Dynamical downscaling of future projections of climate over the Korean Peninsula using Pseudo Global Warming method.

DC Field Value Language
dc.contributor.author 정춘용 -
dc.contributor.author 장찬주 -
dc.contributor.author 김형진 -
dc.contributor.author 권민호 -
dc.date.accessioned 2020-07-16T07:52:24Z -
dc.date.available 2020-07-16T07:52:24Z -
dc.date.created 2020-02-11 -
dc.date.issued 2013-09-12 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/26790 -
dc.description.abstract Global climate change induced by an increased level of greenhouse gases is typically estimated by global general circulation model (GCMs). However, this approach has been difficult to provide regional details due to GCM’s limitations in horizontal resolution as well as in physical parameterizations. To overcome such difficulty, downscaling methods have been proposed, through which local to regional climatic conditions can be produced in greater details. Two major techniques include dynamical downscaling, where GCM output is used to drive a regional model with higher spatiotemporal resolution and more sophiscated physcal schemes, and statistical downscaling, where an observed statistical relationship between large-scale and local variables is applied to GCM simulation results to extract small-scale information (Murphy 1999 Wood et al. 2004 Wang et al. 2004). The conventional dynamical downscaling utilizes GCM outputs as initial and lateral boundary conditions. In comparison, the Pseudo Global Warming Method (PGWM) introduced recently by Kimura (2007) and Sato et al. (2007) adopts a mixture of observations and GCM simulations to carry out regional climate model (RCM) simulation. The present study aims to investigate climate change in an anthropogenically warmed climate with the aid of the PGWM, with particular focus on the summer rainfall variability over East Asia.orizontal resolution as well as in physical parameterizations. To overcome such difficulty, downscaling methods have been proposed, through which local to regional climatic conditions can be produced in greater details. Two major techniques include dynamical downscaling, where GCM output is used to drive a regional model with higher spatiotemporal resolution and more sophiscated physcal schemes, and statistical downscaling, where an observed statistical relationship between large-scale and local variables is applied to GCM simulation results to extract small-scale information (Murphy 1999 Wood et al. 2004 Wang et al. 2004). The conventional dynamical downscaling utilizes GCM outputs as initial and lateral boundary conditions. In comparison, the Pseudo Global Warming Method (PGWM) introduced recently by Kimura (2007) and Sato et al. (2007) adopts a mixture of observations and GCM simulations to carry out regional climate model (RCM) simulation. The present study aims to investigate climate change in an anthropogenically warmed climate with the aid of the PGWM, with particular focus on the summer rainfall variability over East Asia. -
dc.description.uri 1 -
dc.language English -
dc.publisher 서울대 -
dc.relation.isPartOf International Workshop Regional Climate Models-Ⅱ -
dc.title Dynamical downscaling of future projections of climate over the Korean Peninsula using Pseudo Global Warming method. -
dc.type Conference -
dc.citation.conferencePlace KO -
dc.citation.endPage 124 -
dc.citation.startPage 118 -
dc.citation.title International Workshop Regional Climate Models-Ⅱ -
dc.identifier.bibliographicCitation International Workshop Regional Climate Models-Ⅱ, pp.118 - 124 -
dc.description.journalClass 1 -
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Marine Environmental & Climate Research Division > Ocean Circulation Research Center > 2. Conference Papers
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