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Evaluation and Bias Correction of the ERA5 Reanalysis over the United States for Wind and Solar Energy Applications

Author

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  • James M. Wilczak

    (NOAA Physical Sciences Laboratory, Boulder, CO 80305, USA)

  • Elena Akish

    (NOAA Physical Sciences Laboratory, Boulder, CO 80305, USA
    Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO 80309, USA)

  • Antonietta Capotondi

    (NOAA Physical Sciences Laboratory, Boulder, CO 80305, USA
    Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO 80309, USA)

  • Gilbert P. Compo

    (NOAA Physical Sciences Laboratory, Boulder, CO 80305, USA
    Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO 80309, USA)

Abstract

The applicability of the ERA5 reanalysis for estimating wind and solar energy generation over the contiguous United States is evaluated using wind speed and irradiance variables from multiple observational data sets. After converting ERA5 and observed meteorological variables into wind power and solar power, comparisons demonstrate that significant errors in the ERA5 reanalysis exist that limit its direct applicability for a wind and solar energy analysis. Overall, ERA5-derived solar power is biased high, while ERA5-derived wind power is biased low. During winter, the ERA5-derived solar power is biased high by 23% on average, while on an annual basis, the ERA5-derived wind power is biased low by 20%. ERA5-derived solar power errors are found to have consistent characteristics across the contiguous United States. Errors for the shortest duration and most extreme solar negative anomaly events are relatively small in the ERA5 when completely overcast conditions occur in both the ERA5 and observations. However, longer-duration anomaly events on weekly to monthly timescales, which include partially cloudy days or a mix of cloudy and sunny days, have significant ERA5 errors. At 10 days duration, the ERA5-derived average solar power produced during the largest negative anomaly events is 62% greater than observed. The ERA5 wind speed and derived wind power negative biases are largely consistent across the central and northwestern U.S., and offshore, while the northeastern U.S. has an overall small net bias. For the ERA5-derived most extreme negative anomaly wind power events, at some sites at 10 days duration, the ERA5-derived wind power produced can be less than half of that observed. Corrections to ERA5 are derived using a quantile–quantile method for solar power and linear regression of wind speed for wind power. These methods are shown to avoid potential over-inflation of the reanalysis variability resulting from differences between point measurements and the temporally and spatially smoother reanalysis values. The corrections greatly reduce the ERA5 errors, including those for extreme events associated with wind and solar energy droughts, which will be most challenging for electric grid operation.

Suggested Citation

  • James M. Wilczak & Elena Akish & Antonietta Capotondi & Gilbert P. Compo, 2024. "Evaluation and Bias Correction of the ERA5 Reanalysis over the United States for Wind and Solar Energy Applications," Energies, MDPI, vol. 17(7), pages 1-36, March.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:7:p:1667-:d:1367812
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    References listed on IDEAS

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    1. Giovanni Gualtieri, 2021. "Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers," Energies, MDPI, vol. 14(14), pages 1-21, July.
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    3. Draxl, Caroline & Clifton, Andrew & Hodge, Bri-Mathias & McCaa, Jim, 2015. "The Wind Integration National Dataset (WIND) Toolkit," Applied Energy, Elsevier, vol. 151(C), pages 355-366.
    4. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    5. Costoya, X. & Rocha, A. & Carvalho, D., 2020. "Using bias-correction to improve future projections of offshore wind energy resource: A case study on the Iberian Peninsula," Applied Energy, Elsevier, vol. 262(C).
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    Keywords

    wind energy; solar energy; ERA5; bias correction; droughts;
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