The defStormsList() function extracts storm track data from a stormsDataset
and creates a stormsList object based on specified arguments relating to location of interest,
seasons, and names of the storms.
Usage
defStormsList(
sds,
loi,
seasons = c(sds@seasons["min"], sds@seasons["max"]),
names = NULL,
maxDist = 300,
scale = sshs,
scalePalette = NULL,
removeUnder = NULL,
verbose = 2
)Arguments
- sds
stormsDatasetobject.- loi
Location of interest. Can be defined using,
character, a country name (e.g., "Vanuatu")
character, a basin name among "NA", "SA", "EP", "WP", "SP", "SI" and "NI"
numeric vector, a point coordinate (lon, lat in decimal degrees, e.g., c(169.5, -19.2))
sp (SpatialPolygon) or a sf (simple features) object (e.g., created from a shapefile)
- seasons
numeric vector. Seasons of occurrence of the storms (e.g., c(2020,2022)). In the Southern Hemisphere, the cyclone season extends across two consecutive years. Therefore, to capture the 2021 to 2022 cyclone season both years should be specified, with cyclones assigned for the year that originated in. By default all storms from
sdsare extracted.- names
character vector. Names of specific storms (in capital letters).
- maxDist
numeric. Maximum distance between the location of interest and the storm for which track data are extracted. Default
maxDistis set to 300 km.- scale
numeric. List of storm scale thresholds used for the database. Default value is set to the Saffir Simpson Hurricane Scale
- scalePalette
character. Named vector containing the color hex code corresponding to each category interval of
scaleinput- removeUnder
numeric. Storms reaching this maximum level or less in the scale are removed. Default value is set to NULL.
- verbose
numeric. Type of information the function displays. Can be:
2, information about both the processes and the outputs are displayed (default value),1, only information about the processes are displayed, or0, nothing is displayed.
Value
The defStormsList() function returns a stormsList object containing track data for all storms
meeting the specified criteria (e.g., name, season, location).
Details
The available countries for the loi are those provided in the
rwolrdxtra package. This package provide high resolution vector country
boundaries derived from Natural Earth data. More informations on the Natural Earth data
here: http://www.naturalearthdata.com/downloads/10m-cultural-vectors/.
References
Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J., & Neumann, C. J. (2010). The International Best Track Archive for Climate Stewardship (IBTrACS). Bulletin of the American Meteorological Society, 91(3), Article 3. doi:10.1175/2009bams2755.1
Examples
# \donttest{
#Creating a stormsDataset
sds <- defStormsDataset()
#> Warning: No basin argument specified. StormR will work as expected
#> but cannot use basin filtering for speed-up when collecting data
#> === Loading data ===
#> Open database... /home/runner/work/_temp/Library/StormR/extdata/test_dataset.nc opened
#> Collecting data ...
#> === DONE ===
#Getting data using country names
vanuatu.st <- defStormsList(sds = sds, loi = "Vanuatu")
#> === Storms processing ... ===
#>
#> -> Making buffer: Done
#> -> Searching storms from 2015 to 2021 ...
#> -> Identifying Storms: 9 potential candidates...
#> -> Gathering storm(s) ...
#>
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#>
#> === DONE with run time 4.814612 sec ===
#>
#> SUMMARY:
#> (*) LOI: Vanuatu
#> (*) Buffer size: 300 km
#> (*) Number of storms: 7
#> Name - Tropical season - Scale - Number of observation within buffer:
#> PAM - 2015 - 6 - 20
#> SOLO - 2015 - 1 - 4
#> ULA - 2016 - 5 - 12
#> WINSTON - 2016 - 6 - 22
#> ZENA - 2016 - 3 - 8
#> UESI - 2020 - 2 - 5
#> LUCAS - 2021 - 2 - 9
#>
#Getting data using a specific point location
pt <- c(169, -19)
pam.pt <- defStormsList(sds = sds, loi = pt, names = "PAM")
#> === Storms processing ... ===
#>
#> -> Making buffer: Done
#> -> Searching for PAM storm ...
#> -> Identifying Storms: Done
#> -> Gathering storm(s) ...
#>
#> === DONE with run time 0.03578568 sec ===
#>
#> SUMMARY:
#> (*) LOI: 169 -19 lon-lat
#> (*) Buffer size: 300 km
#> (*) Number of storms: 1
#> Name - Tropical season - Scale - Number of observation within buffer:
#> PAM - 2015 - 6 - 8
#>
#Getting data using country and storm names
niran.nc <- defStormsList(sds = sds, loi = "New Caledonia", names = c("NIRAN"))
#> === Storms processing ... ===
#>
#> -> Making buffer: Done
#> -> Searching for NIRAN storm ...
#> -> Identifying Storms: Done
#> -> Gathering storm(s) ...
#>
#> === DONE with run time 0.4747238 sec ===
#>
#> SUMMARY:
#> (*) LOI: New Caledonia
#> (*) Buffer size: 300 km
#> (*) Number of storms: 1
#> Name - Tropical season - Scale - Number of observation within buffer:
#> NIRAN - 2021 - 6 - 10
#>
#Getting data using a user defined spatial polygon
poly <- cbind(c(135, 290, 290, 135, 135),c(-60, -60, 0, 0, -60))
sp <- sf::st_polygon(list(poly))
sp <- sf::st_sfc(sp, crs = 4326)
sp <- sf::st_as_sf(sp)
sts_sp <- defStormsList(sds = sds, loi = sp)
#> === Storms processing ... ===
#>
#> -> Making buffer: Done
#> -> Searching storms from 2015 to 2021 ...
#> -> Identifying Storms: 9 potential candidates...
#> -> Gathering storm(s) ...
#>
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#>
#> === DONE with run time 0.1484265 sec ===
#>
#> SUMMARY:
#> (*) LOI: sf object (use getLOI function for further informations
#> (*) Buffer size: 300 km
#> (*) Number of storms: 9
#> Name - Tropical season - Scale - Number of observation within buffer:
#> PAM - 2015 - 6 - 57
#> SOLO - 2015 - 1 - 29
#> ULA - 2016 - 5 - 119
#> WINSTON - 2016 - 6 - 151
#> ZENA - 2016 - 3 - 21
#> UESI - 2020 - 2 - 67
#> GRETEL - 2020 - 2 - 27
#> LUCAS - 2021 - 2 - 49
#> NIRAN - 2021 - 6 - 65
#>
# }