Stochastic precipitation modeling based on Korean historical data

Title
Stochastic precipitation modeling based on Korean historical data
Author(s)
김용구김현정
Keywords
Generalized linear model; overdispersion; precipitation; stochastic weather generator
Issue Date
201211
Publisher
한국데이터정보과학회
Citation
한국데이터정보과학회지, v.23, no.6, pp.1309 - 1317
Abstract
Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is verified that the addition of these covariates does not distort the performance of the weather generator in other respects.
URI
http://hdl.handle.net/YU.REPOSITORY/26892http://dx.doi.org/10.7465/jkdi.2012.23.6.1309
ISSN
1598-9402
Appears in Collections:
이과대학 > 통계학과 > Articles
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