Temporal precipitation estimation from nearby radar reflectivity using dynamic factor analysis in the mountainous watershed – a case during Typhoon Morakot. Issue 3 (17th December 2012)

• Record Type: Journal Article
• Authors: Kuo, Yi‐Ming; Chu, Hone‐Jay; Pan, Tsung‐Yi
• Is Part Of: Hydrological processes. Volume 28:Issue 3(2014:Jan.)
• Page Start: 999
• Page End: 1008
• Publication Date: 2012-12-17
• Subjects: Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.9639
• Languages: English
• ISSNs: 0885-6087

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>The radar reflectivity (Z)–rain intensity (R) relationship fluctuates in both temporal and spatial scales. The dynamic factor analysis (DFA) and min/max autocorrelation factor analysis (MAFA) was specifically designed for considering various space–time integrations of gauge rainfall and radar reflectivity. We detect representative radar reflectivity observed around rainfall stations that were most responsible for rainfall intensity and identify the crucial patterns of the radar reflectivity in the Kaoping River watershed during Typhoon Morakot. Result shows that the MAFA and DFA can reduce the uncertainty of the dynamic Z‐R relationship effectively. The MAFA separates an entire area into two subareas (southern and northern areas) according to the relationships between the radar reflectivity and min/max autocorrelation factor (MAF) axes. For both areas, the different extents of temporal rainfall correlated with the radar reflectivity were determined using DFA. Especially in the northern area, the radar reflectivity was significantly related to the rainfall intensity for most stations without mountain blockage. Mountain blockages associated with the presence of terrain and wind direction were inferred the major factors that affected the relationship between radar reflectivity and rainfall intensity in the mountainous watershed. Further study can consider the terrain effect and meteorological information, such as wind speed and direction in the DFA model, with the dominant radar reflectivity to estimate the temporal rainfall patterns. Copyright © 2012 John Wiley & Sons, Ltd.</p> </abstract>