Discussion of forcing errors in the Bay and how to deal with these using the LETKF. Assimilation with synthetic obs with realistic coverage

Transcription

1 Discussion of forcing errors in the Bay and how to deal with these using the LETKF Assimilation with synthetic obs with realistic coverage

2 Ecologically and economically important resource Home to over 2,700 species of plants, 348 species of fish, and 29 species of waterfowl Over $1 billion brought in yearly by fishing industry 500 million pounds of seafood per year $300 million in recreational activities NASA/Goddard Space Flight Center Scientific Visualization Studio

3 Largest estuary in North America 300km long, 50km at widest Average depth of 6.5m (max depth around 53 meters) Deep, narrow channel in the main stem (ancient Susquehanna basin)

4 The Chesapeake Bay is a partiallymixed estuary Salt water enters Bay in deep channel Fresh water enters at surface from rivers Tidal amplitude is moderate range is less than 1m

5 Circulation: Salinity May 3, 1999

6 143 million liters of fresh water per minute enter the Bay Choptank NASA/Goddard Space Flight Center Scientific Visualization Studio

7 143 million liters of fresh water per minute enter the Bay 50% comes from the Susquehanna River Choptank NASA/Goddard Space Flight Center Scientific Visualization Studio

8 143 million liters of fresh water per minute enter the Bay 50% comes from the Susquehanna River 18% from the Potomac River Choptank NASA/Goddard Space Flight Center Scientific Visualization Studio

9 143 million liters of fresh water per minute enter the Bay 50% comes from the Susquehanna River 18% from the Potomac River 14% from the James River Choptank NASA/Goddard Space Flight Center Scientific Visualization Studio

10 Numerics are from the Regional Ocean Modeling System (ROMS) Curvilinear grid with 100x150x20 resolution Only 10 levels were used for my dissertation Same bathymetry and forcing as ChesROMS (Xu et al., 2009)

11 Numerics are from the Regional Ocean Modeling System (ROMS) Curvilinear grid with 100x150x20 resolution Same bathymetry and forcing as ChesROMS (Xu et al., 2009) Terrain following sigma coordinate from Xuet al., 2009

12 9 tidal constituents from ADCIRC model Non-tidal water levels are used from NOAA National Ocean Service program Salinity and temperature are nudged to climatology from WOA01 Waves propagate through the boundary (Chapman and Flanders conditions used)

13 Daily freshwater discharges are prescribed for 9 tributaries from United States Geological Survey (USGS) data Air-surface boundary is set from North American Regional Reanalysis (NARR) 3-hourly winds Net shortwave and downward longwave radiation Temperature Relative humidity Pressure

14 Circulation: Salinity

15 Perfect Forcing First assimilation experiments were with perfect forcing Part of my dissertation The filter in this case was converging, even for a relatively small, realistic observation set

16 Perfect Model Convergence With a perfect model (including perfect forcing) the Chesapeake Bay model converges even with incorrect initial conditions

17 Imperfect Forcing In practice, the forcing fields are not perfect To visualize these errors, the surface forcing field is altered Surface winds and surface pressure are perturbed Error is created by adding 70% of a randomly chosen perturbation from within 30 days of the year long forcing field This perturbation is allowed to persist for 3 days

18 Imperfect Forcing Winds at the Duck, NC wind station

19 Year-long free run in temperature Both temperature and salinity fields now do not converge to the true state Year-long free run in salinity

20 Imperfect Single Forcing We first try assimilating exactly as we did in the perfect forcing case However, the ensemble must contain information about the background uncertainty for the filter to work If only one forcing is used for the ensemble, the filter cannot make the proper adjustments For example, consider a 40 member ensemble, each with the same surface, river, and OBC forcing fields

21 Experiment Setup Truth: given by a year long model run beginning from January 1999 Ensemble Size: 40 members Initial Ensemble: Is formed from states of the monthlong spinup and starts in February Observations: Every 5 grid points horizontally and every level in all fields with errors 0.1 C, 0.1 psu, and 0.02 m/s Inflation: 4% fixed multiplicative Localization: sigma is 3 grid points in horizontal, 1 in vertical Assimilation Interval: 6 hours

22 40 member ensemble, each with the same surface, river, and OBC forcing fields This analysis does not converge to the true state. After about 2 weeks, the analysis is converging to the free run

23 The problem is that the ensemble spread is not accurately characterizing the uncertainty in the background Instead, it converges to the free run state Then the filter is no longer able to make adjustments to the observations

24 Ensemble Forcing Instead, an ensemble of forcings is used Now consider a 40 member ensemble, each with the different surface forcing fields Same initial ensemble and inflation parameters Observation network is temperature and salinity every 5 grid points (this is more than in reality)

25 Experiment Setup Ensemble Size: 40 members Initial Ensemble: Is formed from states of the month- long spinup Observations: Every 5 grid points horizontally and every level in all fields with errors 0.3 C and 0.5 psu Inflation: 4% fixed multiplicative Localization: sigma is 3 grid points in horizontal, 1 in vertical Assimilation Interval: 6 hours

26 The temperature and salinity converge to below the observation error The currents, which have no obs, are still corrected and improved

27 The background spread and background error are now close to the same magnitude, which leads to the convergence The currents, which have no obs, are still corrected and improved

28 Real Observational Data Buoy observations are available from the Chesapeake Bay Program (CBP) and the Chesapeake Bay Observing System (CBOS) 6 CBOS and 120+ CBP stations report temp. and salt. profiles CBOS stations report every 6-30 minutes, CBP report every 2 weeks- 1 month

29 Real Observational Data Buoy observations are available from the Chesapeake Bay Program (CBP) and the Chesapeake Bay Observing System (CBOS) 6 CBOS and 120+ CBP stations report temp. and salt. profiles CBOS stations report every 6-30 minutes, CBP report every 2 weeks- 1 month AVHRR gives 1.1km SST obs with an error of 0.5 C

30 Experiment Setup Truth: given by a year long model run beginning from January 1999 Ensemble Size: 40 members Initial Ensemble: Is formed from states of the month- long spinup Observations: SST observations at every surface point with 0.5 C error Inflation: 4% fixed multiplicative Localization: sigma is 3 grid points in horizontal, 7 in vertical Assimilation Interval: 6 hours

31 Assimilating synthetic satellite SST observations (which numberswise dominate the station data) appears to improve all of the prognostic variables This is very promising for starting the assimilation of real data There is still a problem, though

32 While the spread and errors of all of the temperature and current fields are staying relatively constant and consistent, the salinity spread is blowing up This causes the model to crash

33 RMSE at all levels look similar, so it does not appear one level is the cause

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37 Takemasa s LETKF code appears to be working (code is running properly) on ChesROMS The Chesapeake Bay is so forced, that forcing errors can dominate dynamical and chaotic errors Using an ensemble which contains different random forcings appears to help for sufficiently large numbers of observations Using only SST obs there is initial convergence, but the salinity spread eventually diverges These are preliminary results and no tuning has been performed, so this (and things like adaptive inflaiton and obs error, which has been coded by not extensively tested) may help Use of random error increases spread, but does not fully capture the error

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