Using {worldmet} to Locate, Import & Visualise Meteorological Data • worldmet

library(worldmet)

Show all sites

The function to use to find which sites are available is getMeta(). While this function can be run using different options, it can be easiest to run it without any options. This produces a map of all the available sites, which can be quickly accessed.

Click to expand the markers until you find the site of interest (shown by a blue marker). This reveals some site information including the site name and the start and end date of available data. The most important information revealed in the marker is the code, which is used to access the data.

getMeta()
#> # A tibble: 13,241 × 12
#>    usaf  wban  station ctry  st    call  latitude longitude `elev(m)` begin     
#>    <chr> <chr> <chr>   <chr> <chr> <chr>    <dbl>     <dbl>     <dbl> <date>    
#>  1 0100… 99999 EDGEOYA NO    NA    NA        78.2      22.8      14   1973-01-01
#>  2 0100… 99999 NY-ALE… SV    NA    NA        78.9      11.9       7.7 1973-01-06
#>  3 0100… 99999 LONGYE… SV    NA    ENSB      78.2      15.5      26.8 1975-09-29
#>  4 0100… 99999 KARL X… SV    NA    NA        80.6      25         5   1955-01-01
#>  5 0101… 99999 ANDOYA  NO    NA    ENAN      69.3      16.1      13.1 1931-01-03
#>  6 0101… 99999 KVITOYA SV    NA    NA        80.1      31.5      10   1986-11-18
#>  7 0101… 99999 HEKKIN… NO    NA    NA        69.6      17.8      14   1980-03-14
#>  8 0101… 99999 KONGSO… NO    NA    NA        78.9      28.9      20   1993-05-01
#>  9 0101… 99999 AKSELO… SV    NA    NA        77.7      14.8       6   1973-01-01
#> 10 0102… 99999 SORKAP… SV    NA    NA        76.5      16.6      10   2010-10-08
#> # ℹ 13,231 more rows
#> # ℹ 2 more variables: end <date>, code <chr>

When using getMeta() it will probably be useful to read the information into a data frame. Note that plot = FALSE stops the function from providing the map.

met_info <- getMeta(plot = FALSE)

Search based on latitude and longitude

Often, one has an idea of the region in which a site is of interest. For example, if the interest was in sites close to London, the latitude and longitude can be supplied and a search is carried out of the 10 nearest sites to that location. There is also an option n that can be used in change the number of nearest sites shown. If a lat/lon is provided, clicking on the blue marker will show the approximate distance between the site and the search coordinates.

getMeta(lat = 51.5, lon = 0)
#> # A tibble: 10 × 15
#>    usaf  wban  station ctry  st    call  latitude longitude `elev(m)` begin     
#>    <chr> <chr> <chr>   <chr> <chr> <chr>    <dbl>     <dbl>     <dbl> <date>    
#>  1 0376… 99999 CITY    UK    NA    EGLC      51.5     0.055       5.8 1988-01-29
#>  2 0377… 99999 ST JAM… UK    NA    NA        51.5    -0.117       5   2009-12-18
#>  3 0376… 99999 BIGGIN… UK    NA    EGKB      51.3     0.033     182.  1988-01-05
#>  4 0378… 99999 KENLEY… UK    NA    NA        51.3    -0.083     170   1988-02-01
#>  5 0367… 99999 NORTHO… UK    NA    EGWU      51.6    -0.418      37.8 1973-01-01
#>  6 0377… 99999 HEATHR… UK    NA    EGLL      51.5    -0.461      25.3 1948-12-01
#>  7 0377… 99999 GATWICK UK    NA    EGKK      51.1    -0.19       61.6 1973-01-01
#>  8 0368… 99999 ROTHAM… UK    NA    NA        51.8    -0.358     128   2013-08-20
#>  9 0376… 99999 CHARLW… UK    NA    NA        51.1    -0.229      68   1992-03-01
#> 10 0368… 99999 STANST… UK    NA    EGSS      51.9     0.235     106.  1973-01-01
#> # ℹ 5 more variables: end <date>, code <chr>, longr <dbl>, latr <dbl>,
#> #   dist <dbl>

Importing Data

To obtain the data the user must supply a code (see above) and year(s) of interest. For example, to download data for Heathrow Airport in 2010 (code 037720-99999):

met_london <- importNOAA(code = "037720-99999", year = 2010)
head(met_london)
#> # A tibble: 6 × 25
#>   code        station date                latitude longitude  elev    ws      wd
#>   <fct>       <fct>   <dttm>                 <dbl>     <dbl> <dbl> <dbl>   <dbl>
#> 1 037720-999… HEATHR… 2010-01-01 00:00:00     51.5    -0.461  25.3  3.27  17.4  
#> 2 037720-999… HEATHR… 2010-01-01 01:00:00     51.5    -0.461  25.3  3.1    6.13 
#> 3 037720-999… HEATHR… 2010-01-01 02:00:00     51.5    -0.461  25.3  3.1   15.6  
#> 4 037720-999… HEATHR… 2010-01-01 03:00:00     51.5    -0.461  25.3  2.93  17.0  
#> 5 037720-999… HEATHR… 2010-01-01 04:00:00     51.5    -0.461  25.3  2.77   0.606
#> 6 037720-999… HEATHR… 2010-01-01 05:00:00     51.5    -0.461  25.3  2.43 356.   
#> # ℹ 17 more variables: air_temp <dbl>, atmos_pres <dbl>, visibility <dbl>,
#> #   dew_point <dbl>, RH <dbl>, ceil_hgt <dbl>, cl_1 <dbl>, cl_2 <dbl>,
#> #   cl_3 <dbl>, cl <dbl>, cl_1_height <dbl>, cl_2_height <dbl>,
#> #   cl_3_height <dbl>, precip_12 <dbl>, precip_6 <dbl>, pwc <chr>, precip <dbl>

A wind rose (for example) can easily be plotted using openair:

# load openair
openair::windRose(met_london)