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Title: Impact of global atmospheric reanalyses on statistical precipitation downscaling

Abstract

Statistical downscaling based on a perfect prognosis approach often relies on global reanalyses to infer the statistical relationship between synoptic predictors and the local variable of interest, here daily precipitation. Nowadays, many reanalyses are available and their impact on the downscaled variable is not often considered. The present work assessed the impact of ten reanalyses on the performance of seven variants of analogue methods for statistical precipitation downscaling at 301 stations in Switzerland. Even though the study location is in a data-rich region, significant differences were found between reanalyses and their impact on the performance of the method can be even higher than the choice of the predictor variables. There was no single overall winner, but a selection of recommended reanalyses resulting in higher skill scores depending on the considered predictor variables. The impact of the output spatial resolution was assessed for different types of variables. Output resolutions below one degree were found to be often of low to no interest. Reanalyses with longer archives allow the pool of potential analogues to be increased, resulting in better performance. However, when adding variables affected by errors in a more distant past, the skill score decreased again. The use of multiple membersmore » from two reanalyses was also tested over a recent and a past period. The benefit of using members to increase the performance by better incorporating the uncertainties was found to be limited, and even problematic with methods using multiple analogy levels.« less

Authors:
ORCiD logo [1];  [1]
  1. Univ. of Bern (Switzerland). Oeschger Centre for Climate Change Research and Inst. of Geography
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1565716
Resource Type:
Journal Article
Journal Name:
Climate Dynamics
Additional Journal Information:
Journal Volume: 52; Journal Issue: 9-10; Journal ID: ISSN 0930-7575
Publisher:
Springer-Verlag
Country of Publication:
United States
Language:
English
Subject:
Meteorology & Atmospheric Sciences

Citation Formats

Horton, Pascal, and Brönnimann, Stefan. Impact of global atmospheric reanalyses on statistical precipitation downscaling. United States: N. p., 2018. Web. doi:10.1007/s00382-018-4442-6.
Horton, Pascal, & Brönnimann, Stefan. Impact of global atmospheric reanalyses on statistical precipitation downscaling. United States. doi:10.1007/s00382-018-4442-6.
Horton, Pascal, and Brönnimann, Stefan. Tue . "Impact of global atmospheric reanalyses on statistical precipitation downscaling". United States. doi:10.1007/s00382-018-4442-6.
@article{osti_1565716,
title = {Impact of global atmospheric reanalyses on statistical precipitation downscaling},
author = {Horton, Pascal and Brönnimann, Stefan},
abstractNote = {Statistical downscaling based on a perfect prognosis approach often relies on global reanalyses to infer the statistical relationship between synoptic predictors and the local variable of interest, here daily precipitation. Nowadays, many reanalyses are available and their impact on the downscaled variable is not often considered. The present work assessed the impact of ten reanalyses on the performance of seven variants of analogue methods for statistical precipitation downscaling at 301 stations in Switzerland. Even though the study location is in a data-rich region, significant differences were found between reanalyses and their impact on the performance of the method can be even higher than the choice of the predictor variables. There was no single overall winner, but a selection of recommended reanalyses resulting in higher skill scores depending on the considered predictor variables. The impact of the output spatial resolution was assessed for different types of variables. Output resolutions below one degree were found to be often of low to no interest. Reanalyses with longer archives allow the pool of potential analogues to be increased, resulting in better performance. However, when adding variables affected by errors in a more distant past, the skill score decreased again. The use of multiple members from two reanalyses was also tested over a recent and a past period. The benefit of using members to increase the performance by better incorporating the uncertainties was found to be limited, and even problematic with methods using multiple analogy levels.},
doi = {10.1007/s00382-018-4442-6},
journal = {Climate Dynamics},
issn = {0930-7575},
number = 9-10,
volume = 52,
place = {United States},
year = {2018},
month = {9}
}

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