GOAL OF THIS WORK

■ To investigate larval transport in “idealized” simulations

● To describe long term & short term dispersal kernels

● Four scenarios considered

▷ Strong or weak upwelling

▷ Northern or southern California

■ To develop modeling to establish short time kernels

from available data sets

IDEALIZED SIMULATIONS

■ Idealized is state that shows

1) statistical stationarity

2) statistical homogeneity in alongshore

3) physically reasonable coastal current

■ Make particle tracking easier

■ No such simulation in literature

● Need to construct our own

OBJECTIVE OF THIS TALK

■ To show progress in simulation construction

● Focus on summer northern California

● Hard to satisfy three “idealized” conditions

● Still some problems in simulations

ROADMAP

■ Four things to be modeled

1) Numerical domain

2) Boundary conditions

3) Initial conditions

4) Forcings

■ Show obtained simulation fields & trajectories

■ Research plan to obtain kernel

1) NUMERICAL DOMAIN

■ 64 x 64 x 32 grid points

512 km x 512 km Depth: 20 m -- 500 m

2) BOUNDARY CONDITIONS

Periodic

Periodic

Free-slip wall

Nudging &sponge layer

Wind stressOpen B.C.'s

2) BOUNDARY CONDITIONS

■ Open B.C.'s

● Outflow: radiation

▷ Extrapolates boundary values from interior values

● Inflow: nudging

▷ Forces boundary values to reference values

● Sponge & nudging layer

▷ Remove numerical difficulty

3) INITIAL CONDITIONS

■ Determined using CALCOFI Atlas

● Velocity: geostrophic velocity

▷ No motion at 500db (500m)

● Temperature

▷ Consistent with given density field

● Sea level

▷ Dynamic height with zero mean

4) FORCINGS

■ Two external forces:

wind stress & pressure gradient

■ Wind stress:

Modeled with Gaussian random process

whose statistics taken from NBDC archive

○ Cross-shore: 0-m/s mean, 1.2-m/s std, 1-hour corr.

○ Alongshore: -5.6-m/s mean, 4.6-m/s std, 2-hour corr.

4) FORCINGS

■ Pressure gradient: imposed as external force

● Periodic domain cannot develop pressure difference

at north/south boundaries

● Computed from dynamic height difference

between Pt. Arena & Pt. Conception

COMPUTATION

■ Two year simulation with 30-minute time stepping

● Using ICESS cluster

▷ Took 6 hours using 2 CPU's

▷ Eventually using 12 CPU's

■ Lagrangian particles:

● Released after fields are fully developed

● Released every day at fixed location

RESULTS: TEMPERATURE

RESULTS: TEMPERATURE

RESULTS: ALONGSHORE VELOCITY

RESULTS: SEA LEVEL

RESULTS: KINETIC ENERGY

RESULTS: PARTICLE TRAJECTORIES

PLAN TO OBTAIN KERNEL

■ Describe kernel in idealized simulations

● Track “settlers” & sort them by PLD

▷ Issue: what is “settlement”?

● Question: how do they look?

▷ Long term? Short term?

■ Model short term kernel

● From available data set

PLAN TO OBTAIN KERNEL

■ Detect particle correlation time & length

● Say, particles released within 20 hours at same source

go to same destination

● Say, particles released at sources separated 2 km or less

at same time go to same destination

■ Release many particles separated by 2 km every 20 hours

■ Observe when kernel becomes Gaussian

● Possibly a month, or possibly over years

SUMMARY

■ “Idealized” simulations are under development

● Little too excited

● But, shows reasonable turbulence structures

● Will be done shortly

■ Dispersal kernel will be provided soon (hopefully)

■ Adding complexity

● Inhomegeneity, behavior, etc