Evaluation and Optimization of Weather Networks in Athabasca Oil Sands Region

• Main Author: Deshmukh, Dhananjay
• Other Authors: Hassan, Quazi, Gupta, Anil, Achari, Gopal
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Schulich School of Engineering 2023
• Subjects: correlation analysis; similarity analysis; weather network optimization; wind speed and direction; rationalization; Athabasca river basin; weather; redundancy; climate; Engineering; Engineering > Environmental; Athabasca River
• Online Access: http://hdl.handle.net/1880/115798; https://doi.org/10.11575/PRISM/40703

The monitoring of weather is required for climate studies, research, and forecasting. For the monitoring purpose, three networks of 19 stations i.e., Water Quantity Program (WQP), Meteorological Towers (MT), and Edge Sites (ES) were operational in Athabasca oil sands region. The overall objective of the study was to identify similarities/redundancies in meteorological observations for the optimization of weather networks. For this, firstly similarity among meteorological parameters have been quantified for air temperature (AT), relative humidity (RH), solar radiation (SR), barometric pressure (BP), precipitation (PR), and snow depth (SD) among station-pairs of each network. In this process, Pearson’s correlation coefficient (r) and average absolute error (AAE) were the best representative measures from the methods of association and coincidence while proposed percentage of similarity (PS%) was the best in comparison to r and AAE to quantify the similarity. Further, RH found to be the least variable with strong and acceptable similarity in each network while similarity was decreased in order of SD, BP, AT, SR, and PR respectively. Secondly, Wind data has been analyzed for these three networks to find the optimal network. Here, it has been revealed that wind rose diagram only appropriate for visual comparison of wind characteristics while r, AAE and PS measures were suitable for similarity analysis of wind. Later, it has been found that all station from these three networks were required to represent wind variability in the region due to very low and unacceptable PS values. Thirdly, influence of land cover and topography have been evaluated on meteorological parameters of these 19 stations where they categorised under seven groups based on similar kind of land cover and topography. In this evaluation, parameters AT and SR were shown strong correlation but limited similarity while RH exhibit the least variability in each group. Moreover, BP and SD have some similarities while PR and WSD were highly variable due to ...