---
title: "Getting Started"
date: "2026-06-16"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Getting Started}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---





``` r
library(dplyr)
library(ggplot2)
library(weathercan)
```


## Stations

`weathercan` includes the function `stations()` which returns a list of stations and their details (including `station_id`).


``` r
head(stations())
```

```
## # A tibble: 6 × 17
##   prov  station_name        station_id climate_id WMO_id TC_id   lat   lon  elev tz        interval start   end normals normals_1991_2020 normals_1981_2010
##   <chr> <chr>                    <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>     <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
## 1 AB    DAYSLAND                  1795 301AR54        NA <NA>   52.9 -112.  689. Etc/GMT+7 hour        NA    NA FALSE   FALSE             FALSE            
## 2 AB    DAYSLAND                  1795 301AR54        NA <NA>   52.9 -112.  689. Etc/GMT+7 day       1908  1922 FALSE   FALSE             FALSE            
## 3 AB    DAYSLAND                  1795 301AR54        NA <NA>   52.9 -112.  689. Etc/GMT+7 month     1908  1922 FALSE   FALSE             FALSE            
## 4 AB    EDMONTON CORONATION       1796 301BK03        NA <NA>   53.6 -114.  671. Etc/GMT+7 hour        NA    NA FALSE   FALSE             FALSE            
## 5 AB    EDMONTON CORONATION       1796 301BK03        NA <NA>   53.6 -114.  671. Etc/GMT+7 day       1978  1979 FALSE   FALSE             FALSE            
## 6 AB    EDMONTON CORONATION       1796 301BK03        NA <NA>   53.6 -114.  671. Etc/GMT+7 month     1978  1979 FALSE   FALSE             FALSE            
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```

``` r
glimpse(stations())
```

```
## Rows: 26,448
## Columns: 17
## $ prov              <chr> "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", …
## $ station_name      <chr> "DAYSLAND", "DAYSLAND", "DAYSLAND", "EDMONTON CORONATION", "EDMONTON CORONATION", "EDMONTON CORONATION", "FLEET", "FLEET", "FLEET", …
## $ station_id        <dbl> 1795, 1795, 1795, 1796, 1796, 1796, 1797, 1797, 1797, 1798, 1798, 1798, 1799, 1799, 1799, 1800, 1800, 1800, 1801, 1801, 1801, 1802, …
## $ climate_id        <chr> "301AR54", "301AR54", "301AR54", "301BK03", "301BK03", "301BK03", "301B6L0", "301B6L0", "301B6L0", "301B8LR", "301B8LR", "301B8LR", …
## $ WMO_id            <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ TC_id             <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ lat               <dbl> 52.87, 52.87, 52.87, 53.57, 53.57, 53.57, 52.15, 52.15, 52.15, 53.20, 53.20, 53.20, 52.40, 52.40, 52.40, 54.08, 54.08, 54.08, 53.52,…
## $ lon               <dbl> -112.28, -112.28, -112.28, -113.57, -113.57, -113.57, -111.73, -111.73, -111.73, -110.15, -110.15, -110.15, -115.20, -115.20, -115.2…
## $ elev              <dbl> 688.8, 688.8, 688.8, 670.6, 670.6, 670.6, 838.2, 838.2, 838.2, 640.0, 640.0, 640.0, 1036.0, 1036.0, 1036.0, 585.2, 585.2, 585.2, 668…
## $ tz                <chr> "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "E…
## $ interval          <fct> hour, day, month, hour, day, month, hour, day, month, hour, day, month, hour, day, month, hour, day, month, hour, day, month, hour, …
## $ start             <dbl> NA, 1908, 1908, NA, 1978, 1978, NA, 1987, 1987, NA, 1987, 1987, NA, 1980, 1980, NA, 1980, 1980, NA, 1986, 1986, NA, 1987, 1987, NA, …
## $ end               <dbl> NA, 1922, 1922, NA, 1979, 1979, NA, 1990, 1990, NA, 1998, 1998, NA, 2009, 2007, NA, 1981, 1981, NA, 2019, 2007, NA, 1991, 1991, NA, …
## $ normals           <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRU…
## $ normals_1991_2020 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…
## $ normals_1981_2010 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRU…
## $ normals_1971_2000 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…
```

You can look through this data frame directly, or you can use the `stations_search` function:


``` r
stations_search("Kamloops")
```

```
## # A tibble: 40 × 17
##    prov  station_name         station_id climate_id WMO_id TC_id   lat   lon  elev tz        interval start   end normals normals_1991_2020 normals_1981_2010
##    <chr> <chr>                     <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>     <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
##  1 BC    KAMLOOPS                   1274 1163779        NA <NA>   50.7 -120.  379. Etc/GMT+8 day       1878  1982 FALSE   FALSE             FALSE            
##  2 BC    KAMLOOPS                   1274 1163779        NA <NA>   50.7 -120.  379. Etc/GMT+8 month     1878  1982 FALSE   FALSE             FALSE            
##  3 BC    KAMLOOPS A                 1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      1953  2013 TRUE    TRUE              TRUE             
##  4 BC    KAMLOOPS A                 1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 day       1951  2013 TRUE    TRUE              TRUE             
##  5 BC    KAMLOOPS A                 1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 month     1951  2013 TRUE    TRUE              TRUE             
##  6 BC    KAMLOOPS A                51423 1163781     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      2013  2026 TRUE    TRUE              FALSE            
##  7 BC    KAMLOOPS A                51423 1163781     71887 YKA    50.7 -120.  345. Etc/GMT+8 day       2013  2026 TRUE    TRUE              FALSE            
##  8 BC    KAMLOOPS AFTON MINES       1276 1163790        NA <NA>   50.7 -120.  701  Etc/GMT+8 day       1977  1993 TRUE    FALSE             FALSE            
##  9 BC    KAMLOOPS AFTON MINES       1276 1163790        NA <NA>   50.7 -120.  701  Etc/GMT+8 month     1977  1993 TRUE    FALSE             FALSE            
## 10 BC    KAMLOOPS AUT              42203 1163842     71741 ZKA    50.7 -120.  345  Etc/GMT+8 hour      2006  2026 TRUE    TRUE              FALSE            
## # ℹ 30 more rows
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```

You can narrow down your search by specifying time intervals (options are "hour", "day", or "month"):


``` r
stations_search("Kamloops", interval = "hour")
```

```
## # A tibble: 3 × 17
##   prov  station_name station_id climate_id WMO_id TC_id   lat   lon  elev tz        interval start   end normals normals_1991_2020 normals_1981_2010
##   <chr> <chr>             <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>     <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
## 1 BC    KAMLOOPS A         1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      1953  2013 TRUE    TRUE              TRUE             
## 2 BC    KAMLOOPS A        51423 1163781     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      2013  2026 TRUE    TRUE              FALSE            
## 3 BC    KAMLOOPS AUT      42203 1163842     71741 ZKA    50.7 -120.  345  Etc/GMT+8 hour      2006  2026 TRUE    TRUE              FALSE            
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```

You can specify more than one interval:


``` r
stations_search("Kamloops", interval = c("hour", "month"))
```

```
## # A tibble: 21 × 17
##    prov  station_name            station_id climate_id WMO_id TC_id   lat   lon  elev tz        interval start   end normals normals_1991_2020 normals_1981_2010
##    <chr> <chr>                        <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>     <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
##  1 BC    KAMLOOPS                      1274 1163779        NA <NA>   50.7 -120.  379. Etc/GMT+8 month     1878  1982 FALSE   FALSE             FALSE            
##  2 BC    KAMLOOPS A                    1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      1953  2013 TRUE    TRUE              TRUE             
##  3 BC    KAMLOOPS A                    1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 month     1951  2013 TRUE    TRUE              TRUE             
##  4 BC    KAMLOOPS A                   51423 1163781     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      2013  2026 TRUE    TRUE              FALSE            
##  5 BC    KAMLOOPS AFTON MINES          1276 1163790        NA <NA>   50.7 -120.  701  Etc/GMT+8 month     1977  1993 TRUE    FALSE             FALSE            
##  6 BC    KAMLOOPS AUT                 42203 1163842     71741 ZKA    50.7 -120.  345  Etc/GMT+8 hour      2006  2026 TRUE    TRUE              FALSE            
##  7 BC    KAMLOOPS AUT                 42203 1163842     71741 ZKA    50.7 -120.  345  Etc/GMT+8 month     2006  2006 TRUE    TRUE              FALSE            
##  8 BC    KAMLOOPS CDA                  1277 1163810        NA <NA>   50.7 -120.  345  Etc/GMT+8 month     1949  1977 FALSE   FALSE             FALSE            
##  9 BC    KAMLOOPS CHERRY CREEK         1278 1163814        NA <NA>   50.7 -121.  556. Etc/GMT+8 month     1970  1974 FALSE   FALSE             FALSE            
## 10 BC    KAMLOOPS CHERRY CREEK 2       1279 1163815        NA <NA>   50.6 -121.  701  Etc/GMT+8 month     1974  1977 FALSE   FALSE             FALSE            
## # ℹ 11 more rows
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```


You can also search by proximity. These results include a new column `distance` specifying the distance in km from the coordinates:


``` r
stations_search(
  coords = c(50.667492, -120.329049),
  dist = 20,
  interval = "hour"
)
```

```
## # A tibble: 3 × 18
##   prov  station_name station_id climate_id WMO_id TC_id   lat   lon  elev tz        interval start   end normals normals_1991_2020 normals_1981_2010
##   <chr> <chr>             <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>     <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
## 1 BC    KAMLOOPS A         1275 1163780     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      1953  2013 TRUE    TRUE              TRUE             
## 2 BC    KAMLOOPS AUT      42203 1163842     71741 ZKA    50.7 -120.  345  Etc/GMT+8 hour      2006  2026 TRUE    TRUE              FALSE            
## 3 BC    KAMLOOPS A        51423 1163781     71887 YKA    50.7 -120.  345. Etc/GMT+8 hour      2013  2026 TRUE    TRUE              FALSE            
## # ℹ 2 more variables: normals_1971_2000 <lgl>, distance <dbl>
```

We can also perform more complex searches using `filter()` function from the `dplyr` package
direction on the data returned by stations():


``` r
BCstations <- stations() |>
  filter(prov %in% c("BC")) |>
  filter(interval == "hour") |>
  filter(lat > 49 & lat < 49.5) |>
  filter(lon > -119 & lon < -116) |>
  filter(start <= 2002) |>
  filter(end >= 2016)
BCstations
```

```
## # A tibble: 3 × 17
##   prov  station_name                station_id climate_id WMO_id TC_id   lat   lon  elev tz     interval start   end normals normals_1991_2020 normals_1981_2010
##   <chr> <chr>                            <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>  <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
## 1 BC    CRESTON CAMPBELL SCIENTIFIC       6838 114B1F0     71770 WJR    49.1 -116.  641. Etc/G… hour      1994  2026 TRUE    TRUE              FALSE            
## 2 BC    NELSON CS                         6839 1145M29     71776 WNM    49.5 -117.  535. Etc/G… hour      1994  2026 TRUE    TRUE              FALSE            
## 3 BC    WARFIELD RCS                     31067 1148705     71401 XWF    49.1 -118.  567. Etc/G… hour      2001  2026 TRUE    TRUE              FALSE            
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```

``` r
## weather_dl() accepts numbers so we can create a vector to input into weather:
stn_vector <- BCstations$station_id
stn_vector
```

```
## [1]  6838  6839 31067
```

You can update this list of stations with


``` r
stations_dl()
```

And check when it was last updated with

``` r
stations_meta()
```

```
## # A tibble: 1 × 2
##   ECCC_modified       weathercan_modified
##   <dttm>              <date>             
## 1 2026-06-03 23:30:00 2026-06-16
```


## Weather

Once you have your `station_id`(s) you can download weather data:


``` r
kam <- weather_dl(station_ids = 51423, start = "2016-01-01", end = "2016-02-15")
```

```
## As of weathercan v0.3.0 time display is either local time or UTC See Details under ]8;;x-r-help:weather_dl`weather_dl()`]8;; for more information. This message
## is shown once per session
```

``` r
kam
```

```
## # A tibble: 1,104 × 38
##    station_name station_id station_operator prov    lat   lon  elev climate_id WMO_id TC_id date       time                 year month   day hour   qual   temp
##    <chr>             <dbl> <lgl>            <chr> <dbl> <dbl> <dbl> <chr>      <chr>  <chr> <date>     <dttm>              <dbl> <int> <int> <time> <chr> <dbl>
##  1 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 00:00:00  2016     1     1 00:00  <NA>   -9.1
##  2 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 01:00:00  2016     1     1 01:00  <NA>   -9.6
##  3 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 02:00:00  2016     1     1 02:00  <NA>   -9.9
##  4 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 03:00:00  2016     1     1 03:00  <NA>   -9.5
##  5 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 04:00:00  2016     1     1 04:00  <NA>   -9.4
##  6 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 05:00:00  2016     1     1 05:00  <NA>   -9.8
##  7 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 06:00:00  2016     1     1 06:00  <NA>  -10  
##  8 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 07:00:00  2016     1     1 07:00  <NA>  -10.2
##  9 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 08:00:00  2016     1     1 08:00  <NA>  -10.1
## 10 KAMLOOPS A        51423 NA               BC     50.7 -120.  345. 1163781    71887  YKA   2016-01-01 2016-01-01 09:00:00  2016     1     1 09:00  <NA>   -9.7
## # ℹ 1,094 more rows
## # ℹ 20 more variables: temp_flag <chr>, temp_dew <dbl>, temp_dew_flag <chr>, rel_hum <dbl>, rel_hum_flag <chr>, precip_amt <dbl>, precip_amt_flag <chr>,
## #   wind_dir <dbl>, wind_dir_flag <chr>, wind_spd <dbl>, wind_spd_flag <chr>, visib <dbl>, visib_flag <chr>, pressure <dbl>, pressure_flag <chr>, hmdx <dbl>,
## #   hmdx_flag <chr>, wind_chill <dbl>, wind_chill_flag <chr>, weather <chr>
```

You can also download data from multiple stations at once:


``` r
kam.pg <- weather_dl(
  station_ids = c(48248, 51423),
  start = "2016-01-01",
  end = "2016-02-15"
)

kam.pg
```

```
## # A tibble: 2,208 × 38
##    station_name   station_id station_operator prov    lat   lon  elev climate_id WMO_id TC_id date       time                 year month   day hour  qual   temp
##    <chr>               <dbl> <lgl>            <chr> <dbl> <dbl> <dbl> <chr>      <chr>  <chr> <date>     <dttm>              <dbl> <int> <int> <tim> <chr> <dbl>
##  1 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 00:00:00  2016     1     1 00:00 <NA>  -21.2
##  2 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 01:00:00  2016     1     1 01:00 <NA>  -21.4
##  3 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 02:00:00  2016     1     1 02:00 <NA>  -22.8
##  4 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 03:00:00  2016     1     1 03:00 <NA>  -23.1
##  5 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 04:00:00  2016     1     1 04:00 <NA>  -22.9
##  6 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 05:00:00  2016     1     1 05:00 <NA>  -24.2
##  7 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 06:00:00  2016     1     1 06:00 <NA>  -21.8
##  8 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 07:00:00  2016     1     1 07:00 <NA>  -22.7
##  9 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 08:00:00  2016     1     1 08:00 <NA>  -22.7
## 10 PRINCE GEORGE…      48248 NA               BC     53.9 -123.   680 1096453    71302  VXS   2016-01-01 2016-01-01 09:00:00  2016     1     1 09:00 <NA>  -22.9
## # ℹ 2,198 more rows
## # ℹ 20 more variables: temp_flag <chr>, temp_dew <dbl>, temp_dew_flag <chr>, rel_hum <dbl>, rel_hum_flag <chr>, precip_amt <dbl>, precip_amt_flag <chr>,
## #   wind_dir <dbl>, wind_dir_flag <chr>, wind_spd <dbl>, wind_spd_flag <chr>, visib <dbl>, visib_flag <chr>, pressure <dbl>, pressure_flag <chr>, hmdx <dbl>,
## #   hmdx_flag <chr>, wind_chill <dbl>, wind_chill_flag <chr>, weather <chr>
```


And plot it:


``` r
ggplot(
  data = kam.pg,
  aes(x = time, y = temp, group = station_name, colour = station_name)
) +
  theme(legend.position = "top") +
  geom_line() +
  theme_minimal()
```

<div class="figure" style="text-align: center">
<img src="figures/weathercan-unnamed-chunk-12-1.png" alt="plot of chunk unnamed-chunk-12"  />
<p class="caption">plot of chunk unnamed-chunk-12</p>
</div>

Or you can use the vector created above:


``` r
stn_vec_df <- weather_dl(
  station_ids = stn_vector,
  start = "2016-01-01",
  end = "2016-02-15"
)

stn_vec_df
```

```
## # A tibble: 3,312 × 38
##    station_name   station_id station_operator prov    lat   lon  elev climate_id WMO_id TC_id date       time                 year month   day hour  qual   temp
##    <chr>               <dbl> <lgl>            <chr> <dbl> <dbl> <dbl> <chr>      <chr>  <chr> <date>     <dttm>              <dbl> <int> <int> <tim> <chr> <dbl>
##  1 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 00:00:00  2016     1     1 00:00 <NA>   -7.2
##  2 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 01:00:00  2016     1     1 01:00 <NA>   -7.8
##  3 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 02:00:00  2016     1     1 02:00 <NA>   -8  
##  4 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 03:00:00  2016     1     1 03:00 <NA>   -8.1
##  5 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 04:00:00  2016     1     1 04:00 <NA>   -8.4
##  6 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 05:00:00  2016     1     1 05:00 <NA>   -8.5
##  7 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 06:00:00  2016     1     1 06:00 <NA>   -8.9
##  8 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 07:00:00  2016     1     1 07:00 <NA>   -9.1
##  9 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 08:00:00  2016     1     1 08:00 <NA>   -9.2
## 10 CRESTON CAMPB…       6838 NA               BC     49.1 -116.  641. 114B1F0    71770  WJR   2016-01-01 2016-01-01 09:00:00  2016     1     1 09:00 <NA>   -9.5
## # ℹ 3,302 more rows
## # ℹ 20 more variables: temp_flag <chr>, temp_dew <dbl>, temp_dew_flag <chr>, rel_hum <dbl>, rel_hum_flag <chr>, precip_amt <dbl>, precip_amt_flag <chr>,
## #   wind_dir <dbl>, wind_dir_flag <chr>, wind_spd <dbl>, wind_spd_flag <chr>, visib <dbl>, visib_flag <chr>, pressure <dbl>, pressure_flag <chr>, hmdx <dbl>,
## #   hmdx_flag <chr>, wind_chill <dbl>, wind_chill_flag <chr>, weather <lgl>
```

For more information on the data flags, see the [Flags vignette](flags.html), for more information on units and terms, see the [Terms and Units vignette](glossary.html).

## Climate Normals

To access climate normals, you first need to know the `climate_id` associated with the station you're interested in.


``` r
stations_search("Winnipeg", normals_years = "current")
```

```
## The most current normals available for download by weathercan are '1991-2020'
```

```
## # A tibble: 10 × 17
##    prov  station_name                station_id climate_id WMO_id TC_id   lat   lon  elev tz    interval start   end normals normals_1991_2020 normals_1981_2010
##    <chr> <chr>                            <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr> <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
##  1 MB    WINNIPEG A CS                    27174 502S001     71849 XWG    49.9 -97.2  239. Etc/… hour      2013  2026 TRUE    TRUE              FALSE            
##  2 MB    WINNIPEG A CS                    27174 502S001     71849 XWG    49.9 -97.2  239. Etc/… day       1996  2026 TRUE    TRUE              FALSE            
##  3 MB    WINNIPEG A CS                    27174 502S001     71849 XWG    49.9 -97.2  239. Etc/… month     1996  2007 TRUE    TRUE              FALSE            
##  4 MB    WINNIPEG INTL A                  51097 5023227        NA YWG    49.9 -97.2  239. Etc/… hour      2013  2026 TRUE    TRUE              FALSE            
##  5 MB    WINNIPEG INTL A                  51097 5023227        NA YWG    49.9 -97.2  239. Etc/… day       2018  2026 TRUE    TRUE              FALSE            
##  6 MB    WINNIPEG RICHARDSON AWOS         47407 5023226     71852 YWG    49.9 -97.2  239. Etc/… hour      2008  2013 TRUE    TRUE              FALSE            
##  7 MB    WINNIPEG RICHARDSON AWOS         47407 5023226     71852 YWG    49.9 -97.2  239. Etc/… day       2008  2013 TRUE    TRUE              FALSE            
##  8 MB    WINNIPEG RICHARDSON INT'L A       3698 5023222     71852 YWG    49.9 -97.2  239. Etc/… hour      1953  2013 TRUE    TRUE              TRUE             
##  9 MB    WINNIPEG RICHARDSON INT'L A       3698 5023222     71852 YWG    49.9 -97.2  239. Etc/… day       1938  2008 TRUE    TRUE              TRUE             
## 10 MB    WINNIPEG RICHARDSON INT'L A       3698 5023222     71852 YWG    49.9 -97.2  239. Etc/… month     1938  2007 TRUE    TRUE              TRUE             
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```

The current year range is 1991-2020, but you can also search for stations in the
previous year range:


``` r
stations_search("Winnipeg", normals_years = "1981-2010")
```

```
## # A tibble: 3 × 17
##   prov  station_name                station_id climate_id WMO_id TC_id   lat   lon  elev tz     interval start   end normals normals_1991_2020 normals_1981_2010
##   <chr> <chr>                            <dbl> <chr>       <dbl> <chr> <dbl> <dbl> <dbl> <chr>  <fct>    <dbl> <dbl> <lgl>   <lgl>             <lgl>            
## 1 MB    WINNIPEG RICHARDSON INT'L A       3698 5023222     71852 YWG    49.9 -97.2  239. Etc/G… hour      1953  2013 TRUE    TRUE              TRUE             
## 2 MB    WINNIPEG RICHARDSON INT'L A       3698 5023222     71852 YWG    49.9 -97.2  239. Etc/G… day       1938  2008 TRUE    TRUE              TRUE             
## 3 MB    WINNIPEG RICHARDSON INT'L A       3698 5023222     71852 YWG    49.9 -97.2  239. Etc/G… month     1938  2007 TRUE    TRUE              TRUE             
## # ℹ 1 more variable: normals_1971_2000 <lgl>
```

Note that the Winnipeg station has normals for both year ranges.

Then you can download the climate normals with the `normals_dl()` function.


``` r
n <- normals_dl("5023222")
```

```
## The most current normals available for download by weathercan are '1991-2020'
## Using composite locations: WINNIPEG RICHARDSON (AIRPORT)
```

``` r
n
```

```
## # A tibble: 26 × 313
##    location_name             prov  composite_stations period_of_record period daily_average_c daily_average_c_code stddev_mean_monthly_…¹ stddev_mean_monthly_…²
##    <chr>                     <chr> <chr>              <chr>            <chr>            <dbl> <chr>                                 <dbl> <chr>                 
##  1 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Jan              -16.3 A                                       3.6 A                     
##  2 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Feb              -14.1 A                                       4   A                     
##  3 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Mar               -6.1 A                                       3.7 A                     
##  4 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Apr                3.8 A                                       2.9 A                     
##  5 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           May               11.1 A                                       1.9 A                     
##  6 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Jun               17.1 A                                       1.5 A                     
##  7 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Jul               19.5 A                                       1.4 A                     
##  8 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Aug               18.7 A                                       1.5 A                     
##  9 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Sep               13.3 A                                       1.6 A                     
## 10 WINNIPEG RICHARDSON (AIR… MB    WINNIPEG A CS (50… Normal           Oct                5.1 A                                       2.1 A                     
## # ℹ 16 more rows
## # ℹ abbreviated names: ¹​stddev_mean_monthly_temperature_c, ²​stddev_mean_monthly_temperature_c_code
## # ℹ 304 more variables: daily_maximum_c <dbl>, daily_maximum_c_code <chr>, daily_minimum_c <dbl>, daily_minimum_c_code <chr>, maximum_daily_mean_c <dbl>,
## #   maximum_daily_mean_c_code <lgl>, maximum_daily_mean_c_date <date>, maximum_daily_mean_c_date_code <lgl>, minimum_daily_mean_c <dbl>,
## #   minimum_daily_mean_c_code <lgl>, minimum_daily_mean_c_date <date>, minimum_daily_mean_c_date_code <lgl>, extreme_maximum_c <dbl>,
## #   extreme_maximum_c_code <lgl>, extreme_maximum_c_date <date>, extreme_maximum_c_date_code <lgl>, minimum_daily_maximum_c <dbl>,
## #   minimum_daily_maximum_c_code <lgl>, minimum_daily_maximum_c_date <date>, minimum_daily_maximum_c_date_code <lgl>, maximum_daily_minimum_c <dbl>, …
```


Older normals can be downloaded by changing the year


``` r
n <- normals_dl("5023222", normals_year = "1981-2010")
n
```

```
## # A tibble: 1 × 7
##   prov  station_name                climate_id normals_years meets_wmo normals             frost           
##   <chr> <chr>                       <chr>      <chr>         <lgl>     <list>              <list>          
## 1 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble [13 × 197]> <tibble [7 × 8]>
```

Note that older normals have two parts to the data, average weather measurements and average frost dates.


``` r
library(tidyr)
unnest(n, normals)
```

```
## # A tibble: 13 × 203
##    prov  station_name                climate_id normals_years meets_wmo period temp_daily_average temp_daily_average_code temp_sd temp_sd_code temp_daily_max
##    <chr> <chr>                       <chr>      <chr>         <lgl>     <fct>               <dbl> <chr>                     <dbl> <chr>                 <dbl>
##  1 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Jan                 -16.4 A                           4.1 A                     -11.3
##  2 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Feb                 -13.2 A                           4.2 A                      -8.1
##  3 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Mar                  -5.8 A                           3.1 A                      -0.8
##  4 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Apr                   4.4 A                           2.7 A                      10.9
##  5 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      May                  11.6 A                           2.1 A                      18.6
##  6 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Jun                  17   A                           2   A                      23.2
##  7 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Jul                  19.7 A                           1.4 A                      25.9
##  8 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Aug                  18.8 A                           1.9 A                      25.4
##  9 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Sep                  12.7 A                           1.3 A                      19  
## 10 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Oct                   5   A                           1.8 A                      10.5
## 11 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Nov                  -4.9 A                           3.6 A                      -0.5
## 12 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Dec                 -13.2 A                           4.4 A                      -8.5
## 13 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      Year                  3   A                           1.2 A                       8.7
## # ℹ 192 more variables: temp_daily_max_code <chr>, temp_daily_min <dbl>, temp_daily_min_code <chr>, temp_extreme_max <dbl>, temp_extreme_max_code <chr>,
## #   temp_extreme_max_date <date>, temp_extreme_max_date_code <chr>, temp_extreme_min <dbl>, temp_extreme_min_code <chr>, temp_extreme_min_date <date>,
## #   temp_extreme_min_date_code <chr>, rain <dbl>, rain_code <chr>, snow <dbl>, snow_code <chr>, precip <dbl>, precip_code <chr>, snow_mean_depth <dbl>,
## #   snow_mean_depth_code <chr>, snow_median_depth <dbl>, snow_median_depth_code <chr>, snow_depth_month_end <dbl>, snow_depth_month_end_code <chr>,
## #   rain_extreme_daily <dbl>, rain_extreme_daily_code <chr>, rain_extreme_daily_date <date>, rain_extreme_daily_date_code <chr>, snow_extreme_daily <dbl>,
## #   snow_extreme_daily_code <chr>, snow_extreme_daily_date <date>, snow_extreme_daily_date_code <chr>, precip_extreme_daily <dbl>,
## #   precip_extreme_daily_code <chr>, precip_extreme_daily_date <date>, precip_extreme_daily_date_code <chr>, snow_extreme_depth <dbl>, …
```

``` r
unnest(n, frost)
```

```
## # A tibble: 7 × 14
##   prov  station_name                climate_id normals_years meets_wmo normals  frost_code date_last_spring_frost date_first_fall_frost length_frost_free prob 
##   <chr> <chr>                       <chr>      <chr>         <lgl>     <list>   <chr>                       <dbl>                 <dbl>             <dbl> <chr>
## 1 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 10%  
## 2 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 25%  
## 3 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 33%  
## 4 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 50%  
## 5 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 66%  
## 6 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 75%  
## 7 MB    WINNIPEG RICHARDSON INT'L A 5023222    1981-2010     TRUE      <tibble> A                             143                   265               121 90%  
## # ℹ 3 more variables: prob_last_spring_temp_below_0_on_date <dbl>, prob_first_fall_temp_below_0_on_date <dbl>, prob_length_frost_free <dbl>
```