JOURNAL ARTICLE

Improving Spatial Rainfall Estimates at Mt. Merapi Area Using Radar-Rain Gauge Conditional Merging

Roby HambaliDjoko LegonoRachmad JayadiSatoru Oishi

Year: 2019 Journal:   Journal of Disaster Research Vol: 14 (1)Pages: 69-79   Publisher: Fuji Technology Press Ltd.

Abstract

Rainfall monitoring is important for providing early warning of lahar flow around Mt. Merapi. The X-band multi-parameter radar developed to support these warning systems provides rainfall information with high spatial and temporal resolution. However, this method underestimates the rainfall compared with rain gauge measurements. Herein, we performed conditional radar-rain gauge merging to obtain the optimal rainfall value distribution. By using the cokriging interpolation method, kriged gauge rainfall, and kriged radar rainfall data were obtained, which were then combined with radar rainfall data to yield the adjusted spatial rainfall. Radar-rain gauge conditional merging with cokriging interpolation provided reasonably well-adjusted spatial rainfall pattern.

Keywords:
Rain gauge Radar Meteorology Interpolation (computer graphics) Spatial dependence Spatial variability Environmental science Multivariate interpolation Spatial distribution Remote sensing Geology Geography Precipitation Mathematics Computer science Statistics

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Citation History

Topics

Precipitation Measurement and Analysis
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Soil Moisture and Remote Sensing
Physical Sciences →  Environmental Science →  Environmental Engineering
Meteorological Phenomena and Simulations
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
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