Connectivity in SoCal Bight

UCLA-UCSB Telecon 1/14/08

Lagrangian Particle Tracking

• Used 6-hourly mean flow fields from 1996 thru 1999

(Thanks, Charles!)

• 1-hour time stepping for particle tracking

Output particle data every 6 hours

Used UCLA particle tracking code

• Released within 10 km from coast

Every 1 km, every 6 hours (32,748 particles / day)

• Depth is fixed at 5 m below top surface

Single-day, Single-point Release(30-day trajectories)

Release locationRelease location

Red dots = location 30 days later

Release = Jan 1, 1996 Release = Jan 1, 1997

Release = Jan 1, 1998 Release = Jan 1, 1999

• Particles released on the same date from the same

location show different dispersal patterns every year

• Particles released on the same date from the same

location show different dispersal patterns every year

Single-day, Single-point Release(30-day trajectories)

Release locationRelease location

Release = Jan 1, 1996 Release = Jan 16, 1996

Release = Jan 31, 1996 Release = Feb 15, 1999

Red dots = location 30 days later

• 2 weeks of difference in release timing can

result in very different dispersal patterns

• 2 weeks of difference in release timing can

result in very different dispersal patterns

Single-day, Single-Point Release(30-day trajectories)

Release locationRelease location

Palos VerdesNear San Diego

• Dispersal patterns depend on release locations• Dispersal patterns depend on release locations

Points

• Dispersal patterns show strong intra- & inter-annual variability (turbulent dispersion)

Particles released at the same location on the same day shows different patterns every year

15 days of difference in release timing can lead to different dispersal patterns

• Dispersal patterns depend on release location

• Trajectories show chaotic eddying motions, very different from a simple diffusion process

We need statistical description

Comparison with Drifter Data

(Not done yet. Hopefully done by Monday)

Lagrangian (Transition) PDF

• Probability density of Lagrangian particle location after time interval tau from release

• Estimate using all particles (1996-1999)

First, we neglect inter- & intra-annual variability

Pretend as if they were statistically stationary processes (i.e., independent of t0) and assume ergodicity...

Particle release location & dateParticle release location & date

Particle location after time interval tauParticle location after time interval tau

Lagrangian (Transition) PDFx0 = San Nicholas Island

Release locationRelease location

tau = 1 day tau = 10 days

tau = 20 days tau = 30 days

(Bin size: 5 km radius in space; 1 day in time)(Bin size: 5 km radius in space; 1 day in time)• Spread out in 20-30 days; more isotropic• Spread out in 20-30 days; more isotropic

Lagrangian (Transition) PDFx0 = Near San Diego (Oceanside)

Release locationRelease location

tau = 1 day tau = 10 days

tau = 20 days tau = 30 days

(Bin size: 5 km radius in space; 1 day in time)(Bin size: 5 km radius in space; 1 day in time)• Strong directionality (pole-ward transport)• Strong directionality (pole-ward transport)

From 9 Different Sites

Release locationRelease location

tau = 30 days

more isotropic spreadmore isotropic spread

eddy retentioneddy retentionpole-ward transportpole-ward transport

• Strong release-position dependence• Strong release-position dependence

Connectivity Matrix

• Lagrangian PDF in a matrix form

• Or, we can average Lagrangian PDF over some time interval (larval fish dispersal case)

(We can do weighted-mean, too)

Site Locations & Connectivity

MainlandMainland N. IslandsN. Islands S. IslandsS. Islands

Mai

nlan

dM

ainl

and

N.

Isla

nds

N.

Isla

nds

S. I

slan

dsS

. Isl

ands

• Pole-ward transport & eddy retention show up in connectivity

As a Function of Evaluation Time

tau = 30 days tau = 35 days tau = 40 days tau = 45 days

tau = 20 -- 40 days tau = 24 -- 48 days tau = 28 -- 56 days tau = 32 -- 64 days

• Spatial structures in connectivity fade away as tau increases (well mixed)

• Time averaging does not change connectivity

Source & Destination Strength

• Summation of connectivity matrix over i or j

(Would be useful for MPA design)

Source & Destination Strength

tau = 30 days tau = 30 days

tau = 40 days tau = 40 days

• Strongest Destination at Chinese Harbor

• Match well with observation (not shown here)

• Strongest Destination at Chinese Harbor

• Match well with observation (not shown here)

Summary

• Lagrangian particle can reach entire Bight in 30 days

• Dispersal patterns show release-position dependence

Strong directionality along mainland

More isotropic from Islands

Eddy retention in Channel & near San Clemente Island

• After spreading out in entire Bight, spatial patterns in Lagrangian PDF gradually fade away

Particles either go out of domain or go any places in Bight (well mixed)

Summary

• Connectivity shows spatial patterns, reflecting pole-ward transport along mainland & eddy retention

• But, spatial patterns fade away in time (~ 60 days)

As particles from various sources become well mixed

• Almost all sites can be connected in 30 days

• Source & destination strength patterns:

Strong source: mainland (SD ~ SB)

Strong destination: Santa Cruz, E. Anacappa, E. San Nicolas, North mainland (Palos Verdes ~ SB)

Strongest destination: Chinese Harbor (self retention + transport from mainland)

Inter-annual Variability

• Compute Lagrangian PDF using particles released in a particular year instead of using all years

1) 1996, 2) 1997, 3) 1998, or 4) 1998

• Let’s see PDF shows inter-annual variability

Lagrangian (Transition) PDFx0 = Near San Diego (Oceanside), tau = 30 days

Release locationRelease location

• Alongshore transport disappears in 1999 (La Nina);

very strong in 1997 (El Nino)

• Important for species invasion from Mexico

• Alongshore transport disappears in 1999 (La Nina);

very strong in 1997 (El Nino)

• Important for species invasion from Mexico

Lagrangian (Transition) PDFx0 = north shore of Santa Cruz Island, tau = 30 days

Release locationRelease location

• Eddy retention does not occur every year

• Important for species retention

• Eddy retention does not occur every year

• Important for species retention

Destination Strengthtau = 30 days

Source Strengthtau = 30 days

Summary

• Lagrangian PDF shows strong inter-annual variability

Northward transport is strongest in 1997 (El Nino), while it disappears in 1999 (La Nina).

Eddy retention does not appear every year

These will mean a lot to population ecology

• Source & destination strength changes accordingly

Seasonal Variability

• Compute Lagrangian PDF using particles released in a particular season

1) Winter of 1996-1999,

2) Spring of 1996-1999,

3) Summer of 1996-1999, and

4) Autumn of 1996-1999

• Seasonal variations are expected

Lagrangian (Transition) PDFx0 = Near San Diego (Oceanside), tau = 30 days

Release locationRelease location

• Pole-ward transport disappears spring &

summer when equator-ward wind is strong

• Pole-ward transport disappears spring &

summer when equator-ward wind is strong

Lagrangian (Transition) PDFx0 = north shore of Santa Cruz Island, tau = 30 days

Release locationRelease location

• Eddy retention is weakened in spring &

summer when equator-ward wind is strong

• Eddy retention is weakened in spring &

summer when equator-ward wind is strong

Lagrangian (Transition) PDFx0 = Palos Verdes Peninsula, tau = 30 days

Release locationRelease location

• Palos Verdes shows self retention in summer

possibly due to wind sheltering

• Palos Verdes shows self retention in summer

possibly due to wind sheltering

Inter-annual & Seasonal Variability in Connectivity

tau = 30 days

• Seasonal variability is stronger than inter-annual variability (as expected)

Self retention at many sitesSelf retention at many sites Self retention at limited sitesSelf retention at limited sites Pole-ward transportPole-ward transport

Source Strengthtau = 30 days

Destination Strengthtau = 30 days

Summary

• Lagrangian PDF shows strong inter-seasonal variability (as expected)

Pole-ward transport along the mainland appears fall & winter; gone in spring & summer

Eddy retention in Channel appears fall & winter

Depending on strength of equator-ward wind

• Seasonal patterns in connectivity are:

Winter: strong self retention at many sites

Spring & summer: strong self retention at limited places

Fall: strong pole-ward transport

Applications (to be done)

• We need several applications here

Ex. 1. Dispersal of fish larvae

Ex. 2. Spread of pollutants

• Given distributions of materials at x0 and t0, concentrations of materials after tau are given by

This can be larval production, oil spill distributions & etc

If molecular diffusion & chemical reactions are negligible, though