Project Overview:
Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time. People have attempted to predict the weather informally for millennia and formally since the 19th century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere, land, and ocean and using meteorology to project how the atmosphere will change at a given place. There is a vast variety of end uses for weather forecasts. Weather warnings are important because they are used to protect life and property. Forecasts based on temperature and precipitation are important to agriculture, and therefore to traders within commodity markets. Temperature forecasts are used by utility companies to estimate demand over coming days. Weather forecasting is a part of the economy. For example in 2009, the US spent approximately$5.8 billion on it, producing benefits estimated at six times as much.1 In this project a backend application, and ML models will be developed for the purpose of forecasting weather. All packages hosted on https://pypi.org/ can be used to develop the software project.
Objectives:
- Deciding on a data source (such as ECMWF, wunderground etc.)
- Deciding on historical data start date (up to 5 years)
- Gathering historical data until 1th Of April, 2023 from decided data source (via your backend python scraper script) for a location of your choice in Izmir.
- Store relevant data in csv files.
- Develop Models For Forecasting Weather For 3 Days, 7 Days, 14 Days. (Software project output
- should have python project only, Jupyter Notebooks implementations not accepted.)
- Develop a python script which will provide the following when run; o Will ask for forecast start date o Will list available foracast ranges (3 Days, 7 Days, 14 Days) and allow selection of one. o Will show forecasts 1 day per line.
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