Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/13620
Title: | A comparison between single site modeling and multiple site modeling approaches using Kalman filtering |
Author: | Monteiro, Magda Costa, Marco |
Keywords: | Time series analysis State space model Rainfall estimates Weather radar Calibration |
Issue Date: | Mar-2015 |
Publisher: | AIP Publishing |
Abstract: | This work presents a comparative study between two approaches to calibrate radar rainfall in real time. The weather radar provides continuous measurements in real-time which have errors of either meteorological or instrumental nature. Locally, gauge measurements have a greater performance than radar measurements that can be used to improve radar estimates. One way of doing that is via a state space representation associated to the Kalman filter algorithm. In the single- site modeling approach we use the linear calibration model applied in [1] and [3] while the multivariate state-space model proposed in [6] is used in the multiple site approach. This work aims to discuss and compare these two different state space formulations based on the same data set. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/13620 |
DOI: | 10.1063/1.4912410 |
Appears in Collections: | CIDMA - Comunicações ESTGA - Comunicações PSG - Comunicações |
Files in This Item:
File | Description | Size | Format | |
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A comparison between single site modeling and multiple site modeling approaches using Kalman filtering ICNAAM2015 Monteiro Costa.pdf | Documento principal | 345.12 kB | Adobe PDF | View/Open |
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