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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
• 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