Inspiration
This research project is about mapping out climate data on a map of our world by using Python and matplotlib to graph out on a map. The world around us is always changing because of humans. Our carbon emissions that we put into our atmosphere have significantly warmed up our planet due to the greenhouse effect. This leads to both global warming and climate change. Global warming refers to the rise in the Earth's average surface temperature. However, climate change encompasses a broader set of changes of the Earth's climate: temperature, precipitation, wind, sea levels, ecosystems, and more. The one aspect of climate change I chose to focus on in this project was precipitation. Rainfall has been affected by many changes in the climate. In these past couple of years, increased temperatures lead to glacial melting which raise sea levels. This extra water is also added to the atmosphere through evaporation, which is also increased due to greater temperatures, and eventually more rain falls back down to Earth from precipitation.
How I built it
This is built on a jupyter notebook in google colab which allows people to easily see and run the code displayed below. I built this by importing a precipitation predictions dataset from the National Ocean and Atmosphere Association (NOAA). Then I preproccesed and sectioned out the data to understand its shape, size, and contents. Then I created sample graphs and heatmaps to see what the data appears to be at certain longitudes and latitudes. Those graphs were then updated to include more features: coastlines, rivers, lakes, continents, and a color bar. Finally, I created an animated version of the graph that displays the predictions of precipitation over time with different frames. The full detailed process is documented on the jupyter notebook, so take a look!
Challenges I ran into
One big challenge was trying to find a good database that had the type of climate data needed. This project was meant to initially analyze temperatures rising over time but I was unable to find a database for temperatures, so I had to settle for precipitation. Another challenge was also importing the dataset into colab soley by code so everyone could run the code without having to manually download the database into colab.
Accomplishments that I'm proud of
I was really proud of being able to complete this research project in a short timeframe and make the animation display well on google colab. Only able to use online tutorials and resources was hard as I was often left with many questions afterwards, but I was able to perservere and get my code working.
What I learned
-Reviewing the basics of Python -Exploring Python library matplotlib to visualize or analyize data -Looking for viable datasets from trustworthy sources to use for this research project -Understanding the innerworkings of this dataset -Practicing plotting graphs of sample data to understand the different functions -Learning how to save files in Google Colab for everyone to view -Studying on making animations of graph to better depict climate data and trends over time -Compiling this notebook from my gained knowledge
Built With
- cartopy
- googlecolab
- matplotlib
- netcdf4
- python
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