Vaisala Energy Support
Which Wind Time Series dataset should I choose?
Vaisala offers three datasets in our Wind Time Series Tool. Two of these, ERA5 and MERRA2, are global in coverage and considered classic reanalysis datasets, in that great care was taken to ensure consistency over their long periods of record. The third, HRRR (High Resolution Rapid Refresh), is a forecast dataset that covers only the continental United States. HRRR is available for a shorter period of time but at much finer resolution.
The reanalysis models, ERA5 and MERRA2, are fairly coarse in spatial resolution at roughly 30 km and 90 km respectively. To overcome some of the limitations of that coarseness, the ERA5 and MERRA2 data offered by Vaisala have been downscaled to match the long-term annual average value of our 5km global wind dataset as described here
The HRRR data is at a spatial resolution of roughly 3 km and comes from a weather forecast model run every hour, assimilating all the latest observational data from ground, radar, and satellite sources. As a forecast model, HRRR is not expected to be consistent over time so we only offer data since January 2021, after the last major model upgrade. Furthermore, as HRRR is at a finer spatial resolution (3 km) than the Vaisala 5 km dataset, it is provided with no further spatial enhancement or mean matching.
So which version to choose? Where all three sources are available, this question is addressed in detail in Davidson and Millstein, 2022 and Millstein, 2023 (references below). In brief, the most accurate data available is from HRRR though it is only for the USA and the period since January 2021. The ERA5 dataset is considered by many to be the gold standard for long-term global reanalysis data and while it is at coarser resolution than HRRR has a much longer duration, making it more useful as a long-term reference. Although it has the coarsest spatial resolution, MERRA2 also has a long history and can be more accurate at some locations. This makes it useful as a second opinion when considering long-term variability of ERA5 (or vice-versa).
A paper comparing all three datasets against wind energy production data in the USA can be found here (Davidson and Millstein, 2022) and here (Millstein, 2023):
More details about the HRRR model can be found here
More details about ERA5 can be found here
More details about MERRA2 can be found here
The reanalysis models, ERA5 and MERRA2, are fairly coarse in spatial resolution at roughly 30 km and 90 km respectively. To overcome some of the limitations of that coarseness, the ERA5 and MERRA2 data offered by Vaisala have been downscaled to match the long-term annual average value of our 5km global wind dataset as described here
The HRRR data is at a spatial resolution of roughly 3 km and comes from a weather forecast model run every hour, assimilating all the latest observational data from ground, radar, and satellite sources. As a forecast model, HRRR is not expected to be consistent over time so we only offer data since January 2021, after the last major model upgrade. Furthermore, as HRRR is at a finer spatial resolution (3 km) than the Vaisala 5 km dataset, it is provided with no further spatial enhancement or mean matching.
So which version to choose? Where all three sources are available, this question is addressed in detail in Davidson and Millstein, 2022 and Millstein, 2023 (references below). In brief, the most accurate data available is from HRRR though it is only for the USA and the period since January 2021. The ERA5 dataset is considered by many to be the gold standard for long-term global reanalysis data and while it is at coarser resolution than HRRR has a much longer duration, making it more useful as a long-term reference. Although it has the coarsest spatial resolution, MERRA2 also has a long history and can be more accurate at some locations. This makes it useful as a second opinion when considering long-term variability of ERA5 (or vice-versa).
A paper comparing all three datasets against wind energy production data in the USA can be found here (Davidson and Millstein, 2022) and here (Millstein, 2023):
More details about the HRRR model can be found here
More details about ERA5 can be found here
More details about MERRA2 can be found here
More Wind Online Tools Questions
- How do I enter a location?
- How do I interpret the graph provided by the Monthly Mean Wind Speed Tool?
- What does the Annual Mean Wind Speed Tool provide?
- How do I interpret the wind rose provided by the Annual Mean Wind Rose Tool?
- What does the Wind Speed Distribution Tool provide?
- Why do we show a +/- next to the annual value?
- What wind speeds are shown on the map?
- What affects wind at a given site?
- How can I compare sites side-by-side?
- How do I change locations for individual tools?
- What is a hub height?
- What makes a good wind resource?
- What is a wind resource assessment?
- What do the colors on the map mean?
- What is the source of the information?
- How accurate are the Wind Prospecting Tools?
- Why does the map disappear?
- How was the 5 km global wind dataset created?
- Does 3TIER incorporate observational data?
- What were 3TIER's data validation procedures for the 5 km global wind dataset?
- What happened to 3TIER’s Reference Wind Time Series Product?
- Why do all the various datasets have different start and end times?
- Doesn’t horizontal resolution matter? What about downscaling with weather models like WRF and MM5?
- Why are the long-term mean values of each data set so similar and why don’t they match the values I get when I download these data directly from the various global modeling centers?
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