气候变化领域集成服务门户(CCPortal): Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events

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DOI	10.1007/s00382-019-04818-w
	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.
发表日期	2019
ISSN	0930-7575
英文摘要	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. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
语种	英语
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146648
作者单位	Department of Physics, University of Murcia, Murcia, Spain; Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland; Agencia Estatal de Meteorología (AEMET), Murcia, Spain; School of Earth Sciences, The University of Melbourne, Melbourne, VIC, Australia; Department of Geography and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
推荐引用方式 GB/T 7714	Gómez-Navarro J.J.,Raible C.C.,García-Valero J.A.,et al. Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events[J],2019.
APA	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.
MLA	Gómez-Navarro J.J.,et al."Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events".Climate Dynamics (2019).