Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

1. Doctoral Dissertation Proposal Establishing confidence in marine forecast systems The design of an optimal marine forecast model for the NY/NJ Harbor estuary and its adjoining waters Nickitas Georgas, Ph.D. Candidate Stevens Institute of Technology Hoboken, NJ November 14, 2007

2. Presentation in Two Parts:1. Dissertation Proposal Outline2. Preliminary Results to Date

3. PART I DISSERTATION PROPOSAL OUTLINE

4. Coastal O.F.S. Definition A Coastal Operational Nowcast and Forecast (O.F.S.) Hydrodynamic Model System is a set of computer codes that can provide sufficiently reliable predictions about the present and future state of water levels and other hydrodynamic properties (such as currents, T, S, etc.) for a coastal area.

5. OBJECTIVES

6. Objective 1: Quantify and maximize the performance of NYHOPS • A1. Selection and enhancement of computer codes and circulation drivers • A2. Forecast stability and continuous quality control (QC) • A3. Continuous quality assurance (QA) for model predictions • A4. Online distribution of forecast QA • A5. Maximize automation – Minimize user interference

7. Objective 2: Use NYHOPS to investigate marine climatology • B1. Quantification of the dominant tidal circulation components • B2. Investigation of diurnal and spring-neap tide variability • B3. Investigation of longer-time-scale climatological effects • B4. Identification and categorization of synoptic events

8. METHODS

9. Objective 1: Quantify and maximize the performance of NYHOPS

10. January 2004 From Low Res… To High Res… January 2007 • New high-resolution model grid (147x452x10) allows down to 50m resolution in major rivers. • Comprehensive catalogue of fresh water and thermal sources: 241 Treatment Plants, 39 Power Plants, 91 river systems from 9 states. A1. Selection and enhancement of domain, code, and circulation drivers

11. High-Resolution New York Harbor Observing and Prediction system: NYHOPS-HR • Input forcing: • Tides (O+F) • Storm Surge (O+F) • Waves (O+F) • Winds (O+F) • Heating and Cooling (O+F) • Rivers (O+F/P) • Major Dischargers (H) • Engines: • ECOMSED 3D hydrodynamics: • Baroclinic, curvilinear, F.D. model, with Mellor-Yamada closure, W&D. • Coastal Wave module: • Parametric JONSWAP spectrum, wave momentum, shallow water and open BC effects included. • Prognostic variables: • Water level. • 3D Temperature, Salinity, Currents, Speed of Sound. • Significant wave height and average wave period. • (O): Observed • (F): Forecasted • (H): Historic Dissemination www.stevens.edu/maritimeforecast PRESENT CONDITIONS ASSIMILATION Daily 48-hr forecasts Initialized through 24-hr hindcasts Time I C I C I C I C -24 0 24 48 …. hrs Surface BCs + Open Ocean BCs + Internal Inputs NCEP NAM/WRF model (meteorology) NCEP WNA/WWIII model (waves) + EC2001 major tidal constituents + NOAA ETSURGE model (storm surge) + Monthly Levitus (T,S climatology) USGS river flows, T + NWS AHPS river forecasts + Monthly EPA dischargers Q, T, dT. WWW

12. A2. Forecast stability and continuous quality control EDUCATE Protocol External Data Uninterrupted Cashed Acquisition and Transfer Effectiveness. Expansion to acquire and use external, non-Stevens data for model forcing, model QA/QC, and present condition “now”casting. EDUCATE Mantra: External networks fail. Don’t wait till runtime to acquire critical data. Fetch external data in equal download intervals, then use latest available. If none available, build fall-back conditions. STEVENS ATLAS DATABASE # EDUCATE PROTOCOL # “Point” measurements: Water Level, T, S, met, etc. • EDUCATE includes: • Point Observations, • 2D NAM meteorology, • ETSURGE forecasts, • AHPS river flow forecasts

13. A3. Continuous quality assurance (QA) for model predictions • EDUCATE observations used to assess NYHOPS predictive skill. • Continuous stream of data… continuous stream of skill assessments. A4. Online distribution of forecast QA • Online dissemination of forecast skill as plots versus incoming data including RMS errors.

14. A5. Maximize automation – Minimize user interference • EDUCATE uses PERL, Java, and MySQL. • All runtime steps and model routines use FORTRAN, PERL, MySQL. • Post-processing steps use FORTRAN, PERL, MySQL, Java, Matlab, HTML, PHP. • Automated as cron jobs in the LINUX environment.

15. Objective 2: Use NYHOPS to investigate marine climatology

16. Reference Years • Establish forecast skill of the updated NYHOPS by looking at operational 2007 record. • Categorized by five 24hr periods to investigate possible skill loss: • -24..0hrs, -12..+12hrs, 0..+24hrs, +12…+36hrs, +24+48hrs. • Run 2004-2007 hindcasts for climatological record. Four years are a start. Lentz (in press) used 200 days.

17. B1. Quantification of the dominant tidal circulation components • It all starts with validation: Model vs. observations comparisons for all prognostic variables: Model skill, RMSE, etc. • Tidal harmonic analysis for M2, N2, S2, K2, O1, Q1, K1, M4, M6. • Maps of simulated tidal constituents, tidal residuals, form number, asymmetry parameter.

18. B2. Investigation of diurnal and spring-neap tide variability • Tidal datums will be calculated and compared. • Diurnal inequality maps for sea level. • Tidally-averaged transport and salt flux comparisons between model and ADCP. • Estuarine circulation (profile deviation) comparisons to ADCP. • Average neap/spring salt intrusion lengths for the Hudson.

19. B3. Investigation of longer-time-scale climatological effects • Spectral analyses on low-passed fields to investigate significant frequencies. • Will look for spatially-consistent temporal patterns. • Long term monthly and annual means and standard deviations will be computed and mapped for all variables including significant wave heights. • As NYHOPS continues, the dbase will expand.

20. B4. Identification and categorization of synoptic events • Synoptic events will be identified as out-lying a standard-deviation-based range from the long-term means. • Perhaps we will be able to see consistent patterns and categorize the events.

21. PART II WORK COMPLETED AND PRELIMINARY RESULTS TO DATE

22. Objective 1: Quantify and maximize the performance of NYHOPS

23. A1. Selection and enhancement of computer codes and circulation drivers • W&Q, thin dams, waves largely completed, except for the instantaneous depth-adjustment of CD in the ECOMSED code. This will require also adding a 2D Z0 option in the code. Where will Z0 come from?

24. Improvement compared to Low-Res

25. Steps A2-A5 are completed. The EDUCATE protocol is operational and the NYHOPS-HR system and website have not been down a single day since January 17th 2007.

26. Objective 2: Use NYHOPS to investigate marine climatology

27. B1. Quantification of the dominant tidal circulation components • Start from validation: • I have built or adopted routines for model validation based on NOS statistics, generated datum calculators, etc. • I have applied these to hindcast sea level for the 2007 to-date NYHOPS-HR operational system. • Preliminary validation results/findings to follow:

28. Water level validation From Newport, RI To Hastings, Hudson River To Sandy Hook, NJ To Brandywine, Delaware Bay 66 Stations: NOS, USGS, SIT

29. Note possible effects Of river flows Exagerated in confined bays?

30. Sqrt(g*hnew/g*hold)=0.98! For M2 tide, 12.42hrs, translates to 14.9minutes! The NYHOPS-HR error in LIS is close to 7min. Results almost equal to EC2001 for 5 applicable stations Missing 2D friction?

31. 0.63±0.14 Compare to tidal: 0.97±0.17

32. NYHOPS Underestimates Storm Surge? Mean=0.74 (0.35 to 0.88). AC*0.5 is under question.

33. 24 21 15 6 Poor skill in some NJ back bays Poor resolution

34. 21 13 18 12

35. 28 11 10 15 • 24-48hr forecast skill drop vs. hindcast: • Mean RMSE increases from 15cm to 16cm. • Mean CF<15cm decreases from 71.0% to 67.8%. • 13 stations with CF>90% become 7 stations. • 30 “Green” stations become 25 stations (of 65).

36. Temperature validation From Fall River, MA To Poughkeepsie, Hudson River To Newark, NJ To Bowers, Delaware Bay I have found that NYHOPS-HR’s biggest measurable improvement versus NYHOPS-LR is in Temperature. This is really obvious just comparing the website plots.

37. Salinity validation From Newport, RI To Hastings, Hudson River To Pier 40, NY To Newark, NJ Preliminary results show good salinity results in NY/NJ Harbor and the Hudson, but not in East River and Western Long Island Sound (2 psu higher). Missing flows? Missing plug?

38. DEPTH-AVERAGED OVERALL R^2 0.96; NON-TIDAL=0.61; >90% better than 0.5kts. The Narrows Model Mean: () Data Mean: (o) Units are kts RMSE, kts Max Flood Max Ebb D e p t h , m e t e r s CF(<0.4kts) Model Skill

39. PREDICTED SIGNIFICANT WAVE HEIGHT NDBC 44025 CC=0.77, RMSe=0.39m or 28% MLHs. UCONN 44040 CC=0.70, RMSe=0.12m or 59%. LONG ISLAND SOUND O P E N O C E A N NDBC 44009 CC=0.80, RMSe=0.36m or 27%. UCONN 44039 CC=0.77, RMSe=0.14m or 48%. NDBC 44017 CC=0.80, RMSe=0.40m or 29%. SIT AVAN4: Avalon CC=0.67, RMSe=0.28m or 35%. N J C O A S T A L DELAWARE BAY SIT BRNB4: Brant Beach, LBI NDBC 44054: Delaware Bay CC=0.67, RMSe=0.35m or 36%. CC=0.61, RMSe=0.19m or 43%.

40. What’s next • Will need to set up 2004-2006 years for NYHOPS-HR. • Will need to build the CD(z) code. • Will perhaps need to adjust depths, friction, and surge alpha. Should I? How? Build Z0 variability. • Will need to run 2004-2006 and validate sea level, temperature, salinity, and waves (winds). Play with friction, and non-tidal residual. • What about missing watersheds? • Will need to run same stats on the other three 24-hr cycles as I did for hindcasts and 24-48hr forecasts. • And, then, start part B of the research.

41. Drs. Aikman, Blumberg, Herrington, Hires, Miller Thank you! Comments, questions, suggestions, welcome.