Climate Report: Ottawa - Environment Canada

Loading and compiling the daily data

To load the daily data, loop over all the files in the Data folder.

# Find all csv files in the "Data" folder.
files2load = list.files(path="Data",pattern="daily")
data_daily=NULL
for(lp in 1:length(files2load)){
  data_daily = rbind(data_daily,read_csv(paste0("Data/",files2load[lp])))
}

Make some plots

# convert all column names to valid R syntax:
data_daily = data_daily |> rename_all(make.names)
ggplot(data_daily,aes(x=Date.Time,y=Mean.Temp...C.,colour=factor(Year)))+
  geom_line()+
  ggtitle("Daily Mean Temperatures")+
  theme(legend.position = "none") 

## Warning: Removed 130 row(s) containing missing values (geom_path).

However it is tricky to see a change in a few degrees given the enormous seasonal variation. Let’s focus the plots:

data_daily |> 
  filter(Month == "07") |> 
  group_by(Year) |> 
  summarise(MeanOfJulyMax=mean(Max.Temp...C.),
            MeanOfJanMin=mean(Min.Temp...C.)) |>
  ungroup() |>
ggplot()+
  geom_line(aes(x=Year,y=MeanOfJulyMax , color="red"))+
  geom_line(aes(x=Year,y=MeanOfJanMin,color="blue"))+
  ggtitle("Means of the July Max and Jan Min Temperatures")+
  labs(x = "Year", y="degrees C")+
  theme(legend.position = "none") 

data_daily |> 
  filter(Month == "07") |> 
  group_by(Year) |> 
      summarise(MeanOfJulyMax=mean(Max.Temp...C.),
                MeanOfJanMin=mean(Min.Temp...C.)) |>
  ungroup() |>
ggplot()+
  geom_point(aes(x=MeanOfJulyMax,y=MeanOfJanMin))

weather =  data_daily

Loading and compiling the monthly data

Alternatively we can work with the monthly data, but note that the daily record is ongoing, but started much later than the monthly record. Here we find and load downloaded monthly from the Data folder.

# Find all csv files in the "Data" folder.
file2load = list.files(path="Data",pattern="Ottawa-monthly")
data_monthly = read_csv(paste0("Data/",file2load))

## Rows: 1416 Columns: 29

## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (12): Station Name, Date/Time, Month, Mean Max Temp Flag, Mean Min Temp ...
## dbl (13): Longitude (x), Latitude (y), Climate ID, Year, Mean Max Temp (°C),...
## lgl  (4): Dir of Max Gust (10's deg), Dir of Max Gust Flag, Spd of Max Gust ...

## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

# convert all column names to valid R syntax:
data_monthly = data_monthly |> rename_all(make.names)

#convert the dates into valid date format by arbitrarily selecting the 15th of the month to give it a date

data_monthly$Date.Time = as_date(paste0(data_monthly$Date.Time,"-1"))

data_monthly |> 
ggplot(
       aes(x=Date.Time,y=Mean.Temp...C.,colour=factor(Year)))+
  geom_line()+
  ggtitle("Monthly Mean Temperatures")+
  labs(x = "Year", y="degrees C")+
  theme(legend.position = "none") 

## Warning: Removed 10 row(s) containing missing values (geom_path).

All_NA_cols = apply(data_monthly,2,
                    function(x){sum(is.na(x))/length(x)})==1

Data details

• Temperature units are in Celcius.
• Monthly values can be derived from daily ones.
• The speed of maximum gust is in kilometers per hour.
• Heat degree days is the number of degrees Celsius that the mean temperature is less than 18 Celcius, the cool degree days is a number of degrees Celsius that the mean temperature is equal to and above 18 Celcius.
• The direction of the maximum gust is in tens of degrees, 9 means 90 degrees, which is an east wind, and 36 means 360 degrees implies a wind blowing from the geographic north pole.
• Other appeared letters like “M” indicates a missing value, “^” indicates the value displayed is based on incomplete data. All legend is shown at the end of the data source page.