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Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region

Our objective was to quantify the similarity in the meteorological measurements of 17 stations under three weather networks in the Alberta oil sands region. The networks were for climate monitoring under the water quantity program (WQP) and air program, including Meteorological Towers (MT) and Edge...

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Autores principales: Deshmukh, Dhananjay, Ahmed, M. Razu, Dominic, John Albino, Zaghloul, Mohamed S., Gupta, Anil, Achari, Gopal, Hassan, Quazi K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758077/
https://www.ncbi.nlm.nih.gov/pubmed/35025901
http://dx.doi.org/10.1371/journal.pone.0261610
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author Deshmukh, Dhananjay
Ahmed, M. Razu
Dominic, John Albino
Zaghloul, Mohamed S.
Gupta, Anil
Achari, Gopal
Hassan, Quazi K.
author_facet Deshmukh, Dhananjay
Ahmed, M. Razu
Dominic, John Albino
Zaghloul, Mohamed S.
Gupta, Anil
Achari, Gopal
Hassan, Quazi K.
author_sort Deshmukh, Dhananjay
collection PubMed
description Our objective was to quantify the similarity in the meteorological measurements of 17 stations under three weather networks in the Alberta oil sands region. The networks were for climate monitoring under the water quantity program (WQP) and air program, including Meteorological Towers (MT) and Edge Sites (ES). The meteorological parameters were air temperature (AT), relative humidity (RH), solar radiation (SR), barometric pressure (BP), precipitation (PR), and snow depth (SD). Among the various measures implemented for finding correlations in this study, we found that the use of Pearson’s coefficient (r) and absolute average error (AAE) would be sufficient. Also, we applied the percent similarity method upon considering at least 75% of the value in finding the similarity between station pairs. Our results showed that we could optimize the networks by selecting the least number of stations (for each network) to describe the measure-variability in meteorological parameters. We identified that five stations are sufficient for the measurement of AT, one for RH, five for SR, three for BP, seven for PR, and two for SD in the WQP network. For the MT network, six for AT, two for RH, six for SR, and four for PR, and the ES network requires six for AT, three for RH, six for SR, and two for BP. This study could potentially be critical to rationalize/optimize weather networks in the study area.
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spelling pubmed-87580772022-01-14 Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region Deshmukh, Dhananjay Ahmed, M. Razu Dominic, John Albino Zaghloul, Mohamed S. Gupta, Anil Achari, Gopal Hassan, Quazi K. PLoS One Research Article Our objective was to quantify the similarity in the meteorological measurements of 17 stations under three weather networks in the Alberta oil sands region. The networks were for climate monitoring under the water quantity program (WQP) and air program, including Meteorological Towers (MT) and Edge Sites (ES). The meteorological parameters were air temperature (AT), relative humidity (RH), solar radiation (SR), barometric pressure (BP), precipitation (PR), and snow depth (SD). Among the various measures implemented for finding correlations in this study, we found that the use of Pearson’s coefficient (r) and absolute average error (AAE) would be sufficient. Also, we applied the percent similarity method upon considering at least 75% of the value in finding the similarity between station pairs. Our results showed that we could optimize the networks by selecting the least number of stations (for each network) to describe the measure-variability in meteorological parameters. We identified that five stations are sufficient for the measurement of AT, one for RH, five for SR, three for BP, seven for PR, and two for SD in the WQP network. For the MT network, six for AT, two for RH, six for SR, and four for PR, and the ES network requires six for AT, three for RH, six for SR, and two for BP. This study could potentially be critical to rationalize/optimize weather networks in the study area. Public Library of Science 2022-01-13 /pmc/articles/PMC8758077/ /pubmed/35025901 http://dx.doi.org/10.1371/journal.pone.0261610 Text en © 2022 Deshmukh et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Deshmukh, Dhananjay
Ahmed, M. Razu
Dominic, John Albino
Zaghloul, Mohamed S.
Gupta, Anil
Achari, Gopal
Hassan, Quazi K.
Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region
title Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region
title_full Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region
title_fullStr Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region
title_full_unstemmed Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region
title_short Quantifying relations and similarities of the meteorological parameters among the weather stations in the Alberta Oil Sands region
title_sort quantifying relations and similarities of the meteorological parameters among the weather stations in the alberta oil sands region
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758077/
https://www.ncbi.nlm.nih.gov/pubmed/35025901
http://dx.doi.org/10.1371/journal.pone.0261610
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