This function takes a list of US counties, based on their 5-digit Federal Information Processing Standard (FIPS) codes, boundaries on the range of years to be considered, thresholds for distance between each county and the storm track, as well as minimum rainfall over a certain time window for the county to be considered "exposed" to the storm. Based on these inputs, the function returns a dataframe with the subset of Atlantic basin storms meeting those criteria for each of the listed counties.
county_rain(counties, start_year, end_year, rain_limit, dist_limit,
days_included = c(-2, -1, 0, 1))
Character vector of the five-digit Federal Information Processing Standard (FIPS) codes for counties for which the user wants to determine storm exposure.
Four-digit integer with first year to consider.
Four-digit integer with last year to consider.
Minimum of rainfall, in millimeters, summed across the days
selected to be included (days_included
), that must fall in a
county for the county to be classified as "exposed" to the storm.
Maximum distance, in kilometers, of how close the storm track must come to the county's population mean center to classify the county as "exposed" to the storm.
A numeric vector listing the days to include when
calculating total precipitation. Negative numbers are days before the
closest date of the storm to a county. For example,
c(-1, 0, 1)
would calculate rain for a county as the sum of the
rainfall for the day before, the day of, and the day after the date when
the storm center was closest to the county center. Values can range from
-5 to 3 (i.e., at most, you can calculate the total rainfall from five days
to three days after the day when the storm is closest to the
county).
Returns a dataframe with a row for each county-storm pair and with columns for:
storm_id
: Unique storm identifier with the storm name and year,
separated by a hyphen(e.g., "Alberto-1988",
"Katrina-2005")
fips
: County's 5-digit Federal Information Processing Standard
(FIPS) code
closest_date
: Date (based on local time) of the closest
approach of the storm to the county's population
mean center.
storm_dist
: Minimum distance (in kilometers) between the storm's
track and the county's population mean center.
tot_precip
: Cumulative rainfall, in millimeters, in the
county for the days selected using the
days_included
option.
local_time
: Local time of the closest approach of the storm to the
county's population mean center, based on storm tracks
linearly interpolated to 15-minute increments.
closest_time_utc
: Time, in UTC, of the closest approach of the
storm to the county's population mean center,
based on storm tracks linearly interpolated to
15-minute increments.
Al-Hamdan MZ, Crosson WL, Economou SA, Estes MG, Estes SM, Hemmings SN, Kent ST, Puckette M, Quattrochi DA, Rickman DL, Wade GM, McClure LA, 2014. Environmental public health applications using remotely sensed data. Geocarto International 29(1):85-98.
North America Land Data Assimilation System (NLDAS) Daily Precipitation years 1979-2011 on CDC WONDER Online Database, released 2012. http://wonder.cdc.gov/wonder/help/Precipitation.html
Rui H, Mocko D, 2014. README Document for North America Land Data Assimilation System Phase 2 (NLDAS-2) Products. Goddard Earth Sciences Data and Information Services Center.
# NOT RUN {
# 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)) {
county_rain(counties = c("22071", "51700"),
start_year = 1995, end_year = 2005,
rain_limit = 100, dist_limit = 100)
}
# }
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