A unified high-resolution wind and solar dataset from a rapidly updating numerical weather prediction model

James, Eric P.; Benjamin, Stanley G.; Marquis, Melinda

doi:10.1016/j.renene.2016.10.059

i

A unified high-resolution wind and solar dataset from a rapidly updating numerical weather prediction model

2017
By James, Eric P. ; Benjamin, Stanley G. ; Marquis, Melinda

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Journal Title:

Renewable Energy
Personal Author:

James, Eric P. ; Benjamin, Stanley G. ; Marquis, Melinda
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; ESRL (Earth System Research Laboratory)
Description:

A new gridded dataset for wind and solar resource estimation over the contiguous United States has been derived from hourly updated 1-h forecasts from the National Oceanic and Atmospheric Administration High-Resolution Rapid Refresh (HRRR) 3-km model composited over a three-year period (approximately 22 000 forecast model runs). The unique dataset features hourly data assimilation, and provides physically consistent wind and solar estimates for the renewable energy industry. The wind resource dataset shows strong similarity to that previously provided by a Department of Energy-funded study, and it includes estimates in southern Canada and northern Mexico. The solar resource dataset represents an initial step towards application-specific fields such as global horizontal and direct normal irradiance. This combined dataset will continue to be augmented with new forecast data from the advanced HRRR atmospheric/land-surface model. (C) 2016 The Authors. Published by Elsevier Ltd.
Source:

Renewable Energy, 102, 390-405.
DOI:

https://doi.org/10.1016/j.renene.2016.10.059
Document Type:

Journal Article
Rights Information:

CC BY-NC-ND
Compliance:

Submitted
Main Document Checksum:

urn:sha256:76ba7aef77d7b25b1751c06ef80fc83ab2838fec5dbf1298019aead06fef8cdb
Download URL:

https://repository.library.noaa.gov/view/noaa/20582/noaa_20582_DS1.pdf
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[PDF - 9.46 MB ]

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