Abstract
Even though rain rate is notorious for its spatial and temporal intermittency, its effect on the second-order statistics of rain rate, especially the inter-station correlation coefficients, has not been intensively evaluated before. This study has derived and compared the inter-station correlation coefficient of rain rate for three cases of data: (1) only the positive measurements at both locations; (2) the positive measurements at either one or both locations; (3) all the measurements including zero measurement at both locations. For these three cases, the inter-station correlation coefficients are analytically derived by applying the mixed bivariate log-normal distribution. As an application example, the model parameters are estimated using the rain rate data collected at the Geum River basin, Korea, and the resulting inter-station correlation coefficients are evaluated and compared with those estimated by applying the Gaussian distribution. We could find that highly biased inter-station correlation coefficients are unavoidable when simply estimating them under the assumption of Gaussian distribution, or even when using the log-transformed rain rate data.
| Original language | English |
|---|---|
| Pages (from-to) | 3078-3086 |
| Number of pages | 9 |
| Journal | Hydrological Processes |
| Volume | 21 |
| Issue number | 22 |
| DOIs | |
| Publication status | Published - 2007 Oct 30 |
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Keywords
- Bivariate mixed distribution
- Inter-station correlation coefficient
- Intermittency
- Log-normal distribution
- Rain rate
ASJC Scopus subject areas
- Water Science and Technology
Cite this
Use of mixed bivariate distributions for deriving inter-station correlation coefficients of rain rate. / Ha, Eunho; Yoo, Chulsang.
In: Hydrological Processes, Vol. 21, No. 22, 30.10.2007, p. 3078-3086.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Use of mixed bivariate distributions for deriving inter-station correlation coefficients of rain rate
AU - Ha, Eunho
AU - Yoo, Chulsang
PY - 2007/10/30
Y1 - 2007/10/30
N2 - Even though rain rate is notorious for its spatial and temporal intermittency, its effect on the second-order statistics of rain rate, especially the inter-station correlation coefficients, has not been intensively evaluated before. This study has derived and compared the inter-station correlation coefficient of rain rate for three cases of data: (1) only the positive measurements at both locations; (2) the positive measurements at either one or both locations; (3) all the measurements including zero measurement at both locations. For these three cases, the inter-station correlation coefficients are analytically derived by applying the mixed bivariate log-normal distribution. As an application example, the model parameters are estimated using the rain rate data collected at the Geum River basin, Korea, and the resulting inter-station correlation coefficients are evaluated and compared with those estimated by applying the Gaussian distribution. We could find that highly biased inter-station correlation coefficients are unavoidable when simply estimating them under the assumption of Gaussian distribution, or even when using the log-transformed rain rate data.
AB - Even though rain rate is notorious for its spatial and temporal intermittency, its effect on the second-order statistics of rain rate, especially the inter-station correlation coefficients, has not been intensively evaluated before. This study has derived and compared the inter-station correlation coefficient of rain rate for three cases of data: (1) only the positive measurements at both locations; (2) the positive measurements at either one or both locations; (3) all the measurements including zero measurement at both locations. For these three cases, the inter-station correlation coefficients are analytically derived by applying the mixed bivariate log-normal distribution. As an application example, the model parameters are estimated using the rain rate data collected at the Geum River basin, Korea, and the resulting inter-station correlation coefficients are evaluated and compared with those estimated by applying the Gaussian distribution. We could find that highly biased inter-station correlation coefficients are unavoidable when simply estimating them under the assumption of Gaussian distribution, or even when using the log-transformed rain rate data.
KW - Bivariate mixed distribution
KW - Inter-station correlation coefficient
KW - Intermittency
KW - Log-normal distribution
KW - Rain rate
UR - http://www.scopus.com/inward/record.url?scp=35748939059&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35748939059&partnerID=8YFLogxK
U2 - 10.1002/hyp.6526
DO - 10.1002/hyp.6526
M3 - Article
AN - SCOPUS:35748939059
VL - 21
SP - 3078
EP - 3086
JO - Hydrological Processes
JF - Hydrological Processes
SN - 0885-6087
IS - 22
ER -