This Webpage is dedicated to the analysis of weather patterns. Weather analyses is an extremely complex problem often requiring supercomputers for predictive capabilities. However, many basic analyses can be performed experimentally using a python enviroment. As an example of this approach, we acquired data for a range of different cities and evaluated temperature, humidity, cloud cover, and wind speed in relation to the latitude of the city. Using this approach, we demonstrate that both correlated and non-correlated measurements are easily identified.
Summary of Study
This study used the OpenWeatherMap API and Python/Pandas data tools to identify weather data from a range of random cities. These weather data points were plotted against the latitude of the city and are represented using MatPlotLib graphical library function. The date for analyses was 03/05/2022, but alternative dates are possible for further analyses using the OpenWeather API and Python/Pandas scripts stored in my GitHub Repo linked below.