Raise of Global Surface Temperatures
The data we’re looking at here shows the trend in raise of earth’s surface temperatures.
In our dataset, what we have are temperature anomalies. When temperature is referenced in terms of anomalies instead of absolute temperatures, there is a certain meaning to it.
What are Temperature Anomalies?
It’s pretty simple, actually. Let’s understand the concept along with an example:
We consider a long continuous period of time, usually a few decades, and call it base period. The average temperature during this period is calculated and is called as base temperature.
A temperature anomaly is the difference between this base temperature and the average temperature of any given year. For example, say, your base period is 1980–2010, and for this period of thirty years, if you have an average temperature of 15.8°C, then your base temperature will be 15.8°C.
So, your temperature anomaly would be the difference between this base temperature and the average temperature of any given year. If the difference is greater than the base temperature, then you have a raise; and if it’s lower than the base temperature, you have a decline.
Continuing with our example, we have a base temperature of 15.8°C, and if the average temperature for a certain year, say, 2015, is 16.6°C, then the temperature anomaly for that year would be +0.8°C (16.6–15.8). This means that there is an increase of 0.8°C.
Data:
Now, let us take a look at the actual numbers. The dataset used for the following analysis has come from NASA. It is the latest data of Global Surface Temperature anomalies from years 1880 to 2017.
Ref: https://data.giss.nasa.gov/gistemp/
Code:
I develop in R and the code used for generating this plot is as follows:
#importing the dataset
df <- read.csv(file='GLB.Ts+dSST.csv', header = TRUE, skip = 1, sep = ',' ,stringsAsFactors = FALSE)#take 'Year' and 'J.D' (January to December average) columns
st <- df[,c(1,14)]
names(st) <- c('Year','Avg.Temperature')#plotly package is used to create the below graph
install.packages("plotly")
library(plotly)#creating axes labels
xlab <- list(title = "Year")
ylab <- list(title = "Surface Temperature Raise")#plotting using plotly package
p <- plot_ly(x = ~st$Year, y = ~st$Avg.Temperature, mode = 'lines') %>% layout(xaxis=xlab, yaxis=ylab)#now the plot is stored in the vector 'p' - let's render it
p
Graph:
Analysis:
There is a warming of 0.4°C all through 1880s to 1980s. So, it was pretty much stable for over a century.
But what came next is the interesting part. We see a consistent increase in the surface temperatures through the next three and half decades.
By the year 2016, the trendline has almost reached 1°C. That’s a very fast ascent for a thirty year period, considering how stable the temperatures were in the 100 years prior to this period.
Insights:
It is clearly apparent that the problem of Global Warming is worsening at a very fast pace. According to scientific community, the global rise of surface temperatures should not exceed 2°C. If this threshold limit is surpassed, it will result in numerous unforeseen climate catastrophes and collapse the stability of life on earth. The main mission of Paris Climate Accord signed is to make sure such a situation doesn’t happen.
And the graph shows that we’re already reaching 1°C.
Hence, it is high time for every single country on earth (including and especially the USA, one and only country in the world to withdraw from the Paris Agreement) to pay utmost attention to the issue at hand and strive for a sustainable future.
