불확실성을 고려한 기후변화 예측: 2. 내적 변동성 = Projection of Climate Change with Uncertainties: 2. Internal Variability

국문 초록 (Abstract)

연구 I(김종호 등, 2014)의 GCMs앙상블과 이산화탄소 시나리오에서 오는 불확실성과, 본 연구에서 수행한 내적 변동으로부터 오는 불확실성을 고려하는 것은 기후변화 예측연구에 있어서 가장 중요한 요소들 중 하나이다. 본 연구에서는 일기발생기를 이용하여 기온과 강수량에 대한 3,000년에 해당하는 시계열을 3기간(2011-2040년, 2041-2070년, 2071-2100년)과 2개의 이산화탄소 시나리오(RCP4.5, RCP8.5)에 대해 생성하였고, 시계열로부터 자연적으로 발생하는 기후의 변동 정도를 수치화하였다. 세가지 원인에 의한 불확실성을 서로 비교한 결과, 강수량에 대해서는 미래기간에 관계없이 내적 원인으로 발생하는 기후의 변동성이 가장 크며, 기온에 대해서는 현재와 멀어질수록 외적 원인으로 발생하는 기후 변동이 지배적임을 확인할 수 있었다.

다국어 초록 (Multilingual Abstract)

When projecting climate change on future, considering uncertainties due to multiple GCMs and emission scenarios carried out in the previous companion paper and that caused by climate internal variability addressed in this paper is one of the most crucial factors. In this study, a weather generator is employed to generate a time series corresponding to 3,000 years of temperature and precipitation for three future periods, 2011-2040, 2041-2070, 2071-2100, and two emission scenarios, RCP4.5 and RCP8.5, from which the information on climate natural variability was quantified. The comparisons among 3 uncertainty bounds have concluded that for precipitation, the climate internal variability is most significant regardless of time windows while for temperature, the uncertainty by emission scenarios tends to increase as the time passes.

참고문헌 (Reference)

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