Type:	Package
Title:	Tropical Cyclone (Hurricane, Typhoon) Spatial Hazard Modelling
Version:	1.1.3
Date:	2025-05-28
Maintainer:	Julian O'Grady <julian.ogrady@csiro.au>
Description:	Methods for generating modelled parametric Tropical Cyclone (TC) spatial hazard fields and time series output at point locations from TC tracks. R's compatibility to simply use fast 'cpp' code via the 'Rcpp' package and the wide range spatial analysis tools via the 'terra' package makes it an attractive open source environment to study 'TCs'. This package estimates TC vortex wind and pressure fields using parametric equations originally coded up in 'python' by 'TCRM' https://github.com/GeoscienceAustralia/tcrm and then coded up in 'Cuda' 'cpp' by 'TCwindgen' https://github.com/CyprienBosserelle/TCwindgen.
URL:	https://github.com/AusClimateService/TCHazaRds
License:	GPL (≥ 3)
Imports:	Rcpp (≥ 1.0.7), terra, utils, stats, geosphere, ncdf4, methods, sp, rasterVis, raster, latticeExtra
LinkingTo:	Rcpp
RoxygenNote:	7.3.2
Encoding:	UTF-8
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
VignetteBuilder:	knitr
Config/testthat/edition:	3
Language:	en-AU
NeedsCompilation:	yes
Packaged:	2025-05-28 10:57:08 UTC; ogr013
Author:	Julian O'Grady [aut, cre]
Repository:	CRAN
Date/Publication:	2025-05-28 11:20:11 UTC

Double Holland Pressure Profile

Description

Pressure profile at grid points

Usage

DoubleHollandPressureProfile(rMax, rMax2, dP, cP, beta, R)

Arguments

Value

vector of pressures. //@example DoubleHollandPressureProfile(20,20,980,1.2,50)

Double Holland Pressure Profile Time Series

Description

Pressure profile time series at a grid point

Usage

DoubleHollandPressureProfilePi(rMax, rMax2, dP, cP, beta, R)

Arguments

Value

vector of pressures. //@example DoubleHollandPressureProfilePi(20,20,980,1.2,50)

Double Holland Wind Profile

Description

McConochie *et al*'s double Holland vortex model based on Cardone *et al*, 1994.This application is the Coral Sea adaptation of the double vortex model and it can also be used for concentric eye - wall configurations.

Usage

DoubleHollandWindProfile(f, vMax, rMax, rMax2, dP, cP, rho, beta, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example DoubleHollandWindProfile(-1e-4,20,20,10,980,1.15,1.2,50)

Double Holland Wind Profile Time Series

Description

Wind profile time series at a grid point. McConochie *et al*'s double Holland vortex model based on Cardone *et al*, 1994.This application is the Coral Sea adaptation of the double vortex model and it can also be used for concentric eye - wall configurations.

Usage

DoubleHollandWindProfilePi(f, vMax, rMax, rMax2, dP, cP, rho, beta, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example DoubleHollandWindProfilePi(-1e-4,20,20,10,980,1.15,1.2,50)

Holland Pressure Profile

Description

Pressure profile at grid points

Usage

HollandPressureProfile(rMax, dP, cP, beta, R)

Arguments

Value

vector of pressures. //@example HollandPressureProfile(20,20,980,1.2,50)

Holland Pressure Profile Time Series

Description

Pressure profile time series at a grid point.

Usage

HollandPressureProfilePi(rMax, dP, cP, beta, R)

Arguments

Value

vector of pressures. //@example HollandPressureProfilePi(20,20,980,1.2,50)

Holland Wind Profile

Description

wind profile at grid points

Usage

HollandWindProfile(f, vMax, rMax, dP, rho, beta, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example HollandWindProfile(-1e-4,20,20,10,1.15,1.2,50)

Holland Wind Profile Time Series

Description

wind profile time series at a grid point

Usage

HollandWindProfilePi(f, vMax, rMax, dP, rho, beta, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example HollandWindProfilePi(-1e-4,20,20,10,1.15,1.2,50)

Hubbert Wind Field

Description

Grid point vortex Wind field, wind vectors. Hubbert, G.D., G.J.Holland, L.M.Leslie and M.J.Manton, 1991: A Real - Time System for Forecasting Tropical Cyclone Storm Surges. *Weather and Forecasting*, **6 * *, 86 - 97

Usage

HubbertWindField(f, rMax, vFm, thetaFm, Rlam, V, surface)

Arguments

Value

array with two columns for zonal and meridional wind speed vector-components. //@example HubbertWindField(-1e-4,20,2,10,rbind(c(50,35),c(45,40)),c(20,20))

Hubbert Wind Field Time Series

Description

Time series vortex Wind, wind vectors. Hubbert, G.D., G.J.Holland, L.M.Leslie and M.J.Manton, 1991: A Real - Time System for Forecasting Tropical Cyclone Storm Surges. *Weather and Forecasting*, **6 * *, 86 - 97

Usage

HubbertWindFieldPi(f, rMax, vFm, thetaFm, Rlam, V, surface)

Arguments

Value

array with two columns for zonal and meridional wind speed vector-components. //@example HubbertWindFieldPi(-1e-4,20,2,10,rbind(c(50,35),c(45,40)),c(20,20))

Jelesnianski Wind Profile

Description

wind profile at grid points

Usage

JelesnianskiWindProfile(f, vMax, rMax, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example JelesnianskiWindProfile(-1e-4,20,20,50)

Jelesnianski Wind Profile Time Series

Description

wind profile time series at a grid point

Usage

JelesnianskiWindProfilePi(f, vMax, rMax, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example JelesnianskiWindProfilePi(-1e-4,20,20,50)

Kepert Wind Field

Description

Grid point vortex Wind field, wind vectors. Kepert, J., 2001: The Dynamics of Boundary Layer Jets within the Tropical Cyclone Core.Part I : Linear Theory.J.Atmos.Sci., 58, 2469 - 2484

Usage

KepertWindField(rMax, vMax, vFm, thetaFm, f, Rlam, VZ, surface)

Arguments

Value

array with two columns for zonal and meridional wind speed vector-components. //@example KepertWindField(20,20,2,10,-1e-4,rbind(c(50,35),c(45,40)),rbind(c(20,2),c(22,3)))

Kepert Wind Field

Description

Time series vortex Wind, wind vectors. Kepert, J., 2001: The Dynamics of Boundary Layer Jets within the Tropical Cyclone Core.Part I : Linear Theory.J.Atmospheric.Science., 58, 2469 - 2484

Usage

KepertWindFieldPi(rMax, vMax, vFm, thetaFm, f, Rlam, VZ, surface)

Arguments

Value

array with two columns for zonal and meridional wind speed vector-components. //@example KepertWindField(20,20,2,10,-1e-4,rbind(c(50,35),c(45,40)),rbind(c(20,2),c(22,3)))

McConochie Wind Field

Description

Grid point vortex Wind field, wind vectors. McConochie, J.D., T.A.Hardy and L.B.Mason, 2004: Modelling tropical cyclone over - water wind and pressure fields. Ocean Engineering, 31, 1757 - 1782.

Usage

McConochieWindField(rMax, vMax, vFm, thetaFm, Rlam, V, f, surface)

Arguments

Value

array with two columns for zonal and meridional wind speed vector-components. //@example McConochieWindField(-1e-4,20,2,10,rbind(c(50,35),c(45,40)),c(20,20))

McConochie Wind Field Time Series

Description

Time series vortex Wind, wind vectors. McConochie, J.D., T.A.Hardy and L.B.Mason, 2004: Modelling tropical cyclone over - water wind and pressure fields. Ocean Engineering, 31, 1757 - 1782.

Usage

McConochieWindFieldPi(rMax, vMax, vFm, thetaFm, Rlam, V, f, surface)

Arguments

Value

array with two columns for zonal and meridional wind speed vector-components. //@example McConochieWindFieldPi(-1e-4,20,2,10,rbind(c(50,35),c(45,40)),c(20,20))

New Holland Wind Profile Time Series

Description

Wind profile time series at a grid point. Holland et al. 2010. In this version, the exponent is allowed to vary linearly outside the radius of maximum wind. I.e. rather than take the square root, the exponent varies around 0.5.Currently this version does not have a corresponding vorticity profile set up in wind Vorticity, so it cannot be applied in some wind field modelling.

Usage

NewHollandWindProfile(f, rMax, rMax2, dP, rho, R, vMax, beta)

Arguments

Value

array with two columns for velocity and then vorticity. //@example NewHollandWindProfile(-1e-4,20,20,1.15,-14,50,1.3)

New Holland Wind Profile Time Series

Description

Wind profile time series at a grid point. Holland et al. 2010. In this version, the exponent is allowed to vary linearly outside the radius of maximum wind. I.e. rather than take the square root, the exponent varies around 0.5.Currently this version does not have a corresponding vorticity profile set up in wind Vorticity, so it cannot be applied in some wind field modelling.

Usage

NewHollandWindProfilePi(f, rMax, rMax2, dP, rho, R, vMax, beta)

Arguments

Value

array with two columns for velocity and then vorticity. //@example NewHollandWindProfilePi(-1e-4,20,20,1.15,-14,50,1.3)

Rankine Wind Profile Time Series

Description

wind profile time series at a grid point

Usage

RankineWindProfilePi(f, vMax, rMax, R)

Arguments

Value

array with two columns for velocity and then vorticity. //@example RankineWindProfilePi(-1e-4,20,20,50)

TC Distance and Direction From Output Grid Points

Description

Grid points distance and direction to TC.

Usage

Rdist(Gridlon, Gridlat, TClon, TClat)

Arguments

Value

two columns for distance in km and cartesian direction in degrees, counter clockwise from the x axis. //@example Rdist(c(144,145),c(-11,-12),142,-14)

TC Track Distance and Direction From Output Grid Point

Description

Grid point time series of TC distance and direction.

Usage

RdistPi(Gridlon, Gridlat, TClon, TClat)

Arguments

Value

two columns for distance in km and cartesian direction in degrees, counterclockwise from the x axis. //@example RdistPi(142,-14,c(144,145),c(-11,-12))

Compute the Wind and Pressure Spatial Hazards Field Associated with TCs Single Time Step.

Description

Compute the Wind and Pressure Spatial Hazards Field Associated with TCs Single Time Step.

Usage

TCHazaRdsWindField(GEO_land, TC, paramsTable, returnWaves = FALSE)

Arguments

Value

SpatRaster with the following attributes

Examples

require(terra)
dem <- rast(system.file("extdata/DEMs/YASI_dem.tif", package="TCHazaRds"))
land <- dem; land[land > 0] = 0
inland_proximity = distance(land,target = 0)
GEO_land = land_geometry(dem,inland_proximity)

TCi = vect(cbind(c(154,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment
TCi$PRES = 950
TCi$RMAX = 40
TCi$VMAX = 60
TCi$B = 1.4
TCi$ISO_TIME = "2022-10-04 20:00:00"
TCi$LON = geom(TCi)[1,3]
TCi$LAT = geom(TCi)[1,4]
TCi$STORM_SPD = perim(TCi)/(3*3600) #m/s
TCi$thetaFm = 90-returnBearing(TCi)
#OR
TC <- vect(system.file("extdata/YASI/YASI.shp", package="TCHazaRds"))
TC$PRES <- TC$BOM_PRES
TCi = TC[47]
plot(dem);lines(TCi,lwd = 4,col=2)

paramsTable = read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))
#calculate the wind hazard
HAZ = TCHazaRdsWindField(GEO_land,TCi,paramsTable)
plot(HAZ)

#require(rasterVis) #pretty spatial vector plot
#ats = seq(0, 80, length=9)
#UV = as(c(HAZ["Uw"],HAZ["Vw"]),"Raster") #need to convert back to raster
#vectorplot(UV, isField='dXY', col.arrows='white', aspX=0.002,aspY=0.002,at=ats ,
#colorkey=list( at=ats), par.settings=viridisTheme)

Compute the Wind and Pressure Spatial Hazards Field Associated with TC track.

Description

Compute the Wind and Pressure Spatial Hazards Field Associated with TC track.

Usage

TCHazaRdsWindFields(
  outdate = NULL,
  GEO_land,
  TC,
  paramsTable,
  outfile = NULL,
  overwrite = FALSE,
  returnWaves = FALSE
)

Arguments

Value

SpatRasterDataset with the following attributes.

Examples

require(terra)
dem <- rast(system.file("extdata/DEMs/YASI_dem.tif", package="TCHazaRds"))
land <- dem; land[land > 0] = 0
inland_proximity = distance(land,target = 0)
GEO_land = land_geometry(dem,inland_proximity)

TCi = vect(cbind(c(154,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment
TCi$PRES = 950
TCi$RMAX = 40
TCi$VMAX = 60
TCi$B = 1.4
TCi$ISO_TIME = "2022-10-04 20:00:00"
TCi$LON = geom(TCi)[1,3]
TCi$LAT = geom(TCi)[1,4]
TCi$STORM_SPD = perim(TCi)/(3*3600) #m/s
TCi$thetaFm = 90-returnBearing(TCi)
#OR
TC <- vect(system.file("extdata/YASI/YASI.shp", package="TCHazaRds"))
TC$PRES <- TC$BOM_PRES
plot(dem);lines(TC,lwd = 4,col=2)

paramsTable = read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))
#calculate the wind hazard

outdate = seq(strptime(TC$ISO_TIME[44],"%Y-%m-%d %H:%M:%S",tz="UTC"),
              strptime(TC$ISO_TIME[46],"%Y-%m-%d %H:%M:%S",tz="UTC"),
              3600*3)
HAZi = TCHazaRdsWindFields(outdate=outdate,GEO_land=GEO_land,TC=TC,paramsTable=paramsTable)
plot(min(HAZi$Pr))

Compute the Wind and Pressure Spatial Hazards Profile Associated with TCs Single Time Step.

Description

Compute the Wind and Pressure Spatial Hazards Profile Associated with TCs Single Time Step.

Usage

TCHazaRdsWindProfile(GEO_land, TC, paramsTable)

Arguments

Value

SpatRaster with the following attributes

Examples

require(terra)
dem <- rast(system.file("extdata/DEMs/YASI_dem.tif", package="TCHazaRds"))
land <- dem; land[land > 0] = 0
inland_proximity = distance(land,target = 0)
GEO_land = land_geometry(dem,inland_proximity)

TCi = vect(cbind(c(154,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment
TCi$PRES = 950
TCi$RMAX = 40
TCi$VMAX = 60
TCi$B = 1.4
TCi$ISO_TIME = "2022-10-04 20:00:00"
TCi$LON = geom(TCi)[1,3]
TCi$LAT = geom(TCi)[1,4]
TCi$STORM_SPD = perim(TCi)/(3*3600) #m/s
TCi$thetaFm = 90-returnBearing(TCi)
#OR
TC <- vect(system.file("extdata/YASI/YASI.shp", package="TCHazaRds"))
TC$PRES <- TC$BOM_PRES
TCi = TC[47]
TCi$thetaFm = 90-returnBearing(TCi)

#extract a profile/transect at right angles (90 degrees) from the TC heading/bearing direction
pp <- TCProfilePts(TC_line = TCi,bear=TCi$thetaFm+90,length =100,step=1)
#plot(dem);lines(TCi,lwd = 4,col=2)
#points(pp)
GEO_land_v = extract(GEO_land,pp,bind=TRUE,method = "bilinear")

paramsTable = read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))
#calculate the wind hazard
HAZ = TCHazaRdsWindProfile(GEO_land_v,TCi,paramsTable)
#plot(HAZ$radialdist,HAZ$Sw,type="l",xlab = "Radial distance [km]",ylab = "Wind speed [m/s]");grid()
#plot(HAZ,"Sw",type="continuous")

Compute the Wind Hazards Associated Over the Period of a TCs Event at one Given Location

Description

Compute the Wind Hazards Associated Over the Period of a TCs Event at one Given Location

Usage

TCHazaRdsWindTimeSereies(
  outdate = NULL,
  GEO_land = NULL,
  TC,
  paramsTable,
  returnWaves = FALSE
)

Arguments

Details

The function calculates wind speed and direction time series from a tropical cyclone track using various wind profile models.

Value

list() containing a timeseries

Examples

GEO_land = data.frame(dem=0,lons = 147,lats=-18,f=-4e-4,inlandD = 0)

require(terra)
TCi <- vect(system.file("extdata/YASI/YASI.shp", package="TCHazaRds"))
TCi$PRES <- TCi$BOM_PRES

paramsTable = read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))
HAZts = TCHazaRdsWindTimeSereies(GEO_land=GEO_land,TC=TCi,paramsTable = paramsTable)
main =  paste(TCi$NAME[1],TCi$SEASON[1],"at",GEO_land$lons,GEO_land$lats)
#with(HAZts,plot(date,Sw,format = "%b-%d %H",type="l",main = main,ylab = "Wind speed [m/s]"))

Transect points from a origin through a point or with a bearing and to the opposite side.

Description

Transect points from a origin through a point or with a bearing and to the opposite side.

Usage

TCProfilePts(
  TC_line,
  Through_point = NULL,
  bear = NULL,
  length = 200,
  step = 2
)

Arguments

Value

spatial vector of transect profile points with distances in Km (negative for left hand side)

Examples

require(terra)
TCi <- vect(cbind(c(154.1,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment
TCi$PRES <- 950
TCi$RMAX <- 40
TCi$B <- 1.4
TCi$RMAX2 <- 90
TCi$ISO_TIME <- "2022-10-04 20:00:00"
TCi$LON <- geom(TCi)[1,3]
TCi$LAT <- geom(TCi)[1,4]
TCi$STORM_SPD <- perim(TCi)/(3*3600) #m/s
TCi$thetaFm <- 90-returnBearing(TCi)
#Through_point <- isd[isd$OID==isdsi]
pp <- TCProfilePts(TC_line = TCi,Through_point=NULL,bear=TCi$thetaFm+90,length =100,step=10)
plot(pp,"radialdist",type="continuous")
lines(TCi,col=2)

Convert Points to Line Segments

Description

This function converts a set of point geometries into line segments. The input vector must be a set of points, and the function will draw line segments between consecutive points. An additional point is extrapolated from the last two points to ensure the final segment is complete.

Usage

TCpoints2lines(pts_v)

Arguments

Value

A 'SpatVector' containing line geometries created from the input points.

Examples

library(terra)
# Create example points
pts <- vect(matrix(c(1, 1, 2, 2, 3, 3), ncol=2), type="points")
# Convert points to line segments
TClines <- TCpoints2lines(pts)

Temporally Interpolate Along a Tropical Cyclone Track And Compute Along-Track Parameters

Description

Temporally Interpolate Along a Tropical Cyclone Track And Compute Along-Track Parameters

Usage

TCvectInterp(outdate = NULL, TC, paramsTable)

Arguments

Value

SpatVector of Tropical cyclone track parameters

Examples

require(terra)
TCi <- vect(system.file("extdata/YASI/YASI.shp", package="TCHazaRds"))
TCi$PRES <- TCi$BOM_PRES
TCi$PRES[is.na(TCi$PRES)] = 1010
outdate = seq(strptime(TCi$ISO_TIME[1],"%Y-%m-%d %H:%M:%S",tz="UTC"),
strptime(rev(TCi$ISO_TIME)[1],"%Y-%m-%d %H:%M:%S",tz="UTC"),3600)
paramsTable = read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))
TCii = TCvectInterp(outdate = outdate,TC=TCi,paramsTable = paramsTable)

Compute the Exponential TC beta Profile-Curvature Parameter

Description

Compute the Exponential TC beta Profile-Curvature Parameter

Usage

beta_modelsR(betaModel, vMax, rMax, cPs, eP, vFms, TClats, dPdt, rho = 1.15)

Arguments

Value

exponential beta parameter

Examples

beta_modelsR(0,10,10,960,1013,3,-15,1)

Reduce Winds Overland

Description

Reduce Winds Overland

Usage

inlandWindDecay(d, a = c(0.66, 1, 0.4))

Arguments

Value

a reduction factor Km

Examples

inlandWindDecay(10)

Calculate the Geometric Parameters for Terrestrial Wind

Description

Returns geometric data to compute wind fields.

Usage

land_geometry(dem, inland_proximity, returnpoints = FALSE)

Arguments

Value

SpatVector with attributes or SpatRaster

Examples

require(terra)
dem <- rast(system.file("extdata/DEMs/YASI_dem.tif", package="TCHazaRds"))
land <- dem; land[land > 0] = 0
inland_proximity = distance(land,target = 0)
GEO_land = land_geometry(dem,inland_proximity)
plot(GEO_land)

predict_rmax

Description

Predicts the radius of maximum winds (rmax) based on the radius of 17.5 m/s winds (rMax175ms) using the Chavas and Knaff (2022) model.

Usage

predict_rmax(rMax175ms, vMax, TClats)

Arguments

Value

A vector of predicted rmax values (in km).

Examples

rMax175ms <- c(100, 120, 140)
vMax <- c(50, 55, 60)
TClats <- c(20, 25, 30)
predict_rmax(rMax175ms, vMax, TClats)

rMax175ms_solver

Description

A helper function for numerically solving the radius of 17.5 m/s winds using the Chavas and Knaff (2022) model. This function is called by 'uniroot' to compute the difference between the guessed and actual rmax values.

Usage

rMax175ms_solver(rMax175ms_m, vMax, rmax_predict_m, TClats)

Arguments

Value

The difference between the guessed rmax and the target rmax.

Examples

rMax175ms_solver(100000, 50, 36000, 20)

rMax2_modelsR

Description

Numerically solves for the radius of 17.5 m/s winds (rMax175ms) using the Chavas and Knaff (2022) model and 'uniroot'.

Usage

rMax2_modelsR(rMax2Model, rMax, vMax, TClats)

Arguments

Value

A vector of predicted rMax175ms values (in km).

Examples

rMax <- c(30, 36, 40)
vMax <- c(50, 55, 60)
TClats <- c(20, 25, 30)
rMax2_modelsR(2,rMax, vMax, TClats)

Compute the Tropical Cyclone Radius of Maximum Winds

Description

Compute the Tropical Cyclone Radius of Maximum Winds

Usage

rMax_modelsR(
  rMaxModel,
  TClats,
  cPs,
  eP,
  R175ms = 150,
  dPdt = NULL,
  vFms = NULL,
  rho = 1.15,
  vMax = NULL
)

Arguments

Value

radius of maximum winds (km)

Examples

rMax_modelsR(0,-14,950,1013,200,0,0,1.15)

Return the Bearing for Line Segments

Description

Return the Bearing for Line Segments

Usage

returnBearing(x)

Arguments

Value

array of bearings see geosphere::bearing, i.e the Forward direction of the storm geographic bearing, positive clockwise from true north

Examples

### IBTRACS HAS the WRONG BEARING!!
require(terra)
northwardTC <- vect(cbind(c(154,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment
easthwardTC <- vect(cbind(c(154,154.1),c(-26,-26)),"lines",crs="epsg:4283") #track line segment
southhwardTC <- vect(cbind(c(154,154),c(-26,-26.1)),"lines",crs="epsg:4283") #track line segment
westwardTC <- vect(cbind(c(154.1,154),c(-26,-26)),"lines",crs="epsg:4283") #track line segment
returnBearing(northwardTC)
returnBearing(easthwardTC)
returnBearing(southhwardTC)
returnBearing(westwardTC)

Update Parameter List to Calibrated Values

Description

Update Parameter List to Calibrated Values

Usage

tunedParams(
  paramsTable,
  infile = system.file("extdata/tuningParams/QLD_modelSummaryTable.csv", package =
    "TCHazaRds")
)

Arguments

Value

list of params with updated tuning wind parameters.

Examples

paramsTable <- read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))

tunedParams(paramsTable)

Calculate Additional TC Parameters, and temporally Interpolate Along a Tropical Cyclone Track

Description

Calculate Additional TC Parameters, and temporally Interpolate Along a Tropical Cyclone Track

Usage

update_Track(
  outdate = NULL,
  indate,
  TClons,
  TClats,
  vFms,
  thetaFms,
  cPs,
  rMaxModel,
  vMaxModel,
  betaModel,
  rMax2Model,
  eP,
  rho = NULL,
  RMAX,
  VMAX,
  B,
  RMAX2
)

Arguments

Value

list of track data inclining the rMax vMax and Beta.

Examples

paramsTable <- read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds"))
params <- array(paramsTable$value,dim = c(1,length(paramsTable$value)))
colnames(params) <- paramsTable$param
params <- data.frame(params)
require(terra)
TCi <- vect(system.file("extdata/YASI/YASI.shp", package="TCHazaRds"))
TCi$PRES <- TCi$BOM_PRES
TCi$RMAX <- TCi$BOM_RMW*1.852 #convert from nautical miles to km
TCi$VMAX <- TCi$BOM_WIND*1.94 #convert from knots to m/s
TCi$B <- 1.4
TCi$RMAX2 <- 150 
t1 <- strptime("2011-02-01 09:00:00","%Y-%m-%d %H:%M:%S", tz = "UTC") #first date in POSIX format
t2 <- strptime(rev(TCi$ISO_TIME)[1],"%Y-%m-%d %H:%M:%S", tz = "UTC") #last date in POSIX format
outdate <- seq(t1,t2,"hour") #array sequence from t1 to t2 stepping by “hour”
# defult along track parameters are calculated
TCil = update_Track(outdate = outdate,
                   indate = strptime(TCi$ISO_TIME,"%Y-%m-%d %H:%M:%S", tz = "UTC"),
                   TClons = TCi$LON,
                   TClats = TCi$LAT,
                   vFms=TCi$STORM_SPD,
                   thetaFms=TCi$thetaFm,
                   cPs=TCi$PRES,
                   rMaxModel=params$rMaxModel,
                   vMaxModel=params$vMaxModel,
                   betaModel=params$betaModel,
                   rMax2Model = params$rMaxModel,
                   eP = params$eP,
                   rho = params$rhoa,
                   RMAX = TCi$RMAX,
                   VMAX = TCi$VMAX,
                   B = TCi$B,
                   RMAX2 = TCi$RMAX2
                   )
# 'observed' along tack parameters are calculated (#Model = NA)                   
TCil = update_Track(outdate = outdate,
                   indate = strptime(TCi$ISO_TIME,"%Y-%m-%d %H:%M:%S", tz = "UTC"),
                   TClons = TCi$LON,
                   TClats = TCi$LAT,
                   vFms=TCi$STORM_SPD,
                   thetaFms=TCi$thetaFm,
                   cPs=TCi$PRES,
                   rMaxModel=NA,
                   vMaxModel=NA,
                   betaModel=NA,
                   rMax2Model = NA,
                   eP = params$eP,
                   rho = params$rhoa,
                   RMAX = TCi$RMAX,
                   VMAX = TCi$VMAX,
                   B = TCi$B,
                   RMAX2 = TCi$RMAX2
                   )

Compute the Tropical Cyclone Maximum Wind Speeds

Description

Compute the Tropical Cyclone Maximum Wind Speeds

Usage

vMax_modelsR(
  vMaxModel,
  cPs,
  eP,
  vFms = NULL,
  TClats = NULL,
  dPdt = NULL,
  beta = 1.3,
  rho = 1.15
)

Arguments

Value

maximum wind speed m/s.

Examples

vMax_modelsR(vMaxModel=1,cPs=950,eP=1010,vFms = 1,TClats = -14,dPdt = .1)