John Wilkin Julia Levin, Alex Lopez, Javier Zavala-Garay, Hernan Arango, Andrew Moore

Transcription

1 Downscaling, 2-way Nes2ng, and Data Assimila2ve Modeling in Coastal and Shelf Waters of the Mid-Atlan2c Bight and Gulf of Maine John Wilkin Julia Levin, Alex Lopez, Javier Zavala-Garay, Hernan Arango, Andrew Moore Marine and Coastal Sciences Rutgers, The State University of New Jersey h2p://marine.rutgers.edu/wilkin Regional Ocean Modeling System h2p://myroms.org AGU/ASLO/TOS Ocean Sciences Meeting February, 2016, New Orleans

2 ESPreSSO* real-pme and reanalysis ROMS system Doppio** real-pme and reanalysis system ** it s a double espresso *Experimental System for PredicPng Shelf and Slope OpPcs h2p://maracoos.org Mid-AtlanPc Regional AssociaPon of Coastal Ocean Observing Systems

3 ROMS includes three variants of 4D-Var data assimila2on* A primal formulapon of incremental strong constraint 4DVar (I4DVAR) A dual (W4DVAR) formulapon based on a physical-space stapspcal analysis system (4D-PSAS) A dual formulapon Representer-based variant of 4DVar (R4DVar) 4DVar can adjust inipal, boundary, and surface forcing. In real-pme ESPreSSO we adjust only the ini#al condi#ons using I4DVAR In Doppio reanalysis we adjust ini#al condi#ons (3-day cycle not overlapping), open boundary condi#ons and surface fluxes using W4DVAR * Moore, A. M., H. Arango, G. Broquet, B. Powell, A. T. Weaver, and J. Zavala-Garay (2011), The Regional Ocean Modeling System (ROMS) 4-dimensional variaponal data assimilapons systems, Part I - System overview and formulapon, Prog. Oceanog., 91(34-39).

4 Data streams Real-'me Data source Surface and boundary forcing: 72-hour forecast NAM 0Z cycle at 2 am EST NCEP NOMADS Grads DODS Server USGS daily river flow available 11:00 EST waterdata.usgs.gov MERCATOR 7-day forecast updated daily Mercator-ocean.fr HYCOM/NCODA 7-day forecast (for ESPreSSO) U.S. Naval Research Laboratory AssimilaPon data sets: Regional CODAR hourly: 4-hour latency delay Rutgers TDS* IOOS glider T,S (1 hour delay) Rutgers TDS and IOOS glider DAC AVHRR SST passes 6-8 per day (2 hour delay) tds.maracoos.org (from U. Del.) GOES, OceanSat & AMSR-2 IR and u-wave PFEG ERDDAP; NASA PO-DAAC REMSS MW-IR blended SST daily average NASA PO-DAAC Jason-2, CryoSat, AlPKa along-track OGDR RADS.tudelS.nl SOOP XBT/CTD, Argo floats on GTS OSMC.noaa.gov using ERDDAP Gulf of Maine moorings NERACOOS Oleander New York-Bermuda ADCP reanalysis only NSF OOI Pioneer Array moorings and gliders L *THREDDS Data Server unidata.ucar.edu

5 Data pre-processing flow for ESPreSSO and Doppio 4DVar RU CODAR de-pded (harmonic analysis) and binned to 5km variance within bin & OI combiner expected u_err (GDOP) used for QC >> ROMS Pde added to de-pded CODAR so Pde phase error does not enter cost funcpon IOOS glider T,S averaged to ~5 km horiz. and 5 m verpcal bins Satellite SST: bin to 5 km resolupon AVHRR 6-8 passes per day; 3-hour GOES composites; AMSR-E/2 SST Have previously used daily SST OI combinapon of microwave and IR AlPmetry along-track 5 km bins from RADS With coastal alpmetry correcpons can use to ~40 m isobath MDT from 4DVAR on climatological observapons: 3D T,S, velocity (moorings, Oleander vessel ADCP, CODAR), mean τ wind No Dynamic Atmosphere CorrecPon (DAC) Add ROMS harmonic Pde to SLA; repeat obs. +/- 2 hours USGS daily river flow is projected by MCA to un-gauged watersheds Open boundary data from MERCATOR adjusted to remove bias (using 4DVAR climatological analysis on MOCHA and velocity data sets)

6 Data pre-processing flow for ESPreSSO and Doppio 4DVar

7 AlPKa Oct 2 AlPKa Oct 1 Jason Oct 2 Jason Oct 3 Cryosat Oct 1 Example of CODAR data arer quality control, binning and decimapon to a set of independent observapons. Example of along-track alpmeter sea level anomaly data during a single 3-day analysis window.

8 Dynamically adjusted (4D-Var) climatology for bias removal and MDT for al2metry Removing bias from open boundary condipons is crucial 4D-Var will not converge if it cannot reconcile model and data error Co-variances embodied in the Adjoint and Tangent Linear physics are incorrect if the background state is biased Biases in open boundary data from MERCATOR are adjusted using analysis (4D-Var) of climatological mean observapons 4D-Var analysis regional Mean Dynamic Topography (MDT) is added to alpmeter Sea Level Anomaly (SLA) data in forecast/reanalysis system

9 4DVAR analysis of mean climatological ocean state velocity obs. from CODAR (red), moorings (blue, green) and ship ADCP (magenta) 5 cm/s 5 cm/s + high-res regional T/S climatology 4DVAR seasonal and annual mean ROMS MDT Dynamically & kinemapcally adjusted MDT, and seasonal T,S,u,v for OBC bias removal

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12 Lagrangian forecast skill w.r.t. U.S. Coast Guard (SLDMB) driuers Observed Forecast: with satellite data only also with CODAR assimilapon AddiPon of HF-radar (CODAR) to assimilapon system gives modest error reducpon, but more significant reducpon in uncertainty (error bars are 5% and 95%) satellite data only with CODAR assimilapon Median separa2on distance (error) satellite data only with CODAR assimilapon Separa2on normalized by distance traveled

13 Sub-surface velocity analysis skill Shallow Water 2006 SW06 mooring Raw (hourly) Lowpass (33-hr cutoff) SW06 mooring 32 N-S velocity skill scores R (corr. coeff.) BIAS (m s -1 ) CRMS (m s -1 ) Raw ROMS model Lowpass

14 Analysis/forecast skill with respect to subsurface OBS that are NOT assimilated Forward model Forward model auer bias removal

15 Analysis/forecast skill with respect to subsurface OBS that are NOT assimilated Data assimila2on analysis/hindcast 2-day forecast

16 Mul2-model skill assessment: 7 real Pme models of the Mid-AtlanPc Bight Comparison to MARACOOS gliders and NMFS CTD surveys in RUEL ENV MAB EcoMon summer winter summer

17 Mul2-model skill assessment Ensemble Mean BIAS (x-axis) and Centered RMS error (y-axis) Distance from origin is Root Mean Squared Error (RMSE) Error bars are 95% conf. 1 Centered RMS error Mean BIAS 7

18 Mul2-model skill assessment Vectors: 2-year mean surface current compared to CODAR Color: Magnitude of vector complex correlapon (for daily variability) Note: ESPRESSO assimilates CODAR

19 Nes2ng (2-way) downscaling J. Wilkin, A. Moore, H. Arango Nested parent and child grids for the MAB model. The red box indicates the locapon of the NSF OOI Pioneer Coastal Array

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36 Nested 4D-Var Assimila2on J. Wilkin, A. Moore, H. Arango Cycle n: (1) Run 4DVAR on DOPPIO using all far field obs (not PIONEER ) (2) From converged inipal condipons (IC) run forward 2-way nested model (FwN) to obtain new analysis for cycle n. This becomes analysis for DOPPIO (AnD) (3) 4DVAR on PIONEER with BC from FwN, assimilapng PIONEER obs. This becomes analysis for PIONEER (AnP) (4) Interpolate AnP to DOPPIO grid (with "localizapon ) and replace, to obtain new IC for DOPPIO (5) Re-run forward nested 2-way (FwN+) for cycle n. This becomes an analysis with nespng AnN (6) Go to cycle n+1

37 Summary Rutgers ESPreSSO/Doppio ROMS assimilate all available data: Satellite SSH and SST, HF-radar, gliders, Argo, GTS XBT/CTD More and diverse data is be2er Pre-processing for QC; Pdes in alpmetry; binning to independent obs. OBC bias removal essenpal: use 4DVAR-based climatological mean Data ingest exploits web services (OPeNDAP/THREDDS) and interoperability of data convenpons (CDM, CF-convenPons) Downscaling steps: MERCATOR analysis/forecast to ROMS ROMS dynamic refinement via 2-way nespng Useful skill for real-pme applicapons: 4 days for temperature and salinity; 1-2 days for velocity Output of full solupon to THREDDS/FMRC Forecast Model Run CollecPon Surface currents to U.S. Coast Guard; Bo2om temperatures to NOAA Fisheries Development path prioripes: Nested 4DVAR Observing system experiments; Observing system design/operapon AGU/ASLO/TOS Ocean Sciences Meeting February, 2016, New Orleans