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http://dx.doi.org/10.7780/kjrs.2016.32.3.11

Relationship between temporal variability of TPW and climate variables  

Lee, Darae (Department of Spatial Information Engineering, Pukyong National University)
Han, Kyung-Soo (Department of Spatial Information Engineering, Pukyong National University)
Kwon, Chaeyoung (Department of Spatial Information Engineering, Pukyong National University)
Lee, Kyeong-sang (Department of Spatial Information Engineering, Pukyong National University)
Seo, Minji (Department of Spatial Information Engineering, Pukyong National University)
Choi, Sungwon (Department of Spatial Information Engineering, Pukyong National University)
Seong, Noh-hun (Department of Spatial Information Engineering, Pukyong National University)
Lee, Chang-suk (Department of Spatial Information Engineering, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.32, no.3, 2016 , pp. 331-337 More about this Journal
Abstract
Water vapor is main absorption factor of outgoing longwave radiation. So, it is essential to monitoring the changes in the amount of water vapor and to understanding the causes of such changes. In this study, we monitor temporal variability of Total Precipitable Water (TPW) which observed by satellite. Among climate variables, precipitation play an important part to analyze temporal variability of water vapor because it is produced by water vapor. And El $Ni{\tilde{n}}o$ is one of climate variables which appear regularly in comparison with the others. Through them, we analyze relationship between temporal variability of TPW and climate variable. In this study, we analyzed long-term change of TPW from Moderate-Resolution Imaging Spectroadiometer (MODIS) data and change of precipitation in middle area of Korea peninsula quantitatively. After these analysis, we compared relation of TPW and precipitation with El $Ni{\tilde{n}}o$. The aim of study is to research El $Ni{\tilde{n}}o$ has an impact on TPW and precipitation change in middle area of Korea peninsula. First of all, we calculated TPW and precipitation from time series analysis quantitatively, and anomaly analysis is performed to analyze their correlation. As a result, TPW and precipitation has correlation mostly but the part had inverse correlation was found. This was compared with El $Ni{\tilde{n}}o$ of anomaly results. As a result, TPW and precipitation had inverse correlation after El $Ni{\tilde{n}}o$ occurred. It was found that El $Ni{\tilde{n}}o$ have a decisive effect on change of TPW and precipitation.
Keywords
TPW; precipitation; ENSO; anomaly;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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