Finding change in temperature in degree Celsius in R-CodePudding

I have average annual spatial temperature data for the last 15 years, and I am interested in finding the change in temperature in that time period. Basically, the purpose is to see whether the temperature has increased or not (indicating global warming/climate change) over this time, and if it has increased then by how many degrees? Then I will be able to say, for example, the temperature increased in this time period by X degrees Celsius.

How can I do this in R?

Sample data

year = c(2005, 2005, 2005, 2005, 2006, 2006, 2006, 2006, 2007, 2007, 2007, 2007, 2008, 2008, 2008, 2008)
Tmean = c(24, 24.5, 25.8,25, 24.8, 25, 23.5, 23.8, 24.8, 25, 25.2, 25.8, 25.3, 25.6, 25.2, 25)

Code

library(tidyverse)

df = data.frame(year, Tmean)


# Find the change/increase/decrease in temperature in the time period
# Stuck on method.....

CodePudding user response：

First of all, you can plot your data along with a regression line to see whether it looks as though the temperature is indeed increasing:

ggplot(df, aes(year, Tmean))   
  geom_point(colour = 'deepskyblue4', size = 3)  
  geom_smooth(method = lm, linetype = 2, color = 'red4', se = FALSE)  
  theme_light()  
  theme(text = element_text(size = 16))

And it does seem to have increased by about 0.75 degrees between the first and last years of this data set. To quantify this, we can run a linear regression model:

model <- lm(Tmean ~ year, data = df)

summary(model)
#> 
#> Call:
#> lm(formula = Tmean ~ year, data = df)
#> 
#> Residuals:
#>      Min       1Q   Median       3Q      Max 
#> -1.28000 -0.21437  0.00625  0.25625  1.24750 
#> 
#> Coefficients:
#>              Estimate Std. Error t value Pr(>|t|)
#> (Intercept) -431.5850   284.1228  -1.519    0.151
#> year           0.2275     0.1416   1.607    0.130
#> 
#> Residual standard error: 0.6333 on 14 degrees of freedom
#> Multiple R-squared:  0.1557, Adjusted R-squared:  0.09536 
#> F-statistic: 2.581 on 1 and 14 DF,  p-value: 0.1304

The interpretation here is that temperature increased by an average of 0.2275 degrees per year, or 3 * 0.2275, which is 0.6825 degrees. The p value of 0.130 tells us that this change was not statistically significant (i.e. it could have been due to chance)

CodePudding user response：

Is this what you are looking for?

year = c(2005, 2005, 2005, 2005, 2006, 2006, 2006, 2006, 2007, 2007, 2007, 2007, 2008, 2008, 2008, 2008)
Tmean = c(24, 24.5, 25.8,25, 24.8, 25, 23.5, 23.8, 24.8, 25, 25.2, 25.8, 25.3, 25.6, 25.2, 25) 

data = data.frame(year, Tmean)

data = data %>% group_by(year) %>% mutate(min = min(Tmean), max = max(Tmean)) %>% 
  mutate(diff = max - min)
data = data %>% select(-c(Tmean, min, max)) %>% unique()
print(data)