Precipitation bias correction of very high resolution regional climate models
Regional climate models are prone to biases in precipitation that are problematic for use in impact models such as hydrology models. A large number of methods have already been proposed aimed at correcting various moments of the rainfall distribution. They all require that the model produce the same...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2013-11-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/17/4379/2013/hess-17-4379-2013.pdf |
| _version_ | 1828486051205742592 |
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| author | D. Argüeso J. P. Evans L. Fita |
| author_facet | D. Argüeso J. P. Evans L. Fita |
| author_sort | D. Argüeso |
| collection | DOAJ |
| description | Regional climate models are prone to biases in precipitation that are
problematic for use in impact models such as hydrology models. A large number
of methods have already been proposed aimed at correcting various moments of
the rainfall distribution. They all require that the model produce the same
or a higher number of rain days than the observational data sets, which are
usually gridded data sets. Models have traditionally met this condition
because their spatial resolution was coarser than the observational grids.
But recent climate simulations use higher resolution and the models are
likely to systematically produce fewer rain days than the gridded
observations.
<br><br>
In this study, model outputs from a simulation at 2 km resolution are
compared with gridded and in situ observational data sets to determine whether
the new scenario calls for revised methodologies. The gridded observations
are found to be inadequate to correct the high-resolution model at daily
timescales, because they are subjected to too frequent low intensity
precipitation due to spatial averaging. A histogram equalisation bias
correction method was adapted to the use of station, alleviating the problems
associated with relative low-resolution observational grids. The wet-day
frequency condition might not be satisfied for extremely dry biases, but the
proposed approach substantially increases the applicability of bias
correction to high-resolution models. The method is efficient at bias
correcting both seasonal and daily characteristic of precipitation, providing
more accurate information that is crucial for impact assessment studies. |
| first_indexed | 2024-12-11T09:26:12Z |
| format | Article |
| id | doaj.art-659479f4f30f422cb006a420f6b2a0bb |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-11T09:26:12Z |
| publishDate | 2013-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-659479f4f30f422cb006a420f6b2a0bb2022-12-22T01:13:08ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382013-11-0117114379438810.5194/hess-17-4379-2013Precipitation bias correction of very high resolution regional climate modelsD. Argüeso0J. P. Evans1L. Fita2Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, AustraliaClimate Change Research Centre, University of New South Wales, Sydney, NSW 2052, AustraliaClimate Change Research Centre, University of New South Wales, Sydney, NSW 2052, AustraliaRegional climate models are prone to biases in precipitation that are problematic for use in impact models such as hydrology models. A large number of methods have already been proposed aimed at correcting various moments of the rainfall distribution. They all require that the model produce the same or a higher number of rain days than the observational data sets, which are usually gridded data sets. Models have traditionally met this condition because their spatial resolution was coarser than the observational grids. But recent climate simulations use higher resolution and the models are likely to systematically produce fewer rain days than the gridded observations. <br><br> In this study, model outputs from a simulation at 2 km resolution are compared with gridded and in situ observational data sets to determine whether the new scenario calls for revised methodologies. The gridded observations are found to be inadequate to correct the high-resolution model at daily timescales, because they are subjected to too frequent low intensity precipitation due to spatial averaging. A histogram equalisation bias correction method was adapted to the use of station, alleviating the problems associated with relative low-resolution observational grids. The wet-day frequency condition might not be satisfied for extremely dry biases, but the proposed approach substantially increases the applicability of bias correction to high-resolution models. The method is efficient at bias correcting both seasonal and daily characteristic of precipitation, providing more accurate information that is crucial for impact assessment studies.http://www.hydrol-earth-syst-sci.net/17/4379/2013/hess-17-4379-2013.pdf |
| spellingShingle | D. Argüeso J. P. Evans L. Fita Precipitation bias correction of very high resolution regional climate models Hydrology and Earth System Sciences |
| title | Precipitation bias correction of very high resolution regional climate models |
| title_full | Precipitation bias correction of very high resolution regional climate models |
| title_fullStr | Precipitation bias correction of very high resolution regional climate models |
| title_full_unstemmed | Precipitation bias correction of very high resolution regional climate models |
| title_short | Precipitation bias correction of very high resolution regional climate models |
| title_sort | precipitation bias correction of very high resolution regional climate models |
| url | http://www.hydrol-earth-syst-sci.net/17/4379/2013/hess-17-4379-2013.pdf |
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