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Evaluation of Simple Statistical Downscaling Methods for Monthly Regional Climate Model Simulations with Respect to the Estimated Changes in Runoff in the Czech Republic

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Abstract

An ensemble of fifteen regional climate model (RCM) simulations has been used to estimate the climate change impacts on runoff and several drought characteristics for 250 basins in the Czech Republic. The scenario series of precipitation and temperature have been derived with four simple statistical downscaling methods (SDMs): the delta change and bias correction method, both in two alternatives considering the changes/biases in the mean, and in the mean and variance. Bootstrap resampling has been used to assess the effect of sampling variability and the differences in the estimated changes in runoff obtained by different SDMs were evaluated. Further simplification of the SDMs (spatial-average changes/biases and ensemble-average changes in precipitation and temperature) have been considered. It was shown, that given the spread between the projections of individual RCM simulations and the sampling variability, the differences in the estimated changes in mean runoff between the SDMs are not very large. The same partly holds also for the effect of spatial averaging. In general, the SDMs accounting for variability have led to smaller decrease (or larger increase) in runoff and the decrease was also smaller for bias correction methods than in the case of delta change methods. In contrast to changes in mean runoff, significant differences between the estimates based on different SDMs were found for the drought characteristics. In addition, the averaging of the changes in precipitation and temperature over the RCMs resulted in much stronger decrease in runoff than indicated by ensemble average changes in runoff.

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Acknowledgements

The research was conducted within a project “Development of information and data support for design of adaptation measures and longterm planning of water resources considering the climate change effects” (TA02020320) financed by the Technology Agency of the Czech Republic. The regional climate model simulations studied in this work were partially funded by the EU FP6 Integrated Project ENSEMBLES (Contract number 505539) whose support is gratefully acknowledged. The ALADIN-CLIMATE/CZ simulation and the gridded observed data were kindly provided by the Czech Hydrometeorological Institute through the research project on Refining of current estimates of impacts of climate change in sectors of water management, agriculture and forestry and proposals of adaptation measures (project No. SP/1a6/108/07) sponsored by Ministry of the Environment of the Czech Republic. All calculations and plotting was made using R (A language and environment for statistical computing). We thank two anonymous reviewers for constructive comments on the paper.

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Authors and Affiliations

  1. Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 21, Prague 6–Suchdol, Czech Republic

    Martin Hanel, Petr Máca, Adam Vizina & Pavel Pech

  2. T. G. Masaryk Water Research Institute, p. r. i., Podbabská 30, 160 00, Prague 6, Czech Republic

    Martin Hanel, Magdalena Mrkvičková & Adam Vizina

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  1. Martin Hanel
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  2. Magdalena Mrkvičková
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Correspondence to Martin Hanel.

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Hanel, M., Mrkvičková, M., Máca, P. et al. Evaluation of Simple Statistical Downscaling Methods for Monthly Regional Climate Model Simulations with Respect to the Estimated Changes in Runoff in the Czech Republic. Water Resour Manage 27, 5261–5279 (2013). https://doi.org/10.1007/s11269-013-0466-1

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