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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

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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. - PowerPoint PPT Presentation

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Page 1: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Doctoral Dissertation Proposal

Establishing confidence in marine forecast systems

The design of an optimal marine forecast modelfor the NY/NJ Harbor estuary

and its adjoining waters

Nickitas Georgas, Ph.D. CandidateStevens Institute of Technology

Hoboken, NJ

November 14, 2007

Page 2: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Presentation in Two Parts:

1. Dissertation Proposal Outline

2. Preliminary Results to Date

Page 3: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

PART I

DISSERTATION PROPOSAL

OUTLINE

Page 4: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 5: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

OBJECTIVES

Page 6: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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

Page 7: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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

Page 8: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

METHODS

Page 9: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Objective 1: Quantify and maximize the performance of NYHOPS

Page 10: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

January 2004From 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

Page 11: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

High-ResolutionHigh-ResolutionNew York Harbor Observing and Prediction system:New York Harbor Observing and Prediction system:

NYHOPS-HRNYHOPS-HR

Daily48-hr forecasts

Initializedthrough 24-hrhindcasts

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.

Surface BCs +Open

Ocean BCs+

Internal Inputs

WWW

-24 0 24 48 …. hrs

I C I CI C I C

Disseminationwww.stevens.edu/maritimeforecast

Time

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

PRESENT CONDITIONSASSIMILATION

Page 12: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

“Point” measurements:Water Level, T, S, met, etc.

EDUCATE includes:•Point Observations,•2D NAM meteorology,•ETSURGE forecasts,•AHPS river flow forecasts

Page 13: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 14: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 15: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Objective 2: Use NYHOPS to investigate marine climatology

Page 16: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 17: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 18: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 19: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 20: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 21: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

PART II

WORK COMPLETED AND PRELIMINARY RESULTS TO

DATE

Page 22: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Objective 1: Quantify and maximize the performance of NYHOPS

Page 23: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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?

Page 24: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Improvement compared to Low-Res

Page 25: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 26: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Objective 2: Use NYHOPS to investigate marine climatology

Page 27: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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:

Page 28: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Water level validationFrom Newport, RI

To Hastings, Hudson River

To Sandy Hook, NJ

To Brandywine, Delaware Bay

66 Stations: NOS, USGS, SIT

Page 29: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Note possible effectsOf river flows

Exagerated in confined bays?

Page 30: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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 2Dfriction?

Page 31: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

0.63±0.14Compare to tidal:0.97±0.17

Page 32: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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

Page 33: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

2421156

Poor skill in someNJ back baysPoor resolution

Page 34: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

21131812

Page 35: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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).

28111015

Page 36: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Temperature validationFrom 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.

Page 37: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Salinity validationFrom 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?

Page 38: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

The Narrows

D e

p t h

, m e t e

r s

Model Mean: ()Data Mean: (o)Units are kts

CF(<0.4kts)Model Skill

RMSE, ktsMax FloodMax Ebb

DEPTH-AVERAGED OVERALL R^2 0.96; NON-TIDAL=0.61; >90% better than 0.5kts.

Page 39: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

CC=0.77, RMSe=0.39m or 28% MLHs.NDBC 44025

NDBC 44017 CC=0.80, RMSe=0.40m or 29%.

NDBC 44009 CC=0.80, RMSe=0.36m or 27%. UCONN 44039 CC=0.77, RMSe=0.14m or 48%.

UCONN 44040 CC=0.70, RMSe=0.12m or 59%.

NDBC 44054: Delaware Bay

SIT AVAN4: Avalon

CC=0.61, RMSe=0.19m or 43%.

CC=0.67, RMSe=0.28m or 35%.

CC=0.67, RMSe=0.35m or 36%.SIT BRNB4: Brant Beach, LBI

PREDICTED SIGNIFICANT WAVE HEIGHT

O P

E N

O

C E

A

N

LO

NG

ISL

AN

D

SOU

ND

N J

C

O A

S T

A

L

DE

LA

WA

RE

BA

Y

Page 40: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

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.

Page 41: Doctoral Dissertation Proposal Establishing confidence in marine forecast systems

Drs. Aikman, Blumberg, Herrington, Hires, Miller

Thank you!

Comments, questions, suggestions, welcome.