |2 nationallicence | |
| 690 | 7 | |a The all-source Green's functions (ASGFs) |2 nationallicence | |
| 690 | 7 | |a Convolution |2 nationallicence | |
| 773 | 0 | |t Ocean Dynamics |d Springer Berlin Heidelberg |g 65/12(2015-12-01), 1743-1760 |x 1616-7341 |q 65:12<1743 |1 2015 |2 65 |o 10236 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10236-015-0893-z |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10236-015-0893-z |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 100 |E 1- |a Xu |D Zhigang |u Fisheries and Oceans Canada, Maurice Lamontagne Institute, Mont-Joli, Quebec, Canada |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Ocean Dynamics |d Springer Berlin Heidelberg |g 65/12(2015-12-01), 1743-1760 |x 1616-7341 |q 65:12<1743 |1 2015 |2 65 |o 10236 | ||
| 986 | |a SWISSBIB |b 605546630 | ||