TY - JOUR
T1 - Use of a dual Kalman filter for real-time correction of mean field bias of radar rain rate
AU - Kim, Jungho
AU - Yoo, Chulsang
N1 - Funding Information:
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) Grant funded by the Ministry of Eduacation and Technology (No. 2010-0014566 and No. 2013-0110-12 ).
Publisher Copyright:
© 2014.
PY - 2014/11/27
Y1 - 2014/11/27
N2 - This study applied a dual Kalman filter (DKF) for real-time correction of the mean-field bias of radar rain rate. The DKF is a dual estimation system, and is different from the conventional Kalman filter (KF). The DKF is composed of a state estimation system and a model estimation system, thus it operates two KFs. The state estimate system is the same as the conventional KF, but the model estimation system continuously updates the model parameters. The DKF was applied to four radar stations in Korea; the Kwanaksan Radar, Osungsan Radar, Jindo Radar and Kudeoksan Radar. As a result, it was found that the DKF can be superior to the KF application when the temporal variability of the G/R (rain gauge rain rate/radar rain rate) ratio is very high. Additionally, the application of the DKF for a short-duration severe storm event should be emphasized. In particular, for a flash flood warning system, the DKF application can have a special meaning; that of improving the quality of the radar rain rate data.
AB - This study applied a dual Kalman filter (DKF) for real-time correction of the mean-field bias of radar rain rate. The DKF is a dual estimation system, and is different from the conventional Kalman filter (KF). The DKF is composed of a state estimation system and a model estimation system, thus it operates two KFs. The state estimate system is the same as the conventional KF, but the model estimation system continuously updates the model parameters. The DKF was applied to four radar stations in Korea; the Kwanaksan Radar, Osungsan Radar, Jindo Radar and Kudeoksan Radar. As a result, it was found that the DKF can be superior to the KF application when the temporal variability of the G/R (rain gauge rain rate/radar rain rate) ratio is very high. Additionally, the application of the DKF for a short-duration severe storm event should be emphasized. In particular, for a flash flood warning system, the DKF application can have a special meaning; that of improving the quality of the radar rain rate data.
KW - Dual Kalman filter
KW - G/R ratio
KW - Mean field bias correction
UR - http://www.scopus.com/inward/record.url?scp=84918769489&partnerID=8YFLogxK
U2 - 10.1016/j.jhydrol.2014.09.072
DO - 10.1016/j.jhydrol.2014.09.072
M3 - Article
AN - SCOPUS:84918769489
VL - 519
SP - 2785
EP - 2796
JO - Journal of Hydrology
JF - Journal of Hydrology
SN - 0022-1694
IS - PD
ER -