MORPHOS:MORPHOS: A Coupled Modeling A Coupled … - A Coupled Modeling System.pdfCoastal Landforms...

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.

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

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.

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

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.

Wind Module: TC-96

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

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

Hurricane Frances Winds at Landfall0600 UTC, September 5, 2004.

a)

200

Wind Speeds (km/hr)

183166149132115988164

b)

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).

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

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

Beach Morphology Module:XBeach

Dano Roelvink, Ad Reniers,

Ap van Dongeren

Horizontal Grid

Wave Action Balance

Wave Action Propagation Speeds

Wave Energy Dissipation

After Baldock et a. (1998)

Radiation Stresses

Roller Energy Balance

Roller Contributions to Radiation Stresses

Shallow Water Equations

Generalized Lagrangian Mean (GLM)Formulation

Walstra et al. (2000)

Sediment Transport

Soulsby (1997)

Dune Avalanching

0 400 m

0 100 m

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?

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.

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