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Downscaling climate change of mean climatology and extremes of precipitation and temperature: Application to a Mediterranean climate basin

Rong Zhang; João Corte‐Real; Madalena Moreira; Chris Kilsby; Aidan Burton; Hayley J. Fowler; Stephen Blenkinsop; Stephen Birkinshaw; Nathan Forsythe; João P. Nunes; Elsa Sampaio
International Journal of Climatology · Vol. 39, Issue 13 · pp. 4985-5005 · 2019

Abstract

Downscaling is usually necessary for robust hydrological impact assessments. This may be undertaken using a wide range of methods, including a combination of dynamical and statistical‐stochastic downscaling. This study uses the Spatial–Temporal Neyman‐Scott Rectangular Pulses model—RainSimV3, the precipitation‐conditioned daily weather generator—ICAAM‐WG, and the change factor approach for downscaling synthetic climate scenarios for robust hydrological impact assessment at middle‐sized basins. The ICAAM‐WG was developed based on the concept of the Climate Research Unit daily weather generator (CRU‐WG), motivated by the need for improved representation of heat waves by downscaling methods given the positive feedback between low soil moisture and high air temperature. We demonstrated the validity of the proposed methodology in the 705‐km 2 Mediterranean climate basin in southern Portugal. The results show that, for the control period 1980–2010, both RainSimV3 and ICAAM‐WG reproduced not only the mean climatology, but also extreme wet and low precipitation events, as well as the extremes of temperature and heat waves. We found that downscaling with ICAAM‐WG (SIM6), which uses second‐order autoregressive processes for the simulation of temperature during consecutive dry and wet days, outperformed ICAAM‐WG (SIM4), which used only first‐order autoregressive processes, leading to improved simulation of heat waves. ICAAM‐WG (SIM6) well reproduced observed heatwave extremes with return periods of up to 30 years; however, ICAAM‐WG (SIM4) overestimated these extremes substantially. This indicates the importance of incorporating second‐order autoregressive processes in the simulation of heatwave length. In the context of climate warming, the proposed methodology provides a tool to improve downscaled projections of future extremes with confidence intervals for not only wet events but also dry spells and heat waves.

Bibliographic Information

JournalInternational Journal of Climatology
PublisherWiley
Publication Date2019-11-15
Publication Year2019
Volume39
Issue13
Pages4985-5005
Document TypeJournal Article
Print ISSN0899-8418
eISSN1097-0088
DOI10.1002/joc.6122
SubjectAtmospheric Sciences

Access Information

NARA Access Coverage1996-01-01~Current
Journal Homepagehttps://rmets.onlinelibrary.wiley.com/loi/10970088
Publisher PageOpen Publisher Page
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