amseas meteorological forcing: progress & plans pat fitzpatrick and yee lau
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AMSEAS Meteorological Forcing: Progress & Plans Pat Fitzpatrick and Yee Lau Geosystems Research Institute Mississippi State University. Validation efforts Oil spill study using AMSEAS NCOM. Validation effort. Wind Validation, NCOM versus 37 buoys, June 20-July 10, 2010. - PowerPoint PPT PresentationTRANSCRIPT
AMSEAS Meteorological Forcing:Progress & Plans
Pat Fitzpatrick and Yee LauGeosystems Research Institute
Mississippi State University
1) Validation efforts2) Oil spill study using AMSEAS NCOM
Validation effort
Wind Validation, NCOM versus 37 buoys, June 20-July 10, 2010
Wind Validation, NCOM versus 23 buoys, Dec. 1, 2010-Jan. 15, 2011
Analysis 6-h 12-h 18-h 24-hBias direction -13.4 to 18.7 -13.0 to 27.2 -18.2 to 9.7 -29.8 to 12.1 -12.7 to 12.4
Absolute error direction 14.9 to 38.0 12.0 to 35.3 12.5 to 35.2 16.0 to 42.6 15.6 to 39.3
Bias speed -2.4 to 2.1 -2.2 to 2.8 -2.2 to 2.4 -0.8 to 2.3 -2.3 to 2.3
Absolute error speed 0.8 to 2.9 1.1 to 2.8 0.8 to 2.9 0.9 to 2.6 0.9 to 3.1
Wind converted from wind stress using drag coefficient of 0.001
Buoys adjusted to 1-minute average winds, 10-meter height
Analysis 6-h 12-h 18-h 24-hBias direction -33.6 to 24.7 -42.4 to 30.4 -32.6 to 35.5 -13.4 to 41.0 -38.0 to 25.6
Absolute error direction 18.1 to 54.5 14.7 to 62.7 20.9 to 58.5 12.9 to 51.6 21.9 to 48.5
Bias speed -1.6 to 1.3 -1.7 to 2.4 -1.8 to 3.2 -0.6 to 3.4 -1.7 to 1.5
Absolute error speed 0.9 to 2.2 0.8 to 2.5 0.7 to 3.3 0.7 to 3.4 0.7 to 2.6
Most errors less than range extremes shown
Summer validation example, 4 offshore buoys
Winter validation example, 4 offshore buoys
Summer validation example, 4 CMAN buoys
Winter validation example, 4 CMAN buoys
Winter validation example, 2 offshore buoys
Summer validation example, 2 offshore buoys
Future plans
• Document general error trends• Provide details on vector correlation methodology• Document typical case studies• Detailed tables for CMAN versus offshore buoys; other geographical differences?
Oil spill study using NCOM AMSEAS
Model description• Lagrangian particle tracker with random walk diffusion
• Input consistedi. latitude and longitude parcel positions in the oil-contaminated areaii. windiii. currentiv. array of pseudo-random numbers (from Mersenne Twister algorithm, initial seed from machine noise)
• new parcels were released damaged Macondo rig location at each timestep
•Twenty-five parcels were released at each position, and when combined with a 10 m2s-1 diffusion coefficient, resulted in a natural trajectory spread with time
• Initial positions based interpretation oni. NASA MODISii. SAR imagery from http://www.cstars.miami.eduiii. NOAA/NESDIS Satellite Analysis Branch (SAB) experimental surface oil analysis
products at http://www.ssd.noaa.gov/PS/MPS/deepwater.htmliv. NOAA’s Office of Response and Restoration oil trajectory maps
at http://response.restoration.noaa.gov
• Parcels advected at 80% of the ocean current speed and at 3% of the wind speed.Bilinear interpolation of wind and curent applied from model grid to parcel location.
Note inshoremovement of oilstarting late June
Oil spill simulation from 6/20/10-7/10/10Using AMSEAS NCOM data
Elevated water from Alex Elevated water from low
10:10am CDT 29 June 2010
Future workHigh Frequency Radar ocean currents Scatterometer winds (ASCAT)
• Seeking collaborating authors for paper on cyclones’ impact on oil spill• NCOM currents analysis• NCOM water elevation analysis• New oil spill run for whole period, current and wind weights optimized from 3DVAR• Analysis of weather terms• Overall goal: fate and transport analysis
Questions?
HAPPY MARDI GRAS!