NORA3

Spatial domain for the NORA3 mesoscale data in windPRO (we cover approx 300km from the coastline). Image showing average wind speeds from 2007-2021 - snippet from the www.windprospecting.com platform.

Introduction

The 3-km Norwegian Reanalysis (NORA3) is a high resolution mesoscale, hindcast dataset that was modelled and provided by the NEWA consortium. NEWA was established as an ERANET+ project with a total budget of 13.1 million euros and it was executed over the years 2016-2019. One of the project outcomes was a comprehensive mesoscale modelling with a spatial coverage of the whole of the European Union and Turkey - and extending at least 100km from any known coastlines. 10 years of data has been made available in a temporal resolution of 30 minutes. A total of 1.37 million individual data-nodes (points) are instantly available from within windPRO.

Dataset Overview

• Content: Limited feature subset of the NORA3 mesoscale dataset - but full spatial coverage (1.37 million nodes).
• Spatial resolution: 3km
• Temporal resolution: Timestep 30 minutes
• Coverage: European Union and Turkey (see the map to the right)
• Period: 10 years of data from 2009-01-01 to 2018-12-31
• Update schedule: This dataset is not updated

Usage Notes

1. I am interested in other parameters. Where can I get those? See a complete list and download these directly from the NEWA homepage: https://map.neweuropeanwindatlas.eu (time-series download is not directly possible)
2. Why is only 10 years of data available?: The mesoscale modelling in the NEWA project covered 30 years (1989-2018) - but currently only the last 10 years has been made available to the public from the NEWA consortium.
3. Where can I learn about the performance of the data?: The NEWA data was included as part of the EMD data benchmarks for the EMD-WRF Europe+ dataset. Here different reanalysis and mesoscale data sources were compared to 300+ high-quality masts within the European domain. The validation report is freely available - here.
4. How can I get turbulence intensities from the NEWA data - as only the Turbulent Kinetic Energy (TKE) is given as a parameter?: As of October 2021, windPRO does not support the use of TKE as a turbulence parameter. However, you can use a (manual) procedure to convert it - by the use of Microsoft Excel or a similar spreadsheet. A procedure is suggested here.

Dataset Parameters

The following parameters are available from the NEWA mesoscale data-subset in windPRO:

Table: Overview of NEWA Dataset Parameters (3km grid).

Parameter(s)	Description	Unit
time	UTC time stamp	YYYY-MM-DD HH:MM
T.100, T.200	Temperature in 100m and 200m agl	degK
TKE.100	Turbulent Kinetic Energy in 100m agl	(m/s)^2
WD.100, WD.200	Wind direction in 100m and 200m agl	deg
WS.100, WS.200	Wind speed in 100m and 200m agl	m/s

License and Attribution

This dataset is a subset of the NEWA mesoscale dataset that has been released under the Creative Commons By Attribution 4.0 license (CC-BY-40) - https://creativecommons.org/licenses/by/4.0/. As a part of the license conditions, the data-owner requires an attribution, such as:

Source: Data obtained from the “New European Wind Atlas, a free, web-based application developed, owned and operated by the NEWA Consortium. 
For additional information see www.neweuropeanwindatlas.eu". Distribution through EMD and windPRO - EMD International A/S, 2021. License: CC-BY-40.

Required windPRO License and Modules

This dataset can be accessed from the most recent version of windPRO given that you hold an active service agreement and a license to the following modules:

• BASIS
• METEO

External Links and References

• NORA3 - thredds server at the Norwegian Meteorological Instutute - [here https://thredds.met.no/thredds/catalog.html]
• NORA3 Model Description Publication in xxx by xx [here]
• NORA3 Validation Paper in Wind Energy Science by Solbrekke, Sorteberg & Haakenstad - here

Acknowledgement and Credits

1. Credits and Acknowledgement: The NEWA Consortium for the release of the NEWA mesoscale dataset as a free and open dataset.
2. Integration of this dataset into EMD services was co-supported through the RECAST project (http://www.recastproject.dk) which is co-funded by the Danish Innovation Fund