Abstract
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.
Funder
Oil Sands Monitoring (OSM) Program of Alberta Environment and Protected Areas
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference56 articles.
1. World Meteorological Organization (WMO) (2018). Guide to Meteorological Instruments and Methods of Observation, World Meteorological Organization (WMO). [2018th ed.].
2. Weather or Not? Examining the Impact of Meteorological Conditions on Public Opinion Regarding Global Warming;Weather. Clim. Soc.,2014
3. Spatial Variability of Daily Weather Variables in the High Plains of the USA;Agric. For. Meteorol.,1994
4. Evaluating Meteorological Data from Weather Stations, and from Satellites and Global Models for a Multi-Site Epidemiological Study;Environ. Res.,2018
5. Analysis of Meteorological Variations on Wheat Yield and Its Estimation Using Remotely Sensed Data. A Case Study of Selected Districts of Punjab Province, Pakistan (2001-14);Ital. J. Agron.,2017