NOAA Technical Memorandum NOS CS 9

SKILL ASSESSMENT OF NOS LAKE 

SUPERIOR OPERATIONAL FORECAST 

SYSTEM (LSOFS) 

Silver Spring, Maryland 

June 2007 

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. 

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NOAA Technical Memorandum NOS CS 9 

SKILL ASSESSMENT OF NOS LAKE SUPERIOR 

OPERATIONAL FORECAST SYSTEM (LSOFS) 

John G. W. Kelley 

Philip Chu 

Ai-Jun Zhang 

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 

June 2007

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 Development Laboratory 

 Captain Steven R. Barnum, NOAA Mary Erickson 

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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.

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TABLE OF CONTENT

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

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

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

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

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

2. LAKE SUPERIOR.......................................................................................................... 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........................................................................................................... 5 

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

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

5. SEMI-OPERATIONAL NOWCAST SKILL ASSESSMENT...................................... 6 

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

5.2 Method of Evaluation ............................................................................................... 7 

5.3 Assessment of Water Level Nowcasts.................................................................... 15 

5.4 Assessment of Surface Water Temperature Nowcasts ........................................... 18 

6. SEMI-OPERATIONAL FORECAST SKILL ASSESSMENT .................................. 19 

6.1 Description of Forecast Cycles............................................................................... 20 

6.2 Method of Evaluation ............................................................................................. 20 

6.3 Assessment of Water Level Forecast Guidance...................................................... 20 

6.4 Assessment of Surface Water Temperature Forecast Guidance ............................. 24 

7. SUMMARY.................................................................................................................. 25 

8. RECOMMENDATIONS FOR FUTURE WORK ....................................................... 27 

ACKNOWLEDGMENTS ................................................................................................ 28 

REFERENCES ................................................................................................................. 29 

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

and Forecast Guidance at five NOS Gauges in Lake Superior for 2004. ......................... 31 

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

Observations at five NOS Gauges in Lake Superior during 2004.................................... 34 

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

vs. Observations at five NOS Gauges in Lake Superior during 2004. ............................. 39 

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

Temperature Nowcasts and Forecast Guidance at three NWS/NDBC Fixed Buoys in 

Lake Superior for 2004. .................................................................................................... 44 

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

of Surface Water Temperature vs. Observations at two NWS/NDBC fixed buoys in Lake 

Superior during 2004. ....................................................................................................... 46 

LIST OF FIGURES 

Figure 1. Map depicting the POMGL grid domain (10km spatial resolution) used by 

NOS’ Lake Superior Operational Forecast System............................................ 4 

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

........................................................................................................................................... 13 

Figure 3. Map depicting locations of NWS/NDBC fixed buoys in Lake Superior. ........ 14 

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). ....................... 8 

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 LSOFS semi-operational nowcasts and forecasts of water 

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

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

to evaluate LSOFS 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 five NOS NWLON Stations for the Period 15 April to 

17 December 2004. A total of 5832 nowcasts were used in the assessment. 

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

criteria. ............................................................................................................... 15 

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 

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stations in Lake Superior during the Period 15 April to 17 December 2004. 

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

criteria. ............................................................................................................... 16 

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 Superior for the Period 15 April to 17 December 2004. Gray 

shading indicates that the statistic did not pass the NOS acceptance criteria. . 17 

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

Hourly Surface Water Temperatures at three NWS/NDBC fixed buoys in Lake 

Superior for the Period from mid-April to early November 2004. Gray shading 

indicates that the statistic did not pass the NOS acceptance criteria................ 19 

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

Guidance of Hourly Water Levels at NOS NWLON Stations in Lake Superior 

for the Period 15 April to 17 December 2004. A total of 490 forecasts were 

used in the assessment. Gray shading indicates that the statistic did not pass 

the NOS acceptance criteria. ............................................................................ 21 

Table 11. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance to Predict Extreme High Water Level Events at 

NOS NWLON Stations in Lake Superior during the Period 15 April to 17 

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

acceptance criteria. ........................................................................................... 22 

Table 12. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance to Predict Extreme Low Water Level Events at 

NOS NWLON Stations in Lake Superior during the Period 15 April to 17 

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

acceptance criteria. ........................................................................................... 23 

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

Guidance to Predict Surface Water Temperatures 24 hours in advance at 

NWS/NDBC fixed buoys during the period from mid-April to earlyNovember 2004. Gray shading indicates that the statistic did not pass the NOS 

acceptance criteria. ........................................................................................... 25 

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LIST OF ACRONYMS

ASOS Automated Surface Observing System 

AVHRR Advanced 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 

LEOFS Lake Erie Operational Forecast System 

LSOFS Lake Superior Operational Forecast System 

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 Superior Operational Forecast System (LSOFS) 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 Superior. 

LSOFS 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. 

The model system skill assessment of LSOFS 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 MAEe 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 Superior as was 

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

was done for LSOFS. 

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 

Superior 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 Superior. 

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). 

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

below: 

Water levels at five NOS water level gauges: 

 

 Nowcasts: 

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

gauges. The mean algebraic difference (MAE) ranged between -2.9 cm at Duluth, MN 

and +2.4 cm at Port Iroquois, MI located at the extreme western and eastern ends of 

Lake Superior. The nowcast predictions of high and low water level events passed the 

NOS criteria for amplitude at three of five gauges and four of five gauges, respectively. 

In terms of timing, the nowcasts did not meet NOS criteria. 

Forecast Guidance: 

 

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

at all five locations. The MAE ranged between -2.9 cm at Duluth and +2.6 cm at Port 

Iroquois. The forecast guidance of high and low water level events passed the NOS 

criteria for amplitude at thee and four of the five gauges, respectively. Similar to the 

nowcasts, the most difficult forecast locations were at Duluth and Port Iroquois where 

the MAE ranged from -12.3 cm to +11.6 cm. The forecast guidance failed to meet 

NOS criteria in predicting the times of extreme events. 

Surface Water Temperatures at three NWS fixed buoys: 

Nowcasts: 

The hourly surface water temperature nowcasts did not meet the proposed NOS 

acceptance criteria at all three buoys. The MAE ranged from 1.1 to 2.1o

C. 

 Forecast Guidance: 

The hourly surface water temperature forecast guidance came very close to meeting the 

proposed NOS acceptance criteria at the buoys. The MAE ranged between 1.0 and 

2.0o

C. The MAE and the RSME decreased slightly as forecast projection increased. 

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

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

Ocean Model, North American Mesoscale weather prediction model

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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 MAEe 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 MAEe 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 Superior since August 2002. GLCFS for 

Lake Superior 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 MAEe 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 Superior was renamed as the Lake Superior 

Operational Forecast System (LSOFS). LSOFS began making routine experimental lake 

nowcasts and forecasts for Lake Superior on March 30, 2006 at CO-OPS during the icefree season. 

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

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

LSOFS, 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 Superior 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 

LSOFS. 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 Superior and an 

overview of LSOFS are given first. 

2. LAKE SUPERIOR 

Lake Superior is the largest of the Great Lakes and the second largest lake in the world 

with a breadth of 257 km (160 mi) and a length of 563 km (350 mi). It has an average 

depth of 149 m (489 ft) with a maximum of 406 m (1,333 ft). Lake Superior, similar to 

other Great Lakes, has a pronounced annual thermal cycle ranging from vertically wellmixed water body in late autumn to thermal stratification across the entire lake with a 

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

Lake Superior 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. The lowest 

levels occur during winter when evaporation is the greatest and more water is leaving the 

lake than entering it. During the spring the water level begins to rise as runoff from 

melting snow increases, and evaporation decreases, as the air above the lake becomes 

warm and moist, and the lake is relatively cold. The highest levels occur in early to midautumn, just before the amount of water leaving the lake due to outflows and increased 

evaporation exceeds the amount of water entering the lake. Long term water level 

changes occur over consecutive years with wet and cold years causing water levels to 

rise, and warm and dry years resulting in levels decline (GLIN 2006). 

3. SYSTEM OVERVIEW 

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

LSOFS. 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 LSOFS 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-YaMAEa 

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 

(Schwab and Bedford 1994, 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 

Superior, 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 Superior consists of a rectangular grid with a 10-km 

horizontal resolution in both the x- and y-directions. The domain has a total of 1830 grid 

points with 61 points in the x-direction and 30 points in the y-direction (Fig. 1). Of the 

1830 points, there are 807 water cells. 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
meteorological data format, but are decoded and written out to a text file for use by 

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

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

Figure 1. Map depicting the POMGL grid domain (10km spatial resolution) used 

by NOS’ Lake Superior Operational Forecast System. 

4
The text file includes surface observations from a variety of observing networks on and 

around Lake Superior. 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 any of the individual nowcast/forecast systems for the Great Lakes. 

3.4 Nowcast Cycle 

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

3-D state of Lake Superior, 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 analyses of u- and v-wind 

components, and total heat flux valid at two times: one hour prior to the time of the 

nowcast and the current hour of the nowcast. The heat flux analyses are generated by the 

scheme of McCormick and Meadows (1988) which uses adjusted surface meteorological 

observations as well as the previous day’s lake surface average water temperature from 

GLERL’s Great Lakes Surface Environmental Analysis (GLSEA). The GLSEA 

temperature analysis is generated using sea surface temperature (SST) retrievals derived 

from the Advanced High Resolution Radiometer data obtained from NOAA’s polarorbiter satellites. 

3.5 Forecast Cycle 

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

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

initial conditions. The surface meteorological forcing is 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. Presently, 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. The forecast cycle does not use surface pressure guidance from 

NAM in forcing POMGL. 

5
The NAM model forecast guidance is obtained from ODAAS which acquires the NAM 

output from NCEP’s CCS in GRIB format four times per day at 3 hour increments out to 

60 hours. ODAAS decodes the GRIB files and then encodes the output into netCDF files 

following NOS COMF standards. 

3.6 Operational Environment and Scheduling 

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

MD. Each hourly nowcast cycle is launched at 67 minutes past the top of the hour, 12 

minutes past the time the surface meteorological observations are received and processed 

by ODAAS at CO-OPS. 

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

UTC at 67 minutes past the top of these hours. The forecast horizon of each forecast 

cycle is 30 hours. 

LSOFS and the operational forecast systems for Lake Huron and Lake Ontario 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. 

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. (2003), 

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.” 

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

Forecast System (GLCFS) for Lake Superior. Both LSOFS and GLCFS-Lake Superior 

have a spatial grid increment of 10 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 (MAREPS) unlike LSOFS which does not. 

However, this difference was not expected to cause a significant difference in the 

6
nowcasts. 

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

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 Superior, and the other four 

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

each spring. The surface forcing for the nowcast cycles are provided by objective 

analyses 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. Hourly 

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

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 on the 

lake. 

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 LSOFS are presented in Table 3. 

7
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. 

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, ahw 

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) 

8
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 five NOS NWLON stations along the Lake Superior 

shore line (Table 4). A map depicting the locations of the five 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 LSOFS nowcasts on the Web. The final nowcast water levels were then 

compared with the observational data. 

The evaluation of GLCFS water level nowcasts for Lake Superior 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. 

9
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. 

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 three 3-m 

fixed disk buoys in the lake. The buoys are operated by NOAA/National Data Buoy 

Center (NDBC). Information on the buoys 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 points to surface observations from the buoys. A map depicting the locations 

of the NDBC fixed buoys is given in Fig. 3. 

The evaluation of GLCFS surface water temperature nowcasts for Lake Superior 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 MAEe 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. 

10
In evaluating predicted water temperature in tidal regions, NOS sets an acceptable error 

of 7.7o

C 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 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. 

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

were used to evaluate LSOFS 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 

Point 

Iroquois 

MI 9099004 PTIM4 46.49 84.63 59 2 

Marquette 

CG Station 

MI 9099018 MCGM4 46.55 87.30 38 2 

Ontonagon MI 9099044 NS 46.88 89.30 23 7 

Grand 

Marais 

MN 9099090 GDMM5 47.75 90.30 16 16 

Duluth MN 9099064 DULM5 46.78 92.00 3 6 

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

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

used to evaluate LSOFS semi-operational nowcasts and forecasts of surface 

water temperatures. 

Geographic 

Coordinates 

Corresponding 

LSOFS 

Grid Point 

Coordinates 

Buoy ID and 

Name 

Agency Prov. 

or 

State 

WMO 

Buoy 

ID 

Latitude 

(deg N) 

Longitude 

(deg W) 

I J 

45001 – 

Mid Superior 

NWS/ 

NDBC 

MI 45001 48.07 87.78 35 19 

45004 – 

East Superior 

NWS/ 

NDBC 

MI 45004 47.57 86.55 44 14 

45006 – 

West Superior 

NWS/ 

NDBC 

MI 45006 47.35 89.83 19 11 

12
 

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

Superior. 

13
Figure 3. Map depicting locations of NWS/NDBC fixed buoys in Lake Superior. 

14
5.3 Assessment 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 five 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 five NOS gauges are presented together in Table 6 along with the NOS acceptance 

criteria. The hourly nowcasts passed the criteria at all five locations. The mean algebraic 

differences ranged between + 3 cm and the RMSE ranged between 2.5 and 6.2 cm. The 

greatest errors were at Duluth and Port Iroquois gauges located at the extreme western 

and eastern ends of the lake, respectively (Fig. 2), which experience the greatest hourly 

water level variability. The nowcasts under-predicted the water levels at Duluth and overpredicted the levels at Port Iroquois. 

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

Hourly Water Levels at five NOS NWLON Stations for the Period 15 April 

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

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

criteria. 

Statistic, 

Acceptable Error [ 

], and 

Units ( ) 

Grand 

Marais, 

MN 

Duluth, 

MN 

Ontonagon, 

 MI 

Marquette, 

MI 

Port 

Iroquois, 

MI 

NOS 

Accept. 

Criteria 

Mean Diff. (m) -0.012 -0.029 -0.002 -0.000 0.024 na 

RMSE (m) 0.035 0.062 0.031 0.025 0.061 na 

SD (m) 0.033 0.055 0.031 0.025 0.056 na 

NOF [2x15cm] 

(%) 

0.0 0.0 0.0 0.0 0.0 < 1% 

CF [15 cm] (%) 100.0 98.2 99.8 100.0 98.1 > 90% 

POF [2x15 cm] 

(%) 

0.0 0.0 0.0 0.0 0.0 < 1% 

MDPO [2x15 cm ] 

(hour) 

0.0 0.0 0.0 0.0 0.0 < 24 

hours 

MDNO [2x15 cm ] 

(hour) 

0.0 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 the five NOS gauges during 2004 are given together in Table 7. The high water 

level nowcasts passed the NOS acceptance criteria for amplitude at Grand Marais, 

Ontonagon, and Marquette, but not at Duluth and Port Iroquois. The nowcasts ability to 

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

and POF at any of the five gauges. 

15
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 Superior during the Period 15 April to 17 

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

acceptance criteria. 

Grand Marais, 

MN 

N=12 

Duluth, 

MN 

N=27 

Ontonagon, 

MI 

N=11 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amp. Time Amp. Time Amp. Time 

Mean Diff. (m) (min) -0.081 -1.000 -0.123 -0.636 -0.085 -0.077 

RMSE (m) (min) 0.087 3.440 0.136 6.695 0.094 5.211 

SD (m) (min) 0.033 3.438 0.058 6.990 0.043 5.314 

NOF [2x15cm or 90min] % 0.0 25.0 0.0 27.3 0.0 19.2 

CF [15 cm or 90 min] (%) 100.0 16.7 57.7 27.3 90.9 30.8 

POF [2x15 cm or 90 min] 

(%) 

0.0 8.3 0.0 18.2 0.0 23.1 

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 

Marquette, 

MI 

N=9 

Port Iroquois, 

 MI 

N=36 

NOS 

Accept. 

Criteria 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amplitude Time Amplitude Time 

Mean Diff. (m) (min) -0.071 1.778 -0.083 -0.306 na 

RMSE (m) (min) 0.074 5.011 0.097 4.450 na 

SD (m) (min) 0.023 4.969 0.050 4.503 na 

NOF [2x15cm] (90min) % 0.0 11.1 0.0 22.2 < 1% 

CF [15 cm or 90 min] (%) 100.0 22.2 83.3 27.8 > 90% 

POF [2x15 cm or 90 min] 

(%) 

0.0 44.4 0.0 19.4 < 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 

The skill statistics to predict extreme low water level events at the five NOS gauges 

during 2004 are given together in Table 8. The extreme low water level nowcasts passed 

NOS acceptance criteria for amplitude at Grand Marais, Ontonagon, Duluth, and 

Marquette, but not at Port Iroquois where the CF was 81%. The nowcasts ability to 

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

and POF at any of the five gauges. 

Table 8. Summary of Standard Statistics Evaluating the Ability of Semi16
Operational Nowcasts to Simulate Extreme Low Water Level Events at the 

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

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

acceptance criteria. 

Grand Marais, 

MN 

N=23 

Duluth, 

 MN 

N=48 

Ontonagon, 

 MI 

N=15 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amp. Time Amp. Time Amp. Time 

Mean Diff. (m) (min) 0.061 0.087 0.060 -0.479 0.066 -0.267 

RMSE (m) (min) 0.066 3.683 0.068 2.955 0.069 3.204 

SD (m) (min) 0.025 3.765 0.033 2.946 0.018 3.305 

NOF [2x15cm or 90min] 

(%) 

0.0 21.7 0.0 18.8 0.0 20.0 

CF [15 cm or 90 min] (%) 100.0 26.1 100.0 47.9 100.0 46.7 

POF [2x15 cm or 90 min] 

(%) 

0.0 21.7 0.0 6.3 0.0 13.3 

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 

Marquette, 

MI 

N=15 

Port Iroquois, 

 MI 

N=36 

NOS 

Accept. 

Criteria 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amplitude Time Amplitude Time 

Mean Diff. (m) (min) 0.065 0.800 0.121 -0.500 na 

RMSE (m) (min) 0.067 3.366 0.126 3.734 na 

SD (m) (min) 0.013 3.385 0.033 3.753 na 

NOF [2x15cm or 90min] 

(%) 

0.0 13.3 0.0 25.0 < 1% 

CF [15 cm or 90 min] (%) 100.0 33.3 80.6 13.9 > 90% 

POF [2x15 cm or 90 min] 

(%) 

0.0 26.7 0.0 25.0 < 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 

5.4 Assessment of Surface Water Temperature Nowcasts 

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

nowcasts to predict hourly lake surface water temperatures at three NWS/NDBC fixed 

buoys from mid-April to early December 2004 are given in Appendix D. Time series 

plots of the nowcasts (1st sigma level) vs. observations at the buoys are given in 

Appendix E. 

17
The time series plots indicate that the nowcasts were in close agreement to observations 

(+0.5-1oC) from mid-April until mid- to late-June 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 4o

C (Boyce et al. 1989). 

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

maximum density for fresh water, the nowcasts began to deviate from the observations by 

+2-4oC until mid-July at the eastern buoy and until mid- to late-August at the mid-and 

western-buoys located in deeper water (+260 m). August is the usual time when the 

complete thermal stratification of Lake Superior occurs (Boyce et al. 1989). 

From mid-July or mid- to late-August until early October, the nowcasts differed from 

observations by +1-2oC and then the difference generally declined to +1oC or less by the 

end of the evaluation period. 

The skill statistics to predict hourly surface water temperatures at the three NDBC buoys 

are given together in Table 9 along with the NOS acceptance criteria. The hourly water 

temperature nowcasts at the three buoys did not pass the NOS criteria for assessment 

statistics of CF, POF, and MDNO. The hourly nowcasts at the Mid Superior buoy came 

close to passing the criteria, failing primarily in regards to CF by only 5%. The mean 

algebraic differences for the period ranged between 1.3 – 2.1oC and the RMSE ranged 

between 1.9 – 2.7oC at the three buoys. 

18
Table 9. Summary of Skill Assessment Statistics of the Semi-Operational Nowcasts

of Hourly Surface Water Temperatures at three NWS/NDBC fixed buoys 

in Lake Superior 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 ( ) 

45006 

West 

Superior 

N=4811 

45001 

Mid Superior 

N=4831 

45004 

East Superior 

N=4814 

NOS 

Acceptance 

Criteria 

Time Period 23 April to 

11 Nov. 2004 

21 April to 

11 Nov. 2004 

23 April to 

 9 Nov. 2004 

365 days 

Mean Difference (oC) 1.10 1.27 2.13 na 

RMSE (oC) 2.07 1.98 2.70 na 

SD (oC) 1.75 1.54 1.65 na 

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

CF [3oC] (%) 84.9 84.9 75.9 > 90% 

POF [2x3oC] (%) 0.2 1.1 4.2 < 1% 

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

MDNO [2x3oC] (hours) 8.0 15.0 36.0 < 24 hrs 

Notes: na = not applicable 

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 Hess et al. (2003), 

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.” (Similar to the nowcast scenario, the 

data streams for the Great Lakes could include wind stresses, surface heat flux, and river 

flows.) 

For the assessment of the semi-operational forecast scenario for LSOFS, 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. 

19
6.1 Description of Forecast Cycles 

GLCFS performs twice/day 60-hr forecast cycles for Lake Superior. 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 valid time of the nowcasts 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 NWS/NDBC fixed buoys from mid-April 

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 5 

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 three NWS/NDBC fixed buoys 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 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 five NOS Gauges from 15 

April to 17 December 2004 are 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 five NOS gauges are presented together in Table 10 along with the NOS 

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

mean algebraic differences ranged between -2.9 to + 2.6 cm and the RMSE ranged 

between 2.5 and 6.2 cm, very similar to the statistics for the nowcast evaluation. Similar 

20
to the nowcasts, the greatest errors were at Duluth and Port Iroquois Gauges located at 

the extreme western and eastern ends of the lake, respectively. The forecasts underpredicted the water levels at Duluth and over-predicted the levels at Port Iroquois. There 

was no significant increase in the mean differences, RMSE values, or CF as forecast 

projection increased (Appendix A). 

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

Guidance of Hourly Water Levels at NOS NWLON Stations in Lake 

Superior for the Period 15 April to 17 December 2004. A total of 490 

forecasts were used in the assessment. Gray shading indicates that the statistic 

did not pass the NOS acceptance criteria. 

Statistic, Acceptable 

Error [ ], and 

Units ( ) 

Grand 

Marais, 

MN 

Duluth 

 MN 

Onton

agon 

MI 

Marquette

MI 

Port 

Iroquois

MI 

NOS 

Accept. 

Criteria

Mean Diff. (m) -0.005 -0.029 0.002 -0.001 0.026 na 

RMSE (m) 0.037 0.062 0.033 0.025 0.059 na 

SD (m) 0.037 0.055 0.033 0.025 0.053 na 

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

CF [15 cm] (%) 100.0 98.2 99.8 100.0 99.4 > 90% 

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

MDPO [2x15 cm ] 

(hour) 

0.0 0.0 0.0 0.0 0.0 < 24 

hours 

MDNO [2x15 cm ] 

(hour) 

0.0 0.0 0.0 0.0 0.0 < 24 

hours 

Notes: na = not applicable 

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

water level events at the five NOS gauges during 2004 are given together in Table 11. 

The forecasts of extreme high water level passed NOS acceptance criteria for amplitude 

at Grand Marais, Ontonagon, and Marquette, but not at Duluth and Port Iroquois where 

the CF was 67% and 89%, respectively. The forecasts’ ability to simulate the timing of 

these events did not pass NOS acceptance criteria for NOF, CF, and POF at any of the 

five gauges.

21
Table 11. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance to Predict Extreme High Water Level 

Events at NOS NWLON Stations in Lake Superior during the Period 15 

April to 17 December 2004. Gray shading indicates that the statistic did not 

pass the NOS acceptance criteria. 

Grand Marais, 

MN 

N=13 

Duluth, MN 

N=27 

Ontonagon, MI 

N=11 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amp. Time Amp. Time Amp. Time 

Mean Diff. (m) (min) -0.088 -0.308 -0.123 -0.407 -0.087 0.273 

RMSE (m) (min) 0.092 6.239 0.135 5.168 0.095 5.402 

SD (m) (min) 0.028 6.486 0.058 5.250 0.042 5.658 

NOF [2x15cm or90min] 

(%) 

0.0 30.8 0.0 25.9 0.0 18.2 

CF [15 cm or 90 min] (%) 100.0 38.5 66.7 25.9 90.9 27.3 

POF [2x15 cm or 90 min] 

(%) 

0.0 23.1 0.0 22.2 0.0 18.2 

Marquette 

 MI 

N=9 

Port Iroquois 

MI 

N=36 

Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amplitude Time Amplitude Time 

NOS 

Acceptance 

Criteria 

Mean Diff. (m) (min) -0.050 1.889 -0.066 -0.833 na 

RMSE (m) (min) 0.053 4.333 0.084 5.344 na 

SD (m) (min) 0.020 4.137 0.053 5.353 na 

NOF [2x15cm or 90min] (%) 0.0 11.1 0.0 27.8 < 1% 

CF [15 cm or 90 min] (%) 100.0 44.4 88.9 22.2 > 90 % 

POF [2x15 cm or 90 min] 

(%) 

0.0 22.2 0.0 25.0 < 1 % 

Notes: na = not applicable 

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

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

forecasts of extreme low water level passed NOS acceptance criteria for amplitude at 

Grand Marais, Ontonagon, Duluth, and Marquette, but not at Port Iroquosis where the CF 

was 84%. The forecasts ability to simulate the timing of these events did not pass NOS 

acceptance criteria for NOF, CF, and POF at any of the five gauges.

22
Table 12. Summary of Skill Assessment Statistics Evaluating the Ability of SemiOperational Forecast Guidance to Predict Extreme Low Water Level 

Events at NOS NWLON Stations in Lake Superior during the Period 15 

April to 17 December 2004. Gray shading indicates that the statistic did not 

pass the NOS acceptance criteria. 

Grand Marais, 

MN 

N=24 

Duluth 

 MN 

N=46 

Ontonagon 

 MI 

N=14 

 Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amp. Time Amp. Time Amp. Time 

Mean Diff. (m) (min) 0.072 -0.292 0.061 -0.304 0.064 0.429 

RMSE (m) (min) 0.075 3.857 0.071 2.670 0.066 2.449 

SD (m) (min) 0.021 3.928 0.036 2.682 0.014 2.503 

NOF [2x15cm or 90min] 

(%) 

0.0 20.8 0.0 15.2 0.0 7.1 

CF [15 cm or 90 min] (%) 100.0 25.0 100.0 43.5 100.0 42.9 

POF [2x15 cm or 90 min] 

(%) 

0.0 25.0 0.0 6.5 0.0 7.1 

Marquette 

MI 

N=15 

Port Iroquois 

 MI 

N=38 

 Statistic, 

Acceptable Error [ ], and 

Units ( ) 

Amplitude Time Amplitude Time 

NOS 

Acceptance 

Criteria 

Mean Diff. (m) (min) 0.060 -0.067 0.116 -0.684 na 

RMSE (m) (min) 0.062 3.642 0.120 3.479 na 

SD (m) (min) 0.016 3.770 0.032 3.457 na 

NOF [2x15cm or 90min] (%) 0.0 26.7 0.0 21.1 <1% 

CF [15 cm or 90 min] (%) 100.0 20.0 84.2 15.8 > 90% 

POF [2x15 cm or 90 min] 

(%) 

0.0 20.0 0.0 18.4 <1% 

Notes: na = not applicable 

23
6.4 Assessment 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 three NWS/NDBC 

fixed buoys from mid-April to early December 2004 are given in Appendix D. Tables 

therein provide skill statistics at the forecast projections 0, 6, 12, 18, and 24 hours. 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 semioperational 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 are in close agreement to 

observations (+0.5oC) from mid- April until early/mid June, but then begin to deviate 

from the observations by 3-4oC until mid- to late-August. After that the forecasts differ 

from observations by +1-2o

C until early October and then generally decline to +1oC or 

less by the end of the period. The skill statistics assessing the ability of semi-operational 

forecast guidance to predict surface water temperatures 24 hours in advance at the three 

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

forecast guidance at the Mid Superior buoy came close to passing all the criteria (failing 

to meet the CF criteria by only 2%). The forecast guidance at the East Superior buoy 

failed the CF criteria by approximately 10% and the POF by only 0.3%. The mean 

algebraic differences ranged between 1.2 and 2.0oC and the RMSE ranged between 1.9 

and 2.5oC at the three buoys. The mean differences and RMSEs for the forecast guidance 

were slightly lower than for the nowcasts. 

It is interesting to note that the mean differences, RMSE, and the CF and POF values 

decreased as forecast projection increased in time. For example, at the East Superior 

buoy, the RMSE was 2.7o

C at the 0-hr projection and 2.5oC at 24-hrs (see Table D.3). 

This suggests that the surface heat flux is being overestimated during the nowcast cycle. 

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

24
Guidance to Predict Surface Water Temperatures 24 hours in advance at 

NWS/NDBC fixed buoys during the period from mid-April to earlyNovember 2004. Gray shading indicates that the statistic did not pass the 

NOS acceptance criteria. 

 Time Period, Statistic, 

Acceptable Error [ ], and 

Units ( ) 

45006 

West Superior

N=397 

45001 

Mid Superior 

N=399 

45004 

East Superior 

N=398 

NOS 

Acceptance 

Criteria 

Time Period 20 April to 

7 Nov. 2004 

21 April to 

11 Nov. 2004 

23 April to 

 9 Nov. 2004 

365 days 

Mean Difference (oC) 0.960 1.16 1.96 na 

RMSE (oC) 1.99 1.90 2.48 na 

SD (oC) 1.75 1.51 1.52 na 

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

CF [3oC] (%) 85.6 88.0 79.4 > 90% 

POF [2x3oC] (%) 0.5 0.5 1.3 < 1% 

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

MDNO [2x3oC] (hours) 12.0 0.0 0.0 < 24 hrs 

Notes: na = not applicable 

7. SUMMARY 

NOS’ Lake Superior Operational Forecast System (LSOFS) 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. 

LSOFS 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 surface air temperature and wind forcing from 

NWS/NCEP’s NAM-12 weather prediction model. During the forecast cycle, the heat 

flux is set to zero. 

An assessment of the LSOFS 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 

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

conducted comparisons between POMGL vs. field data for Lake Superior which could be 

used to fulfill the hindcast scenario. 

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

25
observations at five NOS NWLON stations and surface temperatures at three 

NWS/NDBC fixed buoys in the lake. Due to the lack of sub-surface water temperatures 

and current observations, no assessment of these variables was conducted for LSOFS. 

Water Levels 

The hourly water nowcasts met the NOS acceptance criteria at all five NOS gauges. The 

mean algebraic differences ranged between -2.9 cm at Duluth, MN and +2.4 cm at Port 

Iroquois, MI. Thus, the nowcasts under-predicted the hourly water levels at Duluth and 

over-predicted the levels at Port Iroquois. The RMSE among the five gauges ranged 

between 2.5 and 6.2 cm. 

The ability of the nowcasts to predict extreme high and low water level events was also 

assessed using a proposed modification to the NOS evaluation standards. The nowcast 

predictions of high water level events passed the NOS criteria for amplitude at three of 

the five NOS gauges, failing at Duluth and Port Iroquois. The predictions of low water 

level events passed the NOS criteria at four of the five NOS gauges, failing at Port 

Iroquois. The nowcasts failed to meet NOS criteria in predicting the timing of both 

extreme high and low water events at all the NOS gauges. 

The hourly forecast guidance met the NOS criteria at all five locations. The mean 

algebraic differences ranged between -2.9 to + 2.6 cm and the RMSE ranged between 2.5 

and 6.2 cm, very similar to the statistics for the nowcast evaluation. Similar to the 

nowcasts, the greatest errors were at Duluth and Port Iroquois gauges located at the 

extreme western and eastern ends of the lake, respectively. The forecast under-predicted 

the water levels at Duluth and over-predicted the levels at Port Iroquois. There was no 

significant increase in the mean algebraic errors or RMSE values, or CF as forecast 

projection increased. 

The forecast guidance of extreme high and low water level events passed NOS criteria at 

three and four of the five gauges, respectively. Again, the least satisfactory locations for 

forecasts were Duluth and Port Iroquois. The highest mean algebraic differences for the 

forecast of extreme high and low events were -12.3 cm at Duluth and +11.6 cm at Port 

Iroquois, respectively. The forecast guidance failed to meet NOS criteria in predicting the 

timing of both extreme high and low water events at all NOS gauges. 

Surface Water Temperatures 

The hourly water temperature nowcasts did not meet the NOS criteria at the three buoys. 

The nowcasts came very close to meeting NOS criteria at the Western- and Mid-Superior 

buoys, failing to meet the CF by 5%. The mean algebraic errors for the period ranged 

between 1.1 and 2.1o

C and the RMSE ranged between 1.9 and 2.7oC. 

The hourly water temperature forecast guidance at 24 hours came very close to meeting 

NOS criteria at all buoys. The mean algebraic difference ranged between 1.0 and 2.0o

C 

and RMSE between 1.9 and 2.5o

C which were slightly lower than for the nowcasts. The 

26
RMSE of the hourly water temperature forecasts decreased slightly as the forecast 

projection increased in time. 

8. RECOMMENDATIONS FOR FUTURE WORK 

Recommendation #1 

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

temperature to observations at buoys, especially in the mid and eastern parts of the lake 

indicate a problem with surface water temperature predictions, especially during the 

Spring and Summer. This could be caused by the inaccuracy in the model’s depiction of 

the three dimensional thermal structure at the start of spring warming. It is recommended 

that sensitivity runs be conducted to determine the impacts of 1) re-initializing the 

model’s three-dimensional thermal structure at start of each spring based on a historical 

mean temperature profile and 2) using an ice module in POMGL. (GLERL is presently 

testing ice module in POMGL for Lakes Erie and Michigan.) 

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 western and eastern ends of the lake according to NOS standards. This 

would likely involve sensitivity tests with POMGL using higher grid resolution and 

incorporating atmospheric pressure forcing. 

27
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 

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. Richard Schmalz, Eugene Wei, and Zhizhang Yang as 

well as Lorraine Robidoux in CSDL for their helpful comments and suggestions to 

improve this technical report. 

28
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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). 

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.] 

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

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

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

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

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

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2070 Neil Avenue, Ohio State University, Columbus, OH 43210-1275.] 

29
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. 

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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. 

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. 

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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.] 

30
APPENDIX A. Skill Assessment Statistics of Semi-Operational Water Level 

Nowcasts and Forecast Guidance at five NOS Gauges in 

Lake Superior for 2004. 

Table A.1. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Port Iroquois, MI 

Gauge (NOS ID 9099004) for 2004. 

Station: Point Iroquois, Lake Superior, MI 

Observed data-longest continuous time segment 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 183.407 

h 5832 183.383 

H-h 15 cm 24h 5832 0.024 0.061 0.056 0.0 98.1 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 36 -0.083 0.097 0.050 0.0 83.3 0.0 0.0 0.0 

ALW-alw 15 cm 24h 36 0.121 0.126 0.033 0.0 80.6 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 36 -0.306 4.450 4.503 22.2 27.8 19.4 0.0 0.0 

TLW-tlw 1.50 hr 25h 36 -0.500 3.734 3.753 25.0 13.9 25.0 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 0.025 0.062 0.057 0.2 98.8 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 0.023 0.058 0.053 0.0 98.6 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 0.028 0.059 0.053 0.0 99.6 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 0.023 0.058 0.053 0.0 98.6 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 0.026 0.059 0.053 0.0 99.4 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 36 -0.066 0.084 0.053 0.0 88.9 0.0 

ALW-alw 15 cm 24h 38 0.116 0.120 0.032 0.0 84.2 0.0 

THW-thw 1.50 hr 25h 36 -0.833 5.344 5.353 27.8 22.2 25.0 

TLW-tlw 1.50 hr 25h 38 -0.684 3.479 3.457 21.1 15.8 18.4 

31
Table A.2. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Marquette CG Station 

Gauge (NOS ID 9099018) for 2004. 

Station: Marquette CG Station, Lake Superior, MI 

Observed data-longest continuous time segment 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 183.403 

h 5832 183.403 

H-h 15 cm 24h 5832 0.000 0.025 0.025 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 9 -0.071 0.074 0.023 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 15 0.065 0.067 0.013 0.0 100.0 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 9 1.778 5.011 4.969 11.1 22.2 44.4 0.0 0.0 

TLW-tlw 1.50 hr 25h 15 0.800 3.366 3.385 13.3 33.3 26.7 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 0.000 0.026 0.026 0.0 100.0 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 -0.003 0.024 0.024 0.0 100.0 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 0.001 0.026 0.026 0.0 100.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 -0.003 0.025 0.025 0.0 100.0 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 -0.001 0.025 0.025 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 9 -0.050 0.053 0.020 0.0 100.0 0.0 

ALW-alw 15 cm 24h 15 0.060 0.062 0.016 0.0 100.0 0.0 

THW-thw 1.50 hr 25h 9 1.889 4.333 4.137 11.1 44.4 22.2 

TLW-tlw 1.50 hr 25h 15 -0.067 3.642 3.770 26.7 20.0 20.0 

Table A.3. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Ontonagon, MI Gauge 

(NOS ID 9099044) for 2004. 

Station: Ontonagon, Lake Superior, MI 

Observed data-longest continuous time segment 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 183.401 

h 5832 183.403 

H-h 15 cm 24h 5832 -0.002 0.031 0.031 0.0 99.8 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 11 -0.085 0.094 0.043 0.0 90.9 0.0 0.0 0.0 

ALW-alw 15 cm 24h 15 0.066 0.069 0.018 0.0 100.0 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 11 -0.636 6.695 6.990 27.3 27.3 18.2 0.0 0.0 

TLW-tlw 1.50 hr 25h 15 -0.267 3.204 3.305 20.0 46.7 13.3 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 -0.001 0.032 0.032 0.0 99.8 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 -0.004 0.032 0.032 0.0 99.8 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 -0.003 0.032 0.032 0.0 99.8 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 -0.004 0.032 0.032 0.0 99.8 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 -0.002 0.033 0.033 0.0 99.8 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 11 -0.087 0.095 0.042 0.0 90.9 0.0 

ALW-alw 15 cm 24h 14 0.064 0.066 0.014 0.0 100.0 0.0 

THW-thw 1.50 hr 25h 11 0.273 5.402 5.658 18.2 27.3 18.2 

TLW-tlw 1.50 hr 25h 14 0.429 2.449 2.503 7.1 42.9 7.1 

32
Table A.4. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Grand Marais, MN 

Gauge (NOS ID 9000090) for 2004.

Station: Grand Marais, Lake Superior, MI47.750 -9 

Observed data-longest continuous time segment 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 183.393 

h 5832 183.405 

H-h 15 cm 24h 5832 -0.012 0.035 0.033 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 12 -0.081 0.087 0.033 0.0 100.0 0.0 0.0 0.0 

ALW-alw 15 cm 24h 23 0.061 0.066 0.025 0.0 100.0 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 12 -1.000 3.440 3.438 25.0 16.7 8.3 0.0 0.0 

TLW-tlw 1.50 hr 25h 23 0.087 3.683 3.765 21.7 26.1 21.7 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 -0.012 0.035 0.033 0.0 100.0 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 -0.007 0.037 0.036 0.0 100.0 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 -0.007 0.036 0.035 0.0 100.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 -0.006 0.037 0.037 0.0 100.0 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 -0.005 0.037 0.037 0.0 100.0 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 13 -0.088 0.092 0.028 0.0 100.0 0.0 

ALW-alw 15 cm 24h 24 0.072 0.075 0.021 0.0 100.0 0.0 

THW-thw 1.50 hr 25h 13 -0.308 6.239 6.486 30.8 38.5 23.1 

TLW-tlw 1.50 hr 25h 24 -0.292 3.857 3.928 20.8 25.0 25.0 

Table A.5. Skill Assessment Statistics of Semi-Operational Predictions at the NOS Duluth, MI Gauge a 

(NOS ID 9000064) for 2004. 

Station: Duluth, Lake Superior, MI 

Observed data-longest continuous time segment 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 183.397 

h 5832 183.426 

H-h 15 cm 24h 5832 -0.029 0.062 0.055 0.0 98.2 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 26 -0.123 0.136 0.058 0.0 57.7 0.0 0.0 0.0 

ALW-alw 15 cm 24h 48 0.060 0.068 0.033 0.0 100.0 0.0 0.0 0.0 

THW-thw 1.50 hr 25h 26 -0.077 5.211 5.314 19.2 30.8 23.1 0.0 0.0 

TLW-tlw 1.50 hr 25h 48 -0.479 2.955 2.946 18.8 47.9 6.3 0.0 0.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

H00-h00 15 cm 24h 494 -0.028 0.061 0.055 0.0 98.4 0.0 0.0 0.0 

H06-h06 15 cm 24h 490 -0.031 0.065 0.057 0.0 98.0 0.0 0.0 0.0 

H12-h12 15 cm 24h 490 -0.031 0.064 0.055 0.0 98.0 0.0 0.0 0.0 

H18-h18 15 cm 24h 490 -0.029 0.065 0.058 0.0 98.2 0.0 0.0 0.0 

H24-h24 15 cm 24h 490 -0.029 0.062 0.055 0.0 98.2 0.0 0.0 0.0 

AHW-ahw 15 cm 24h 27 -0.123 0.135 0.058 0.0 66.7 0.0 

ALW-alw 15 cm 24h 46 0.061 0.071 0.036 0.0 100.0 0.0 

THW-thw 1.50 hr 25h 27 -0.407 5.168 5.250 25.9 25.9 22.2 

TLW-tlw 1.50 hr 25h 46 -0.304 2.670 2.682 15.2 43.5 6.5 

33
APPENDIX B. Time Series Plots of Semi-Operational Water Level Nowcasts 

vs. Observations at five NOS Gauges in Lake Superior during 

2004. 

100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Point Iroquois

Fig. B.1. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at the NOS Port 

Iroquois, MI Gauge during 2004. 

34
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Marquette

Fig. B.2. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at the NOS 

Marquette CG Station, MI Gauge during 2004. 

35
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Ontonagon

Fig. B.3. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at the NOS 

Ontonagon, MI Gauge during 2004. 

36
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Grand Marais

Fig. B.4. Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at the NOS Grand 

Marais, MN Gauge during 2004. 

37
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationnowcastevents in observationevents in nowcast

Duluth

Fig. B.5 Time Series Plot of Semi-Operational Water Level Nowcasts vs. Observations at the NOS 

Duluth, MN Gauge during 2004. 

38
 

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

Guidance vs. Observations at five NOS Gauges in Lake 

Superior during 2004. 

100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Point Iroquois

Fig. C.1. Times Series Plot of Semi-Operational Water Level Forecasts vs. Observations at the NOS Port 

Iroquois, MI Gauge during 2004. 

39
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Marquette

Fig. C.2. Time Series Plot of Semi-Operational Water Level Forecasts vs. Observations at the NOS 

Marquette CG Station, MI Gauge during 2004. 

40
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Ontonagon

Fig. C.3. Time Series Plot of Semi-Operational Water Level Forecasts vs. Observations at the NOS 

Ontonagon, MI Gauge during 2004. 

41
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Grand Marais

Fig. C.4. Time Series Plot of Semi-Operational Water Level Forecasts vs. Observations at the NOS Grand 

Marais, MN Gauge during 2004. 

42
100 150 200 250 300 350

Julian Day (2004)

184.0183.5183.0

Water Levels (meters, IGLD1985)

observationforecastevents in observationevents in forecast

Duluth

Fig. C.5 Time Series Plot of Semi-Operational Water Level Forecasts vs. Observations at the NOS 

Duluth, MN Gauge during 2004. 

43
APPENDIX D. Skill Assessment Statistics of Semi-Operational Surface 

Water Temperature Nowcasts and Forecast Guidance at 

three NWS/NDBC Fixed Buoys in Lake Superior 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 

45006 (Western Superior) for the Period 20 April to 7 November 2004. 

Station: NDBC Buoy 45006 in Lake Superior 

Observed data-longest continuous time segment from: 4/20/2004 to 11/ 7/2004 

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 POFMDNO MDPO 

CRITERION - - - - - - <1% >90% <1% <N <N 

------------------------------------------------------------------------------- 

 SCENARIO: SEMI-OPERATIONAL NOWCAST 

T 4811 9.009 

t 4811 7.905 

T-t 3.0 c 24h 4811 1.103 2.066 1.746 0.0 84.9 0.2 0.0 8.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

T00-t00 3.0 c 24h 400 1.125 2.098 1.773 0.0 85.5 0.3 0.0 0.0 

T06-t06 3.0 c 24h 398 1.080 2.040 1.733 0.0 84.4 0.5 0.0 0.0 

T12-t12 3.0 c 24h 398 1.029 2.069 1.797 0.0 84.7 0.5 0.0 0.0 

T18-t18 3.0 c 24h 397 1.003 1.986 1.717 0.0 85.6 0.3 0.0 0.0 

T24-t24 3.0 c 24h 397 0.960 1.992 1.748 0.0 85.6 0.5 0.0 12.0 

Table D.2. Skill Assessment Statistics of Semi-Operational Nowcasts and Forecast 

Guidance of Surface Water Temperatures at the NWS/NDBC Fixed Buoy 

45001 (Mid Superior) for the Period 21 April to 11 November 2004. 

Station: NDBC Buoy 45001 in Lake Superior 

Observed data-longest continuous time segment from: 4/23/2004 to 11/ 9/2004 

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 4831 7.504 

t 4831 6.233 

T-t 3.0 c 24h 4831 1.271 1.997 1.540 0.0 84.9 1.1 0.0 15.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

T00-t00 3.0 c 24h 403 1.285 2.018 1.558 0.0 84.9 1.0 0.0 12.0 

T06-t06 3.0 c 24h 399 1.237 1.951 1.510 0.0 85.7 1.3 0.0 0.0 

T12-t12 3.0 c 24h 399 1.229 1.999 1.578 0.0 86.2 1.0 0.0 0.0 

T18-t18 3.0 c 24h 399 1.183 1.893 1.480 0.0 85.7 0.8 0.0 0.0 

T24-t24 3.0 c 24h 399 1.157 1.899 1.508 0.0 88.0 0.5 0.0 0.0 

44
Table D.3. Skill Assessment Statistics of Semi-Operational Nowcasts and Forecast 

Guidance of Surface Water Temperatures at the NWS/NDBC Fixed Buoy 

45004 (Eastern Superior) for the Period 21 April to 11 November 2004. 

Station: NDBC Buoy 45004 in Lake Superior 

Observed data-longest continuous time segment from: 4/23/2004 to 11/ 9/2004 

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 4814 8.379 

t 4814 6.245 

T-t 3.0 c 24h 4814 2.134 2.700 1.654 0.0 75.9 4.2 0.0 36.0 

 SCENARIO: SEMI-OPERATIONAL FORECAST 

T00-t00 3.0 c 24h 402 2.137 2.696 1.646 0.0 76.9 4.2 0.0 36.0 

T06-t06 3.0 c 24h 397 2.120 2.697 1.669 0.0 75.6 3.0 0.0 36.0 

T12-t12 3.0 c 24h 398 2.036 2.599 1.617 0.0 78.4 4.3 0.0 24.0 

T18-t18 3.0 c 24h 397 2.019 2.553 1.564 0.0 76.8 1.5 0.0 12.0 

T24-t24 3.0 c 24h 398 1.959 2.478 1.519 0.0 79.4 1.3 0.0 0.0 

45
APPENDIX E. Time Series Plots of Semi-Operational Nowcasts and 

Forecast Guidance of Surface Water Temperature vs. 

Observations at two NWS/NDBC fixed buoys in Lake 

Superior during 2004. 

100 150 200 250 300 350

Julian Day (2004)

5.00.0

25.020.015.010.0

Temperature (Degrees)

observationnowcastforecast

NDBC 45006

Fig. E.1. Time Series Plot of Semi-Operational Nowcasts and Forecast Guidance of 

Surface Water Temperatures (o

C) vs. Observations at the NWS/NDBC Fixed 

Buoy 45006 (West Superior) for the Period mid-April to mid-December 2004. 

The forecast values depicted on the plot are from the 0000 UTC forecast cycle. 

46
100 150 200 250 300 350

Julian Day (2004)

5.00.0

25.020.015.010.0

Temperature (Degrees)

observationnowcastforecast

NDBC 45001

Fig. E.2. Time Series Plot of Semi-Operational Nowcasts and Forecast Guidance of 

Surface Water Temperatures (o

C) vs. Observations at the NWS/NDBC Fixed 

Buoy 45001 (Mid Superior) for the Period mid-April to mid-December 2004. 

The forecast values depicted on the plot are from the 0000 UTC forecast cycle. 

47
100 150 200 250 300 350

Julian Day (2004)

5.00.0

25.020.015.010.0

Temperature (Degrees)

observationnowcastforecast

NDBC 45004

Fig. E.3. Time Series Plot of Semi-Operational Nowcasts and Forecast Guidance of 

Surface Water Temperatures (o

C) vs. Observations at the NWS/NDBC Fixed 

Buoy 45004 (Eastern Superior) for the Period 23 April to 9 November 2004. 

The forecast values depicted on the plot are from the 0000 UTC forecast cycle. 

48