About the Hydrodynamic Model Each system is described in its own separate section in what refers to forcing data. 7. Panel groups show (top) time series, (bottom left) scatterplots, and (bottom right) quantile–quantile plots. The GLSEA lake surface water temperature analysis is generated daily based on data from the AVHRR sensor on board NOAA's polar orbiting The U.S. Army Corps of Engineers (USACE) has been generating and constantly upgrading more recent wave hindcast databases in several oceanic basins, and in major inland water bodies such as the Great Lakes. The development of a Great Lakes operational wave forecasting system at NCEP is described. Even if unrealistic, this provided a lower bound for spectral ranges of dominant waves. BLT plots for Tp indicate that GLW-TC96-ANL provides predictions that are generally more consistent with measurements than GLERL-ANL for all validation statistics. Therefore, only results for that year were retained for model intercomparison. Validation of surface wind fields focuses on wind speeds, since these have a dominant effect on wave model error. After dealing with NDFD data feed issues that required additional adjustments to ensure continuity of the forecasting system over time, the GLW-NDFD was implemented operationally in 2009. WAVEWATCH III uses a custom Great Lakes sector of the NDFD dataset designed to match the spatial grid used by NCEP’s wave models, and include Canadian waters, which were initially left out of the operational NDFD products. Buoy and model data were collocated whenever the latter fell within a ±1-h window centered at the buoy measurement time stamp. Bulk validation statistics were computed for model runs made with NCEP’s GLW and the GLERL wave systems, forced with GLERL wind analyses. BLT diagrams summarizing the validation of NAM (blue) and NDFD (red) surface wind forecasts at (left) 24 and (right) 48 h, relative to NDBC buoys in the Great Lakes. The assessment of the 10-m height wind speeds is made at the 24- and 48-h forecast outputs. 15 and 16).
The system is an implementation of the WAVEWATCH III model, forced with atmospheric data from NCEP’s regional Weather Research and Forecasting (WRF) Model [the North American Mesoscale Model (NAM)] and the National Digital Forecast Database …
5 for a description of the BLT structure. Solutions to these problems require improvements in NAM and NDFD, which are currently being discussed with NCEP’s mesoscale modeling group.
CO-OPS OPeNDAP web sever at http://opendap.co-ops.nos.noaa.gov/netcdf/. Another strong constraint for defining spatial grid resolutions is the available computer time for operational forecasting at, initially, a forecast horizon of up to 84 h in the NAM-driven GLW (a 90-h-long model run, since a 6-h hindcast is run at every model cycle), and up to 144 h for the GLW-NDFD.
The initial operational implementation of NCEP’s Great Lakes wave model system was forced with winds from the Eta Model (Black 1994). 8. You can be assured our editors closely monitor every feedback sent and will take appropriate actions. National Centers for Environmental Prediction (NCEP) and Mr. Greg Lang at GLERL. The underlying validation statistics used for performance assessment are bias, standard deviation, scatter index, correlation coefficient, root-mean-square error, and slope of a linear regression forced through the origin. Validation statistics indicated that model results were generally insensitive to the bulk correction, so that a decision was made to go ahead with a future operational implementation without a bulk surface wind correction component. Xue noted that a typical operational forecast system should include three components: modeling, an observation network and data analysis. Section 5 provides a discussion centered on recent model upgrades that led to a higher accuracy of severe sea-state predictions relative to the current operational system, and presents associated supporting validation results. Directional distribution of biases as a function of wind speeds at coastal station DBLN6. Search by city or zip code. Validation statistics of 24-h forecast surface wind speeds from the (a) NAM model and (b) NDFD, at the location of NDBC buoy 45001 (Lake Superior), during 2009. of tide, water level, current, and other marine environmental information. One key advantage of a model, especially in a large and complex environment like the Great Lakes, is that it can produce continuous fields in 3-D space, predicting—at any time and any place—temperature, water levels, and currents. Resolutions of the original GLERL wave model grids were on the order of 5 km, except for Lake Superior, which had a 10-km grid, and was inadequate for the higher-resolution grid used in NCEP’s system. Global statistics were then derived from associated error matrices in an attempt to define a generalized relationship between wind speed biases and wind-fetch geometry. In the subsections below, a detailed description is provided of forcing fields and spectral and spatial resolutions used in both operational Great Lakes wave forecasting systems at NCEP. Background The Great Lakes Operational Forecast System (GLOFS) is a NOAA automated model-based prediction system aimed at providing improved predictions (guidance) of water levels, water currents and water temperatures in the 5 Great Lakes (Erie, Michigan, Superior, Huron and Ontario) for the commercial, recreation, and emergency response communities. Part I: Model framework and validation against field data, The new NMC mesoscale Eta Model: Description and forecast examples, doi:10.1175/1520-0434(1994)009<0265:TNNMEM>2.0.CO;2, Second-order space–time climate difference statistics, Performance of NCEP regional wave models in predicting peak sea states during the 2005 North Atlantic hurricane season, Effects of long waves on wind-generated waves, Development, implementation, and skill assessment of the NOAA/NOS Great Lakes operational forecast system, A new methodology for the extension of the impact of data assimilation on ocean wave prediction, The new digital forecast database of the National Weather Service, A nonhydrostatic model based on a new approach, Quasi-linear theory of wind-wave generation applied to wave forecasting, Comparison of a two-dimensional wave prediction model with synoptic measurements in Lake Michigan, A comprehensive meteorological modeling system—RAMS, Automated wave forecasting for the Great Lakes, Estimation of overlake wind speed from overland wind speed: A comparison of three methods, Application of a simple numerical wave prediction model to Lake Erie, Distributed-memory concepts in the wave model WAVEWATCH III, Source terms in a third-generation wind wave model, Development and implementation of wind-generated ocean surface wave models at NCEP, This site uses cookies.
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