Transcript
Page 1: Ocean Surface Current Observations in PWS Carter Ohlmann

Ocean Surface Current Observations in PWS

Carter Ohlmann

Institute for Computational Earth System Science, University of California, Santa Barbara, CA 93106

Page 2: Ocean Surface Current Observations in PWS Carter Ohlmann

ROMS-based dispersal simulationROMS-based dispersal simulation

Deployment sites have 5 km radius and are adjacent to the coast

From each site, around 100 particles are released every 12 hours from Jan. 1996 – Dec. 2002

Lagrangian PDFs are calculated for 1 – 14 day advection times

PDFs = probability density functions

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Drifter dataDrifter data (CODE 1 meter; MMS SBC-SMB (CODE 1 meter; MMS SBC-SMB study)study)

SCB drifter data on the regional scale

Drifters deployed ~ quarterly from 1993 – 1999. 568 drifters sampling for an average of ~24 days give ~13,500 drifter days of data.

Drifter dispersal from a single site

Red circle: “release” site

Blue dots: drifter locations for a give advection time

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Lagrangian PDF vs Drifter Lagrangian PDF vs Drifter DistributionDistribution

Drifter locationsDrifter locations

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Project Goal: Provide improved real-time ocean current and wind forecasts with error estimates for inclusion in USGC DSTs.

Pathway to Project Goal:• Benchmark DSTs (year 1)

• Develop and evaluate improved data assimilating models (year 2)

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24 hrs

1000 m

100 m

10 m

Motivation for this research component:

Benchmarking, evaluating, and assimilating data into DSTs (focused on transport pathways) requires a thorough understanding of surface current observations.

Data from drifting buoys are key as drifters provide direct observations of both advection and diffusion, the two processes responsible for defining a search area.

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Outline:• Instrumentation for measuring ocean surface currents- HF radar derived surface currents- Drifting buoys- SLDMBs

• Ocean surface current data collected during year 1 field program- 54 drifter tracks w/ 12 drifters

• Preliminary analysis of year 1 surface current data- SLDMB performance- HF radar “ground truth”

• Work plan for year 2

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Microstar Drifters:• tri-star drogue centered at 1 m depth

• 10 minute position sampling w/ GPS

• data transmission through Iridium

• 1 cm/s slip in 10 m/s wind

• 7 day life expectancy

• real time data on web

• recoverable

Ohlmann et al. 2005, and Ohlmann et al. 2007

www.drifterdata.com

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Microstar drifter data during PWS FE:

• 12 drifters used; 12 drifters worked; 1 drifter lost

• 54 drifter trajectories sampled

• mostly ~2 days in length

• positions every 10 minutes

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USCG SLDMB• marker buoy used by USCG

• based on 1970’s design

• altered dimensions

•water-following characteristics not found in scientific literature

• 30 minute position data

• data transmission: Argos

• difficult to recover

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USCG SLDMB data during PWS FE: • 9 drifters used; 8 drifters worked; 9 drifters lost

• 8 drifter trajectories sampled

• mostly numerous days in length

• positions every 30 minutes

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HF radar surface currents – Bragg scattering off surface gravity waves with known wavelength, extract wave speed, get surface current.Typically 15 – 30 minute averages reported hourly for a 1 – 10 km grid.

Velocity “errors” of 10 cm/s typically quoted

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HF radar surface currents – time-space (1 hr - 1 km) average surface current maps such as this were produced throughout the PWS FE (~14 days).

PWS HF radar locations

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PWS HF radar surface current map – spatial extent of coverage is highly variable.

PWS HF radar locations

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starting positions

ending positions

USCG SLDMBsMicrostar drifters

Preliminary analysis of data:

Q: What can be learned of SLDMB water-following capabilities?

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Preliminary analysis of data:

A: SLDMBs move ~1.0 cm/s slower.

~400 m separation after ~18 hours

advection difference

diffusion differencesimilar diffusion characteristics for first 19 hours

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Preliminary analysis of data:

Ocean turbulence, u’(x,y,t), complicates comparative analyses.

starting positions

ending positions

USCG SLDMBsMicrostar drifters

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Preliminary analysis of data:

A: SLDMBs move ~3 – 4 cm/s “differently”. Need to understand why?

~8000 m separation after ~55 hours

advection difference

diffusion difference

similar diffusion characteristics

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Preliminary analysis of data:

Q: How well do drifter and HF radar observations agree?

7 HF radar radial cells

20 drifter tracks

Need to compute time-space averages from drifter clusters for HF radar ground truth.

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Preliminary analysis of data:

Q: How well do drifter and HF radar observations agree?

14 HF radar radial cells

20 drifter tracks

Need to compute time-space averages from drifter clusters for HF radar ground truth.

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Preliminary analysis of data:

Q: How well do drifter and HF radar observations agree?

HF radar velocities show large variance on few km space scales

> 70 cm/s range

Page 22: Ocean Surface Current Observations in PWS Carter Ohlmann

Preliminary analysis of data:

Q: How well do drifter and HF radar observations agree?

HF radar velocities show large variance on few km space scales

> 40 cm/s range

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Preliminary analysis of data:

Looking at a single radial cell comparison.

> 25 cm/s difference between drifter and HF radar derived surface velocities

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Preliminary analysis of data:

Looking at a single radial cell comparison.

drifter and HF radar velocities agree to within a few cm/s

> 40 cm/s difference between drifter and HF radar derived surface velocities

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Summary:

Year 1 accomplishments

• Successful field experiment. 12 drifters were used to sample 54 drifter tracks, only 1 drifter lost

• First set of coincident SLDMB and drifter observations

• Observations for evaluating HF radar surface currents

Year 2 workplan

• SLDMB performance analysis with wind data

• HF radar ground truth analysis

• Benchmark for ROMS simulations

• Quantify parameters for a PWS Lagrangian Stochastic Model

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exponential growth during first 4 hours

Mean Dispersion Values:

D2(t) = exp(At) ; A-1 = 60 min ; r2 = 0.911000 m

100 m

10 m

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Definitions:

Relative Dispersion

• Spread (or variance) of a set of particles relative to coordinate

frame fixed to the cloud’s center of mass (“two particle” statistics)

Eddy Diffusivity

• Time rate of change of dispersion

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)( 2i

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tDxx

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DK xxxx

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