NOAA Technical Memorandum NOS CS 13

SKILL ASSESSMENT OF NOS LAKE 

ONTARIO OPERATIONAL FORECAST 

SYSTEM (LOOFS) 

Silver Spring, Maryland 

April 2008 

noaa National Oceanic and Atmospheric Administration 

U.S. DEPARTMENT OF COMMERCE 

National Ocean Service 

Coast Survey Development Laboratory 
Office of Coast Survey 

National Ocean Service 

National Oceanic and Atmospheric Administration 

U.S. Department of Commerce

The Office of Coast Survey (OCS) is the Nation’s only official chartmaker. As the 

oldest United States scientific organization, dating from 1807, this office has a 

long history. Today it promotes safe navigation by managing the National 

Oceanic and Atmospheric Administration’s (NOAA) nautical chart and 

oceanographic data collection and information programs. 

There are four components of OCS: 

The Coast Survey Development Laboratory develops new and efficient 

techniques to accomplish Coast Survey missions and to produce new and 

improved products and services for the maritime community and other 

coastal users. 

The Marine Chart Division acquires marine navigational data to construct 

and maintain nautical charts, Coast Pilots, and related marine products for 

the United States. 

The Hydrographic Surveys Division directs programs for ship and shorebased hydrographic survey units and conducts general hydrographic 

survey operations. 

The Navigational Services Division is the focal point for Coast Survey 

customer service activities, concentrating predominately on charting 

issues, fast-response hydrographic surveys, and Coast Pilot updates. 

ii 
NOAA Technical Memorandum NOS CS 13 

SKILL ASSESSMENT OF NOS LAKE ONTARIO 

OPERATIONAL FORECAST SYSTEM (LOOFS) 

John G. W. Kelley 

Ai-Jun Zhang 

Philip Chu 

Office of Coast Survey, Coast Survey Development Lab, Silver Spring, MD 

Gregory A. Lang 

Office of Oceanic and Atmospheric Research 

Great Lakes Environmental Research Laboratory, Ann Arbor, MI 

April 2008

noaa National Oceanic and Atmospheric Administration 

U. S. DEPARTMENT National Oceanic and National Ocean Service 

OF COMMERCE Atmospheric Administration John H. Dunnigan 

Carlos Gutierrez, Secretary Conrad C. Lautenbacher, Jr., Assistant Administrator 

 VADM USN (Ret.), Under Secretary 

Office of Coast Survey Coast Survey 

Captain Steven R. Barnum, NOAA Development Laboratory 

 Mary Erickson 

iii 
NOTICE 

Mention of a commercial company or product does not constitute an 

endorsement by NOAA. Use for publicity or advertising purposes of 

information from this publication concerning proprietary products or 

the tests of such products is not authorized. 

iv 
TABLE OF CONTENTS

LIST OF FIGURES ........................................................................................................... vi 

LIST OF TABLES............................................................................................................. vi 

LIST OF ACRONYMS ...................................................................................................viii 

EXECUTIVE SUMMARY ............................................................................................... ix 

1. INTRODUCTION .......................................................................................................... 1 

2. LAKE ONTARIO........................................................................................................... 2 

3. SYSTEM OVERVIEW .................................................................................................. 2 

3.1 Description of Model................................................................................................ 3 

3.2 Grid Domain ............................................................................................................. 3 

3.3 Data Ingest ................................................................................................................ 3 

3.4 Nowcast Cycle .......................................................................................................... 5 

3.5 Forecast Cycle........................................................................................................... 6 

3.6 Operational Environment and Scheduling................................................................ 6 

4. HINDCAST SKILL ASSESSMENT ............................................................................. 6 

5. SEMI-OPERATIONAL NOWCAST SKILL ASSESSMENT...................................... 7 

5.1 Description of Nowcast Cycles................................................................................ 7 

5.2 Method of Evaluation .............................................................................................. 8 

5.3 Assessment of Water Level Nowcasts................................................................... 14 

5.4 Assessment of Surface Water Temperature Nowcasts .......................................... 17 

6. SEMI-OPERATIONAL FORECAST SKILL ASSESSMENT .................................. 17 

6.1 Description of Forecast Cycles.............................................................................. 19 

6.2 Method of Evaluation ............................................................................................ 19 

6.3 Assessment of Water Level Forecast Guidance...................................................... 19 

6.4 Assessment of Surface Water Temperature Forecast Guidance ............................. 22 

7. SUMMARY.................................................................................................................. 22 

8. RECOMMENDATIONS FOR FUTURE WORK ...................................................... 25 

ACKNOWLEDGMENTS ................................................................................................ 25 

REFERENCES ................................................................................................................. 26 

APPENDIX A. Skill Assessment Statistics of Semi-Operational Water Level Nowcasts 

and Forecast Guidance at NOS Gauges in Lake Ontario for 2004............................. 29 

v 
APPENDIX B. Time Series Plots of Semi-Operational Water Level Nowcasts vs. 

Observations at NOS Gauges in Lake Ontario during 2004....................................... 31 

APPENDIX C. Time Series Plots of Semi-Operational Water Level Forecast Guidance 

vs. Observations at the NOS Gauges in Lake Ontario during 2004. .......................... 35 

APPENDIX D. Skill Assessment Statistics of Semi-Operational Surface Water 

Temperature Nowcasts and Forecast Guidance at one NWS/NDBC Fixed Buoy in 

Lake Ontario for 2004................................................................................................. 39 

APPENDIX E. Time Series Plots of Semi-Operational Nowcasts and Forecast Guidance 

of Surface Water Temperature vs. Observations at the NWS/NDBC fixed buoy in 

Lake Ontario during 2004........................................................................................... 40 

LIST OF FIGURES 

Figure 1. Map depicting the POMGL grid domain (5 km grid increment) and bathymetry 

(m) (labeled contours) used by NOS’ Lake Ontario Operational Forecast 

System.................................................................................................................. 4 

Figure 2. Map depicting locations of NOS/CO-OPS NWLON stations in Lake Ontario 

along with the model grid of LOOFS. ............................................................... 12 

Figure 3. Map depicting location of NWS/NDBC fixed buoy 45012 in Lake Ontario 

along with the model grid of LOOFS. ............................................................... 13 

LIST OF TABLES 

Table 1. NOS Skill Assessment Statistics (Hess et al. 2003). ............................................ 8 

Table 2. Data series groups and the variables in each. Note that upper case letters 

indicate a prediction series (e.g., H), and lower case letters (e.g., h) indicate a 

reference series (observation) (Modified from Hess et al. 2003). ................................ 9 

Table 3. Acceptance error limits (X) and the maximum duration limits (L) modified from 

Hess et al. (2003) for use in the Great Lakes................................................................ 9 

Table 4. Information on NOAA/NOS/CO-OPS NWLON stations whose observations 

were used to evaluate LOOFS semi-operational nowcasts and forecasts of water 

levels. .......................................................................................................................... 11 

Table 5. Information on NOAA/NWS/NDBC fixed buoy whose observations were used 

to evaluate LOOFS semi-operational nowcasts and forecasts of surface water 

temperatures................................................................................................................ 12 

Table 6. Summary of Skill Assessment Statistics of Semi-Operational Nowcasts of 

Hourly Water Levels at NOS NWLON Stations in Lake Ontario for the Period 15 

April to 17 December 2004. A total of 5757 to 5832 nowcasts were used in the 

assessment. Gray shading if present, indicates that the statistics did not pass the NOS 

acceptance criteria....................................................................................................... 14 

vi 
Table 7. Summary of Standard Statistics Evaluating the Ability of the Semi-Operational 

Nowcasts to Predict Extreme High Water Level Events at the NOS NWLON stations 

in Lake Ontario during the Period 15 April to 17 December 2004. Gray shading 

indicates that the statistic did not pass the NOS acceptance criteria. ......................... 15 

Table 8. Summary of Standard Statistics Evaluating the Ability of Semi-Operational 

Nowcasts to Simulate Extreme Low Water Level Events at the NOS NWLON 

Stations in Lake Ontario for the Period 15 April to 17 December 2004. Gray shading 

indicates that the statistic did not pass the NOS acceptance criteria. ......................... 16 

Table 9. Summary of Skill Assessment Statistics of the Semi-Operational Nowcasts of 

Hourly Surface Water Temperatures at a NWS/NDBC fixed buoy in Lake Ontario for 

the Period from mid-April to early November 2004. Gray shading indicates that the 

statistic did not pass the NOS acceptance criteria. ..................................................... 18 

Table 10. Summary of Skill Assessment Statistics of 24-hr Semi-Operational Forecast 

Guidance of Hourly Water Levels at NOS NWLON Stations in Lake Ontario for the 

Period 15 April to 17 December 2004. Approximately 490 forecasts were used in the 

assessment. Gray shading, if present, indicates that the statistic did not pass the NOS 

acceptance criteria....................................................................................................... 20 

Table 11. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance (0 to 24 hours) to Predict Extreme High Water Level 

Events at NOS NWLON Stations in Lake Ontario during the Period 15 April to 17 

December 2004. Gray shading indicates that the statistic did not pass the NOS 

acceptance criteria....................................................................................................... 21 

Table 12. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance (0 to 24 hours) to Predict Extreme Low Water Level 

Events at NOS NWLON Stations in Lake Ontario during the Period 15 April to 17 

December 2004. Gray shading indicates that the statistic did not pass the NOS 

acceptance criteria....................................................................................................... 21 

Table 13. Summary of Skill Assessment Statistics for Semi-Operational Forecast 

Guidance (0 to 24 hours) to Predict Surface Water Temperatures at a NWS/NDBC 

fixed buoy in Lake Ontario during the period from mid-April to early-November 

2004. Gray shading indicates that the statistic did not pass the NOS acceptance 

criteria. ........................................................................................................................ 23 

vii 
LIST OF ACRONYMS

ASOS Automated Surface Observing System 

AVHRR Advanced Very High Resolution Radiometer 

AWOS Automated Weather Observing System 

BUFR Binary Universal Form for the Representation of 

meteorological data 

C-MAN Coastal-Marine Automated Network 

CCS Central Computer System 

COMF Common Ocean Modeling Framework 

CO-OPS Center for Operational Oceanographic Products and Services 

CORMS Continuously Operating Real-Time Monitoring System 

CSDL Coast Survey Development Laboratory 

DOD Department of Defense 

EPA Environmental Protection Agency 

ETA Eta Mesoscale Numerical Weather Prediction Model 

GLCFS Great Lakes Coastal Forecast System 

GLERL Great Lakes Environmental Research Laboratory 

GLFS Great Lakes Forecasting System 

GLOFS Great Lakes Operational Forecast System 

GLSEA Great Lakes Surface Environmental Analysis 

GRIB GRIdded Binary 

LEOFS Lake Erie Operational Forecast System 

LHOFS Lake Huron Operational Forecast System 

LMOFS Lake Michigan Operational Forecast System 

LOOFS Lake Ontario Operational Forecast System 

LSOFS Lake Superior Operational Forecast System 

MAREP MARriner REPort 

MMAP Marine Modeling and Analysis Programs 

NAM North America Mesoscale Model 

NCEP National Centers for Environmental Prediction 

NCOP National Coastal Ocean Program 

NDBC National Data Buoy Center 

NOAA National Oceanic and Atmospheric Administration 

NOS National Ocean Service 

NWLON National Water Level Observation Network 

NWS National Weather Service 

ODAAS Operational Data Acquisition and Archive System 

OSU The Ohio State University 

POMGL Princeton Ocean Model – Great Lakes version 

USCG United States Coast Guard 

VOS Voluntary Observing Ship 

viii 
EXECUTIVE SUMMARY

This document describes the Lake Ontario Operational Forecast System (LOOFS) and an 

assessment of its skill. The lake forecast system, based on a hydrodynamic model, uses 

near real-time atmospheric observations and numerical weather prediction forecast 

guidance to produce three-dimensional forecast guidance of water temperature and 

currents and two-dimensional forecasts of water levels for Lake Ontario. 

LOOFS is the result of technology transfer of the Great Lake Forecasting System (GLFS) 

and Great Lakes Coastal Forecasting System (GLCFS) from The Ohio State University 

(OSU) and NOAA’s Great Lakes Environmental Research Laboratory (GLERL) to 

NOAA’s National Ocean Service (NOS). 

The model system skill assessment of LOOFS follows scenarios specified by Hess et al. 

(2003) which are applicable to forecast systems for non-tidal water bodies. However, 

this is the first time that the NOS standards have been applied to these freshwater forecast 

systems. These scenarios include 1) hindcast, 2) semi-operational nowcast, and 3) semioperational forecast. The hindcast is a long simulation using the best available observed 

meteorological observations and verification data. The semi-operational nowcast and 

forecast are simulations made in a real-time environment where there are occasional 

periods of missing inputs (i.e. meteorological observations and/or forecast guidance from 

atmospheric forecast models). 

Unfortunately, there was no known research study comparing surface and subsurface 

observations to simulations from the Princeton Ocean Model for Lake Ontario as was the 

case for Lakes Michigan and Erie. Therefore, no hindcast scenario skill assessment was 

done for LOOFS. 

For the semi-operational nowcast and forecast scenarios, an evaluation of GLERL’s realtime four times/day nowcast and twice daily forecast cycles from GLCFS for Lake 

Ontario was used to satisfy Hess et al. (2003) requirements. Although Hess et al. (2003) 

recommends conducting evaluations for 365 days in order to capture all expected 

seasonal conditions, GLCFS nowcasts and forecasts were evaluated for the ice-free 

period from 15 April to 17 December 2004. Due to the lack of regularly monitored 

currents and sub-surface water temperatures, only water levels and surface water 

temperatures at a few sites could be evaluated for Lake Ontario. 

The primary statistics used to assess the model performance for water levels and surface 

water temperatures are those required by Hess et al. (2003) for evaluating predicted water 

levels in non-tidal regions. These included Series Means (SM), Mean Algebraic Error 

(MAE), Root Mean Square Error (RMSE), Standard Deviation (SD), Negative Outlier 

Frequency (NOF), Positive Outlier Frequency (POF), Maximum Duration of Positive 

Outlier (MDPO), and Maximum Duration of Negative Outlier (MDNO). 

The skill statistics for the semi-operational nowcast and forecast scenarios are summarized 

below: 

ix 
Water levels: 

 

 Nowcasts: 

The hourly nowcasts of water level for amplitude met the NOS acceptance criteria at 

the four NOS gauges in Lake Ontario: Cape Vincent, Oswego, Rochester, and Olcott, 

NY. In terms of other statistics, the mean algebraic error or difference (MAE) ranged 

between -1.1 and +2.6 cm. The RSME ranged from 2.9 to 4.4 cm. 

The nowcast predictions of high water level events were assessed at two NOS gauges: 

Cape Vincent and Oswego, NY where there were 12 and two events, respectively. The 

nowcast of high water events passed the NOS criteria for amplitude at these two 

gauges. In terms of timing, the nowcasts met the NOS criteria at only Oswego. 

The nowcast predictions of low water level events were assessed at the four NOS 

gauges: Cape Vincent, Oswego, Rochester, and Olcott, NY where there were six, five, 

two, and two events, respectively. The nowcasts of low water events met the NOS 

criteria for amplitude at the four gauges but did not pass the criteria in terms of timing 

at any of these gauges. 

Forecast Guidance: 

The hourly forecast guidance met the NOS criteria for predicting water level amplitude 

at all four locations. In terms of other statistics, the MAE ranged between -1.0 and +2.8 

cm and RSME ranged from 3.4 to 4.8 cm. 

The forecast guidance of high water level events were assessed at two NOS gauges: 

Cape Vincent and Oswego, NY where there were 11 and four events, respectively. 

The guidance of high water events passed the NOS criteria for amplitude at both 

locations. The forecast guidance failed to meet NOS criteria in predicting the times of 

these extreme events at either of the gauges. 

The forecast guidance of low water level events were assessed at all four NOS gauges 

however, the number of ‘events’ were low ranging from two to six. The guidance of 

low water events passed the NOS criteria for amplitude at all gauges. The forecast 

guidance met NOS criteria in predicting the times of these extreme events at only one 

gauge. 

Surface Water Temperatures: 

Nowcasts: 

The hourly surface water temperature nowcasts was very close to meeting the proposed 

NOS acceptance criteria at the NOAA/National Weather Service (NWS) buoy in Lake 

Ontario (45012). The CF was 88.6% slightly below the target of 90% or greater. The 

MAE was 0.003o

C and RMSE was 1.88oC. 

x 
 Forecast Guidance: 

The hourly surface water temperature forecast guidance also came very close to 

meeting the proposed NOS acceptance criteria at the NWS buoy. The guidance only 

failed to meet the CF target by 2.4%. The MAE was -0.13oC and the RSME was 1.89 o

C. The times series plots indicated that LOOFS over predicted the SST during the 

Spring months and under predicted during August and September. 

Surface Currents: 

Due to the lack of water current observations, no quantitative assessment could be 

conducted for LOOFS. However, animation of surface current nowcasts and forecast 

guidance indicated that LOOFS did simulate the known cyclic clockwise rotation of 

surface currents present in the Great Lakes when the lake water is density stratified. 

This stratification occurs usually from May through October. 

Key Words: short-term lake predictions, nowcasts, model forecast guidance, Lake 

Ontario, skill assessment, water levels, water currents, water temperatures, Princeton 

Ocean Model, North American Mesoscale weather prediction model 

xi 
xii 
1. INTRODUCTION 

The Great Lakes Forecasting System (GLFS) was developed by The Ohio State 

University (OSU) and NOAA's Great Lakes Environmental Research Laboratory 

(GLERL) in the late 1980s and 1990s to provide nowcasts and short-range forecasts of 

the physical conditions (temperature, currents, water level, and waves) of the five Great 

Lakes. The development of GLFS was directed by Drs. Keith Bedford (OSU) and David 

Schwab (GLERL) and involved over a dozen OSU graduate students, research assistants 

and post doctoral researchers at GLERL and OSU, and other OSU faculty members. The 

development of GLFS was funded by over 36 contracts from 25 different sources. From 

the start, GLERL and OSU were interested in working cooperatively with NOAA in 

“assessing the potential benefits [of GLFS] to NOAA’s scientific and operational 

programs in the coastal ocean”. In April 1991, Drs. Bedford and Schwab met with 

representatives from the National Weather Service (NWS) and the National Coastal 

Ocean Program (NCOP) in Silver Spring, MD to discuss how they could work with 

NOAA line offices (NWS, NOS, etc.) to have GLFS products carefully evaluated through 

a demonstration program prior to NWS adopting the products as ‘guidance tools’ and 

which products might be distributed directly to end users. 

GLFS used the Princeton Ocean Model (Blumberg and Mellor 1987; Mellor 1996) and 

GLERL-Donelan wave model (Schwab et al. 1984). The first 3-D nowcast for the Great 

Lakes was made for Lake Erie in 1992 at the Ohio Supercomputer Center on the OSU 

Columbus campus (Yen et al. 1994; Schwab and Bedford 1994). Starting in July 1995, 

twice per day forecasts were made for Lake Erie. GLFS was recognized with an award in 

2001 by the American Meteorological Society as the first U.S. coastal forecasting system 

to make routine real-time predictions of currents, temperatures, and key trace 

constituents. 

In 1996, GLFS was ported to GLERL in Ann Arbor, MI. GLERL’s workstation version 

of GLFS, called The Great Lakes Coastal Forecast System (GLCFS), has been running in 

semi-operational mode at GLERL for Lake Ontario since August 2002. GLCFS for 

Lake Ontario generates nowcasts four times/day and forecast guidance out to 60 hours 

twice per day. The predictions are displayed on the GLERL web page 

(http://www.glerl.noaa.gov/res/glcfs/) and digital output is made available in GRIdded 

Binary (GRIB) format to NWS Weather Forecast Offices in the region. GLCFS nowcasts 

and forecasts are archived at GLERL. 

In 2004, the hydrodynamic model code of GLCFS for all five Great Lakes was ported to 

NOS Center for Operational Oceanographic Products and Services (CO-OPS) in Silver 

Spring, MD. GLCFS was reconfigured to run in the NOS Common Modeling 

Framework (COMF) and to use surface meteorological observations from NOS 

Operational Data Acquisition and Archive System (ODAAS) (Kelley et al. 2001). The 

CO-OPS version of GLCFS for Lake Ontario was renamed as the Lake Ontario 

Operational Forecast System (LOOFS). LOOFS began making routine operational lake 

nowcasts and forecasts for Lake Ontario on March 30, 2006 at CO-OPS during the icefree season. The forecast systems for Lake Huron and Superior were also implemented 

on this date. 

1 
The predictions from LOOFS, similar to those from NOS estuarine forecast systems, 

must be evaluated to inform users about the skill of the nowcasts and forecasts. In 

evaluating LOOFS, NOS sought to take advantage of previous evaluations done by 

researchers at OSU and GLERL to fulfill the hindcast scenario requirements described in 

Hess et al. (2003). Unfortunately, there was no modeling research study for Lake Ontario 

using the Princeton Ocean Model adapted to the Great Lakes (POMGL), as was the case 

for Lakes Michigan and Erie. Therefore, no hindcast scenario skill assessment was done 

for LOOFS. However, NOS did utilize the routinely-produced nowcasts and forecasts 

produced by GLERL to fulfill the semi-operational nowcast and forecast scenarios 

required by Hess et al. (2003). 

This report describes the model performance based on NOS requirements for operational 

nowcast/forecast systems (Hess et al. 2003). Brief descriptions of Lake Ontario and an 

overview of LOOFS are given first. 

2. LAKE ONTARIO 

Lake Ontario is the smallest of the Great Lakes in terms of surface area and the 14th

largest lake in the world with a breadth of 85 km (53 mi) and a length of 311 km (193 

mi). It has an average depth of 86 m (283 ft) with a maximum of 244m (802ft). Lake 

Ontario, similar to other Great Lakes, has a pronounced annual thermal cycle ranging 

from a vertically well-mixed water body in late autumn to a thermally stratified lake with 

a well-developed thermocline by August (Boyce et al. 1989). 

Lake Ontario, as do all the Great Lakes, experiences three types of water level 

fluctuations. Short-term changes occur due to surface winds and changes in atmospheric 

pressure. Seasonal changes occur with the lowest levels during the winter and highest 

during the early autumn. Long term water level changes occur over consecutive years, 

with wet/cold years causing water levels to rise and warm/dry years resulting in lower 

water levels (GLIN 2006). 

In terms of mean currents, the winter circulation in Lake Ontario is characterized by a 

two-gyre circulation pattern while summer circulation is predominantly cyclonic 

(Beletsky et al. 1999). On a short time period, Lake Ontario and other Great Lakes 

exhibit a cyclic clockwise rotation of surface currents when the lake water is density 

stratified during the warm season (May through October). Observational studies have 

found that the clockwise rotation has a near-inertial period of 18 hours (Saylor and Miller, 

1987). Additional information on currents in the Great Lakes can be found in Boyce et 

al. (1989). 

3. SYSTEM OVERVIEW 

This section provides a brief description of the numerical hydrodynamic model used by 

LOOFS. Detailed descriptions of the model as it has been applied to Lake Michigan can 

be found in Schwab and Beletsky (1998). Similar descriptions of the model as it has 

been applied to Lake Erie are given by Hoch (1997), Kuan (1995), and Kelley (1995). 

2 
3.1 Description of Model 

The core numerical model in LOOFS is the Princeton Ocean Model (POM) developed by 

Blumberg and Mellor (Mellor 1996). The model is a fully three-dimensional, non-linear 

primitive equation coastal ocean circulation model, with a second order Mellor-Yamada 

turbulence closure scheme to provide parameterization of vertical mixing processes. The 

model solves the continuity equation, momentum equation, and the conservation equation 

for temperature simultaneously in an iterative fashion, and the resulting predictive 

variables are free upper surface elevation, full three-dimensional velocity and 

temperature fields, Turbulence Kinetic Energy (TKE), and turbulence macroscale. Other 

main features of the model include: terrain following coordinate in the vertical (sigma 

coordinate), finite difference numerical scheme, Boussinesq and hydrostatic 

approximation, and mode splitting technique. 

POM was modified by researchers at OSU and GLERL for use in the Great Lakes 

(Bedford and Schwab 1991, O’Connor and Schwab 1993). For the rest of this report, the 

modified version of the POM for the Great Lakes will be referred to as POMGL. Lake 

Ontario, like the other Great Lakes, is treated as an enclosed basin. Therefore, there are 

no inflow/outflow boundary conditions: no fluid exchange between the lake and its 

tributaries, between the lake and ground water sources, or between the lake and 

anthropogenic influences. Thus the model simulations do not include seasonal changes 

in lake wide mean water level due to precipitation and evaporation. GLERL is presently 

evaluating the impact of using climatological estimates of river discharge on POMGL 

simulations. 

3.2 Grid Domain 

The POMGL domain for Lake Ontario consists of a rectangular grid with a 5-km 

horizontal resolution in both the x- and y-directions. The domain has a total of 1525 grid 

points with 61 points in the x-direction and 25 points in the y-direction (Fig. 1). The 

bottom topography for the domain is based on GLERL’s 2-km digital bathymetry data 

compiled by Schwab and Sellers (1980) but slightly smoothed to minimize the 

development of “two delta x noise.” The model uses 20 sigma levels in the vertical, with 

vertical levels spaced more closely in the upper 30 m of water and near the bottom to 

better resolve both the seasonal thermocline and bottom boundary layer (Schwab and 

Beletsky, 1998). The levels are located at sigma equal to 0, -.0227, -.0454, -.0681, -

.0908, -.1135, -.1362, -.1589, -.1816, -.2043, -.2270, -.2724, -.3405, -.4313, -.5448, -

.6810, -.7945, -.8853, -.9534, and -1.0. 

3.3 Data Ingest 

The nowcast cycle relies on surface meteorological observations obtained from NOS’ 

Operational Data Acquisition and Archive System (ODAAS). ODAAS acquires 

meteorological observations from the NWS/NCEP Central Operations (NCO) 

observational ‘data tanks’ located on NCEP’s Central Computer Systems (CCS) twice 

per hour at approximately 25 and 48 minutes past the top of the hour. The observations 

are originally in unblocked Binary Universal Form of Representation (BUFR) of 

3 
Figure 1. Map depicting the POMGL grid domain (5 km grid increment) and 

bathymetry (m) (labeled contours) used by NOS’ Lake Ontario 

Operational Forecast System.

4 
meteorological data format, but are decoded and written out to a text file for use by 

LOOFS and other NOS operational forecast systems. The surface observation text file is 

available to LOOFS within a minute of receiving the observations from the CCS. 

The text file includes surface observations from a variety of observing networks on and 

around Lake Ontario. On land, these networks include Automated Surface Observing 

System (ASOS), Coastal-Marine Automated Network (C-MAN), NOS National Water 

Level Observing Network (NWLON), and NOAA GLERL’s Real-Time Meteorological 

Observation Network. Presently, the surface meteorological observations from U.S. 

Coast Guard (USCG) stations around the lake are not available in the NCEP’s operational 

data tanks. Over water, the networks include the fixed buoys operated by the 

NWS/NDBC and Environment Canada, as well as observations from ships participating 

in the Voluntary Observing Ship (VOS) program. However, observations from VOS 

ships are not presently used by GLOFS due to occasional errors in observations from 

ships. 

To support the forecast cycle, ODAAS obtains gridded forecasts from NWS/NCEP 

models and NWS National Digital Forecast Database (NDFD). 

3.4 Nowcast Cycle 

The nowcast cycle of LOOFS is run hourly at NOS to generate updated nowcasts of the 

3-D state of Lake Ontario, including 3-D water temperatures and currents. The cycle also 

generates hourly nowcasts of 2-D water levels. 

The initial conditions for the nowcast cycle are provided by the previous hour’s nowcast 

cycle. The nowcast cycle is forced by gridded surface meteorological analyses valid at 

two times, one hour prior to the time of the nowcast and the current time of the nowcast. 

The gridded surface meteorological analyses are generated by interpolating surface 

observations of wind, air temperature, dew point temperature, and cloud cover using the 

natural neighbor technique (Sambridge et al. 1995) using the program interpnn.f. 

Before being interpolated, the surface wind and air temperature observations are adjusted 

to a common anemometer height of 10 m above the ground or water. Surface 

observations of wind direction, wind speed, air temperature, and dew point temperature 

from overland stations are adjusted to be more representative of overwater conditions. 

Both the height adjustment correction and overland adjustment procedure use the 

previous day’ lake average water temperature from GLERL’s Great Lakes Surface 

Environmental Analysis (GLSEA). The GLSEA temperature analysis is generated using 

SST retrievals derived from the Advanced Very High Resolution Radiometer data 

obtained from NOAA’s polar-orbiter satellites. The adjustments to the observations 

along with simple quality control checks are performed by the program edit_sfcmarobs.f 

The gridded surface wind fields are then used by POMGL to calculate wind stress at each 

model grid point. The surface meteorological fields along with POMGL lake surface water 

temperatures predictions from POMGL are used by a heat flux scheme (McCormick and 

Meadows 1988) to estimate the net rate of heat transfer at each lake grid point. The heat flux 

5 
scheme can be found in POMGL’s subroutine FLUX1. Additional information on the wind 

stress and heat flux schemes can be found in Kelley (1995). 

3.5 Forecast Cycle 

The forecast cycle of LOOFS is run four times per day to generate forecast guidance of 

the 3-D state of Lake Ontario. The forecast cycle uses the most recent nowcast for its 

initial conditions. From March 2006 to March 2007, the surface meteorological forcing 

was provided by the latest forecast guidance of surface (10 m AGL) u- and v-wind 

components and surface air temperature (2 m AGL) from the 0, 6, 12, or 18 UTC forecast 

cycles of NWS/NCEP’s North American Mesoscale (NAM) model. NAM has a spatial 

resolution of 12 km and uses the Weather Research and Forecast (WRF) model as its 

core. The surface wind velocity forecast guidance from the NAM model is valid at a 

height of 10 m above the ground or lake surface. However, in April 2007, CO-OPS 

decided to switch to using gridded forecasts of surface wind velocity and surface air 

temperature from the NWS NDFD. The NDFD fields are obtained from the NWS 

Weather Forecast Office (WFO) in Cleveland, OH by CO-OPS four times/day in 

netCDF. The NDFD forecasts have a spatial resolution of 5 km and cover both U.S. and 

Canadian waters of the Great Lakes. 

3.6 Operational Environment and Scheduling 

LOOFS is run operationally on a Linux workstation at NOS/CO-OPS in Silver Spring, 

MD. Each hourly nowcast cycle is launched at 56 minutes past the top of the hour to 

ensure that a sufficient amount of surface meteorological observations from both 

Canadian and U.S. networks are received at NCEP and then processed at CO-OPS by 

ODAAS. 

The forecast cycle of LOOFS is run four times per day at 0000, 0600, 1200, and 1800 

UTC at 56 minutes past the top of these hours. The forecast horizon of each forecast 

cycle is 30 hours. 

LOOFS and the operational forecast systems for Lakes Huron and Superior were 

officially implemented as operational forecast systems at CO-OPS on March 30, 2006. 

4. HINDCAST SKILL ASSESSMENT 

NOS standards (Hess et al. 2003) require the hydrodynamic model of any NOS 

nowcast/forecast system to run in the hindcast scenario. A hindcast is defined as a long 

simulation using the best available gap-filled observed data for boundary water levels, 

wind, and river flows. Unfortunately, unlike the skill assessments of the operational 

forecast systems for Lake Erie and Lake Michigan, there were no field observing 

programs in order to compare POMGL simulations to surface and subsurface data. 

Therefore, no skill assessment was done to fulfill the hindcast scenario requirement. 

6 
5. SEMI-OPERATIONAL NOWCAST SKILL ASSESSMENT 

This section describes the model system performance based on NOS requirements for 

semi-operational nowcast scenario (Hess et al. 2003). According to Hess et al., the 

definition of the model run scenario for a semi-operational nowcast is the following: 

“In this scenario, the model is forced with actual observational input data streams 

including open ocean boundary water levels, wind stresses, river flows, and water density 

variations. Significant portions of the data may be missing, so the model must be able to 

handle this.” 

LOOFS, as described in Chapter 2, is based on NOAA/GLERL’s Great Lakes Coastal 

Forecast System (GLCFS) for Lake Ontario. Both LOOFS and GLCFS-Lake Ontario 

have a spatial grid increment of 5 km, 20 sigma layers, and use similar surface 

meteorological forcing. Neither of the systems employed any river inflow or assimilated 

any limnological data. GLCFS used surface observations from USCG stations and 

cooperative marine weather observations called MARinter REPort (MAREP) unlike 

LOOFS which does not. However, this difference was not expected to cause a significant 

difference in the nowcasts due to low number of observations available from USCG and 

MAREP locations during any given hour. 

Due to the similar characteristics of LOOFS and GLCFS, the assessment of the LOOFS 

semi-operational nowcasts was performed using archived nowcasts from GLCFS four 

times/day nowcast cycles. 

This chapter describes the GLCFS nowcast cycles, the evaluation method including time 

period and assessment statistics, and the results of the evaluation. 

5.1 Description of Nowcast Cycles 

GLCFS performs four times/day nowcast cycles for Lake Ontario, and the other four 

Great Lakes, year round. The POMGL used by each forecast system are not reinitialized 

each spring. (GLOFS at NOS is reinitialized each spring around April using isothermal 

conditions based on SST from the Great Lakes Surface Environmental Analysis.) The 

surface forcing for the nowcast cycles are provided by objective analyses (Sambridge et 

al. 1995) of surface meteorological observations from land-based and overwater 

observing stations. The four nowcast cycles produce nowcasts valid at 0000, 0600, 1200, 

and 1800 UTC each day. The nowcast cycles are launched at approximately 80 minutes 

past the valid time of the nowcasts. For example, the nowcast cycle to generate a 

nowcast valid at 0000 UTC is launched at 0120 UTC to allow for observations from late 

reporting NDBC C-MAN stations to be received at GLERL via NOAAPORT broadcast 

system. Hourly model output from the four nowcast cycles are archived at GLERL. 

7 
5.2 Method of Evaluation 

The hourly model results from the GLCFS nowcasts were compared to observations from 

coastal and offshore observing platforms in the lake for the period from mid-April to 

mid-December 2004. This was a period when there was no significant ice cover. The 

evaluation used the standard suite of assessment statistics, as defined in Hess et al. 

(2003). The standard suite of statistics is given in Table 1. The target frequencies of the 

associated statistics are the following: 

 CF(X) ≥90%, POF(2X) ≤1%, NOF(2X) ≤1%, WOF(2X) ≤0.5% 

 MDPO(2X) ≤ L, MDNO(2X) ≤ L 

There are three types of data sets (Table 2): Group 1, a time series of values at uniform 

time intervals; Group 2, a set of values representing the consecutive occurrences of an 

event (such as high or low water); and Group 3, a set of values representing a forecast 

valid at a given projection time. The acceptable error limits (X) and maximum duration 

limits (L) for the associated variable applied to the LOOFS are presented in Table 3. 

Table 1. NOS Skill Assessment Statistics (Hess et al. 2003). 

Variable Explanation 

Error The error is defined as the predicted value, p, minus the reference (observed or astronomical tide 

value, r : ei = pi - ri. 

SM Series Mean. The mean value of a series y. Calculated as y N yi

i

N

= =

∑1

1

. 

RMSE Root Mean Square Error. Calculated as RMSE e N i

i

N

= =

∑1 2

1

.

SD Standard Deviation. Calculated as SD e e N i

i

N

= − −

=

∑1

1

1

2 ( )

CF(X) Central Frequency. Fraction (percentage) of errors that lie within the limits +X. 

POF(X) Positive Outlier Frequency. Fraction (percentage) of errors that are greater than X. 

NOF(X) Negative Outlier Frequency. Fraction (percentage) of errors that are less than -X. 

MDPO(X) Maximum Duration of Positive Outliers. A positive outlier event is two or more consecutive 

occurrences of an error greater than X. MDPO is the length of time (based on the number of 

consecutive occurrences) of the longest event. 

MDNO(X) Maximum Duration of Negative Outliers. A negative outlier event is two or more consecutive 

occurrences of an error less than -X. MDNO is the length of time (based on the number of 

consecutive occurrences) of the longest event. 

WOF(X) Worst Case Outlier Frequency. Fraction (percentage) of errors that, given an error of magnitude 

exceeding X, either (1) the simulated value of water level is greater than the astronomical tide and 

the observed value is less than the astronomical tide, or (2) the simulated value of water level is 

less than the astronomical tide and the observed value is greater than the astronomical tide. 

8 
Table 2. Data series groups and the variables in each. Note that upper case letters 

indicate a prediction series (e.g., H), and lower case letters (e.g., h) indicate a 

reference series (observation) (Modified from Hess et al. 2003). 

Group Variable Symbol 

Group 1 Water level H, h 

(Time Series) Water temperature T, t 

Group 2 Amplitude of high water AHW, ahw 

(Values Amplitude of low water ALW, alw 

at Extreme Event) Time of high water THW, thw 

 Time of low water TLW, tlw 

Group 3 Water level at forecast projection time of nn hrs Hnn, hnn 

(Values from a Water temperature at forecast projection time of nn hrs Tnn, tnn 

Forecast) 

Table 3. Acceptance error limits (X) and the maximum duration limits (L) modified 

from Hess et al. (2003) for use in the Great Lakes. 

Variables X L (hours) 

H, Hnn, AHW, ALW 15 cm 24 

THW, TLW 1.5 hours+ 25 

T, Tnn, 3oC* 24 

_______________________________________________________________________ 

Notes: +1.0 hours for tidal regions, *7.7oC for tidal regions. 

The evaluation utilized the NOS skill assessment software (Zhang et al. 2006), but was 

modified for use in the Great Lakes. The software computes the skill assessment scores 

automatically using files containing observations and nowcast or forecast guidance. 

Since the GLCFS output was not in netCDF, the output was reformatted to meet the text 

format input requirements of the skill assessment code. 

Nowcasts of Water Levels

The evaluation of GLCFS nowcasts of water levels were based on time series of observed 

and model-based water levels at four NOS NWLON stations along the Lake Ontario 

shore line (Table 4). A map depicting the locations of the four NOS stations in the lake is 

given in Fig. 2. 

Since water level nowcasts and forecasts generated by GLCFS were vertical 

displacements relative to the flat lake, further adjustment was necessary to bring the 

water levels relative to the mean lake level. An offset value based on a dynamic 7-day 

average mean lake water level was computed and added to the model nowcast of water 

level displacement from model’s mean. This is the same method used by CO-OPS prior 

to displaying the LOOFS nowcasts on the Web. The final nowcast water levels were then 

9 
compared with the observational data. 

The evaluation of GLCFS water level nowcasts for Lake Ontario was done by comparing 

time series differences using SM, RMSE, SD, NOF, POF, MDPO, and MDNO statistics 

described in Hess et al. (2003). Since tides are not significant in the Great Lakes there 

were no comparisons of the times and amplitudes of tidally-forced high and low waters. 

However, significant high amplitude water events do occur in several of the Great Lakes, 

especially in Lake Erie. Following the recommendations of Hess et al. (2003), a method 

was developed and implemented in the NOS skill assessment software to analyze the 

nowcast/forecast system’s ability to simulate large amplitude events. This is the first 

attempt at evaluating the ability of a NOS prediction system to simulate high and low 

water events in non-tidal regions. Other methods such as described by Dingman and 

Bedford (1986) and used by Kelley (1995) and Hoch (1997) may be considered for future 

versions of the NOS standards and skill assessment code. 

The NOS skill assessment software identifies high and low water events in the Great 

Lakes using the following method. 

Step 1. For the observed time series of water level, pick all high and low values. A data 

point is selected if it is either higher than its two neighboring points (both sides), 

or lower than its two neighboring points. 

Step 2. For each selected peak from Step 1, a seven day window is centered on the 

particular peak and the mean value and standard deviation (called sigma 

hereafter) of the observed time series are computed within the seven day period. 

Upper/lower limits are then computed as the mean value +/- 2 sigma. 

Step 3. The peak is identified as a high/low water level event if it exceeds the upper and 

lower limits. (Step 2 was performed to remove the impact of periodical 

variations, such as semi-diurnal and diurnal frequency signals on event 

selection.) 

Step 4. For each high and low water level event in the observed time series, the 

maximum/minimum water level value and occurrence time are selected from 

the model simulated time series within a 12 hour window (the occurrence time 

of the observed event is centered), and paired with the observed events for 

comparison and statistic evaluation. 

Step 5. The paired observed and simulated extreme events are compared to each other 

to assess the ability of the forecast system to simulate large amplitude events. 

10 
Table 4. Information on NOAA/NOS/CO-OPS NWLON stations whose observations 

were used to evaluate LOOFS semi-operational nowcasts and forecasts of 

water levels. 

Geographic Coordinates Corresponding I 

and J model 

coordinates 

Station Name State NOS 

Station ID 

Number 

NWS 

Station 

ID 

Latitude 

(deg N) 

Longitude 

(deg W) 

I J 

Cape Vincent NY 9052000 NS 44.13 76.34 56* 22* 

Oswego NY 9052030 OSGN6 43.46 76.51 54 9* 

Rochester NY 9052058 NS 43.27 77.65 36 4 

Olcott NY 9052076 NS 43.34 78.73 18 6* 

Notes: NS = A official NWS station ID has not been assigned to the station yet. 

 * = I and J coordinates assigned to nearest water grid cell. 

Nowcasts of Surface Water Temperatures

The evaluation of GLCFS nowcasts of surface water temperatures was based on 

comparisons of time series of model-predicted temperatures vs. observations at a 3-m 

fixed disk buoy in the lake. The buoy is operated by NOAA/National Data Buoy Center 

(NDBC). Information on the buoy is given in Table 5. The lake surface temperatures at 

NDBC Buoys are measured using a Yellow-Springs thermistor sealed in epoxy in a 

copper slug clamped to the inside of the buoy’s hull (Gillhousen 1987). The thermistor 

depth is 0.5 m and is sampled once per hour. The point evaluations were conducted by 

comparing surface (highest sigma layer) temperature nowcasts at the nearest grid point to 

surface observations from the buoy. A map depicting the locations of the NDBC fixed 

buoy is given in Fig. 3. 

The evaluation of GLCFS surface water temperature nowcasts for Lake Ontario was 

done by comparing time series differences using SM, RMSE, SD, NOF, POF, MDPO, 

and MDNO statistics described in Hess et al. (2003). No attempt was made to assess the 

nowcast/forecast system’s ability to simulate diurnal or larger temperature fluctuations. 

Other methods for evaluating water temperature predictions such as those used by Kelley 

(1995) and Hoch (1997) may be implemented in the future. 

In evaluating predicted water temperature in tidal regions, NOS sets an acceptable error 

of 7.7oC to meet the acceptable error of draft of 7.5 cm (3 inches), as water density is a 

function of temperature and salinity. Since the Great Lakes are fresh water bodies and 

non-tidal, there is no preset standard for a lake temperature prediction. Based on the 10 

years experience of running the Great Lakes Forecasting System and input from the Great 

Lakes user community, Dr. David Schwab of NOAA/GLERL (Schwab 2006) suggested a 

3o

C criteria for water temperature skill assessment in the Great Lakes region (personal 

communication). Thus, all the statistical evaluation and skill scores are based on a 3o

C 

criteria. 

11 
Table 5. Information on NOAA/NWS/NDBC fixed buoy whose observations were 

used to evaluate LOOFS semi-operational nowcasts and forecasts of 

surface water temperatures. 

Geographic Coordinates and 

Depth 

Corresponding 

LOOFS Grid Point 

Coordinates and 

Depth 

Buoy Name Agency State WMO 

Buoy 

ID Latitude 

(deg N) 

Longitude 

(deg W) 

Depth 

(m) 

I J Depth 

(m) 

Lake Ontario 

Buoy 

(20nm NNE of 

Rochester, NY) 

NWS/ 

NDBC 

NY 45012 45.62 77.41 145 40 11 150 

Figure 2. Map depicting locations of NOS/CO-OPS NWLON stations in Lake 

Ontario along with the model grid of LOOFS. 

12 
Figure 3. Map depicting location of NWS/NDBC fixed buoy 45012 in Lake Ontario 

along with the model grid of LOOFS. 

13 
5.3 Assessment Results of Water Level Nowcasts 

The standard suite of skill assessment statistics evaluating the ability of semi-operational 

nowcasts and forecast guidance to predict hourly and extreme water levels at four NOS 

gauges from 15 April to 17 December 2004 are given in Appendix A. Time series plots 

of the nowcasts vs. observations at the gauges are given in Appendix B. 

The skill statistics assessing the ability of the nowcasts to predict hourly water levels at 

the four NOS gauges are presented together in Table 6 along with the NOS acceptance 

criteria. The hourly nowcasts passed the criteria at all four locations. The mean 

algebraic errors or differences ranged between -1.1 and 2.6 cm and the RMSE ranged 

between 2.9 and 4.4 cm. The greatest RSME was at Cape Vincent, NY gauge located at 

the extreme NE part of the lake (Fig. 2). The nowcasts generally over predicted the water 

levels at most gauges but under predicted levels at Olcott, NY. 

Table 6. Summary of Skill Assessment Statistics of Semi-Operational Nowcasts of 

Hourly Water Levels at NOS NWLON Stations in Lake Ontario for the 

Period 15 April to 17 December 2004. A total of 5757 to 5832 nowcasts were 

used in the assessment. Gray shading if present, indicates that the statistics did 

not pass the NOS acceptance criteria. 

Statistic, Acceptable 

Error [ ], and 

Units ( )

Cape 

Vincent, 

NY 

Oswego, 

NY 

Rochester, 

NY 

Olcott, 

NY 

NOS 

Accept. 

Criteria 

Mean Diff. (m) 0.026 0.005 0.000 -0.011 na 

RMSE (m) 0.044 0.032 0.029 0.033 na 

SD (m) 0.036 0.031 0.029 0.031 na 

NOF [2x15cm] (%) 0.0 0.0 0.0 0.0 < 1% 

CF [15 cm] (%) 99.9 100.0 100.0 100.0 > 90% 

POF [2x15 cm] (%) 0.0 0.0 0.0 0.0 < 1% 

MDPO [2x15 cm ] (hour) 0.0 0.0 0.0 0.0 < 24 

hours 

MDNO [2x15 cm ] (hour) 0.0 0.0 0.0 0.0 < 24 

hours 

Notes: na = not applicable 

The skill statistics assessing the ability of nowcasts to predict extreme high water level 

events at NOS gauges during 2004 are given together in Table 7. The statistics are for 

only two gauges (Cape Vincent and Oswego) since no extreme high water level events 

occurred at Olcott or Rochester, NY based on the event definition. The high water level 

nowcasts at the two gauges passed the NOS acceptance criteria for amplitude. The 

nowcasts ability to simulate the timing of these events did not pass the NOS acceptance 

criteria for NOF, CF, and POF at Cape Vincent but did pass at Oswego. However, the 

skill assessment results of extreme water level events might be suspect due to only a few 

high water events occurred at Oswego. The skill statistics to predict extreme low water 

level events at the four NOS gauges during 2004 are given together in Table 8. 

Depending on the gauge, there were 2 to 6 events during the time period. The extreme 

14 
low water level nowcasts passed NOS acceptance criteria for amplitude at the four 

gauges. The nowcasts ability to simulate the timing of these events did not pass the NOS 

acceptance criteria for one or two of the skill statistics (i.e. NOF, CF, and POF) at the 

four gauges 

Table 7. Summary of Standard Statistics Evaluating the Ability of the SemiOperational Nowcasts to Predict Extreme High Water Level Events at the 

NOS NWLON stations in Lake Ontario during the Period 15 April to 17 

December 2004. Gray shading indicates that the statistic did not pass the NOS 

acceptance criteria. 

Cape Vincent, 

NY 

N=12 

Oswego, NY 

N=2 

NOS 

Accept. 

Criteria 

Statistic, 

Acceptable Error [ ], and Units ( ) 

Amp. Time Amp. Time 

Mean Diff. (m) (min) -0.046 -1.333 -0.074 0.500 na 

RMSE (m) (min) 0.050 4.472 0.074 0.707 na 

SD (m) (min) 0.022 4.458 0.008 0.707 na 

NOF [2x15cm or 90min] % 0.0 33.3 0.0 0.0 < 1% 

CF [15 cm or 90 min] (%) 100.0 33.3 100.0 100.0 > 90% 

POF [2x15 cm or 90 min] (%) 0.0 16.7 0.0 0.0 < 1% 

MDPO [2x15 cm or 90 min] (#) 0.0 0.0 0.0 0.0 < 24 hrs 

MDNO [2x15 cm or 90min] (#) 0.0 0.0 0.0 0.0 < 24 hrs 

Notes: na = not applicable 

15 
Table 8. Summary of Standard Statistics Evaluating the Ability of SemiOperational Nowcasts to Simulate Extreme Low Water Level Events at the 

NOS NWLON Stations in Lake Ontario for the Period 15 April to 17 

December 2004. Gray shading indicates that the statistic did not pass the NOS 

acceptance criteria. 

Cape Vincent, 

NY 

N=6 

Oswego, NY 

N=5 

Rochester, NY 

N=2 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amp. Time Amp. Time Amp. Time 

Mean Diff. (m) (min) 0.067 0.167 0.052 0.800 0.067 1.000 

RMSE (m) (min) 0.069 1.225 0.053 3.098 0.067 3.162 

SD (m) (min) 0.021 1.329 0.010 3.347 0.010 4.243 

NOF [2x15cm or 90min] (%) 0.0 0.0 0.0 20.0 0.0 0.0 

CF [15 cm or 90 min] (%) 100.0 8.3 100.0 20.0 100.0 0.0 

POF [2x15 cm or 90 min] (%) 0.0 0.0 0.0 0.0 0.0 50.0 

MDPO [2x15 cm or 90 min] 

(#) 

0.0 0.0 0.0 0.0 0.0 0.0 

MDNO [2x15 cm or 90min] (#) 0.0 0.0 0.0 0.0 0.0 0.0 

Table 8 (cont.) 

Olcott, NY 

N=2 

NOS 

Accept. 

Criteria 

Statistic, 

Acceptable Error [ ], and Units ( ) 

Amplit

ude 

Time 

Mean Diff. (m) (min) 0.001 -3.500 na 

RMSE (m) (min) 0.015 4.301 na 

SD (m) (min) 0.021 3.536 na 

NOF [2x15cm or 90min] (%) 0.0 50.0 < 1% 

CF [15 cm or 90 min] (%) 100.0 50.0 > 90% 

POF [2x15 cm or 90 min] (%) 0.0 0.0 < 1% 

MDNO [2x15 cm or 90 min] (#) 0.0 0.0 < 24 hrs 

MDPO [2x15 cm or 90min] (#) 0.0 0.0 < 24 hrs 

Notes: na = not applicable 

16 
5.4 Assessment of Surface Water Temperature Nowcasts 

The standard suite of skill assessment statistics evaluating the ability of the semioperational nowcasts to predict hourly lake surface water temperatures at the 

NWS/NDBC fixed buoy in Lake Ontario (45012) from mid-April to early December 

2004 is given in Appendix D. The time series plot of the nowcasts (1st sigma level) vs. 

observations at the buoy is given in Appendix E. 

The time series plots indicate that the nowcasts were in close agreement to observations 

(+0.5-1oC) from mid-April until mid-May corresponding to the spring warming period. 

During the warming period, surface heating causes convective overturning 

(destabilization of the water column) over the entire lake as the water warms from 

temperatures close to freezing to 4oC (Boyce et al. 1989). 

However, when the surface water temperature nowcasts reached 4oC, the temperature of 

maximum density for fresh water, the nowcasts deviated from the observations by +2-3o

C 

until mid-June at the buoy. From mid-June until approximately the beginning of August 

the nowcasts matched the observations. August is the time when complete thermal 

stratification of the lake usually occurs (Boyce et al. 1989). 

From the beginning of August until late September the nowcasts were cooler than 

observations by 2-3oC. The difference then declined to -1oC or less by mid October. 

This corresponds to the time of the year when the vertical temperature structure becomes 

homogeneous through surface cooling and storm induced destabilization (Bedford 1992). 

However, starting in mid November the nowcasts were approximately 2-3oC warmer than 

observations until the buoy was removed from the lake by NDBC for the winter, similar 

to what occurred in the early spring. 

The skill statistics assessing the ability of LOOFS to predict hourly surface water 

temperatures at the NDBC buoy are given together in Table 9 along with the NOS 

acceptance criteria. The hourly water temperature nowcasts came close to passing the 

NOS criteria, failing to achieve the CF criteria by only 1.4%. The MAE for the period 

was 0.003oC and the RMSE was 1.88oC. 

6. SEMI-OPERATIONAL FORECAST SKILL ASSESSMENT 

This section describes the model system performance for a semi-operational forecast 

scenario based on NOS requirements (Hess et al. 2003). According to NOS 

requirements, the definition of the model run scenario for a semi-operational forecast is 

the following: 

“In this scenario, the model is forced with actual forecast input data streams, including 

open ocean boundary water levels, wind, river flows, and water density variations. Initial 

conditions are generated by observed data. Significant portions of the data may be 

missing, so the model must be able to handle this.” 

17 
For the assessment of the semi-operational forecast scenario for LOOFS, archived 

forecast guidance from GLCFS twice per day forecast cycles (0000 and 1200 UTC) 

during 2004 were compared to available observations in the lake. 

This chapter provides a description of the GLCFS forecast cycles, the method of 

evaluation including time period and assessment statistics, and the evaluation results. 

Table 9. Summary of Skill Assessment Statistics of the Semi-Operational Nowcasts

of Hourly Surface Water Temperatures at a NWS/NDBC fixed buoy in 

Lake Ontario for the Period from mid-April to early November 2004. Gray 

shading indicates that the statistic did not pass the NOS acceptance criteria. 

Time Period, Statistic, 

Acceptable Error [ ], and Units ( )

45012 

Lake Ontario 

N=5078 

NOS 

Acceptance 

Criteria 

Time Period April to 

Nov. 2004 

365 days 

Mean Difference (oC) 0.003 na 

RMSE (oC) 1.880 na 

SD (oC) 1.880 na 

NOF [2x3oC] (%) 0.0 < 1% 

CF [3oC] (%) 88.6 > 90% 

POF [2x3oC] (%) 0.1 < 1% 

MDNO [2x3oC] (hours) 0.0 < 24 hrs 

MDPO [2x3oC] (hours) 2.0 < 24 hrs 

 Notes: na = not applicable 

18 
6.1 Description of Forecast Cycles 

GLCFS performs twice/day 60-hr forecast cycles for Lake Ontario. The two forecast 

cycles are initialized at 0000 and 1200 UTC each day. The forecast cycles are launched 

at approximately 2 hours and 45 minutes past the start time of the cycle to allow for 

complete ingestion of atmospheric forecast fields. For example, the forecast cycle with 

initial conditions valid at 1200 UTC is launched at 1445 UTC. The initial conditions for 

each forecast cycle are provided by the nowcast cycle. The surface forcing for the 

forecast cycles consists of surface (10 m AGL) wind velocity and surface (2 m AGL) air 

temperatures from NWS/NCEP North America Mesoscale (NAM) Model. The wind 

velocity and air temperature are used to calculate surface wind stress for input into the 

lake model. The surface heat fluxes into the lake model during the forecast cycle are 

zero. 

6.2 Method of Evaluation 

The semi-operational forecast guidance at 1 hour increments from +1 to +24 hours from 

GLCFS were compared to water level observations from NOS NWLON stations in the 

lake from 15 April to 17 December 2004 and to the NWS/NDBC fixed buoy from midApril to early November for the surface water temperature forecasts. This was a period 

when there was no significant ice cover on the lake. 

The evaluation used the standard suite of assessment statistics as defined in Hess et al. 

(2003) but modified for non-tidal regions. The evaluation of GLCFS forecasts of water 

levels were based on time series of observed and model-based water levels at the same 

four NOS NWLON stations along the lake shore line used in the evaluation of the 

nowcasts. 

The evaluation of semi-operational forecast guidance of surface water temperatures were 

based on comparisons of time series of observed vs. model-predicted temperatures at the 

same NWS/NDBC fixed buoy used in the nowcast evaluation. There are a few gaps in 

the record of forecast guidance due to computer, and/or network problems, or incomplete 

surface forcing from the NAM Model for a particular forecast cycle. 

6.3 Assessment Results of Water Level Forecast Guidance 

The standard suite of skill assessment statistics evaluating the ability of semi-operational 

forecast guidance to predict hourly and extreme water levels at four NOS Gauges from 15 

April to 17 December 2004 is given in Appendix A. Time series plots of the forecast 

guidance from the 0000 UTC model forecast cycle vs. observations at the gauges are 

given in Appendix C. 

The skill statistics assessing the ability of the forecast guidance to predict hourly water 

levels at the four NOS gauges are presented together in Table 10 along with the NOS 

acceptance criteria. The hourly forecasts passed the criteria at all gauge locations. The 

MAE ranged between +0.1 to + 2.8 cm and the RMSE ranged between 3.4 and 4.8 cm, 

19 
very similar to the statistics for the nowcast evaluation. Similar to the nowcasts, the 

greatest errors were at Cape Vincent located at in the NE end of the lake. The forecasts 

under-predicted the water levels at Olcott but over-predicted the levels at the other 

gauges. There was no significant increase in the mean differences, RMSE values, or CF 

as forecast projection time increased (Appendix A). 

The skill statistics to assess the ability of the forecast guidance to predict extreme high 

water level events at NOS Oswego and Cape Vincent gauges during 2004 are given 

together in Table 11. There were no extreme high water events at Rochester and Olcott 

based on the event selection method defined in 5.2. The forecasts of extreme high water 

level passed NOS acceptance criteria for amplitude at the two gauges. However, it 

should be noted there were only four and 11 high water level events at Oswego and Cape 

Vincent, respectively. The forecasts’ ability to simulate the timing of these events did not 

pass NOS acceptance criteria for NOF and CF at the two gauges but did pass POF criteria 

at the Oswego gauge.

The skill statistics to assess the ability of the forecast guidance to predict extreme low 

water level events at the four NOS gauges in 2004 are given together in Table 12. The 

number of events ranged from two to six. The forecasts of extreme low water level 

passed NOS acceptance criteria for amplitude at all four gauges. The forecasts ability to 

simulate the timing of these events did not pass all the NOS acceptance criteria for NOF, 

CF, and POF except at the Rochester gauge. However, there were only two low water 

events at this gauge. 

Table 10. Summary of Skill Assessment Statistics of 24-hr Semi-Operational 

Forecast Guidance of Hourly Water Levels at NOS NWLON Stations in 

Lake Ontario for the Period 15 April to 17 December 2004. 

Approximately 490 forecasts were used in the assessment. Gray shading, if 

present, indicates that the statistic did not pass the NOS acceptance criteria. 

Statistic, Acceptable 

Error [ ], and 

Units ( ) 

Cape 

Vincent, 

NY 

Oswego, 

NY 

Rochester, 

NY 

Olcott, 

NY 

NOS 

Accept. 

Criteria 

Mean Diff. (m) 0.028 0.005 0.001 -0.010 na 

RMSE (m) 0.048 0.036 0.034 0.037 na 

SD (m) 0.039 0.035 0.034 0.035 na 

NOF [2x15cm] (%) 0.0 0.0 0.0 0.0 < 1% 

CF [15 cm] (%) 100.0 100.0 100.0 100.0 > 90% 

POF [2x15 cm] (%) 0.0 0.0 0.0 0.0 < 1% 

MDPO [2x15 cm ] 

(hour) 

0.0 0.0 0.0 0.0 < 24 

hours 

MDNO [2x15 cm ] 

(hour) 

0.0 0.0 0.0 0.0 < 24 

hours 

Notes: na = not applicable 

20 
Table 11. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance (0 to 24 hours) to Predict Extreme High 

Water Level Events at NOS NWLON Stations in Lake Ontario during 

the Period 15 April to 17 December 2004. Gray shading indicates that the 

statistic did not pass the NOS acceptance criteria. 

Notes: na = not applicable

Table 12. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance (0 to 24 hours) to Predict Extreme Low 

Water Level Events at NOS NWLON Stations in Lake Ontario during 

the Period 15 April to 17 December 2004. Gray shading indicates that the 

statistic did not pass the NOS acceptance criteria. 

Cape Vincent, 

NY 

N=6 

Oswego, NY 

N=5 

Rochester, NY 

N=2 

 Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amp. Time Amp. Time Amp. Time 

Mean Diff. (m) (min) 0.074 -0.667 0.052 0.800 0.066 0.500 

RMSE (m) (min) 0.076 3.873 0.053 3.098 0.067 2.550 

SD (m) (min) 0.021 4.179 0.010 3.347 0.013 3.536 

NOF [2x15cm or 90min] (%) 0.0 33.3 0.0 20.0 0.0 0.0 

CF [15 cm or 90 min] (%) 100.0 16.7 100.0 20.0 100.0 0.0 

POF [2x15 cm or 90 min] (%) 0.0 0.0 0.0 0.0 0.0 0.0 

Cape Vincent, NY

N=11 

Oswego, NY 

N=4 

Statistic, 

Acceptable Error [ ], and 

Units ( ) Amp. Time Amp. Time 

NOS 

Acceptance 

Criteria 

Mean Diff. (m) (min) -0.041 0.545 -0.058 -1.250 na 

RMSE (m) (min) 0.067 3.861 0.068 2.693 na 

SD (m) (min) 0.055 4.009 0.040 2.754 na 

NOF [2x15cm or90min] (%) 0.0 18.2 0.0 25.0 < 1% 

CF [15 cm or 90 min] (%) 90.9 27.3 100.0 25.0 > 90 % 

POF [2x15 cm or 90 min] (%) 0.0 27.3 0.0 0.0 < 1 % 

21 
Table 12 (cont.) 

 

 

 

 

 Notes: na = not applicable 

6.4 Assessment Results of Surface Water Temperature Forecast Guidance 

The standard suite of skill assessment statistics evaluating the ability of semi-operational 

forecast guidance to predict hourly lake surface water temperatures at the NWS/NDBC 

Lake Ontario fixed buoy (45012) from mid-April to early December 2004 is given in 

Appendix D. Tables therein provide skill statistics at the forecast projection hours of 0, 

6, 12, 18, and 24. Time series plots of the forecasts (1st sigma level) from the 0000 UTC 

forecast cycle vs. buoy observations are given in Appendix E. The time series plots 

indicate that the forecast guidance from the 0000 UTC forecast cycle resembles the 

nowcast very closely. This reflects the fact that the lake model configuration (i.e. 

POMGL) used for the semi-operational forecast cycles does not include any input of 

surface heat fluxes either directly or indirectly from the NAM-12 model forecast 

guidance. Specifically, the lake model uses subroutine FLUX5 in which the heat fluxes 

are zero. 

Similar to the nowcasts, the semi-operational forecast guidance is in close agreement to 

observations. The skill statistics assessing the ability of semi-operational forecast 

guidance to predict surface water temperatures 24 hours in advance at the NDBC buoy 

are given in Table 13 along with the NOS acceptance criteria. The hourly forecast 

guidance at the buoy came close to passing all the criteria (failing to meet the CF criteria 

by only 2.4%). The MAE was -0.13o

C and the RMSE was 1.89oC. The MAE and RMSE 

values for the forecast guidance were slightly lower than for the nowcasts. It is 

interesting to note that the mean differences increased and reversed sign as forecast 

projection time increased. The MAE was 0.08o

C at the 0-hr projection and -0.13oC at 24-

hrs (see Table D.1). 

7. SUMMARY 

NOS’ Lake Ontario Operational Forecast System (LOOFS) generates hourly nowcasts 

and forecast guidance out to 30 hours four times per day. It is based on the Great Lakes 

Coastal Forecasting System (GLCFS) developed by the Ohio State University and 

NOAA/GLERL. 

Olcott, NY 

N=2 

 Statistic, 

Acceptable Error [ ], and 

Units ( ) Amplitude Time 

NOS 

Acceptance 

Criteria 

Mean Diff. (m) (min) 0.010 1.500 na 

RMSE (m) (min) 0.010 2.915 na 

SD (m) (min) 0.006 3.536 na 

NOF [2x15cm or 90min] (%) 0.0 0.0 <1% 

CF [15 cm or 90 min] (%) 100.0 50.0 > 90% 

POF [2x15 cm or 90 min] (%) 0.0 50.0 <1% 

22 
Table 13. Summary of Skill Assessment Statistics for Semi-Operational Forecast 

Guidance (0 to 24 hours) to Predict Surface Water Temperatures at a NWS/NDBC 

fixed buoy in Lake Ontario during the period from mid-April to early-November 

2004. Gray shading indicates that the statistic did not pass the NOS acceptance criteria. 

 

Notes: na = not applicable

Time Period, Statistic, 

Acceptable Error [ ], 

and Units ( ) 

45012 

Lake Ontario 

N=420 

NOS 

Acceptance 

Criteria 

Time Period 20 April to 

7 Nov. 2004 

365 days 

Mean Difference (oC) -0.130 na 

RMSE (oC) 1.891 na 

SD (oC) 1.889 na 

NOF [2x3oC] (%) 0.0 < 1% 

CF [3oC] (%) 87.6 > 90% 

POF [2x3oC] (%) 0.0 < 1% 

MDPO [2x3oC] (hours) 0.0 < 24 hrs 

MDNO [2x3oC] (hours) 0.0 < 24 hrs 

LOOFS became operational at CO-OPS on March 30, 2006. The hourly nowcast cycles 

are forced by surface wind stress and surface heat flux estimated from objectively 

analyzed surface meteorological fields and the initial conditions are provided by the 

previous hour’s nowcast. The four times/day forecast cycle uses the most recent 

nowcasts for its initial conditions and gridded NWS forecasts of surface air temperature 

and wind forcing from NWS/National Digital Forecast Database. Prior to April 1, 2007, 

LOOFS used forecast guidance from NCEP’s NAM-12 weather prediction model. 

During the forecast cycle, the heat flux is set to zero. 

An assessment of the LOOFS nowcasts and forecast guidance was conducted according 

to the NOS evaluation standards (Hess et al. 2003). To comply with the NOS required 

semi-operational nowcast and forecast scenarios, the evaluation used archived output 

from NOAA/GLERL’s GLCFS semi-operational nowcasts and forecasts for Lake 

Ontario from 15 April to 17 December 2004. Unfortunately, neither GLERL or OSU 

conducted comparisons between POMGL output vs. field data for Lake Ontario which 

could be used to fulfill the hindcast scenario. 

The semi-operational nowcasts and forecast guidance were compared to water level 

observations at four NOS NWLON stations and surface temperatures at one NWS/NDBC 

23 
fixed buoy 45012 in western part of the lake. Due to the lack of sub-surface water 

temperatures and current observations, no quantitative assessment of these variables was 

conducted for LOOFS. 

Water Levels 

The hourly nowcasts of water level for amplitude met the NOS acceptance criteria at the 

four NOS gauges in Lake Ontario: Cape Vincent, Oswego, Rochester, and Olcott, NY. 

The mean algebraic error or difference (MAE) ranged between -1.1 cm at Rochester, NY 

and +2.6 cm at Cape Vincent, NY located at the extreme eastern end of Lake Ontario at 

the entrance of the St. Lawrence River. The RSME ranged from 2.9 to 4.4 cm at 

Rochester and Cape Vincent. The nowcasts of high water level events were assessed at 

two NOS gauges where high events occurred. The nowcast of high water events passed 

the NOS criteria for amplitude at the two gauges but met the NOS criteria for timing at 

only one gauge. The nowcasts of low water level events were assessed at the four NOS 

gauges. The nowcasts of low water events met the NOS criteria for amplitude at the four 

gauges, but did not pass the criteria in terms of timing at any of the gauges. 

The hourly forecast guidance met the NOS criteria for predicting water level amplitude at 

all four locations. The MAE ranged between -1.0 cm and +2.8 cm at Olcott and Cape 

Vincent, respectively. The RSME ranged from 3.4 to 4.8 cm. The forecast guidance of 

high water events passed the NOS criteria for amplitude at the two gauges where high 

events occurred. The guidance failed to meet NOS criteria in predicting the times of 

these extreme events. The guidance of low water level events was assessed at all four 

NOS gauges. The guidance of low water events passed the NOS criteria for amplitude at 

locations but only met NOS criteria in predicting the times of these extreme events at the 

Rochester gauge. 

Surface Water Temperatures 

The hourly water temperature nowcasts came very close in meeting the NOS criteria at 

the NDBC buoy 45012, only failing to meet the CF by 1.4%. The MAE was 0.003o

C and 

the RMSE was 1.88o

C. The hourly water temperature forecast guidance at 24 hours came 

very close to meeting NOS criteria at the buoy only failing to meet the CF by 2.4%. The 

MAE for the period was -0.13o

C and the RMSE was 1.89oC. The time series plots 

indicated that LOOFS over predicted the SST during the spring months and under 

predicted the SST during August and September. 

Surface Currents

Due to the lack of water current observations, no quantitative assessment could be 

conducted for LOOFS. However, animation of surface current nowcasts and forecast 

guidance indicated that LOOFS did properly simulate the known cyclic clockwise 

rotation of surface currents present in the Great Lakes when the lake water is density 

stratified. This occurs usually from May through October. Observational studies have 

found that the clockwise rotation has a near-inertial period of 18 hours (Saylor and Miller, 

24 
1987). 

8. RECOMMENDATIONS FOR FUTURE WORK 

Recommendation #1: 

The comparisons of the semi-operational nowcasts and forecast guidance of surface water 

temperature to observations at the NDBC Lake Ontario buoy (45012) indicate a potential 

problem with the prediction of surface water temperatures, especially during the spring 

and early summer. A similar problem occurred with LSOFS, LMOFS, and LEOFS. 

Since surface water temperatures comparisons were done only at one buoy it is difficult 

to conclude whether this is an issue over the entire model grid domain. Therefore, it is 

recommended that in the future, LOOFS SST nowcasts and forecast guidance also be 

evaluated at the Canadian fixed buoys: Prince Edward Point (45135) in the western end 

and West Lake Ontario-Grimsby (45139) in the far western end of the lake. 

Recommendation #2: 

A study is needed to determine the reason why POMGL was unable to better forecast the 

timing of water level of extreme high and low water level events and the water level 

amplitudes in the lake. This would likely involve sensitivity tests with POMGL using 

higher grid resolution and incorporating atmospheric pressure forcing. 

This was our first attempt to assess extreme water level events in non-tidal freshwater 

regions. We currently used a so-called two-sigma rule to select extreme high and low 

water level events. Other approaches can be tested to define a high/low water level event 

more reasonably in the future. 

Recommendation #3: 

Investigate in cooperation with GLERL, the possibility of incorporating climatological or 

near-real time river discharge in the nowcoast cycle of LOOFS and surface heat flux 

estimates in the forecast cycle of LOOFS. 

Recommendation #4: 

The LOOFS surface water temperature predictions should also be evaluated at the 

Canadian buoys 45135 and 45139 in Lake Ontario. 

ACKNOWLEDGMENTS 

The development of the Great Lakes Forecasting System was a joint effort of The Ohio 

State University and NOAA’s Great Lakes Environmental Research Laboratory led by 

Dr. Keith Bedford (OSU) and Dr. David Schwab (GLERL). During the eleven-year life 

of the GLFS the following OSU staff members have been associated with the 

development of the system: fifteen graduate students; seven faculty; six postdocs; and 

25 
seven research scientists. Funding came from over 26 different sources ranging from 

small grants from private foundations and companies to several large federal grants. The 

operation and further development of GLCFS at GLERL has involved two research 

scientists and three support scientists. 

The porting of the GLCFS from GLERL to NOS was conducted by the GLOFS System 

Development and Implementation Team consisting of personnel from GLERL, OSU, 

CO-OPS, CSDL, and Aqualinks.com. In particular, we acknowledge the hard work of 

Dr. Mark Vincent, Greg Mott, Zack Bronder, and others at CO-OPS. 

The archived GLCFS nowcast and forecast guidance used in the skill assessment were 

provided by Greg Lang and David Schwab at NOAA/GLERL. The skill assessment 

software was modified for use in the Great Lakes based on suggestions from Drs. Kurt 

Hess and Eugene Wei in CSDL. 

We express our thanks to Drs. Eugene Wei, Richard Schmalz, and Zhizhang Yang in 

CSDL’s MMAP for their helpful comments and suggestions during the internal review 

process to improve this technical memorandum. 

REFERENCES 

Bedford, K.W. and D. J. Schwab, 1991: The Great Lakes Forecasting System- Lake Erie 

nowcasts/forecasts, Proceedings, Marine Technology Society National Meeting, 

New Orleans, LA, Marine Technology Society, 206-264. 

Bedford, K.W., 1992: The physical effects of the Great Lakes on tributaries and wetlands. 

J. Great Lakes Res., 18, 571-589. 

Beletsky, D., J.H. Saylor, and D.J. Schwab, 1999: Mean circulation in the Great Lakes. 

J. Great Lakes Res., 25, 78-93. 

Blumberg, A. F. and G. L. Mellor, 1987: A Description of a Three-Dimensional Coastal 

Ocean Circulation Model, Three-Dimensional Coastal Ocean Models, Vol. 4, Ed. N. 

Heaps, American Geophysical Union, Washington, DC, pp. 1-16. 

Boyce, F. M., M. A. Donelan, P. F. Hamlin, C. R. Murthy, and T. J. Simons, 1989: 

Thermal structure and circulation in the Great Lakes. Atmos.-Ocean, 27, 607-642. 

Dingman, J.S. and K. W. Bedford, 1986: Skill tests and parametric statistics for model 

evaluation. J. Hydraul. Eng., 112, 124-141. 

Gilhousen, D.B., 1987: A field evaluation of NDBC moored buoy winds. J. Atmos. 

Oceanic Technol., 4, 94-104. 

Great Lakes Information Network (GLIN), 2006: Water Levels on the Great Lakes, 

(http://www.great-lakes.net/teach/envt/levels/lev_2.html). 

26 
Hess, K. W., T. F. Gross, R. A. Schmalz, J. G. W. Kelley, F. Aikman, III, E. Wei, and M. 

S. Vincent, 2003: NOS standards for evaluating operational nowcast and forecast 

hydrodynamic model systems, NOAA Technical Report NOS CS 17, 47 pp. 

[Available from NOAA/NOS Coast Survey Development Lab, 1315 E-W Highway, 

Silver Spring, MD 20910.] 

Hoch, B. 1997: An evaluation of a one-way coupled atmosphere-lake model for Lake 

Erie. M.S. thesis, Atmospheric Sciences Program, Ohio State University, 226 ppp. 

[Available from Atmospheric Sciences Program, 1049 Derby Hall, 154 N. Oval 

Mall, Ohio State University, Columbus, OH 43210-1361.] 

Kelley, J.G.W., 1995: One-way coupled atmospheric-lake model forecasts for Lake Erie. 

Ph.D. dissertation, Ohio State University, 450 pp. [Available from Atmospheric 

Sciences Program, 1049 Derby Hall, 154 N. Oval Mall, Ohio State University, 

Columbus, OH 43210-1361.] 

Kelley, J.G.W., M. Westington, E. Wei, S. Maxwell, and A. Thomson, 2001: Description 

of the Operational Data Acquisition and Archive System (ODAAS) to support the 

NOS Chesapeake Bay Operational Forecast System (CBOFS), NOAA Technical 

Report NOS CS 10, 45 pp. [Available from NOAA/NOS Coast Survey 

Development Lab, 1315 E-W Highway, Silver Spring, MD 20910.] 

Kuan, C.-F., 1995: Performance evaluation of the Princeton Circulation Model for Lake 

Erie. Ph.D. Dissertation, Ohio State University, 376 pp. [Available from Dept. of 

Civil and Environmental Engineering and Geodetic Science, 470 Hitchcock Hall, 

2070 Neil Avenue, Ohio State University, Columbus, OH 43210-1275.] 

McCormick, M. J. and G. A. Meadows, 1988: An intercomparison of four mixed layer 

models in a shallow inland sea. J. Geophys. Res., 93, 6774-6788. 

Mellor, G. L., 1996: Users guide for a three-dimensional, primitive equation, numerical 

ocean model. Program in Atmospheric and Oceanic Sciences, Princeton 

University, Princeton, NJ, 39 pp. [Available from Program in Atmospheric and 

Oceanic Sciences, P.O. Box CN710, Sayre Hall, Princeton University, Princeton, 

NJ 08544-0710.] 

O’Connor, W. P. and D. J. Schwab, 1993: Sensitivity of Great Lakes Forecasting System 

nowcasts to meteorological fields and model parameters. Proc. ASCE Third Int. 

Conf. on Estuarine and Coastal Modeling, Oak Brook, IL, Amer. Soc. Civil Eng., 

149-157. 

Sambridge, M., Braun, J., and H. McQueen, 1995: Geophysical parameterization and 

interpolation of irregular data using natural neighbors. Geophys. J. Int., 122, 837-

857. 

Saylor, J. H. and G. S. Miller, 1987: Studies of Large-Scale Currents in Lake Erie, 1979-

80. J. Great Lakes Res., 13, 487-514. 

27 
Schwab, D. J. and K. W. Bedford, 1994: Initial implementation of the Great Lakes 

Forecasting System: A real-time system for predicting lake circulation and thermal 

structure. Water Pollution Res. J. of Canada, 29, 203-220. 

Schwab, D. J., and D. Beletsky, 1998: Lake Michigan Mass Balance Study: 

Hydrodynamic Modeling Project. NOAA Technical Memorandum ERL GLERL108, 53 pp. [Available from NOAA/Great Lakes Environmental Research 

Laboratory, Publications Office, 2205 Commonwealth Blvd., Ann Arbor, MI 

48105-2945.] 

Schwab, D. J. and D. L. Sellers, 1980: Computerized bathymetry and shorelines. NOAA 

Data Rep. ERL GLERL-16, Great Lakes Environmental Research Laboratory, Ann 

Arbor, MI, 13 pp. [Available from NOAA/Great Lakes Environmental Research 

Laboratory, Publications Office, 2205 Commonwealth Blvd., Ann Arbor, MI 

48105-2945.] 

Schwab, D. J., J. R. Bennett, P. C. Liu, M. A. Donelan, 1984: Application of a Simple 

Numerical Wave Prediction Model to Lake Erie, J. Geophys. Res., 89, no. C3, 

3586-3592. 

Schwab, D. J. Personal communication of May 2006. 

Yen, C.C. J., J. G. W. Kelley, and K. W. Bedford, 1994: Daily procedure for GLFS 

nowcasts. Proc. National Conf. on Hydraulic Engineering, Buffalo, NY, Amer. 

Soc. Civil Eng., 202-206. 

Zhang, A.-J., K. W. Hess, E. Wei, and E. Myers, 2006: Implementation of model skill 

assessment software for water level and current in tidal regions. NOAA Technical 

Report NOS CS 24, 61 pp. [Available from NOAA/NOS Coast Survey 

Development Lab, 1315 E-W Highway, Silver Spring, MD 20910.] 

28 
APPENDIX A. Skill Assessment Statistics of Semi-Operational Water Level 

Nowcasts and Forecast Guidance at NOS Gauges in Lake 

Ontario for 2004. 

Table A.1. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Cape Vincent, NY 

Gauge (NOS ID 9052000) for 2004. 

Station: Cape Vincent, Lake Ontario, NY 

Observed data time period from: 5/14/2004 to 12/20/2004 

Data gap is filled using SVD method 

Data are filtered using 3.0 Hour Fourier Filter 

------------------------------------------------------------------------------- 

VARIABLE X N IMAX SM RMSE SD NOF CF POF MDNO MDPO 

CRITERION - - - - - - <1% >90% <1% <N <N 

------------------------------------------------------------------------------- 

SCENARIO: SEMI-OPERATIONAL NOWCAST 

H 5757 74.901 

h 5757 74.875 

H-h 15 cm 24h 5757 0.026 0.044 0.036 0.0 99.9 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 12 -0.046 0.050 0.022 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 6 0.067 0.069 0.021 0.0 100.0 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 12 -1.333 4.472 4.458 33.3 33.3 16.7 0.0 0.0 

TLW-tlw 1.50 hr 25h 6 0.167 1.225 1.329 0.0 83.3 0.0 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 488 0.025 0.045 0.037 0.0 100.0 0.0 0.0 0.0 

H06-h06 15 cm 24h 484 0.028 0.048 0.039 0.0 99.8 0.0 0.0 0.0 

H12-h12 15 cm 24h 484 0.027 0.047 0.038 0.0 100.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 484 0.028 0.048 0.039 0.0 99.8 0.0 0.0 0.0 

H24-h24 15 cm 24h 484 0.028 0.048 0.039 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 11 -0.041 0.067 0.055 0.0 90.9 0.0 

ALW-alw 15 cm 24h 6 0.074 0.076 0.021 0.0 100.0 0.0 

THW-thw 1.50 hr 25h 11 0.545 3.861 4.009 18.2 27.3 27.3 

TLW-tlw 1.50 hr 25h 6 -0.667 3.873 4.179 33.3 16.7 0.0 

Table A.2. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Oswego, NY Gauge 

(NOS ID 9052030) for 2004. 

Station: Oswego, Lake Ontario, NY 

Observed data time period from: 4/15/2004 to 12/20/2004 

Data gap is filled using SVD method 

Data are filtered using 3.0 Hour Fourier Filter 

------------------------------------------------------------------------------- 

VARIABLE X N IMAX SM RMSE SD NOF CF POF MDNO MDPO 

CRITERION - - - - - - <1% >90% <1% <N <N 

------------------------------------------------------------------------------- 

SCENARIO: SEMI-OPERATIONAL NOWCAST 

H 5832 74.896 

h 5832 74.891 

H-h 15 cm 24h 5832 0.005 0.032 0.031 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 2 -0.074 0.074 0.008 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 5 0.052 0.053 0.010 0.0 100.0 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 2 0.500 0.707 0.707 0.0 100.0 0.0 0.0 0.0 

TLW-tlw 1.50 hr 25h 5 0.800 3.098 3.347 20.0 20.0 0.0 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 0.004 0.032 0.032 0.0 100.0 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 0.006 0.033 0.032 0.0 99.8 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 0.004 0.033 0.033 0.0 100.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 0.006 0.035 0.034 0.0 100.0 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 0.005 0.036 0.035 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 4 -0.058 0.068 0.040 0.0 100.0 0.0 

ALW-alw 15 cm 24h 5 0.046 0.046 0.002 0.0 100.0 0.0 

THW-thw 1.50 hr 25h 4 -1.250 2.693 2.754 25.0 25.0 0.0 

TLW-tlw 1.50 hr 25h 5 -0.800 1.414 1.304 0.0 60.0 0.0 

29 
Table A.3. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Rochester, NY Gauge 

(NOS ID 9052058) for 2004. 

Station: Rochester, Lake Ontario, NY 

Observed data time period from: 4/15/2004 to 12/20/2004 

Data gap is filled using SVD method 

Data are filtered using 3.0 Hour Fourier Filter 

------------------------------------------------------------------------------- 

VARIABLE X N IMAX SM RMSE SD NOF CF POF MDNO MDPO 

CRITERION - - - - - - <1% >90% <1% <N <N 

------------------------------------------------------------------------------- 

SCENARIO: SEMI-OPERATIONAL NOWCAST 

H 5832 74.894 

h 5832 74.894 

H-h 15 cm 24h 5832 0.000 0.029 0.029 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 2 0.067 0.067 0.010 0.0 100.0 0.0 0.0 0.0 

TLW-tlw 1.50 hr 25h 2 1.000 3.162 4.243 0.0 0.0 50.0 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 0.000 0.029 0.029 0.0 100.0 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 -0.001 0.030 0.030 0.0 100.0 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 0.000 0.032 0.032 0.0 100.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 -0.001 0.032 0.032 0.0 100.0 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 0.001 0.034 0.034 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 2 0.066 0.067 0.013 0.0 100.0 0.0 

TLW-tlw 1.50 hr 25h 2 0.500 2.550 3.536 0.0 0.0 0.0 

Table A.4. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Olcott, NY Gauge 

(NOS ID 9052076) for 2004. 

Station: Olcott, Lake Ontario, NY 

Observed data time period from: 4/15/2004 to 12/20/2004 

Data gap is filled using SVD method 

Data are filtered using 3.0 Hour Fourier Filter 

------------------------------------------------------------------------------- 

VARIABLE X N IMAX SM RMSE SD NOF CF POF MDNO MDPO 

CRITERION - - - - - - <1% >90% <1% <N <N 

------------------------------------------------------------------------------- 

SCENARIO: SEMI-OPERATIONAL NOWCAST 

H 5832 74.892 

h 5832 74.903 

H-h 15 cm 24h 5832 -0.011 0.033 0.031 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 2 0.001 0.015 0.021 0.0 100.0 0.0 0.0 0.0 

TLW-tlw 1.50 hr 25h 2 -3.500 4.301 3.536 50.0 50.0 0.0 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 -0.010 0.032 0.031 0.0 100.0 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 -0.012 0.034 0.032 0.0 100.0 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 -0.010 0.034 0.033 0.0 100.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 -0.011 0.036 0.034 0.0 100.0 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 -0.010 0.037 0.035 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 2 0.010 0.010 0.006 0.0 100.0 0.0 

TLW-tlw 1.50 hr 25h 2 1.500 2.915 3.536 0.0 50.0 50.0 

30 
APPENDIX B. Time Series Plots of Semi-Operational Water Level Nowcasts 

vs. Observations at NOS Gauges in Lake Ontario during 2004. 

100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Cape Vincent

Fig. B.1. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at NOS Cape 

Vincent, NY Gauge during 2004. 

31 
100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Oswego

Fig. B.2. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at NOS Oswego, 

NY Gauge during 2004. 

32 
100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Rochester

Fig. B.3. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at NOS 

Rochester, NY Gauge during 2004. 

33 
100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Olcott

Fig. B.4. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at NOS Olcott, 

NY Gauge during 2004. 

34 
APPENDIX C. Time Series Plots of Semi-Operational Water Level Forecast 

Guidance vs. Observations at NOS Gauges in Lake Ontario 

during 2004. 

100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Cape Vincent

Fig. C.1. Time Series Plot of Semi-Operational Water Level Forecast Guidance vs. Observations at NOS 

Cape Vincent, NY Gauge during 2004. 

35 
100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Oswego

Fig. C.2. Time Series Plot of Semi-Operational Water Level Forecast Guidance vs. Observations at NOS 

Oswego, NY Gauge during 2004. 

36 
100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Rochester

Fig. C.3. Time Series Plot of Semi-Operational Water Level Forecast Guidance vs. Observations at NOS 

Rochester, NY Gauge during 2004. 

37 
100 150 200 250 300 350

Julian Day (2004)

75.575.074.574.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Olcott

Fig. C.4. Time Series Plot of Semi-Operational Water Level Forecast Guidance vs. Observations at NOS 

Olcott, NY Gauge during 2004. 

38 
APPENDIX D. Skill Assessment Statistics of Semi-Operational Surface 

Water Temperature Nowcasts and Forecast Guidance at the 

NWS/NDBC Fixed Buoy in Lake Ontario for 2004. 

Table D.1. Skill Assessment Statistics of Semi-Operational Nowcasts and Forecast Guidance of Surface 

Water Temperatures at the NWS/NDBC Fixed Buoy 45012 (Lake Ontario) for the Period 20 

April to 17 November 2004. 

Station: NDBC Buoy 45012 in Lake Ontario 

Observed data time period from: 4/20/2004 to 11/17/2004 

Data gap is filled using SVD method 

Data are filtered using 3.0 Hour Fourier Filter 

------------------------------------------------------------------------------- 

VARIABLE X N IMAX SM RMSE SD NOF CF POF MDNO MDPO 

CRITERION - - - - - - <1% >90% <1% <N <N 

------------------------------------------------------------------------------- 

 SCENARIO: SEMI-OPERATIONAL NOWCAST 

T 5078 13.607 

t 5078 13.604 

T-t 3.0 c 24h 5078 0.003 1.880 1.880 0.0 88.6 0.1 0.0 2.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

T00-t00 3.0 c 24h 424 0.082 1.885 1.886 0.0 88.7 0.0 0.0 0.0 

T06-t06 3.0 c 24h 419 -0.080 1.929 1.930 0.0 86.9 0.0 0.0 0.0 

T12-t12 3.0 c 24h 420 -0.036 1.929 1.931 0.0 87.6 0.2 0.0 0.0 

T18-t18 3.0 c 24h 419 -0.169 1.903 1.898 0.0 87.6 0.0 0.0 0.0 

T24-t24 3.0 c 24h 420 -0.130 1.891 1.889 0.0 87.6 0.0 0.0 0.0 

39 
APPENDIX E. Time Series Plots of Semi-Operational Nowcasts and 

Forecast Guidance of Surface Water Temperature vs. 

Observations at the NWS/NDBC fixed buoy in Lake Ontario 

during 2004. 

100 150 200 250 300 350

Julian Day (2004)

5.00.0

25.020.015.010.0

Temperature (Degrees)

observationnowcastforecast

NDBC 45012

Figure E.1. Time Series of Semi-Operational Nowcasts and Forecast Guidance of Surface Water 

Temperature (o

C) vs. Observations at the NWS/NDBC Fixed Buoy 45012 (Lake Ontario) for 

the Period 20 April to 17 November 2004. The forecast values depicted on the plots are from 

the 0000 UTC forecast cycle.

40