MORPHOS:MORPHOS: A Coupled Modeling A Coupled … - A Coupled Modeling System.pdfCoastal Landforms...
Transcript of MORPHOS:MORPHOS: A Coupled Modeling A Coupled … - A Coupled Modeling System.pdfCoastal Landforms...
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MORPHOS:MORPHOS: A Coupled ModelingA Coupled ModelingSystem for Predicting Change toSystem for Predicting Change to
Coastal Landforms From HurricanesCoastal Landforms From Hurricanes
David C. Froehlich, Ph.D., P.E., D.WREDavid C. Froehlich, Ph.D., P.E., D.WRE
Woolpert, Inc.Woolpert, Inc.
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MORPHOS Project Overview• Primary objective of the MORPHOS
project is to develop and verify adefensible 3D coastal simulation andprediction capability with a storm-driven climatology. Specific objectivesof the project are as follows:– Develop a synthetic tropical cyclone
generator for long-term risk analysisbased on NHC historic tracks
– Implement a wave model withimproved shallow water 3G wavephysics
– Develop an improved 3D circulation(initially barotropic) model
– Implement an improved hurricanedriven morphology evolution model
– Develop and implement 2-way modelcomponent coupling
– Provide foundation for improved Corpspredictive capability
– Close coordination with ONR, USGS,FEMA, and NOAA
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Predicting Short-term CoastlineChanges
• Beaches change their shape (or morphology) in response to theprevailing environmental conditions – a combination of waves,currents, water levels and wind.
• Engineeredstructures such asgroynes, artificialheadlands anddetachedbreakwaters areused as means tocontrol themovement ofsediment on thebeach.
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Data Entry/Display Modules(SMS and others)• Winds, Waves, Currents, Sediment Transport• Set-up, Surge, Beach Profile
MORPHOS Overview
Waves Module• 3G Source Terms• Shallow water physics
Circulation Module• 3D Dynamics• Coastal mass conservation
Sediment DynamicsModule• Physics / Empirical• Non-cohesive
Coupler
Atmospheric Module• Wind Field Generation
Dynamical Core• Auto-Nesting
Climate Module• Storm Tracks and Parameters
Historical Synthetic ForecastData Interface
Data Base• Bathymetry, Topography• Observations• Climatology
Validation Module• Auto-Validation• Data Comparisons• Model Benchmarking
• Grid Generation • Output Specification• Event SpecificationUser Interface
25 Oct 2005
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Atmospheric Modeling
• The atmospheric model isbased on the slab boundarylayer concept originallyconceived by Ooyama(1969).
• Similar models based onthis concept have beendeveloped by Chow (1971),Thompson and Cardone(1996) and Vickery et al.(2000).
• The model is initialized by aboundary layer vortex ingradient balance.
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Wind Module: TC-96
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2004 Atlantic Hurricanes Making Landfall in Florida
StormName
ActiveDates
Stormcategory
at peak
intensity
Max
Wind
(mph)
Min.
Press.
(mbar)
ACE
Landfall(s)Damage
(millions
USD)
DeathsWhere When
Wind
(mph)
Charley August9–14
Category4
Hurricane150 941 10.6
Playa del Cajio,Cuba 13 August 120
16000 15(20)Cayo Costa,
Florida August 13 150
Punta Gorda,Florida August 13 145
Cape Romain,South Carolina August 14 80
North MyrtleBeach, SouthCarolina
August 14 75
Frances27Aug -8 Sept
Category4
Hurricane145 936 45.9
San SalvadorIsland, Bahamas Sept 2 125 9600 7 (42)
Cat Island,Bahamas Sept 3 115
Eleuthera,Bahamas September 3 110
Grand BahamaIsland Sept 4 105
HutchinsonIsland South,Florida
Sept 5 105
Mouth of AucillaRiver, Florida Sept 6 60
Ivan Sept2–24
Category5
Hurricane165 910 70.4
Pine Beach,Alabama Sept 16 120 17200 92 (32)
Holly Beach,Louisiana Sept 24 35
Jeanne 24–29Sept
Category3
Hurricane120 950 24.2
near Guadeloupe Sept 14 35 7000 3035+
Near Guayama,Puerto Rico Sept 15 70
Eastern tip ofDominicanRepublic
Sept 16 80
Abaco Island,Bahamas Sept 25 115
HutchinsonIsland South,Florida
Sept 26 120
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Hurricane FrancesAugust 25 - September 8, 2004
100°W 90°W 80°W 70°W 60°W
40°N
30°N
20°N
10°N
2930311
23
4567
8
9
10
Tropical Storm
0000 UTC Position/Date1200 UTC Position
Tropical Depression/Extratropical
Hurricane
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Hurricane Frances Winds at Landfall0600 UTC, September 5, 2004.
a)
200
Wind Speeds (km/hr)
183166149132115988164
b)
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Wave Module: STWAVE• STWAVE (STeady State spectral
WAVE) is an easy-to-apply, flexible,robust, half-plane model fornearshore wind-wave growth andpropagation.
• STWAVE simulates– Depth-induced wave refraction and
shoaling– Current-induced refraction and shoaling– Depth- and steepness-induced wave
breaking– Wave diffraction– Wind-wave interaction– White capping that redistribute and
dissipate energy in a growing wavefield.
• STWAVE is being extended from ahalf-plane model to a full-plane,unsteady-state model (includingpropagation and generation from alldirections).
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Ocean Module: ADCIRC-DGFEM
1e
1e
2e
3e
1m
2m
3m
hu
hu huin
1; set of polynomial basis functions
N
m m mm
u u b b
u
u
x
y
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2D Depth-Integrated Flow Equations
cos10
cos
VHUHt R
0 0
1 1 tan 1 10
cos cosS SpU U U
U V U f V g M Ut R R R R H H
0 0
1 1 tan 1 10
cosSSpV V V
U V U f U g M Vt R R R R H H
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Beach Morphology Module:XBeach
Dano Roelvink, Ad Reniers,
Ap van Dongeren
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Horizontal Grid
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Wave Action Balance
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Wave Action Propagation Speeds
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Wave Energy Dissipation
After Baldock et a. (1998)
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Radiation Stresses
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Roller Energy Balance
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Roller Contributions to Radiation Stresses
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Shallow Water Equations
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Generalized Lagrangian Mean (GLM)Formulation
Walstra et al. (2000)
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Sediment Transport
Soulsby (1997)
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Dune Avalanching
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0 400 m
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0 100 m
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General Grid Transfer• General grid transfer operations on a
distributed-memory parallelmachine.
• For each of the nodal points it ownsin one mesh, how does a processordetermine which element in theother mesh contains that node, andwhat processor owns that element?
• To what other processor(s) should aprocessor send its interpolatedquantities?
• Since the resulting pattern of datatransfer is irregular and dynamic (ifthe grids are moving or adapting),how can the communication of gridgeometry and interpolated solutionsbe carried out optimally?
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Geometric Partitioning• A fast and simple geometric partitioning
algorithm is known as recursive coordinatebisectioning (RCB)
• Uses cutting planes normal to the x-, y-, or z-axis.
• Takes as input the geometric locations of aset of objects
• (elements or nodes in this case)• Determines in which coordinate direction the
set of objects is most elongated, and thendivides the objects in half by positioning acutting plane normal to that direction.
• Processors are likewise split into two groups.• The original set of points is split in half.• halves, each on a subset of processors, which
can be further divided by applying the sameprocedure recursively.
• Recursive coordinate bisectioning of 30points across 15 processors is shown. Thetop-level cut is shown in red, the second-level in blue, the 3rd in green, and thelowest-level in yellow.
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Geometric Rendezvous
Plimpton, S. J., Hendrickson, B., and Stewart, J. R. (2004). “A parallel rendezvous algorithm forinterpolation between multiple grids.” Journal of Parallel and Distributed Computing, 64(2),266–276.
Sourceprimaryregion
Destinationprimaryregion
Sourcesecondary
region
Destinationsecondary
region
Local interpolation
Local geometric search
Geometric rendezvous decomposition
Mesh data Interpolatedfield data
Mesh andfield data
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