Index of /clawpack/links/noaa-tsunami-benchmarks/BM_MATLAB_SCRIPT

[ICO]NameLast modifiedSizeDescription

[PARENTDIR]Parent Directory   -  
[DIR]FieldBM1/ 2010-09-22 12:34 -  
[DIR]LabBM1/ 2010-09-22 12:31 -  
[DIR]LabBM4/ 2010-09-22 12:33 -  
[DIR]LabBM5/ 2010-09-22 12:33 -  


From: Juan Horrillo 
Date: Mon, 07 Mar 2011 15:19:00 -0600


Please refer to:
http://nctr.pmel.noaa.gov/benchmark/index.html



B) Laboratory benchmarking
1-Solitary wave on a simple beach
Matlab Script                   : LabBM_SW_01
Data Files                         : SW_01_00185.mat
                                         SW_01_03.mat
Example(Model result file): NEOWAVE_SW_01_00185.dat
                                         NEOWAVE_SW_01_03.dat
4-Tsunami runup onto a complex three-dimensional beach; Monai Valley
 Matlab Script                  : LabBM_IW_04
Data Files                        : IW_04_gages.mat
Example(Model result file): TSUNAMI_IW_04.dat
5-Tsunami generation and runup due to three-dimensional landslide
Matlab Script                   : LabBM_SL_05
Data Files                         : SL_05_025.mat
                                         SL_05_100.mat
Example(Model result file): FUNWAVE_SL_05_025.dat
                                         FUNWAVE_SL_05_100.dat
C) Field benchmarking
1- Rat Islands tsunami
Matlab Script                    : FieldBM_CS_01
Data Files                          : CS_01_gage.mat
Example(Model result file) : ADCIRC_CS_01.dat

Matlab script-functions are self-containing and easy to use. They load
lab/field data automatically to facilitate user comparison, peer review and
determine model performance. For instance, by just running the script eg. >
LabBM_SW_01 directions will pop-up with preloaded fake files pretending
model results. To see that try this >FieldBM_CS_01('ADCIRC_CS_01.dat')  .
Users just have to change the model result file name or names for theirs in
the argument of the script function according to a pre-established format
indicated in the direction, then they can obtain their model comparison and
performance.
I adopted  the normalized root mean square deviation (NRMSD) or normalized
root mean square error to measure the numerical model precision. However,
other statistical quantities  like the correlation coef., index of
agreement,  scatter Index or absolute error  are as well valid and  can be
implemented with little effort (more discussion is needed here and I open to
suggestions) .  The   NRMSD measures the differences/desviations between
values predicted by the   numerical model and the values actually observed
in the experiment   or in the field. In some benchmark problem the NRMSD is
plotted in time to visualize model   performance in a particular moment.  As
it is known tsunami models    usually predict fairly well the leading waves
but perform poorly in  predicting subsequent waves.  This feature allows
users  quantify model  performance for the first, first two or first three
waves and so forth.
Notice there are some benchmarks still in need of a Matlab Script-function.
1- Single wave on a simple beach
2- Solitary wave on a composite beach (no available on the webpage)
3- Solitary wave on a conical island
 4-Okushiri Tsunami

Sincerely,

JUAN