Recent - 30d
Weather has been WET and WARM between 2022-12-04 and 2023-01-03.
Column
Rainy Days
22Total Recent Precipitation (cm)
Highest Recent Temp. (c)
Lowest Recent Temp. (c)
Recent date range
2022-12-04 to 2023-01-03
30 days
Source info
Column
Recent Precipitation
Monthly Precipation (red diamonds = current yr)
Column
Recent Temperature (dot = daily ave.; lines = period aves.)
Monthly Temperature Comp. (red diamonds = current yr)
90 days
Weather has been WET and WARM between 2022-10-05 and 2023-01-03.
Column
Rainy Days
43Total Precipitation (cm)
Highest Temp. (c)
Lowest Temp. (c)
Date range
2022-10-05 to 2023-01-03
90 days
Source info
Column
Precipitation
Monthly Precipation (red diamonds = current yr)
Column
Temperature (dot = daily ave.; lines = period aves.)
Monthly Temperature Comp. (red diamonds = current yr)
1 year
Weather has been DRY and HOT so far in 2023.
Column
Rainy Days
157Total Precipitation (cm)
Highest Temp. (c)
Lowest Temp. (c)
Date range
2022-01-03 to 2023-01-03
365 days
Source info
Column
Precipitation
Annual Precipation (black dot = current yr extrapolation)
Column
Temperature (dot = daily ave.; lines = period aves.)
Annual Temperature Comparisons
Data Source
Produced by John Yuill
All source code and data used is
available in my Github repo:
proj-r-van-weather
latest processed data (csv) -
download
Govt of Canada Historical Weather data
Data
is collected from:
climate.weather.gc.ca/historical_data/search_historic_data_e.html
Data is available from the government on a daily basis and updated occasionally here. ;)
Date range currently covered:
Earliest date: 1970-01-01
Most recent date: 2023-01-03
The following weather stations are represented. Not the preferred approach but I couldn’t find continuous data for any single weather station.
Data Structure
Check data structure and summary:
spc_tbl_ [19,360 × 11] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ Date : Date[1:19360], format: "1970-01-01" "1970-01-02" ...
$ Year : Factor w/ 54 levels "1970","1971",..: 1 1 1 1 1 1 1 1 1 1 ...
$ Month : Factor w/ 12 levels "1","2","3","4",..: 1 1 1 1 1 1 1 1 1 1 ...
$ Day : num [1:19360] 1 2 3 4 5 6 7 8 9 10 ...
$ Season : Factor w/ 4 levels "Winter","Spring",..: 1 1 1 1 1 1 1 1 1 1 ...
$ Season.Yr : num [1:19360] 1970 1970 1970 1970 1970 1970 1970 1970 1970 1970 ...
$ Max.Temp : num [1:19360] 6.1 2.2 5 2.8 1.7 5.6 3.3 4.4 7.2 5.6 ...
$ Min.Temp : num [1:19360] -1.7 0 -1.7 -3.3 -2.8 -1.7 -3.3 0 2.8 -2.8 ...
$ Mean.Temp : num [1:19360] 2.2 1.1 1.7 -0.3 -0.6 2 0 2.2 5 1.4 ...
$ Total.Precip: num [1:19360] 0 1 0.5 0 0 0 0 4.6 6.6 0.5 ...
$ Station : chr [1:19360] "VANCOUVER INT'L A" "VANCOUVER INT'L A" "VANCOUVER INT'L A" "VANCOUVER INT'L A" ...
- attr(*, "spec")=
.. cols(
.. Date = col_date(format = ""),
.. Year = col_double(),
.. Month = col_double(),
.. Day = col_double(),
.. Season = col_character(),
.. Season.Yr = col_double(),
.. Max.Temp = col_double(),
.. Min.Temp = col_double(),
.. Mean.Temp = col_double(),
.. Total.Precip = col_double(),
.. Station = col_character()
.. )
- attr(*, "problems")=<externalptr> Date Year Month Day
Min. :1970-01-01 1972 : 366 1 :1646 Min. : 1.00
1st Qu.:1983-04-02 1976 : 366 3 :1643 1st Qu.: 8.00
Median :1996-07-03 1980 : 366 5 :1643 Median :16.00
Mean :1996-07-03 1984 : 366 7 :1643 Mean :15.73
3rd Qu.:2009-10-03 1988 : 366 8 :1643 3rd Qu.:23.00
Max. :2023-01-03 1992 : 366 10 :1643 Max. :31.00
(Other):17164 (Other):9499
Season Season.Yr Max.Temp Min.Temp Mean.Temp
Winter:4785 Min. :1970 Min. :-8.70 Min. :-15.300 Min. :-11.6
Spring:4876 1st Qu.:1983 1st Qu.: 8.90 1st Qu.: 2.800 1st Qu.: 6.0
Summer:4876 Median :1996 Median :13.30 Median : 6.800 Median : 10.0
Fall :4823 Mean :1996 Mean :13.84 Mean : 6.717 Mean : 10.3
3rd Qu.:2009 3rd Qu.:19.00 3rd Qu.: 11.300 3rd Qu.: 15.2
Max. :2023 Max. :34.40 Max. : 22.400 Max. : 28.4
NA's :47 NA's :40 NA's :49
Total.Precip Station
Min. : 0.000 Length:19360
1st Qu.: 0.000 Class :character
Median : 0.000 Mode :character
Mean : 3.217
3rd Qu.: 3.600
Max. :91.600
NA's :55