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  Statistical precipitation bias correction of gridded model data using point measurements

Haerter, J., Eggert, B., Moseley, C., Piani, C., & Berg, P. (2015). Statistical precipitation bias correction of gridded model data using point measurements. Geophysical Research Letters, 42, 1919-1929. doi:10.1002/2015GL063188.

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Haerter, J.O., Author
Eggert, B., Author
Moseley, Christopher1, Author           
Piani, C., Author
Berg, P., Author
Affiliations:
1Climate Modelling, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society, ou_913569              

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Free keywords: climate model; extreme events; precipitation; rain gauge; statistical bias correction
 Abstract: It is well known that climate model output data cannot be used directly as input to impact models, e.g., hydrology models, due to climate model errors. Recently, it has become customary to apply statistical bias correction to achieve better statistical correspondence to observational data. As climate model output should be interpreted as the space-time average over a given model grid box and output time step, the status quo in bias correction is to employ matching gridded observational data to yield optimal results. Here we show that when gridded observational data are not available, statistical bias correction can be carried out using point measurements, e.g., rain gauges. Our nonparametric method, which we call scale-adapted statistical bias correction (SABC), is achieved by data aggregation of either the available modeled or gauge data. SABC is a straightforward application of the well-known Taylor hypothesis of frozen turbulence. Using climate model and rain gauge data, we show that SABC performs significantly better than equal-time period statistical bias correction. Key Points Statistical bias correction using station data Improved corrections through scale adaptation Additional applications when comparing to station data for extreme events ©2015. American Geophysical Union. All Rights Reserved.

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Language(s): eng - English
 Dates: 2015-03-28
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/2015GL063188
 Degree: -

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Title: Geophysical Research Letters
  Abbreviation : GRL
Source Genre: Journal
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Publ. Info: Washington, D.C. : American Geophysical Union
Pages: - Volume / Issue: 42 Sequence Number: - Start / End Page: 1919 - 1929 Identifier: ISSN: 0094-8276
CoNE: https://pure.mpg.de/cone/journals/resource/954925465217