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Within this assignment, a collection of weather station data over three years has containing fourteen variables of data e.g. wind speed, temperature, wind direction, etc. With this mass collection of data there are many ideas for a investigations to find a correlation between 2 or more of the variables of data. This allows connections to be made between set data and thus help predict future occurrences when the pattern of the correlation of data connects. The purpose of this assignment as stated above is to find a correlation between two or more of the variables of data, the chosen investigation which is stated in this report is;
"Whether an correlation exists between wind speed and temperature. Whether the coldest/ hottest temperatures are associated with fast/ slow wind speeds". The following idea for investigation implies this was chosen as the hypothesis of a strong connection between temperature and wind speed must be true due to the scientific fact of hot temperatures makes molecules increase in size and gain velocity and thus cold temperatures make molecules decrease in size and lose velocity.
Starting with comparing temperature and wind speed in the year 2015, a correlation already exists between both variables of data that the lower wind speed is a directly result of low temperature. Unfortunately the weather station that collects the data variables was off-line for a few months during the year 2015 thus the data collected from this year does not accurately prove that the correlation is there.
During the year 2016, the weather station collected data throughout the whole year unlike the data collected in 2015, the data for 2016 is shown but does not show a accurate correlation between low temperature and low wind speed. This disproves the hypothesis but the graph does show a strong cluster between 0-20 degrees and wind speeds under 20 kph (kilometers per hour), even though this does not specifically relate to the hypothesis, it is a key factor to note.
Much like 2015, there is only a brief amount of data from the year 2017, thus this data cannot fully support the hypothesis but does again show the same key factor shown in the 2016 data, the same cluster between 0-20 degrees and wind speeds under 20 kph (kilometers per hour). As only there is only one whole years worth of data that represents seasonal change of the planet Earth rotation around the Sun causing different temperature and wind speeds during the different seasons of the year then the data is not enough to support the hypothesis.
The hypothesis is currently not accurately supported thus another graph must be made to concentrate all three years worth of data even though two of the three years have incomplete data, the data provided shows strong clusters. Analyzing the data in found is the priority graph to observe and accurate observations, within this section, correlations have been made but only to a specific year and a short time frame, shows not only one year but all three years thus showing a strong accurate correlation over a long period of time. It shows that the lower the temperature (higher humidity) there are lower wind speeds compared to the higher temperature (lower humidity) and high wind speeds.
In conclusion of the analysis of the weather station in relation of the original hypothesis;
"Whether an correlation exists between wind speed and temperature. Whether the coldest/ hottest temperatures are associated with fast/ slow wind speeds".
As the data from 2015 and 2017 are incomplete, there is no accurate answer to the selected hypothesis but using the data that was collected then, there is a strong cluster showing a correlation within the margin of low wind speeds under 20 kph (kilometers per hour) within the temperature range of 0-20 degrees, as stated there is a connection between temperature affecting air pressure which directly relates to the velocity of the wind. Using the research, the hypothesis is proven to be correct but with the data collected by the weather station at the University of Kent due to the incomplete data sets, it cannot be proven from said data.
Python, matplotlib, numpy
LaTeX Report: https://github.com/Mysftz/weather-station-analysis-report
Python Files: https://github.com/Mysftz/weather-station-analysis
This report was submitted for the degree of a Bachelors of Science in Astronomy, Space Science and Astrophysics at the University of Kent in March 2018.
Distributed under the CC-BY-SA-4.0: Creative Commons Attribution Share Alike 4.0 International License. See LICENSE.txt for more information.
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