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 Fl… `Snow Grnd Last … `Snow Grnd Last…
## <chr> <chr> <chr> <chr> <chr> <chr>
## 1 MAGOG 2017-03 30.4 ^ <NA> M
## 2 MAGOG 2017-04 114.0 ^ 0 <NA>
## 3 MAGOG 2017-05 78.8 ^ 0 <NA>
## 4 MAGOG 2017-06 140.7 ^ 0 <NA>
## 5 MAGOG 2017-07 80.7 <NA> 0 <NA>
## 6 MAGOG 2017-08 135.8 <NA> 0 <NA>
## 7 MAGOG 2017-09 63.0 ^ 0 <NA>
## 8 MAGOG 2017-10 140.8 ^ 0 <NA>
## 9 MAGOG 2017-11 70.0 ^ 0 <NA>
## 10 MAGOG 2017-12 45.7 ^ 10 <NA>
## 11 MAGOG 2018-01 34.6 ^ 2 <NA>
## 12 MAGOG 2018-02 77.2 ^ 0 <NA>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 |
|---|---|
| [empty] | Indicates an unobserved value |
| † | Data that is not subject to review by the National Climate Archives |
| ^ | The value displayed is based on incomplete data |
| 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 |
| 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_c… temp_daily_min
## <fct> <dbl> <chr> <dbl> <chr> <dbl>
## 1 Jan -16.6 A -11.1 A -21.9
## 2 Feb -13.6 A -8.1 A -19
## 3 Mar -6.2 A -1 A -11.4
## 4 Apr 4 A 10.5 A -2.6
## 5 May 10.6 A 17.8 A 3.4
## 6 Jun 15.9 A 22.4 A 9.3
## 7 Jul 18.5 A 25.2 A 11.7
## 8 Aug 17.7 A 24.9 A 10.4
## 9 Sep 11.8 A 18.9 A 4.7
## 10 Oct 4.1 A 10.4 A -2.2
## 11 Nov -5.6 A -0.5 A -10.6
## 12 Dec -14 A -9 A -19
## 13 Year 2.2 A 8.4 A -3.9
## # … with 1 more variable: temp_daily_min_code <chr>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 |