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The use of bivariate copulas for bias correction of reanalysis air temperature data

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  • Fakhereh Alidoost
  • Alfred Stein
  • Zhongbo Su

Abstract

Air temperature data retrieved from global atmospheric models may show a systematic bias with respect to measurements from weather stations. This is a common concern in local climate studies. The current study presents two methods based upon copulas and Conditional Probability (CP) to predict bias-corrected mean air temperature in a data-scarce environment: CP-I offers a single conditional probability as a predictor, CP-II is a pixel-wise version of CP-I and offers spatially varying predictors. The methods were applied on daily air temperature in the Qazvin Plain, Iran that were collected at 24 weather stations and 150 ECMWF ERA-interim grid cells from a single month (June) over 11 years. We compared the methods with the commonly applied conditional expectation and conditional median methods. Leave-k-out cross-validation and correlation scores show that the new methods reduced the bias with 44–68% for the full data set and with 34–74% on a homogeneous subarea. We conclude that the two methods are able to locally improve ECMWF air temperatures in a data-scarce area.

Suggested Citation

  • Fakhereh Alidoost & Alfred Stein & Zhongbo Su, 2019. "The use of bivariate copulas for bias correction of reanalysis air temperature data," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-22, May.
    • Handle: RePEc:plo:pone00:0216059
    DOI: 10.1371/journal.pone.0216059
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    References listed on IDEAS

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    1. V. Durai & Rashmi Bhradwaj, 2014. "Evaluation of statistical bias correction methods for numerical weather prediction model forecasts of maximum and minimum temperatures," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(3), pages 1229-1254, September.
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    1. Khun La Yaung & Amnat Chidthaisong & Atsamon Limsakul & Pariwate Varnakovida & Can Trong Nguyen, 2021. "Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand," Sustainability, MDPI, vol. 13(19), pages 1-21, October.

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