Local Ensemble Kalman Filter (LETKF) Analysis of Loop Current & Eddy in the Gulf of Mexico - PowerPoint PPT Presentation

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Local Ensemble Kalman Filter (LETKF) Analysis of Loop Current & Eddy in the Gulf of Mexico

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  1. Local Ensemble Kalman Filter (LETKF) Analysis of Loop Current & Eddy in the Gulf of Mexico Fanghua Xu1, Leo Oey1, YasumasaMiyazawa2, Peter Hamilton3 IWMO, 2012 1: Princeton University 2: JAMSTEC 3: SAIC

  2. mpiPOM-LETKF SSHA SST obs +2d T&S U&V Observation increments/innovations

  3. LETKF parameters 90-day Experiments (2010/04/22 – 2010/07/21)

  4. Loop Currents mooring locations LETKF015 Positions of the observation data assimilated in GOM, red: satellite SST; blue: AVISO SSHA Mooring locations near the Loop currents, red: measurements from ~80m to ~3000m Blue: measurements in deep (about 3000m)

  5. Model results are compared with • Satellite Sea Surface height (SSH);AVISO NRT map data (http://www.aviso.oceanobs.com/) • Loop Currents mooring data; (Dr. Peter Hamilton) • ADCP data.(http://www.ndbc.noaa.gov/maps/ADCP_WestGulf.shtml)

  6. Comparison between model and AVISO SSH Color: model SSH; white line: AVISO SSH=0 line LETKF015 OI

  7. OI for the first 30 days 015 for the first 30 days -100m OI for the entire 90 days 015 for the entire 90 days Blue: mooring; red: model

  8. OI for the first 30 days 015 for the first 30 days -500m OI for the entire 90 days 015 for the entire 90 days Blue: mooring; red: model

  9. 90 days Vector CorrCoef (R) & Angles averaged over 4 moorings as a function of depth

  10. Comparison between model & d moorings (54 days) Vector CorrCoef (R) & Angles (θ) at d moorings

  11. Comparison of model and mooring D over 54 days 015 OI 014 013 Blue: mooring; red: model

  12. LETKF comparison with 3 ADCPs 20100501~20100721 OI 012

  13. Summary • The LETKF data assimilation results are in good agreement with the observation data, including satellite SSH, ADCPs, and moorings. • LETKF data assimilation improves model simulation significantly, compared with the traditional OI assimilation results; • The Loop current and its eddies are well represented, especially in mid water depth.

  14. Principles Observation increments/innovations • Xb: background field • Yo: observed variable • H : the observation operator that performs the necessary interpolation and transformation from model variables to observation space • H(Xb): background or first guess of observations • W: weights determined by the estimated statistical error covariance of the forecast and the observations. • Xa: analysis SCM, OI, 3D-Var, and KF…

  15. 015 OI 013 014

  16. Corr. & RMS error of model with satellite SSHA (h>500m) in GOM

  17. 100m Model comparison with ADCP in the northern Gulf 500m