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

dc.contributor.authorZhang, Rong
dc.contributor.authorCorte-Real, Joao
dc.contributor.authorMoreira, Madalena
dc.contributor.authorKilsby, Chris
dc.contributor.authorBurton, Aidan
dc.contributor.authorFowler, Hayley J.
dc.contributor.authorBlenkinsop, Stephen
dc.contributor.authorBirkinshaw, Stephen
dc.contributor.authorForsythe, Nathan
dc.contributor.authorNunes, João P.
dc.contributor.authorSampaio, Elsa
dc.contributor.editorCaloi, Liz
dc.date.accessioned2019-06-17T15:41:23Z
dc.date.available2019-06-17T15:41:23Z
dc.date.issued2019-04-30
dc.description.abstractDownscaling 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‐km2 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.por
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dc.identifier.citationRong Zhang João Corte‐Real Madalena Moreira Chris Kilsby Aidan Burton Hayley J. Fowler Stephen Blenkinsop Stephen Birkinshaw Nathan Forsythe João P. Nunes Elsa Sampaio "Downscaling climate change of mean climatology and extremes of precipitation and temperature: Application to a Mediterranean climate basin" Int Journal Climatology, Doi.org/10.1002/joc.6122por
dc.identifier.doi10.1002/joc.6122por
dc.identifier.scientificarea242por
dc.identifier.urihttps://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6122
dc.identifier.urihttp://hdl.handle.net/10174/25631
dc.language.isoporpor
dc.peerreviewedyespor
dc.publisherInternational Journal of climatologypor
dc.rightsopenAccesspor
dc.subjectdry spellpor
dc.subjectheat wavepor
dc.subjecthydrological impact assessmentpor
dc.subjectMediterranean climatepor
dc.subjectprecipitation modelpor
dc.subjectsecond‐order autoregressive processpor
dc.subjectweather generatorpor
dc.titleDownscaling climate change of mean climatology and extremes of precipitation and temperature: Application to a Mediterranean climate basinpor
dc.typearticlepor
degois.publication.titleInternational Journal of Climatologypor

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