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INUNDATION TESTBED PI MEETING: LSU FVCOM Progress. Chunyan Li (with ACKNOWLEDGEMENT to UMASS Team and Dr. Zheng ) Louisiana State University. Computer Resource Usage. LONI computers: Queen Bee - 668 Compute Nodes 50.7 TFlops Peak Performance - PowerPoint PPT Presentation
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INUNDATION TESTBED PI MEETING: LSU FVCOM Progress
Chunyan Li (with ACKNOWLEDGEMENT to UMASS Team and Dr. Zheng)
Louisiana State University
1
2
Computer Resource UsageLONI computers:
Queen Bee - 668 Compute Nodes50.7 TFlops Peak PerformanceTwo 2.33 GHz Quad Core Xeon 64-bit Processors8 GB Ram10 Gb/sec Infniband network interface10/100/1000 Ethernet network interfaceRed Hat Enterprise Linux 4
Painter - 128 compute node cluster4.77 TFlops Peak Performance Two 2.33 GHz Quad Core Xeon 64-bit ProcessorsA Dell Linux cluster housed at Louisiana Tech University10 Gb/sec Infniband network interface10/100/1000 Ethernet network interfaceRed Hat Enterprise Linux 4
Louie …Poseidon …
3
Total used 166003 SUsWith ~ 80% used for this project
270K SU More LONI allocations Requested
4
Cases that have been run –1. 2D tide only:
dtE = 2 sec.2008.8.1 – 2008.10.1nodes=32:ppn=8 256 CPUsfinished in 12:47:33 (12.7925 hr.) walltime
61 days of simulation 12.7925 hr./61 day =12.5828 min./day2a. 2D tide only new run
2008.7.1 – 2008.11.1nodes=16:ppn=8 128 CPUsStart saving Aug. 1: 93 days of simulation ran from 2/27, 5:02:43 AM to 2/28, 14:49:39
a total of 1.4076 days 1.4076 days /92 days = 22.03 min/day
5
Cases that have been run –2b. 2D tide only new run:
dtE = 2 sec.2008.7.1 – 2008.11.1nodes=16:ppn=8 128 CPUsfinished in 45:14:52 (45.2478 hr.) walltime
123 days of simulation 45.2478 hr./123 day =22.07 min./day
Scaling: doubling CPUs 22.07/12.5828=1.75
6
Cases that have been run (continued) –4. 2D tide + hurricane surge:
dtE = 2 sec.2008.9.6 – 2008.9.16nodes=16:ppn=8 128 CPUs
5. 2D wave only2008.9.6 – 2008.9.16nodes=32:ppn=8 256 CPUs
7
Cases that have been run (continued) –6. 3D tide only (new):
dtE = 1 sec.2008.7.1 – 2008.11.1nodes=48:ppn=8 384 CPUs~ Finished in 3 days 3 hr.
75 hr./day ~ 0.625 hr./day7. 3D tide + hurricane surge
nodes=16:ppn=8 128 CPUs2008.9.6 – 2008.9.16 (10 days) ~ Finished in 16 hr.
1.6 hr./day Scaling: 384/128=3, tripling CPUs 1.6/0.625=2.56
8
Observations for Hurricane storm surges by Hurricanes Gustav and Ike
OUR OWN DATALi, C., E. Weeks, B. W. Blanchard, 2010, Storm surge induced flux through multiple tidal passes during Hurricanes Gustav and Ike, Estuarine, Coastal and Shelf Science, 87 (2010) 517–525.
Rate of water flux in m3/s and the 40-hour low-pass filtered time series.
Rigolets
Chef Menteure
Industrial Canal
9
Observations for Hurricane storm surges by Hurricanes Gustav and Ike
Li, C., E. Weeks, B. W. Blanchard, 2010, Storm surge induced flux through multiple tidal passes during Hurricanes Gustav and Ike, Estuarine, Coastal and Shelf Science, 87 (2010) 517–525.
10
WAVCIS DATA
0 5 10 15 20 25 30 35-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3Grand Isle
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model: no tidal potential
0 5 10 15 20 25 30 35-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4Shell Beach
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3Cypremort Point
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8Calcasieu Pass
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6Bay Waveland YachtClub
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4Gulfport Harbor
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4Freshwater Canal Locks
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8Sabine Pass North
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6Galveston Pleasure Pier
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4USCG Freeport data
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5Dock E Port Pascagoula
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4Dauphin Island
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4Panama City
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5Apalachicola
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6Clearwater Beach
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
0 5 10 15 20 25 30 35-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6Naples
Wat
er L
evel
(m)
Time (days) from July 25, 2008
PredictedModeled
Results from Initial Run of the 2D Model
data1 = t8724698;data2 = t8726724;data3 = t8727333;data4 = t8727520;data5 = t8729210;data6 = t8729678;data7 = t8735180;data8 = t8737048;data9 = t8737373;data10= t8741041;data11= t8741196;data12= t8741533;data13= t8742221;data14= t8743281;data15= t8744117;data16= t8745557;data17= t8747437;data18= t8747766;data19= t8760551;data20= t8760922;data21= t8760943;data22= t8761305;data23= t8761720;data24= t8761724;data25= t8761927;data26= t8762075;data27= t8762372;data28= t8764025;data29= t8764044;data30= t8764227;
data31= t8764311;data32=t8765251;data33=t8766072;data34=t8767816;data35=t8767961;data36=t8768094;data37=t8770475;data38=t8770520;data39=t8770559;data40=t8770570;data41=t8770613;data42=t8770743;data43= t8770777;data44= t8770933;data45= t8770971;data46=t8771013;data47= t8771450;data48= t8771510;data49= t8772447;data50= t8773037;data51= t8773701;data52=t8774513;data53=t8774770;data54=t8775188;data55=t8775237;data56=t8775283;data57=t8775296;data58=t8775792;data59=t8775870;
Node numbers in the order of the numbers
%=========================================================% DATE: FEB. 11, 2011% NOTE: THE JULIAN DATE WAS DEFINED% BY THE "MODIFIED JULIAN DAY" STARTING FROM% 1858, 11, 17, 0:00%% It can be verified by datenum(2008, 8,1)-t0-time(1) = 0% See below for definition of t0.%==========================================================
t0 = datenum(1858,11,17);dt = t0+time(1) - datenum(2008, 1,1);
time1 = time - time(1);times = (0:length(zetas1)-1)*1/24 - dt; % delta t = 1 hour
Note: station 25 is New Canal station, which did not seem to have predicted data on NOAA’s web site.
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)data1 = t8724698
modelpredicted
Results from New Run of the 2D Model: w/ Tidal Potential
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data2 = t8726724
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data3 = t8727333
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data4 = t8727520
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data5 = t8729210
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data6 = t8729678
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data7 = t8735180
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data8 = t8737048
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data9 = t8737373
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data10= t8741041
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data11= t8741196
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data12= t8741533
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data13= t8742221
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data14= t8743281
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data15= t8744117
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data16= t8745557
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data17= t8747437
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data18= t8747766
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data19= t8760551
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data20= t8760922
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data21= t8760943
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data22= t8761305
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data23=t8761720
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data24= t8761724
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data25= t8761927
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data26= t8762075
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data27= t8762372
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data28= t8764025
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data29=t8764044
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data30=t8764227
modelpredicted
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data31=t8764311
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data32=t8765251
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data33=t8766072
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data34=t8767816
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data35=t8767961
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data36=t8768094
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data37=t8770475
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data38=t8770520
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data39=t8770559
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data40= t8770570
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data41= t8770613
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data42= t8770743
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data43=t8770777
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data44= t8770933
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data45= t8770971
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data46= t8771013
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data47= t8771450
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data48= t8771510
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data49=t8772447
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data50=t8773037
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data51=t8773701
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data52=t8774513
modelpredicted
Results from New Run of the 2D ModelResults from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data53=t8774770
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data54=t8775188
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data55=t8775237
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data56=t8775283
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data57=t8775296
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data58=t8775792
modelpredicted
Results from New Run of the 2D Model
30 35 40 45-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Days from 2008.8.1
Z (m
)
data59=t8775870
modelpredicted
Results from New Run of the 2D Model
88
3-D Results (FVCOM) 2-D Results (FVCOM)
8724698 zmamp zpamp zmphs zpphs dphs zmamp zpamp zmphs zpphs dphs
O1 0.1181 0.1261 57.4217 4.3942 53.0275 0.1256 0.1261 37.5831 4.3942 33.1889
K1 0.0848 0.1077 2.5141 3.9161 -1.402 0.1018 0.1077 12.4268 3.9161 8.5107
N2 0.0219 0.0228 89.8083 16.1022 73.7061 0.0226 0.0228 89.7996 16.1022 73.6974
M2 0.1218 0.133 64.2292 89.2734 -25.0442 0.1256 0.133 64.192 89.2734 -25.0814
S2 0.0493 0.0528 89.9738 89.4887 0.4851 0.051 0.0528 89.9785 89.4887 0.4899
K2 0.0187 0.0118 0.857 71.4762 -70.6192 0.0196 0.0118 0.6832 71.4762 -70.793
Q1 0.0265 0.0263 88.214 13.9924 74.2216 0.0275 0.0263 83.6412 13.9924 69.6488
P1 0.0028 0.0297 85.4583 0.412 85.0463 0.0034 0.0297 60.0943 0.412 59.6823
M4 0.0006 0.0044 89.1759 88.8083 0.3676 0.0005 0.0044 87.051 88.8083 -1.7573
M6 0.001 0 89.9979 85.7334 4.2645 0.0013 0 89.1471 85.7334 3.4138
Harmonic Analysis Results
89
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.50
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Modeled Amplitude (m)
Pre
dict
ed A
mpl
itude
(m)
3D Results
90
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.50
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Modeled Amplitude (m)
Pre
dict
ed A
mpl
itude
(m)
2D Comparison
91
Reasons of discrepancy:
1.Bathymetry 2.Topography3.Dry – wet points
92
Solution?
1. update bathymetry2. upgrade topography3. delete dry points for
comparison
