the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Three novel copula-based bias correction methods for daily ECMWF air temperature data
Abstract. Data retrieved from global weather forecast systems are typically biased with respect to measurements at local weather stations. This paper presents three copula-based methods for bias correction of daily air temperature data derived from the European Centre for Medium-range Weather Forecasts (ECMWF). The aim is to predict conditional copula quantiles at different unvisited locations, assuming spatial stationarity of the underlying random field. The three new methods are: bivariate copula quantile mapping (types I and II), and a quantile search. These are compared with commonly applied methods, using data from an agricultural area in the Qazvin Plain in Iran containing five weather stations. Cross-validation is carried out to assess the performance. The study shows that the new methods are able to predict the conditional quantiles at unvisited locations, improve the higher order moments of marginal distributions, and take the spatial variabilities of the bias-corrected variable into account. It further illustrates how a choice of the bias correction method affects the bias-corrected variable and highlights both theoretical and practical issues of the methods. We conclude that the three new methods improve local refinement of weather data, in particular if a low number of observations is available.
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RC1: 'comments to hess-2017-93', Anonymous Referee #1, 16 Mar 2017
- AC1: 'Response to the comments by reviewer 1', Fakhereh Alidoost, 19 May 2017
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RC2: 'Review of the article "Three novel copula-based bias correction methods for daily ECMWF air temperature data" by Alidoost et al., submitted to HESS', Anonymous Referee #2, 23 Mar 2017
- AC2: 'Response to the comments by reviewer 2', Fakhereh Alidoost, 19 May 2017
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RC3: 'Three novel copula-based bias correction methods for daily ECMWF air temperature data', Geoff Pegram, 23 Mar 2017
- AC3: 'Response to the comments by reviewer 3', Fakhereh Alidoost, 19 May 2017
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RC4: 'review comment', Anonymous Referee #4, 10 Apr 2017
- AC4: 'Response to the comments by reviewer 4', Fakhereh Alidoost, 19 May 2017
- AC5: 'Track-change mode manuscript', Fakhereh Alidoost, 19 May 2017
-
RC1: 'comments to hess-2017-93', Anonymous Referee #1, 16 Mar 2017
- AC1: 'Response to the comments by reviewer 1', Fakhereh Alidoost, 19 May 2017
-
RC2: 'Review of the article "Three novel copula-based bias correction methods for daily ECMWF air temperature data" by Alidoost et al., submitted to HESS', Anonymous Referee #2, 23 Mar 2017
- AC2: 'Response to the comments by reviewer 2', Fakhereh Alidoost, 19 May 2017
-
RC3: 'Three novel copula-based bias correction methods for daily ECMWF air temperature data', Geoff Pegram, 23 Mar 2017
- AC3: 'Response to the comments by reviewer 3', Fakhereh Alidoost, 19 May 2017
-
RC4: 'review comment', Anonymous Referee #4, 10 Apr 2017
- AC4: 'Response to the comments by reviewer 4', Fakhereh Alidoost, 19 May 2017
- AC5: 'Track-change mode manuscript', Fakhereh Alidoost, 19 May 2017
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Cited
4 citations as recorded by crossref.
- Bivariate bias correction of the regional climate model ensemble over the Adriatic region R. Sokol Jurković et al. 10.1002/joc.7564
- Linking ECMWF 2 m Temperature Forecast Errors with Upper-Level Circulation Situation: A Case-Study for China X. Wei et al. 10.3390/atmos12060725
- On projected hydrological scenarios under the influence of bias-corrected climatic variables and LULC S. Sahoo et al. 10.1016/j.ecolind.2019.105440
- Bias Correction of RCM Precipitation by TIN-Copula Method: A Case Study for Historical and Future Simulations in Cyprus G. Lazoglou et al. 10.3390/cli8070085