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Enhancing Coastal Modeling with IS4DVAR Data Assimilation | Hawaii Domain Analysis

Explore the use of IS4DVAR data assimilation in near-coastal modeling systems for improved transport studies. This study focuses on the Hawaiian Islands region, tackling challenges in bathymetry, forcing, and boundary conditions for enhanced accuracy. The research delves into coastal dynamics, model set-up, and preliminary results to enhance circulation prediction.

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Enhancing Coastal Modeling with IS4DVAR Data Assimilation | Hawaii Domain Analysis

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  1. Using IS4DVAR Data Assimilation in the near coastal modeling system Ivica Janeković & Brian Powell

  2. #ifdef LAYOUT • Region of interest, domain, bathymetry • Forward model setup • IS4DVAR setup • TLM validation • Problems on the way • Results & discussion • Preliminary results – still running, suggestions are welcome

  3. Domain • Hawaiian Islands -> challenge for model skill • Complex bathymetry, forcing, boundary… • Hawaiian Ridge – major barotropic to baroclinic tidal conversion site -> Kaena Ridge, Niihau-Maui • Coastal dynamics in shallow/slope region on high resolution model for transport study of ordnance • We used nested approach from 2 model grids above • 4 km Hawaiian Islands Grid • -> 1.2 km Oahu-Maui Grid • -> 200 - 900 m Western Oahu Grid • Our focus is Western Oahu region & DA • 5 ADCP observations at “nice position” (07/09-07/10) • SST data from MODIS T/A

  4. Kauai Kaena Ridge Niihau

  5. (59,35) 33 km 12 km ADCP West Oahu Grid

  6. Bathymetry transect ADCP

  7. Forward model setup • We used hi-res bathymetry + LP smoothing • variable rx0 smoothing, iterative way, many grids… • 20 vertical levels (on the edge with rx1(!)) • increased number of levels in surface zone -> Θ_s= 7, Θ _b= 0.1 • vtransform, vstretching = 2 • variable resolution, in region where we have ADCPs (~200m) while at boundary ~900m (outer grid 1.2km) • Spin-up from 2004 - 2009 using: • forcing with local MM5 (1.5km), WRF (1.5km) • boundary from HIOG (1.2km outer model), tides inside • Model setup using: • U3 for advection, GLS - gen, IS4DVAR, small diffusion and viscosity, clamped BC,… • Forward model is doing well with tides • dominantly tidally driven (barotropic/baroclinic) • we want to improve circulation & phase

  8. IS4DVAR setup • in the beginning 40, 30, 20 inner loops, 1 outer loop • time window of 3 days (based on init and MTLM) • clamped boundary conditions • adjust initial filed + atmo. forcing, NO BRY ADJUSTMENT • OBS: • ADCPs (1 2 3 4) • discarded at the bottom • model/obs depths doesn’t match, bottom layer?! • ADCP 2 out of phase • SSH (1 2 3 4) • de-mean, added model mean value, nr. 2 faulty • MODIS T/A SST • not many data, proximity to coast, small domain • small grid (tiles), short time step of 60s (ncpu?) • small de-correlation scale (patchy fields) • run experiments with: • using only ADCPs • using ADCPs + SSH • using ADCPs + SSH + MODIS SST

  9. NLM-TLM approximation • In order to check validity of TLM approx: • we made inside domain perturbation (“wrong” SST) • run MTLM (10 inner loops) • used 40 (Modified Gram-Schmidt ortho-normalized) perturbations in init field for all state variables • horizontal de-correlation scale set to 3 km • run TLM and NLM (40 members) • correlation (NLM,TLM) for all state variables • system is OK for 5 days, high correlation (>0.6) • mixing in the 1st time step for salt, unstable perturbs • mostly driven by atmo and boundary forcing

  10. Effect of init field inside NLM • we run NLM from day_0 (1st of Nov 2009) using: • real BC, atmo. forcing and initial field • -> state_0 • we run NLM as before but with: • initial field randomly picked (Jun 2009) and then only “changed” ocean_time = day_0 • -> state_1 • compute correlation btw state_0 & state_1 for all state variables in time • After 2-3 days information in init field is swept away by BC and atmo forcing, correlation is round 1. • This have us interval how frequent we should assimilate

  11. correlation (state_0, state_1)

  12. Results/disscusion • If only looking at the ADCPs locations • all seems perfect, high correlation (~0.7 - 0.8) • What is really happening? • We do have high dimensionality case with small number of obs -> constraint • We made experiments gradually adding obs to see how it affects solutions and constraints • Did we corrected/destroyed baroclinic tides? • What happened to density filed in whole domain?

  13. Exp 1: ADCPs only

  14. Exp 1: ADCPs only

  15. Exp 1: ADCPs only

  16. Exp 1: ADCPs only ADCP 1 Correlation/STD depth U0 UA V0 VA -53.4 0.68/0.17 0.72/0.15 -0.60/0.15 -0.57/0.15 -45.4 0.70/0.18 0.75/0.16 -0.49/0.12 -0.44/0.12 -37.4 0.70/0.19 0.76/0.16 -0.38/0.11 -0.27/0.11 -29.4 0.71/0.19 0.77/0.16 -0.32/0.11 -0.18/0.10 -21.4 0.72/0.19 0.78/0.16 -0.31/0.10 -0.17/0.10 -13.4 0.71/0.20 0.77/0.17 -0.25/0.11 -0.21/0.11 ADCP 3 Correlation/STD depth U0 UA V0 VA -9.9 0.70/0.16 0.78/0.13 0.27/0.04 0.26/0.04 -8.4 0.71/0.16 0.78/0.13 0.27/0.04 0.26/0.04 -6.9 0.71/0.16 0.79/0.13 0.25/0.04 0.25/0.04 -5.4 0.70/0.16 0.79/0.13 0.23/0.04 0.23/0.05 -4.2 0.70/0.16 0.78/0.13 0.21/0.04 0.22/0.05 ADCP 4 Correlation/STD depth U0 UA V0 VA -5.9 0.56/0.21 0.64/0.18 -0.18/0.07 -0.14/0.08 -3.2 0.56/0.21 0.64/0.19 -0.09/0.08 -0.12/0.09

  17. Exp 2: ADCPs + SSH

  18. Exp 2: ADCPs + SSH

  19. Exp 2: ADCPs + SSH

  20. Exp 2: ADCPs + SSH ADCP 1 Correlation/STD depth U0 UA V0 VA -53.4 0.68/0.17 0.72/0.15 -0.60/0.15 -0.58/0.15 -45.4 0.69/0.18 0.75/0.16 -0.49/0.12 -0.46/0.13 -37.4 0.70/0.19 0.76/0.16 -0.36/0.11 -0.30/0.11 -29.4 0.71/0.19 0.77/0.16 -0.30/0.11 -0.20/0.10 -21.4 0.71/0.19 0.77/0.16 -0.29/0.10 -0.16/0.10 -13.4 0.71/0.20 0.77/0.17 -0.25/0.11 -0.13/0.10 ADCP 3 Correlation/STD depth U0 UA V0 VA -9.9 0.71/0.16 0.77/0.14 0.27/0.04 0.27/0.04 -8.4 0.71/0.16 0.78/0.13 0.26/0.04 0.25/0.04 -6.9 0.71/0.16 0.78/0.13 0.24/0.04 0.24/0.04 -5.4 0.71/0.16 0.78/0.13 0.23/0.04 0.23/0.05 -4.2 0.70/0.16 0.78/0.14 0.21/0.04 0.22/0.05 ADCP 4 Correlation/STD depth U0 UA V0 VA -5.9 0.56/0.21 0.64/0.18 -0.19/0.07 -0.17/0.08 -3.2 0.56/0.21 0.64/0.19 -0.09/0.08 -0.15/0.09

  21. Exp 3: ADCPs + SSH + SST

  22. Exp 3: ADCPs + SSH + SST

  23. Exp 3: ADCPs + SSH + SST

  24. Exp 3: ADCPs + SSH + SST

  25. Exp 3: ADCPs + SSH + SST

  26. Exp 3: ADCPs + SSH + SST ADCP 1 Correlation/STD depth U0 UA V0 VA -53.4 0.68/0.17 0.71/0.16 -0.61/0.14 -0.58/0.15 -45.4 0.69/0.18 0.74/0.16 -0.50/0.12 -0.45/0.12 -37.4 0.69/0.19 0.75/0.16 -0.39/0.11 -0.29/0.11 -29.4 0.70/0.20 0.76/0.16 -0.33/0.10 -0.19/0.10 -21.4 0.71/0.20 0.77/0.17 -0.32/0.10 -0.18/0.10 -13.4 0.70/0.20 0.76/0.17 -0.27/0.11 -0.17/0.10 ADCP 3 Correlation/STD depth U0 UA V0 VA -9.9 0.70/0.16 0.78/0.13 0.28/0.04 0.31/0.04 -8.4 0.71/0.16 0.78/0.13 0.29/0.04 0.30/0.04 -6.9 0.71/0.16 0.78/0.14 0.27/0.04 0.29/0.04 -5.4 0.70/0.16 0.78/0.14 0.25/0.04 0.26/0.04 -4.2 0.70/0.16 0.78/0.14 0.23/0.04 0.24/0.05 ADCP 4 Correlation/STD depth U0 UA V0 VA -5.9 0.55/0.21 0.63/0.18 -0.20/0.07 -0.15/0.08 -3.2 0.55/0.22 0.63/0.19 -0.11/0.08 -0.13/0.09 Corr(ssh_obs,ssh_nlm_0)=0.75 Corr(ssh_obs,ssh_nlm_0)=0.75 Corr(SST_obs,SST_nlm_0)=0.69 Corr(SST_obs,SST_nlm_1)=0.70

  27. Still work in progress • All indicates that the key is to fix outer model as much as possible (use DA) in order to get right BC • Right now we are only adjusting atmo+initial • We do need to perform observation sensitivity • How sensitive is our system to ADCP obs? • Ek vs Ep inside model • Impact studies • Overlapping could help to avoid shocks • Would W4DVAR help?

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