Estimation of monsoon rainfall by single polarization weather radar

Weather radar can offer synoptic measurement at a higher temporal and spatial resolution to extract the rain information. Rainfall can be inverted from the radar reflectivity using the power-law relation to ground rain gauge measurement. The relationship known as Z-R model has been established in ma...

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Main Author:	Roslan, Nurulhani
Format:	Thesis
Language:	English
Published:	2021
Subjects:	G70.212-70.215 Geographic information system
Online Access:	http://eprints.utm.my/id/eprint/96187/1/NurulhaniRoslanPFABU2021.pdf.pdf
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spelling	my-utm-ep.961872022-07-25T04:37:12Z Estimation of monsoon rainfall by single polarization weather radar 2021 Roslan, Nurulhani G70.212-70.215 Geographic information system Weather radar can offer synoptic measurement at a higher temporal and spatial resolution to extract the rain information. Rainfall can be inverted from the radar reflectivity using the power-law relation to ground rain gauge measurement. The relationship known as Z-R model has been established in many variants but the uncertainty from the sampling bias and the Z-R variability of single-polarization radar observation on monsoon rain becomes subject to research. This study reports a novel research framework to systematically estimate the monsoon rainfall using new Z-R model on the single-polarization weather radar in Kelantan. The sampling bias was quantified by the pixel matching procedure while the non-linear Levenberg Marquardt (LM) regression and the Artificial Neural Network (ANN) regression at different rain intensity and radar range were introduced to minimise the Spatio-temporal variability of the new Z-R model. This study uses 10-minute reflectivity data recorded in Kota Bahru radar station and hourly rain record at the nearby 58 gauge stations in 2013 to 2015. The three-dimensional nearest neighbour interpolation proves that the sampling bias can be quantified. The LM shows an improvement of about 12% if the spatial adjustment was applied in the regression. Unlike LM, the ANN is more robust and independent to the spatial adjustment thus it could provide more accurate and reliable monsoon rain information in heterogenous rainy condition. The ANN model provides accuracy of ± 0.4 mm/hr, ± 1.0 mm/hr and ± 8.2 mm/hr for low, medium and high rain intensity respectively with correlation coefficient > 0.7 (p < 0.05). Comparing to other Z-R models, the ANN gives model efficiency ratio of > 0.5 and accuracy improvement about 8 %, 10% and 5% for abovementioned rain intensity respectively. Radar derived rainfall maps present the rain distribution was more concentrated in all downstream but only covered 1/3 of the upstream in Kelantan rivers. Further research is needed before the technique could be applied to any single-polarization system in Southeast Asia to achieve better accuracy of rain information extraction. 2021 Thesis http://eprints.utm.my/id/eprint/96187/ http://eprints.utm.my/id/eprint/96187/1/NurulhaniRoslanPFABU2021.pdf.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:142739 phd doctoral Universiti Teknologi Malaysia Faculty of Built Environment & Surveying
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	G70.212-70.215 Geographic information system
spellingShingle	G70.212-70.215 Geographic information system Roslan, Nurulhani Estimation of monsoon rainfall by single polarization weather radar
description	Weather radar can offer synoptic measurement at a higher temporal and spatial resolution to extract the rain information. Rainfall can be inverted from the radar reflectivity using the power-law relation to ground rain gauge measurement. The relationship known as Z-R model has been established in many variants but the uncertainty from the sampling bias and the Z-R variability of single-polarization radar observation on monsoon rain becomes subject to research. This study reports a novel research framework to systematically estimate the monsoon rainfall using new Z-R model on the single-polarization weather radar in Kelantan. The sampling bias was quantified by the pixel matching procedure while the non-linear Levenberg Marquardt (LM) regression and the Artificial Neural Network (ANN) regression at different rain intensity and radar range were introduced to minimise the Spatio-temporal variability of the new Z-R model. This study uses 10-minute reflectivity data recorded in Kota Bahru radar station and hourly rain record at the nearby 58 gauge stations in 2013 to 2015. The three-dimensional nearest neighbour interpolation proves that the sampling bias can be quantified. The LM shows an improvement of about 12% if the spatial adjustment was applied in the regression. Unlike LM, the ANN is more robust and independent to the spatial adjustment thus it could provide more accurate and reliable monsoon rain information in heterogenous rainy condition. The ANN model provides accuracy of ± 0.4 mm/hr, ± 1.0 mm/hr and ± 8.2 mm/hr for low, medium and high rain intensity respectively with correlation coefficient > 0.7 (p < 0.05). Comparing to other Z-R models, the ANN gives model efficiency ratio of > 0.5 and accuracy improvement about 8 %, 10% and 5% for abovementioned rain intensity respectively. Radar derived rainfall maps present the rain distribution was more concentrated in all downstream but only covered 1/3 of the upstream in Kelantan rivers. Further research is needed before the technique could be applied to any single-polarization system in Southeast Asia to achieve better accuracy of rain information extraction.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Roslan, Nurulhani
author_facet	Roslan, Nurulhani
author_sort	Roslan, Nurulhani
title	Estimation of monsoon rainfall by single polarization weather radar
title_short	Estimation of monsoon rainfall by single polarization weather radar
title_full	Estimation of monsoon rainfall by single polarization weather radar
title_fullStr	Estimation of monsoon rainfall by single polarization weather radar
title_full_unstemmed	Estimation of monsoon rainfall by single polarization weather radar
title_sort	estimation of monsoon rainfall by single polarization weather radar
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Built Environment & Surveying
publishDate	2021
url	http://eprints.utm.my/id/eprint/96187/1/NurulhaniRoslanPFABU2021.pdf.pdf
_version_	1747818644595802112

Estimation of monsoon rainfall by single polarization weather radar

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