| 22 Jan 2026
Identification of optimal ERA5 model level for wind resource assessments in mountainous terrain
Abstract. Accurate estimation of hub-height wind speed is crucial for wind resources assessment at prospective sites. Traditionally, long-term wind speed series are derived from short-term site observations combined with reanalysis products, most commonly the ERA5 single-level data at 10 m and 100 m heights. However, the coarse spatial resolution of ERA5 limits their reliability in complex mountainous regions, leading to weak correlations with local wind measurements due to not adequately resolved near-surface flow. This study investigates whether the use of wind speed estimates from upper atmospheric levels (i.e., model levels) of ERA5 model level data set can improve wind speed representation in complex terrain. We compared ERA5 with hourly wind speed observations at 80 m from four meteorological masts located at high elevations (2829–3796 m a.s.l.) in the tropical Andes of southern Ecuador, and developed site-specific Random Forest (RF) models for calibrate ERA5 wind speeds. Our findings reveal that wind speeds from upper model levels (~ 1000 – 1500 m for most of the sites) exhibit substantially stronger correlations with mast observations than the theoretical hub-height. Compared with single-level inputs, model-level-driven RF estimates achieved average improvements of 59 % in Perkins Skill Score (PSS), 40 % in R², and 23 % in MAE/RMSE. Importantly, the bias in annual energy production (AEP) decreased to less than 7 %, in contrast with 22 % when using ERA5 single-level data. These improvements were greater for sites located on exposed peaks, which are often preferred locations for wind farms, where the local flow is better captured by upper model levels. Overall, our results demonstrate that selecting appropriate upper ERA5 model levels offers a cost-effective strategy to generate accurate, site-specific hub-height wind speed time series in complex terrain. We encourage the wind energy community to exploit these upper atmospheric levels of ERA5 to enhance wind resource assessments in mountainous regions.
General comments
This study investigates how well ERA5 model-level wind speeds at different geometric heights represent 80-m mast observations in complex terrain and coastal/flat sites. The work addresses an important practical question for wind-energy applications: at which ERA5 heights are hub-height conditions best represented, and how does this depend on terrain complexity.
Overall, the paper poses a clear scientific question. The scientific approach is sound and the results are clearly presented. I therefore recommend minor revision, mainly to clarify some key statements, correct small inconsistencies in figures/tables, and explicitly summarize the main uncertainties and limitations in the Conclusions. The manuscript addresses an important and practical question for wind-energy applications and provides useful guidance on the representativeness of ERA5 model-level winds in different terrain types.
Minor comments
In addition, it would be very helpful to explicitly include the correlations between the mast observations and the ERA5 10-m and 100-m single-level winds for each site (e.g. additional markers or lines). This would make the comparison between single-level and model-level performance more transparent to the reader.
Similar to Figure 2, I recommend also indicating the correlations between the mast observations and the ERA5 10-m and 100-m single-level winds for each coastal site, to facilitate comparison.
In addition, the important findings stated in Lines 444–445 (“higher underestimations would be expected for sites with high frequencies of low wind speed”) and in Lines 289–292 (“wind speeds over flat terrain are representative of hub-height conditions at coastal and inner flat sites but are not representative in mountainous areas”) could also be briefly restated in the Conclusions section so that the main messages are more clearly visible to the reader.
– the limited number of masts and regions considered;
– the representativeness of individual masts for complex terrain;
– the dependence on the chosen ERA5 grid point and the computation of geometric heights from model levels;
– and the relatively short analysis period (2021–2024).
Such a paragraph would help frame how far the results can be generalized to other complex-terrain regions.