multi_county_wind {hurricaneexposure}

Hurricane exposure by wind for communities

Description

This function takes a dataframe with multi-county communities and returns a community-level dataframe of "exposed" storms, based on the highest of the maximum sustained wind speed for each county in the community.

Usage

multi_county_wind(communities, start_year, end_year, wind_limit)

Arguments

communities

A dataframe with the FIPS codes for all counties within each community. It must include columns with a column identifier (commun) and with the FIPS codes of counties included in each community (fips). See the example code.

start_year

Four-digit integer with first year to consider.

end_year

Four-digit integer with last year to consider.

wind_limit

A numeric vector of length one giving the minimum wind speed (in meters per second) or duration of winds of 20 m / s or more (in minutes) to use in the filter. The units of this variable will depend on the user's choice for the wind_var parameter. If the Extended Best Tracks wind radii are used as the source of the wind data, the sustained winds will only be available for cutpoints of 34 knots, 50 knots, and 64 knots, so these values should be used (e.g., to get all counties with winds of 34 knots or higher, you could use wind_limit = 17.4, with the limit given as a value just below 34 knots in the units meters per second).

Value

Returns the same type dataframe as county_rain, but with storms listed by community instead of county.

Note

This function currently will only input a threshold for the sustained wind metric. If you would like to use gust winds or duration of winds, you will need to use the county_wind function to pull storms and aggregate to the multi-county community level yourself.

Examples

# Ensure that data package is available before running the example.
#  If it is not, see the `hurricaneexposure` package vignette for details
# on installing the required data package.
if (requireNamespace("hurricaneexposuredata", quietly = TRUE)) {

communities <- data.frame(community_name = c(rep("ny", 6), "no", "new"),
                         fips = c("36005", "36047", "36061",
                                  "36085", "36081", "36119",
                                  "22071", "51700"))
wind_df <- multi_county_wind(communities = communities,
                                     start_year = 1988, end_year = 2005,
                                     wind_limit = 20)
}