Evidence map›Paper›PMID 35025901›Full record

ArticlePloS one

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

Dhananjay Deshmukh, M Razu Ahmed, John Albino Dominic, Mohamed S Zaghloul, Anil Gupta, Gopal Achari, Quazi K Hassan

Abstract read
In one paragraph

Article in PloS one. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Dhananjay DeshmukhSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
M Razu AhmedSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.ORCID https://orcid.org/0000-0002-4771-3353
John Albino DominicSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
Mohamed S ZaghloulSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
Anil GuptaSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
Gopal AchariSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
Quazi K HassanSchulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.ORCID https://orcid.org/0000-0002-7034-359X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ClimateOil and Gas FieldsAlbertaAtmospheric PressureHumidityRainSolar EnergyTemperature

Identifiers

PMID35025901
PMCPMC8758077

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.