Revised spatial weighting methods for estimation of missing rainfall data

A complete daily rainfall dataset with no missing values is highly in demand for a variety of meteorological and hydrological purposes. In most situations, spatial interpolation techniques such as normal ratio and inverse distance methods are used for estimating missing rainfall values at a particul...

Full description

Bibliographic Details
Main Authors: Suhaila, Jamaludin, Sayang, Mohd. Deni, Jemain, Abdul Aziz
Format: Article
Published: 2008
Subjects:
Online Access:http://eprints.utm.my/7639/
_version_ 1848891510558294016
author Suhaila, Jamaludin
Sayang, Mohd. Deni
Jemain, Abdul Aziz
author_facet Suhaila, Jamaludin
Sayang, Mohd. Deni
Jemain, Abdul Aziz
author_sort Suhaila, Jamaludin
building UTeM Institutional Repository
collection Online Access
description A complete daily rainfall dataset with no missing values is highly in demand for a variety of meteorological and hydrological purposes. In most situations, spatial interpolation techniques such as normal ratio and inverse distance methods are used for estimating missing rainfall values at a particular target station based on the available rainfall values recorded at the neighboring stations. Moreover, these two methods are found to be very useful in the case where the neighboring-stations are very close and highly correlated with the target stations. In this study, several modifications and improvements have been proposed to these methods in order to estimate the missing rainfall values at the target station using the information from the nearby stations. The methods have been tested with different percentages of missing rainfall values and also with a radius range of 75 km to 200 km. The result indicate that the performance of these modified methods improved the estimation of missing rainfall values at the target station based on the similarity index (S-index), mean absolute error (MAE) and coefficient of correlation (R).
first_indexed 2025-11-15T20:59:07Z
format Article
id utm-7639
institution Universiti Teknologi Malaysia
institution_category Local University
last_indexed 2025-11-15T20:59:07Z
publishDate 2008
recordtype eprints
repository_type Digital Repository
spelling utm-76392017-10-23T04:18:57Z http://eprints.utm.my/7639/ Revised spatial weighting methods for estimation of missing rainfall data Suhaila, Jamaludin Sayang, Mohd. Deni Jemain, Abdul Aziz QH301 Biology A complete daily rainfall dataset with no missing values is highly in demand for a variety of meteorological and hydrological purposes. In most situations, spatial interpolation techniques such as normal ratio and inverse distance methods are used for estimating missing rainfall values at a particular target station based on the available rainfall values recorded at the neighboring stations. Moreover, these two methods are found to be very useful in the case where the neighboring-stations are very close and highly correlated with the target stations. In this study, several modifications and improvements have been proposed to these methods in order to estimate the missing rainfall values at the target station using the information from the nearby stations. The methods have been tested with different percentages of missing rainfall values and also with a radius range of 75 km to 200 km. The result indicate that the performance of these modified methods improved the estimation of missing rainfall values at the target station based on the similarity index (S-index), mean absolute error (MAE) and coefficient of correlation (R). 2008 Article PeerReviewed Suhaila, Jamaludin and Sayang, Mohd. Deni and Jemain, Abdul Aziz (2008) Revised spatial weighting methods for estimation of missing rainfall data. Asia-Pacific Journal of Atmospheric Sciences, 44 (2). pp. 93-104. https://science.utm.my/shariffah/files/2015/03/7451_APJASApril2008.pdf
spellingShingle QH301 Biology
Suhaila, Jamaludin
Sayang, Mohd. Deni
Jemain, Abdul Aziz
Revised spatial weighting methods for estimation of missing rainfall data
title Revised spatial weighting methods for estimation of missing rainfall data
title_full Revised spatial weighting methods for estimation of missing rainfall data
title_fullStr Revised spatial weighting methods for estimation of missing rainfall data
title_full_unstemmed Revised spatial weighting methods for estimation of missing rainfall data
title_short Revised spatial weighting methods for estimation of missing rainfall data
title_sort revised spatial weighting methods for estimation of missing rainfall data
topic QH301 Biology
url http://eprints.utm.my/7639/
http://eprints.utm.my/7639/