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Extreme precipitation under climate change conditions: Validation of a regional climate model over a small watershed using a spatial disaggregation model.

Gagnon, Patrick; Rousseau, Alain N. (2013). Extreme precipitation under climate change conditions: Validation of a regional climate model over a small watershed using a spatial disaggregation model. In: CMOS-CGU-AMS joint Scientific congress, 26-30 mai 2013, Saskatoon, Canada.

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Résumé

Regional Climate Models (RCMs) are valuable tools to evaluate impacts of climate change (CC) at regional scale. However, as the size of the area of interest decreases, the ability of a RCM to simulate extreme precipitation events decreases due to the RCM spatial resolution. Thus, it is difficult to: (i) evaluate whether a RCM bias on localized extreme precipitation is caused by the spatial resolution or by a misrepresentation of the physical processes by the model and (ii) consequently assess projections of CC impacts for localized extreme precipitation. Spatial statistical disaggregation models can bring the RCM precipitation data at a finer scale and reduce the bias caused by the spatial resolution. In addition, disaggregation models can generate an ensemble of outputs, producing an estimate by interval instead of a unique punctual estimate. The objective of this work is to illustrate how a spatial statistical disaggregation model applied on extreme daily precipitations can provide a framework to assess a RCM for a period of reference and help to evaluate the impacts of CC over a small area. Three simulations of the Canadian RCM (CRCM) covering the period 1961-2099 are used over a small watershed (130 sq km) located in southern Quebec, Canada. The disaggregation model applied is based on Gibbs sampling and accounts for physical properties of the events (wind speed, wind direction, and convective available potential energy (CAPE)), leading to realistic spatial distributions of precipitation. The use of the disaggregation model reduces significantly the impact of the RCM spatial resolution and enables the estimation of the level of significance for the difference between observed and simulated extremes for the reference period. The results indicate that the three simulations tend to overestimate precipitation, but with different levels of significance. When comparing to the RCM raw data, the disaggregation does not affect the CC signal, and does indicate that the impact is statistically significant for each simulation tested.

Type de document: Document issu d'une conférence ou d'un atelier
Mots-clés libres: précipitations; changement climatique; modèle climatique; bassin versant
Centre: Centre Eau Terre Environnement
Date de dépôt: 19 nov. 2020 20:44
Dernière modification: 19 nov. 2020 20:44
URI: http://espace.inrs.ca/id/eprint/4418

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