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Layer: Cumulative degree-days (ID: 0)

Name: Cumulative degree-days

Display Field: FOOTPRINT.STArea()

Type: Raster Layer

Geometry Type: null

Description: Cumulative degree-days (CDD) is the accumulation of temperature over a period of time whenever the temperature is above a predetermined threshold. In this case a base temperature of 0⁰C was used to accumulate the mean daily temperature, in ⁰C, from January 1 through December 31 for each year from 2006 to 2012 for the mean daily surface water temperature (coastal margin zone) and the mean daily vertical water temperature for the 0 to 20m water column (nearshore and offshore zones). The NOAA Great Lakes Coastal Forecast System (GLCFS) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce 3-D Nowcasts and forecasts of water temperature and currents, and 2-D Nowcasts and forecasts of water levels of the Great Lakes. This system was originally called the Great Lakes Coastal Forecasting system (GLCFS) from NOAA’s Great Lakes Environmental Research Laboratory (GLERL). A thorough description of the history, operation, and validation of GLCFS can be found in Chu et al. 2011 (full reference below). Data was obtained from NOAA-GLERL for years 2006-2012 in NetCDF format. The data was processed using Python 2.7 and the netCDF4 module downloaded from (http://code.google.com/p/netcdf4-python/). The data was converted from NetCDF to .csv for each time step and sigma level. The data was then averaged into actual depth bins from the sigma layers, and then temporally averaged for each horizontal grid cell. The final averaged layer was saved in ASCII format and imported into ArcGIS for Desktop 10.1 ArcGRID File Geodatabase format. Cumulative degree-days (CDD) are a measure of heat accumulation over an entire season or year. In this case, the daily vertical water temperature mean for the 0-20 m depth was calculated and then summed over the year. The lower threshold is 0 deg. C and no upper threshold. The Great Lakes Coastal Forecast System (GLCFS) has been implemented by NOAA’s National Ocean Service (NOS) to provide the maritime community with improved short-term predictions of water levels, water currents and water temperatures of the Great Lakes. The main uses for predicted variables are 1) hazard warning and avoidance, 2) enhancement of recreational and commercial activities, 3) scenario test and risk assessment, and 4) natural resource preservation and decision making.The GLOFS website: http://tidesandcurrents.noaa.gov/ofs/glofs.htmlThe GLCFS website: http://www.glerl.noaa.gov/res/glcfs/

Service Item Id: def7fc9d9ec8420ba5a16488ba0a48c9

Copyright Text: 1) Chu, P. Y., J. G. W. Kelley, G. V. Mott, A. Zhang, and G. A. Lang. 2011. Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System. Ocean Dynamics 61(9):1305-1316 (DOI:10.1007/s10236-011-0424-5) (available at http://www.glerl.noaa.gov/pubs/fulltext/2011/20110016.pdf). 2) The Great Lakes Aquatic Habitat Framework (GLAHF) project has been funded by the Great Lakes Fishery Trust and led by Dr. Catherine Riseng, PI at the University of Michigan School of Natural Resources and Environment, with partners from Michigan Department of Natural Resources-Institute for Fisheries Research, NOAA Great Lakes Environmental Research Laboratory, International Joint Commission, Michigan State University, The Nature Conservancy, Ontario Ministry of Natural Resources, University of Minnesota-Duluth, U.S. Fish & Wildlife Service, U.S. Geological Survey and many collaborating partners in both the USA and Canada. More information about this project can be found at http://glahf.org/.

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Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 144000000

Max Scale: 4000

Supports Advanced Queries: false

Supports Statistics: false

Has Labels: false

Can Modify Layer: false

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

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Type ID Field: null

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