Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events

Gómez-Navarro, J. J.; Raible, C. C.; García-Valero, J. A.; Messmer, M.; Montávez, J. P.; Martius, O. (2019). Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events. Climate dynamics Springer-Verlag 10.1007/s00382-019-04818-w

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This study presents a new dynamical downscaling strategy for extreme events. It is based on a combination of statistical downscaling of coarsely resolved global model simulations and dynamical downscaling of specific extreme events constrained by the statistical downscaling part. The method is applied to precipitation extremes over the upper Aare catchment, an area in Switzerland which is characterized by complex terrain. The statistical downscaling part consists of an Artificial Neural Network (ANN) framework trained in a reference period. Thereby, dynamically downscaled precipitation over the target area serve as predictands and large-scale variables, received from the global model simulation, as predictors. Applying the ANN to long term global simulations produces a precipitation series that acts as a surrogate of the dynamically downscaled precipitation for a longer climate period, and therefore are used in the selection of events. These events are then dynamically downscaled with a regional climate model to 2 km. The results show that this strategy is suitable to constraint extreme precipitation events, although some limitations remain, e.g., the method has lower efficiency in identifying extreme events in summer and the sensitivity of extreme events to climate change is underestimated.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Physics Institute > Climate and Environmental Physics
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography
08 Faculty of Science > Institute of Geography > Physical Geography > Unit Impact
08 Faculty of Science > Institute of Geography > Physical Geography
08 Faculty of Science > Physics Institute

UniBE Contributor:

Raible, Christoph; Messmer, Martina Barbara and Romppainen-Martius, Olivia

Subjects:

500 Science > 530 Physics
500 Science > 550 Earth sciences & geology
900 History > 910 Geography & travel

ISSN:

0930-7575

Publisher:

Springer-Verlag

Language:

English

Submitter:

Hélène Christine Louise Barras

Date Deposited:

13 Feb 2020 09:49

Last Modified:

22 May 2020 02:30

Publisher DOI:

10.1007/s00382-019-04818-w

BORIS DOI:

10.7892/boris.138757

URI:

https://boris.unibe.ch/id/eprint/138757

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