The data output of the weather_dl()
function include corresponding _flag
columns for each data column. These columns are used by ECCC to add notes regarding measurements.
Similarly, the data output of the normals_dl()
function include corresponding _code
columns. These columns are used by ECCC to add notes regarding the amount of data used to calculate the normals.
In the weather_dl()
function if format = TRUE
(the default), data corresponding to flags M
, NA
, [empty]
and L
are all replaced with NA
.
For example, a sample of unformatted data from Magog station in Quebec looks like:
## # A tibble: 12 × 6 ## station_name `Date/Time` `Total Precip (mm)` `Total Precip Flag` `Snow Grnd Last Day (cm)` ## <chr> <chr> <chr> <chr> <chr> ## 1 MAGOG 2017-03 30.4 ^ <NA> ## 2 MAGOG 2017-04 114.0 ^ 0 ## 3 MAGOG 2017-05 78.8 ^ 0 ## 4 MAGOG 2017-06 140.7 ^ 0 ## 5 MAGOG 2017-07 80.7 <NA> 0 ## 6 MAGOG 2017-08 135.8 <NA> 0 ## 7 MAGOG 2017-09 63.0 ^ 0 ## 8 MAGOG 2017-10 140.8 ^ 0 ## 9 MAGOG 2017-11 70.0 ^ 0 ## 10 MAGOG 2017-12 45.7 ^ 10 ## 11 MAGOG 2018-01 34.6 ^ 2 ## 12 MAGOG 2018-02 77.2 ^ 0
In this output, you can see two flags: ^
in Total Precip
and M
in Snow Grnd Last Day
This same sample, formatted looks like:
## # A tibble: 12 × 5 ## date total_precip total_precip_flag snow_grnd_last_day snow_grnd_last_day_flag ## <date> <dbl> <chr> <dbl> <chr> ## 1 2017-03-01 30.4 ^ NA M ## 2 2017-04-01 114 ^ 0 <NA> ## 3 2017-05-01 78.8 ^ 0 <NA> ## 4 2017-06-01 141. ^ 0 <NA> ## 5 2017-07-01 80.7 <NA> 0 <NA> ## 6 2017-08-01 136. <NA> 0 <NA> ## 7 2017-09-01 63 ^ 0 <NA> ## 8 2017-10-01 141. ^ 0 <NA> ## 9 2017-11-01 70 ^ 0 <NA> ## 10 2017-12-01 45.7 ^ 10 <NA> ## 11 2018-01-01 34.6 ^ 2 <NA> ## 12 2018-02-01 77.2 ^ 0 <NA>
As you can see, we still have the two flags, but the missing data flag (M
) is now replaced with NA. The other flag ^
is not, as it indicates that "The value displayed is based on incomplete data" (see below).
The flags index can be accessed through the built in data frame: flags
|code |meaning | |:-------|:-------------------------------------------------------------------| |A |Accumulated | |B |More than one occurrence and estimated | |C |Precipitation occurred, amount uncertain | |E |Estimated | |F |Accumulated and estimated | |L |Precipitation may or may not have occurred | |M |Missing | |N |Temperature missing but known to be > 0 | |S |More than one occurrence | |T |Trace | |Y |Temperature missing but known to be < 0 | |[empty] |Indicates an unobserved value | |^ |The value displayed is based on incomplete data | |† |Data that is not subject to review by the National Climate Archives | |NA |Not Available |
In the normals_dl
() function, codes are associated with each variable:
## # A tibble: 13 × 7 ## period temp_daily_average temp_daily_average_code temp_daily_max temp_daily_max_code ## <fct> <dbl> <chr> <dbl> <chr> ## 1 Jan -16.6 A -11.1 A ## 2 Feb -13.6 A -8.1 A ## 3 Mar -6.2 A -1 A ## 4 Apr 4 A 10.5 A ## 5 May 10.6 A 17.8 A ## 6 Jun 15.9 A 22.4 A ## 7 Jul 18.5 A 25.2 A ## 8 Aug 17.7 A 24.9 A ## 9 Sep 11.8 A 18.9 A ## 10 Oct 4.1 A 10.4 A ## 11 Nov -5.6 A -0.5 A ## 12 Dec -14 A -9 A ## 13 Year 2.2 A 8.4 A
For example, here, the code indicates that these temperature variables meet the WMO '3 and 5 rule' (no more than 3 consecutive and no more than 5 total missing for either temperature or precipitation).
The codes index for climate normals can be accessed through the built-in data frame: codes
|code |meaning | |:----|:-----------------------------------------------------------------------------------------------------------------------------| |A |WMO '3 and 5 rule' (i.e. no more than 3 consecutive and no more than 5 total missing for either temperature or precipitation) | |B |At least 25 years | |C |At least 20 years | |D |At least 15 years |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.