# D Exercise 02

Last updated: 2020-08-12 00:41:46

## D.1 Question 1

• Run the following four expressions to load two vectors named year and co2 into memory
data(co2)
means = aggregate(co2, FUN = mean)
year = as.vector(time(means))
co2 = as.vector(means)
• The co2 vector contains $$CO_2$$ measurements in the atmosphere, in ppm units, during the period 1959-1997. The year vector contains the corresponding years.
• Assuming that the rate of $$CO_2$$ increase was constant and equal to the average rate during 1959-1997, calculate the predicted $$CO_2$$ concentration during each of the years 1998-2018.
• Create a plot (Figure D.1) showing $$CO_2$$ concentration as function of time, with:
• Observed values during 1959-1997, based on the year and co2 vectors, in black
• Predicted values during 1998-2018 in blue
• Add a point in red showing the true concentration in 2018, which was 409.92.

(50 points)

## D.2 Question 2

• Read the rainfall.csv file into a data.frame object
• Find and print the station names where all nine months are with <10 mm of rainfall
## [1] "Yotveta" "Eilat"
• Note: you can define the vector m with month names in your code to subset the columns with monthly rainfall amounts, as shown in Section 4.4.3.
m = c("sep","oct","nov","dec","jan","feb","mar","apr","may")

(50 points)