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  Evaluation and Bias correction of regional climate model results using model evaluation measures

Schoetter, R., Hoffmann, P., Rechid, D., & Schlünzen, H. (2012). Evaluation and Bias correction of regional climate model results using model evaluation measures. Journal of Applied Meteorology and Climatology, 51, 1670-1684. doi:10.1175/JAMC-D-11-0161.1.

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 Creators:
Schoetter, Robert, Author
Hoffmann, Peter, Author
Rechid, Diana1, Author           
Schlünzen, Heinke2, Author           
Affiliations:
1Climate Modelling, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_913569              
2B 5 - Urban Systems - Test Bed Hamburg, Research Area B: Climate Manifestations and Impacts, The CliSAP Cluster of Excellence, External Organizations, ou_1863485              

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 Abstract: For the assessment of regional climate change the reliability of the regional climate models needs to be known. The main goal of this paper is to evaluate the quality of climate model data that are used for impact research. Temperature, precipitation, total cloud cover, relative humidity, and wind speed simulated by the regional climate models Climate Local Model (CLM) and Regional Model (REMO) are evaluated for the metropolitan region of Hamburg in northern Germany for the period 1961–2000. The same evaluation is performed for the global climate model ECHAM5 that is used to force the regional climate models. The evaluation is based on comparison of the simulated and observed climatological annual cycles and probability density functions of daily averages. Several model evaluation measures are calculated to assure an objective model evaluation. As a very selective model evaluation measure, the hit rate of the percentiles is introduced for the evaluation of daily averages. The influence of interannual climate variability is considered by determining confidence intervals for the model evaluation measures by bootstrap resampling. Evaluation shows that, with some exceptions, temperature and wind speed are well simulated by the climate models; whereas considerable biases are found for relative humidity, total cloud cover, and precipitation, although not for all models in all seasons. It is shown that model evaluation measures can be used to decide for which meteorological parameters a bias correction is reasonable.

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Language(s): eng - English
 Dates: 2012-09
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1175/JAMC-D-11-0161.1
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Title: Journal of Applied Meteorology and Climatology
Source Genre: Journal
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Pages: - Volume / Issue: 51 Sequence Number: - Start / End Page: 1670 - 1684 Identifier: -