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Ocean Surface Current Observations in PWS Carter Ohlmann Institute for Computational Earth System Science, University of California, Santa Barbara, CA.

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Presentation on theme: "Ocean Surface Current Observations in PWS Carter Ohlmann Institute for Computational Earth System Science, University of California, Santa Barbara, CA."— Presentation transcript:

1 Ocean Surface Current Observations in PWS Carter Ohlmann Institute for Computational Earth System Science, University of California, Santa Barbara, CA 93106

2 ROMS-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

3 Drifter data (CODE 1 meter; MMS SBC-SMB 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

4 Lagrangian PDF vs Drifter Distribution Drifter locations

5 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)

6 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.

7 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

8 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

9 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

10 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

11 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

12 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

13 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

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

15 starting positions ending positions USCG SLDMBs Microstar drifters Preliminary analysis of data: Q: What can be learned of SLDMB water-following capabilities?

16 Preliminary analysis of data: A: SLDMBs move ~1.0 cm/s slower. ~400 m separation after ~18 hours advection difference diffusion difference similar diffusion characteristics for first 19 hours

17 Preliminary analysis of data: Ocean turbulence, u’(x,y,t), complicates comparative analyses. starting positions ending positions USCG SLDMBs Microstar drifters

18 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

19 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.

20 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.

21 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

22 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

23 Preliminary analysis of data: Looking at a single radial cell comparison. > 25 cm/s difference between drifter and HF radar derived surface velocities

24 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

25 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

26

27 exponential growth during first 4 hours Mean Dispersion Values: D 2 (t) = exp(At) ; A -1 = 60 min ; r 2 = 0.91 1000 m 100 m 10 m

28 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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