Week 06 (W51 Dec22) Global Climate Dataset

1- Summary

Last week we were not able to efficiently show the correlation between the climatic variations in Austria and the environmental factors that are contributing to it, so this week tried to explore more to gauge the effect of global and local factors on average Temperature rise in Austria. The local factors include emissions like CO2, methane,etc from within the country itself. We didn't divide the country into various states to gauge individual effects because Austria as a whole is very small to undertake factors on the city level. Overall, on the global, scale we studied 7 countries of Europe for example Germany, Switzerland, Italy, Slovenia, Hungary, Czech Republic and studied their emissions and correlated them with the average temperature rise of Austria. The correlation was further studied and individual percentage impact from each country was laid down as the basis of understanding regarding which factors from each of these countries plays the major role in the increase of average Temperature.

2 - Dataset Stats

Global Climate Data (GCD) : Main Dataset

• Number of files: 100.791
• Format: .dly files (Complete Works Wordprocessing Template)
• Size: 26.5 GB
• Features: 46
• Source Date: 1763 - 2015

World Bank (WB) : Complementary Dataset

• Number of files: 1
• Format: .csv
• Size: ~15 MB
• Features: 82
• Source Date: 1960 - 2015

3 - Goals achieved

• Analysis of core environmental data
• Correlation of Austria data with aggregated data and distinct data of neighboring countries
• Show who is contributing more to Austria's pollution

4 - Analysis of average temperature

Following as presented during the previous week, we are following the option of interpolation with spline of order 2 to fill in the missing values in our data. We decided to merge the data of Tmax and T min to study the average temperature of the Austria from the years 1960 to 2016. ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201.png) As can be clearly seen from the graph the average Temperature of Austria has increased over the years. The reason may be many but through this week's work, we have tried to show the correlation between emissions and their source. As, Austria is too small to be considered as a source ground of emissions and be the major contributor for its average Temperature rise, it is interesting to determine other countries as an indirect players to impact climatic variations in Austria.

3- Correlation of emissions and average temperature rise is Austria

Here in this graph we see the correlation of Austria temperature with the total aggregated emissions of its neighbors (Germany, Switzerland, Italy, Czech Republic, Hungary, Slovenia). We notice that CO2 emissions as well as other greenhouse gases emissions and SF6 emissions are positively correlated to the rise of temperature. For methane and PFC emissions there is hardly any correlation noticed, while for HFC gas and Nitrous oxide emissions we observe a negative correlation. This may be due to the reduction of the emissions in recent years due to measurements taken by the countries to limit their production. We followed this approach to see the possible effect of the neighboring countries to a country's rise of temperature, since locally we could not derive safe conclusions. Pollution does not take place locally only but at a wider zone which depends on various environmental conditions and it hard to define. However, it makes more sense to take into account the emissions of the neighboring countries as well besides Austria's to obtain more realistic results.

![] (https://github.com/magiob/DataMining/blob/2e59bf3bfb3214d42dbbcd5d6bac973ef854e073/latest/Plot%201%20(1).png)

5 - Study and Correlation

So, what is actually done here is correlation of 7 features (CO2 emissions (kt), Other greenhouse gas, emissions(Thousand tonnes metric of CO2), HFC gas emissions (thousand metric tons of CO2 equivalent), Methane emissions (kt of CO2 equivalent), Nitrous oxide emissions (thousand metric tons of CO2 equivalent), PFC gas emissions (thousand metric tons of CO2 equivalent), SF6 gas emissions (thousand metric tons of CO2 equivalent) for each of the seven countries with the average temperature rise of Austria. These features are directly related to the global warming according to multiple scientific reports. The positive correlation is stacked, measured and visualized with a pie chart to show individual percentage contribution. The goal here is to identify the biggest contributor pollution-wise of Austria for each variable known to be "blamed" for global warming.

![] (https://github.com/magiob/DataMining/blob/master/latest/ger.png) ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201%20(1).png) ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201%20(2).png) ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201%20(3).png) ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201%20(5).png) ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201%20(6).png) ![] (https://github.com/magiob/DataMining/blob/master/latest/Plot%201%20(7).png)

As, you can see locally in Austria CO2 is the major contributor for rise in average Temperature as it had shown the most positive correlation with the temperature rise. But, for other countries like Slovania, Switzerland and Italy four different gases are playing important role in average temperature rise of Austria.

6 - Next Week Goals

• Correlate Austria climate data with global environmental data
• Improve visualization, attempt map visualization to show effects
• Set up prediction model about the biggest contributor to a country's pollution level

7 - Presentation Link

No presentation this week. Just wiki

References

1. Menne, M.J., I. Durre, R.S. Vose, B.E. Gleason, and T.G. Houston, 2012: An overview of the Global Historical Climatology Network-Daily Database. Journal of Atmospheric and Oceanic Technology, 29, 897-910, doi:10.1175/JTECH-D-11-00103.1.
2. Menne, M.J., I. Durre, B. Korzeniewski, S. McNeal, K. Thomas, X. Yin, S. Anthony, R. Ray, R.S. Vose, B.E.Gleason, and T.G. Houston, 2012: Global Historical Climatology Network - Daily (GHCN-Daily), Version 3. [indicate subset used following decimal, e.g. Version 3.12]. NOAA National Climatic Data Center. http://doi.org/10.7289/V5D21VHZ
3. WB Dataset - http://data.worldbank.org
4. Correlation Analysis - http://sphweb.bumc.bu.edu/otlt/MPH-Modules/BS/BS704_Multivariable/BS704_Multivariable5.html
5. Climate change impacts on Austrian ski areas, Robert Steiger & Bruno Abegg (Link)
6. HFCs? Curbing Them Is Key to Climate-Change Strategy (Op-Ed), Hallie Kennan, Energy Innovation: Policy and Technology (Link)
7. How do we know more CO2 is causing warming? (Link)