Can Reanalysis Products Outperform Mesoscale Numerical Weather Prediction Models in Modeling the Wind Resource in Simple Terrain?

Vincent Pronk, Nicola Bodini, Mike Optis, Julie Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, Ethan Young

Research output: Contribution to journalArticlepeer-review

14 Scopus Citations


Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-The-Art NWP model-the Weather Research and Forecasting (WRF) Model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-Term Ensemble Dataset (WTK-LED) to those observed by lidars at a site in Oklahoma, United States, and in a United States Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (∼1/4-1ms-1) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a limited negative bias (∼1/4-0.5ms-1) offshore and a slight positive bias (∼1/4+0.5ms-1) at the land-based site. On the other hand, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED's higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle. At the land-based site, this is partially caused by wind plant wake effects not being accurately captured by WTK-LED.

Original languageAmerican English
Pages (from-to)487-504
Number of pages18
JournalWind Energy Science
Issue number2
StatePublished - 2022

Bibliographical note

See NREL/JA-5000-80651 for article as published in Wind Energy Science Discussions

NREL Publication Number

  • NREL/JA-5000-82501


  • ERA-5
  • offshore wind
  • SGP
  • validation
  • WRF


Dive into the research topics of 'Can Reanalysis Products Outperform Mesoscale Numerical Weather Prediction Models in Modeling the Wind Resource in Simple Terrain?'. Together they form a unique fingerprint.

Cite this