Stochastic bias-correction of daily rainfall scenarios for hydrological applications
The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2011-09-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | http://www.nat-hazards-earth-syst-sci.net/11/2497/2011/nhess-11-2497-2011.pdf |
| _version_ | 1818357439458705408 |
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| author | I. Portoghese E. Bruno N. Guyennon V. Iacobellis |
| author_facet | I. Portoghese E. Bruno N. Guyennon V. Iacobellis |
| author_sort | I. Portoghese |
| collection | DOAJ |
| description | The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge. <br><br> In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM) was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists. |
| first_indexed | 2024-12-13T20:13:08Z |
| format | Article |
| id | doaj.art-32ab2da519124e6a82c83eaa2caeff33 |
| institution | Directory Open Access Journal |
| issn | 1561-8633 1684-9981 |
| language | English |
| last_indexed | 2024-12-13T20:13:08Z |
| publishDate | 2011-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj.art-32ab2da519124e6a82c83eaa2caeff332022-12-21T23:32:53ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812011-09-011192497250910.5194/nhess-11-2497-2011Stochastic bias-correction of daily rainfall scenarios for hydrological applicationsI. PortogheseE. BrunoN. GuyennonV. IacobellisThe accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge. <br><br> In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM) was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.http://www.nat-hazards-earth-syst-sci.net/11/2497/2011/nhess-11-2497-2011.pdf |
| spellingShingle | I. Portoghese E. Bruno N. Guyennon V. Iacobellis Stochastic bias-correction of daily rainfall scenarios for hydrological applications Natural Hazards and Earth System Sciences |
| title | Stochastic bias-correction of daily rainfall scenarios for hydrological applications |
| title_full | Stochastic bias-correction of daily rainfall scenarios for hydrological applications |
| title_fullStr | Stochastic bias-correction of daily rainfall scenarios for hydrological applications |
| title_full_unstemmed | Stochastic bias-correction of daily rainfall scenarios for hydrological applications |
| title_short | Stochastic bias-correction of daily rainfall scenarios for hydrological applications |
| title_sort | stochastic bias correction of daily rainfall scenarios for hydrological applications |
| url | http://www.nat-hazards-earth-syst-sci.net/11/2497/2011/nhess-11-2497-2011.pdf |
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