Large Hurricane Analysis - Distance and Wind • exposhur

Program Background

Script name: Large Hurricane Analysis - Distance and Wind
Project name: ADRD and Hurricane Exposure
Program description:

Maximum wind was calculated for each tract using the stormwindmodel published by Anderson at the geocentroid for each tract/zcta.
Data:
- HURDAT2
Restrictions:
Outline of program/analysis:
- Specify all storms
- Download and process hurdat2 tracks
- Calculate geo-centroid for each tract/zcta
- Utilize stormwindmodel to produce wind exposure estimates
- Output imputed track geojsons for visualization
Author: Ryan Zomorrodi
Revisions
Input files
- All files are downloaded using R functions
- Cache is stored in raw-data\hurdat2

Output files

tract/{storm_id}/distance_wind.csv

zcta/{storm_id}/distance_wind.csv

Column	Description
geoid	2010 geographic identifier
closest_datetime	Date and time in UTC that storm is closest to the imputed storm track
closest_dist	Closest distance (km) to imputed central track
highwind_datetime	Date and time in UTC of maximum wind speed
vmax_sust	Maximum 10-m 1-min sustained wind for the tropical cyclone (m/s)
vmax_gust	Max 10-m 1-min gust wind experienced at grid point (m/s)
sust_dur	Duration of time a certain sustained wind was experienced at grid point (minutes)
gust_dur	Duration of time a certain gust wind was experienced at grid point (minutes)

tract/{storm_id}/track_line.geojson
zcta/{storm_id}/track_line.geojson
tract/{storm_id}/track_points.geojson
zcta/{storm_id}/track_points.geojson

Start Time

start_time <- Sys.time()
cat(start_time, "\n")

library(exposhur)
library(tidyverse)
library(tigris)
library(sf)

The following hurricanes were selected.

hur_info <- readRDS( "raw-data/RF1_Hurricanes_Final.rds")
# get fips codes for each state
fips_codes <- distinct(tigris::fips_codes, state, state_code)
hur_info$fips <- pmap(hur_info, function(states, ...) {
  fips_codes$state_code[match(states, fips_codes$state)]
})

Get hurdat2 info for each storm

exposhur:::download_newest_hurdat2(path = "raw-data/hurdat2")

hur_info$hurdat2 <- pmap(hur_info, function(hurricane, ...){
  hurdat  <- get_hurdat2(
    storm_id = hurricane,
    path = "raw-data/hurdat2"
  )
  
  list(
    start_date = min(hurdat$datetime),
    end_date = max(hurdat$datetime),
    hurdat = hurdat
  )
})
hur_info <- unnest_wider(hur_info, hurdat2)

Get states

hur_info$tracts_sf <- pmap(hur_info, function(start_date, fips, ...) {
  tracts_list <- map(fips, 
    ~ tracts(state = .x, year = 2010, cb = TRUE)
  )
  bind_rows(tracts_list) %>%
    mutate(GEOID = str_sub(GEO_ID, -11)) %>% # get tract geoids
    filter(!st_is_empty(.)) %>% # remove tracts with empty geographies
    st_transform(4326) %>% # transform to WGS 84
    rename(geoid = GEOID) %>%
    st_centroid() # get geo-centroid of each tract
})

hur_info$zctas_sf <- pmap(hur_info, function(start_date, fips, ...) {
  zctas_list <- map(fips, 
    ~ zctas(state = .x, year = 2010, cb = FALSE)
  )
  bind_rows(zctas_list) %>%
    filter(!st_is_empty(.)) %>% # remove zctas with empty geographies
    st_transform(4326) %>%
    rename(geoid = GEOID10) %>%
    st_centroid() # get geo-centroid of each zctas
})

Calculate interpolated track

hur_info$track <- pmap(hur_info, function(hurdat, ...) {
  calc_interpolated_track(hurdat)
})

pwalk(hur_info, function(track, hurricane, ...) {
  st_write(track, str_c("tract/", hurricane, "/track_points.geojson"))
  
  track %>%
    st_combine() %>%
    st_cast("LINESTRING") %>%
    st_write(str_c("tract/", hurricane, "/track_line.geojson"))
})

pwalk(hur_info, function(track, hurricane, ...) {
  st_write(track, str_c("zcta/", hurricane, "/track_points.geojson"))
  
  track %>%
    st_combine() %>%
    st_cast("LINESTRING") %>%
    st_write(str_c("zcta/", hurricane, "/track_line.geojson"))
})

Calculate closest distance

hur_info$tract_closest_dist <- pmap(hur_info, function(track, tracts_sf, ...) {
  calc_closest_dist(track, tracts_sf, geoid = "geoid")
})

hur_info$zcta_closest_dist <- pmap(hur_info, function(track, zctas_sf, ...) {
  calc_closest_dist(track, zctas_sf, geoid = "geoid")
})

Calculate wind speed

hur_info$tract_anderson_wind <- pmap(hur_info, function(hurdat, tracts_sf, ...) {
  calc_anderson_wind(hurdat, tracts_sf)
})

hur_info$zcta_anderson_wind <- pmap(hur_info, function(hurdat, zctas_sf, ...) {
  calc_anderson_wind(hurdat, zctas_sf)
})

Join output and write to file

pwalk(hur_info, function(tract_closest_dist, tract_anderson_wind, hurricane, ...) {
  full_join(tract_closest_dist, tract_anderson_wind, join_by(geoid)) %>%
    relocate(closest_date, .before = closest_dist) %>%
    rename(highwind_datetime = datetime, closest_datetime = closest_date) %>%
    write_csv(str_c("tract/", hurricane, "/distance_wind.csv"))
})
 
pwalk(hur_info, function(zcta_closest_dist, zcta_anderson_wind, hurricane, ...) {
  full_join(zcta_closest_dist, zcta_anderson_wind, join_by(geoid)) %>%
    relocate(closest_date, .before = closest_dist) %>%
    rename(highwind_datetime = datetime, closest_datetime = closest_date) %>%
    write_csv(str_c("zcta/", hurricane, "/distance_wind.csv"))
})

End Time

end_time <- Sys.time()
cat("End time: ", end_time, "\n")
cat("Duration: ", start_time - end_time, "\n")

Visualizations

Storm	Mean	SD	Min	25% Quantile	Median	75% Quantile	Max	Proportion 34+ knots
Estimated Maximum Wind Velocity (km/h)
stormwindmodel estimates at 2010 tract geocentroid
ALLISON-2001	25.788	19.236	2.220	9.821	22.308	34.356	82.259	0.096
CHARLEY-2004	82.594	38.314	9.372	61.207	74.864	104.236	229.757	0.700
FLORENCE-2018	54.939	24.065	25.195	37.982	46.542	68.633	149.182	0.285
FRANCES-2004	49.652	28.276	9.961	26.541	43.254	70.405	155.705	0.286
HARVEY-2017	42.653	24.895	4.033	23.121	39.595	57.789	208.693	0.166
IKE-2008	48.213	36.008	3.212	25.803	40.482	51.648	169.524	0.181
IRENE-2011	64.229	25.675	9.007	44.521	66.186	88.897	131.869	0.546
IRMA-2017	64.582	33.614	13.870	33.130	70.543	87.528	171.575	0.546
IVAN-2004	29.284	20.513	5.153	18.484	23.176	35.746	187.711	0.046
KATRINA-2005	66.003	37.805	13.455	36.397	50.237	95.118	203.678	0.409
MATTHEW-2016	53.072	27.057	9.616	30.706	46.570	72.139	131.526	0.323
MICHAEL-2018	49.903	29.165	9.818	29.125	45.507	68.668	250.210	0.302
RITA-2005	41.564	27.803	2.925	24.638	31.641	62.374	175.649	0.247
SANDY-2012	66.865	25.770	12.256	41.173	68.184	86.468	127.014	0.565
WILMA-2005	75.566	47.825	4.688	42.593	52.651	119.569	182.511	0.438

Storm	Mean	SD	Min	25% Quantile	Median	75% Quantile	Max
Estimated Closest Approach (km)
Smallest distance from 2010 tract geocentroid to points on 15 min imputed track
ALLISON-2001	338.441	246.730	0.069	154.922	255.680	515.935	1002.884
CHARLEY-2004	146.054	122.959	0.216	55.697	105.757	206.345	634.756
FLORENCE-2018	162.146	97.937	0.125	76.375	167.990	228.261	400.053
FRANCES-2004	176.385	138.003	0.151	53.609	144.778	276.453	630.581
HARVEY-2017	262.566	186.763	0.541	133.278	201.477	386.138	910.878
IKE-2008	298.520	215.277	0.730	147.279	255.453	414.476	1069.358
IRENE-2011	156.282	146.666	0.070	33.478	118.346	216.809	696.714
IRMA-2017	159.393	122.923	0.405	64.332	141.426	191.935	565.556
IVAN-2004	246.729	137.177	0.105	150.398	246.460	331.967	771.765
KATRINA-2005	201.392	142.318	0.118	64.503	188.290	309.571	588.148
MATTHEW-2016	257.748	132.837	2.357	151.113	248.476	357.505	657.001
MICHAEL-2018	250.988	186.092	0.201	99.333	212.237	381.521	641.120
RITA-2005	321.107	218.944	0.648	164.012	281.815	398.255	1183.030
SANDY-2012	182.828	131.410	0.562	84.768	142.204	284.651	666.805
WILMA-2005	207.888	166.815	0.462	71.454	212.564	261.597	772.423