Evaluating the Impact of Land Cover and Topography on Meteorological Parameters’ Relations and Similarities in the Alberta Oil Sands Region

Herein, the focus was on the identification of similarities in the weather parameters collected within 19 stations, consisting of 3 weather networks located in the Lower Athabasca River Basin operated under the Oil Sands Monitoring program. These stations were then categorised into seven distinct gr...

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Bibliographic Details
Published in:Applied Sciences
Main Authors: Dhananjay Deshmukh, M. Razu Ahmed, John Albino Dominic, Mohamed S. Zaghloul, Anil Gupta, Gopal Achari, Quazi K. Hassan
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2022
Subjects:
Athabasca River Basin
network optimization
redundancy analysis
weather parameters
Technology
T
Engineering (General). Civil engineering (General)
TA1-2040
Biology (General)
QH301-705.5
Physics
QC1-999
Chemistry
QD1-999
Athabasca River
Online Access:https://doi.org/10.3390/app122312004
https://doaj.org/article/af4c82dae1f64876874374bdd7e26ddf
Description
Summary:Herein, the focus was on the identification of similarities in the weather parameters collected within 19 stations, consisting of 3 weather networks located in the Lower Athabasca River Basin operated under the Oil Sands Monitoring program. These stations were then categorised into seven distinct groups based on comparable topography and land cover. With regard to weather parameters, these were air temperature (AT), precipitation (PR), relative humidity (RH), solar radiation (SR), atmospheric/barometric pressure (BP), snowfall depth (SD), and wind speed/direction (WSD). For all seven groups, relational analysis was conducted for every station pair using Pearson’s coefficient (r) and average absolute error (AAE), except for wind direction and wind speed. Similarity analysis was also performed for each station pair across all seven groups using percentage of similarity (PS) measures. Our similarity analysis revealed that there were no similarities (i.e., PS value < 75%) for: (i) SR, PR, and WSD for all groups; (ii) AT for all groups except group G3; (iii) RH for group G7; and (iv) BP for group G1. This study could potentially be decisive in optimizing or rationalising existing weather networks. Furthermore, it could be constructive in the development of meteorological prediction models for any place and that requires input from surrounding stations.

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