Connectivity in socal bight
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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

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Connectivity in SoCal Bight

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Connectivity in socal bight

Connectivity in SoCal Bight

  • UCLA-UCSB Telecon 1/14/08


Lagrangian particle tracking

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

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

Release = Jan 1, 1996

Release = Jan 1, 1997

Red dots = location 30 days later

Release location

Release = Jan 1, 1998

Release = Jan 1, 1999

  • Particles released on the same date from the same location show different dispersal patterns every year


Single day single point release 30 day trajectories1

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

Release = Jan 1, 1996

Release = Jan 16, 1996

Red dots = location 30 days later

Release location

Release = Jan 31, 1996

Release = Feb 15, 1999

  • 2 weeks of difference in release timing can result in very different dispersal patterns


Single day single point release 30 day trajectories2

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

Near San Diego

Palos Verdes

Release location

  • Dispersal patterns depend on release locations


Points

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

Comparison with Drifter Data

(Not done yet. Hopefully done by Monday)


Lagrangian transition pdf

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 location after time interval tau

Particle release location & date


Lagrangian transition pdf1

Lagrangian (Transition) PDF

x0 = San Nicholas Island

tau = 1 day

tau = 10 days

Release location

tau = 20 days

tau = 30 days

  • Spread out in 20-30 days; more isotropic

(Bin size: 5 km radius in space; 1 day in time)


Lagrangian transition pdf2

Lagrangian (Transition) PDF

x0 = Near San Diego (Oceanside)

tau = 1 day

tau = 10 days

Release location

tau = 20 days

tau = 30 days

  • Strong directionality (pole-ward transport)

(Bin size: 5 km radius in space; 1 day in time)


From 9 different sites

From 9 Different Sites

tau = 30 days

pole-ward transport

eddy retention

Release location

more isotropic spread

  • Strong release-position dependence


Connectivity matrix

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

Site Locations & Connectivity

S. Islands

N. Islands

Mainland

Mainland

N. Islands

S. Islands

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


As a function of evaluation time

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

Source & Destination Strength

  • Summation of connectivity matrix over i or j

(Would be useful for MPA design)


Source destination strength1

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)


Summary

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)


Summary1

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

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 pdf3

Lagrangian (Transition) PDF

x0 = Near San Diego (Oceanside), tau = 30 days

Release location

  • Alongshore transport disappears in 1999 (La Nina); very strong in 1997 (El Nino)

  • Important for species invasion from Mexico


Lagrangian transition pdf4

Lagrangian (Transition) PDF

x0 = north shore of Santa Cruz Island, tau = 30 days

Release location

  • Eddy retention does not occur every year

  • Important for species retention


Destination strength

Destination Strength

tau = 30 days


Source strength

Source Strength

tau = 30 days


Summary2

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

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 pdf5

Lagrangian (Transition) PDF

x0 = Near San Diego (Oceanside), tau = 30 days

Release location

  • Pole-ward transport disappears spring & summer when equator-ward wind is strong


Lagrangian transition pdf6

Lagrangian (Transition) PDF

x0 = north shore of Santa Cruz Island, tau = 30 days

Release location

  • Eddy retention is weakened in spring & summer when equator-ward wind is strong


Lagrangian transition pdf7

Lagrangian (Transition) PDF

x0 = Palos Verdes Peninsula, tau = 30 days

Release location

  • Palos Verdes shows self retention in summer possibly due to wind sheltering


Inter annual seasonal variability in connectivity

Inter-annual & Seasonal Variability in Connectivity

tau = 30 days

Self retention at many sites

Self retention at limited sites

Pole-ward transport

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


Source strength1

Source Strength

tau = 30 days


Destination strength1

Destination Strength

tau = 30 days


Summary3

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

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


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