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Title: Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

Journal Article · · Advances in Meteorology
DOI:https://doi.org/10.1155/2016/7957490· OSTI ID:1268267
 [1];  [1];  [1]
  1. Korea Univ., Seoul (Republic of Korea). School of Civil, Environmental and Architectural Engineering, College of Engineering

This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO2) and 2x CO2conditions. As a result of this study, the increase or decrease in the mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.

Research Organization:
Korea Univ., Seoul (Republic of Korea)
Sponsoring Organization:
Advanced Water Management Research Program - Ministry of Land, Infrastructure and Transport of Korean Government; USDOE
OSTI ID:
1268267
Journal Information:
Advances in Meteorology, Vol. 2016; ISSN 1687-9309
Publisher:
HindawiCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

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