Abstract
This study 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.
Highlights
To assess the impacts of climate change on regional or local water resources, hydrological modeling with hypothetical climate input has been used
This study evaluated the effects of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity
We assumed that the mechanism of rainfall occurrences follows the first-order Markov chain model
Summary
To assess the impacts of climate change on regional or local water resources, hydrological modeling with hypothetical climate input has been used. Mean air temperature is known to have higher precision than daily rainfall [20] For this reason, the GCM outputs are interpreted as alternative climate scenarios rather than predictions [21]. To evaluate the impact of climate change on daily rainfall using the Markov chain model, we began by investigating the historic measurements of daily rainfall to quantify the transition characteristics between wet and dry days depending on the monthly rainfall amount. This is basically to estimate the changes of the transition probabilities of wet to wet, wet to dry, dry to wet, and dry to dry conditions due to the climate change. This study will lead us to know more detailed information about the rainfall pattern due to the climate change
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