Work Description

Title: Big Ship Data: Pre- and Post-Processed Spatiotemporal Data for 2006-2014 for Great Lakes Air Temperature, Dew Point, Surface Water Temperature, and Wind Speed Open Access Deposited

http://creativecommons.org/licenses/by/4.0/
Attribute Value
Methodology
  • Pre-Processed data was acquired from the NDFD for air temperature, dew point, and wind speed, and from the GLCFS for lake surface temperature. This data was re-gridded to be on a 0.1-degree grid and at hourly resolution (3-hourly for lake temperature). Ship Observations were acquired from NOAA's Volunteer Observing Ships program. Using Gaussian Process Regression, the ship observations were assimilated into the modeled data to generate new spatiotemporal estimates of the 4 study variables. Additionally, uncertainty estimates were provided
Description
  • This data is in support of the WRR paper by Fries and Kerkez: Big Ship Data: Using Vessel Measurements to Improve Estimates of Temperature and Wind Speed on the Great Lakes Code is also provided
Creator
Depositor
  • kjfries@umich.edu
Contact information
Discipline
Keyword
Date coverage
  • 2006-01-01 to 2014-12-31
Citations to related material
  • Fries, K., and B. Kerkez (2017), Big Ship Data: Using vessel measurements to improve estimates of temperature and wind speed on the Great Lakes, Water Resour. Res., 53, 3662–3679, http://doi.org/10.1002/2016WR020084.
Resource type
Last modified
  • 08/16/2018
Published
  • 03/30/2017
License
To Cite this Work:
Fries, K. (2017). Big Ship Data: Pre- and Post-Processed Spatiotemporal Data for 2006-2014 for Great Lakes Air Temperature, Dew Point, Surface Water Temperature, and Wind Speed [Data set]. University of Michigan - Deep Blue.

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