| Title: | Tropical Cyclone (Hurricane, Typhoon) Spatial Hazard Modelling |
|---|---|
| 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>. |
| Authors: | Julian O'Grady [aut, cre] |
| Maintainer: | Julian O'Grady <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 1.1.2 |
| Built: | 2025-03-04 03:03:19 UTC |
| Source: | https://github.com/ausclimateservice/tchazards |
Compute the Exponential TC beta Profile-Curvature Parameter
beta_modelsR(betaModel, vMax, rMax, cPs, eP, vFms, TClats, dPdt, rho = 1.15)beta_modelsR(betaModel, vMax, rMax, cPs, eP, vFms, TClats, dPdt, rho = 1.15)
betaModel |
0=Holland (2008),1=Powell (2005),2=Willoughby & Rahn (2004),3=Vickery & Wadhera (2008),4=Hubbert (1991) |
vMax |
maximum wind speed m/s. see |
rMax |
radius of maximum winds (km). see |
cPs |
Tropical cyclone central pressure (hPa) |
eP |
Background environmental pressure (hPa) |
vFms |
Forward speed of the storm m/s |
TClats |
Tropical cyclone central latitude |
dPdt |
rate of change in central pressure over time, hPa per hour from Holland 2008 |
rho |
density of air |
exponential beta parameter
beta_modelsR(0,10,10,960,1013,3,-15,1)beta_modelsR(0,10,10,960,1013,3,-15,1)
Pressure profile at grid points
DoubleHollandPressureProfile(rMax, rMax2, dP, cP, beta, R)DoubleHollandPressureProfile(rMax, rMax2, dP, cP, beta, R)
rMax |
radius of maximum winds in km |
rMax2 |
radius of outer radial winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
cP |
TC central pressure in hPa |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
vector of pressures. //@example DoubleHollandPressureProfile(20,20,980,1.2,50)
Pressure profile time series at a grid point
DoubleHollandPressureProfilePi(rMax, rMax2, dP, cP, beta, R)DoubleHollandPressureProfilePi(rMax, rMax2, dP, cP, beta, R)
rMax |
radius of maximum winds in km |
rMax2 |
radius of outer radial winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
cP |
TC central pressure in hPa |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
vector of pressures. //@example DoubleHollandPressureProfilePi(20,20,980,1.2,50)
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.
DoubleHollandWindProfile(f, vMax, rMax, rMax2, dP, cP, rho, beta, R)DoubleHollandWindProfile(f, vMax, rMax, rMax2, dP, cP, rho, beta, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
rMax2 |
radius of outer radial winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
cP |
TC central pressure in hPa |
rho |
density of air in Kg/m3 |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example DoubleHollandWindProfile(-1e-4,20,20,10,980,1.15,1.2,50)
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.
DoubleHollandWindProfilePi(f, vMax, rMax, rMax2, dP, cP, rho, beta, R)DoubleHollandWindProfilePi(f, vMax, rMax, rMax2, dP, cP, rho, beta, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
rMax2 |
radius of outer radial winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
cP |
TC central pressure in hPa |
rho |
density of air in Kg/m3 |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example DoubleHollandWindProfilePi(-1e-4,20,20,10,980,1.15,1.2,50)
Pressure profile at grid points
HollandPressureProfile(rMax, dP, cP, beta, R)HollandPressureProfile(rMax, dP, cP, beta, R)
rMax |
radius of maximum winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
cP |
TC central pressure in hPa |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
vector of pressures. //@example HollandPressureProfile(20,20,980,1.2,50)
Pressure profile time series at a grid point.
HollandPressureProfilePi(rMax, dP, cP, beta, R)HollandPressureProfilePi(rMax, dP, cP, beta, R)
rMax |
radius of maximum winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
cP |
TC central pressure in hPa |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
vector of pressures. //@example HollandPressureProfilePi(20,20,980,1.2,50)
wind profile at grid points
HollandWindProfile(f, vMax, rMax, dP, rho, beta, R)HollandWindProfile(f, vMax, rMax, dP, rho, beta, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
rho |
density of air in Kg/m3 |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example HollandWindProfile(-1e-4,20,20,10,1.15,1.2,50)
wind profile time series at a grid point
HollandWindProfilePi(f, vMax, rMax, dP, rho, beta, R)HollandWindProfilePi(f, vMax, rMax, dP, rho, beta, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
rho |
density of air in Kg/m3 |
beta |
exponential term for Holland vortex |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example HollandWindProfilePi(-1e-4,20,20,10,1.15,1.2,50)
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
HubbertWindField(f, rMax, vFm, thetaFm, Rlam, V, surface)HubbertWindField(f, rMax, vFm, thetaFm, Rlam, V, surface)
f |
single coriolis parameter at the centre of TC in hz |
rMax |
radius of maximum winds in km |
vFm |
input forward velocity of TC |
thetaFm |
input forward direction of TC |
Rlam |
two columns for distances and direction from grid points to TC centre in km |
V |
velocity profile |
surface |
equals one if winds are reduced from the gradient level to the surface, otherwise gradient winds. |
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))
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
HubbertWindFieldPi(f, rMax, vFm, thetaFm, Rlam, V, surface)HubbertWindFieldPi(f, rMax, vFm, thetaFm, Rlam, V, surface)
f |
single coriolis parameter at the centre of TC in hz |
rMax |
radius of maximum winds in km |
vFm |
input forward velocity of TC |
thetaFm |
input forward direction of TC |
Rlam |
two columns for distances and direction from grid points to TC centre in km |
V |
velocity profile |
surface |
equals one if winds are reduced from the gradient level to the surface, otherwise gradient winds. |
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))
Reduce Winds Overland
inlandWindDecay(d, a = c(0.66, 1, 0.4))inlandWindDecay(d, a = c(0.66, 1, 0.4))
d |
inland distance in km |
a |
three parameter of decay model a1,a2,a3 |
a reduction factor Km
inlandWindDecay(10)inlandWindDecay(10)
wind profile at grid points
JelesnianskiWindProfile(f, vMax, rMax, R)JelesnianskiWindProfile(f, vMax, rMax, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example JelesnianskiWindProfile(-1e-4,20,20,50)
wind profile time series at a grid point
JelesnianskiWindProfilePi(f, vMax, rMax, R)JelesnianskiWindProfilePi(f, vMax, rMax, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example JelesnianskiWindProfilePi(-1e-4,20,20,50)
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
KepertWindField(rMax, vMax, vFm, thetaFm, f, Rlam, VZ, surface)KepertWindField(rMax, vMax, vFm, thetaFm, f, Rlam, VZ, surface)
rMax |
radius of maximum winds in km |
vMax |
maximum wind velocity calculation in m/s |
vFm |
input forward velocity of TC |
thetaFm |
input forward direction of TC |
f |
single coriolis parameter at the centre of TC in hz |
Rlam |
two columns for distances and Cartesian direction clocwise from the x axis from grid points to TC centre in km |
VZ |
array two columns velocity then vorticity |
surface |
equals one if winds are reduced from the gradient level to the surface, otherwise gradient winds. |
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)))
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.Atmos.Sci., 58, 2469 - 2484
KepertWindFieldPi(rMax, vMax, vFm, thetaFm, f, Rlam, VZ, surface)KepertWindFieldPi(rMax, vMax, vFm, thetaFm, f, Rlam, VZ, surface)
rMax |
radius of maximum winds in km |
vMax |
maximum wind velocity calculation in m/s |
vFm |
input forward velocity of TC |
thetaFm |
input forward direction of TC |
f |
single coriolis parameter at the centre of TC in hz |
Rlam |
two columns for distances and direction from grid points to TC centre in km |
VZ |
array two columns velocity then vorticity |
surface |
equals one if winds are reduced from the gradient level to the surface, otherwise gradient winds. |
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)))
Returns geometric data to compute wind fields.
land_geometry(dem, inland_proximity, returnpoints = FALSE)land_geometry(dem, inland_proximity, returnpoints = FALSE)
dem |
SpatRaster object, digital elevation model |
inland_proximity |
SpatRaster object, distance from the coast inland |
returnpoints |
Return SpatVector of points or SpatRaster |
SpatVector with attributes or SpatRaster
| Abbreviated attribute | description | units |
| dem | Digital Elevation Model | m |
| lat | Latitude | degs |
| lon | Longitude | degs |
| slope | slope of terrain | - |
| aspect | DEM aspect | - |
| inlandD | distance inland from coast | m |
| f | Coriolis parameter | hz |
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)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)
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.
McConochieWindField(rMax, vMax, vFm, thetaFm, Rlam, V, f, surface)McConochieWindField(rMax, vMax, vFm, thetaFm, Rlam, V, f, surface)
rMax |
radius of maximum winds in km |
vMax |
maximum wind velocity calculation in m/s |
vFm |
input forward velocity of TC |
thetaFm |
input forward direction of TC |
Rlam |
two columns for distances and direction from grid points to TC centre in km |
V |
velocity profile |
f |
coriolis parameter at the centre of TC in hz |
surface |
equals one if winds are reduced from the gradient level to the surface, otherwise gradient winds. |
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))
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.
McConochieWindFieldPi(rMax, vMax, vFm, thetaFm, Rlam, V, f, surface)McConochieWindFieldPi(rMax, vMax, vFm, thetaFm, Rlam, V, f, surface)
rMax |
radius of maximum winds in km |
vMax |
maximum wind velocity calculation in m/s |
vFm |
input forward velocity of TC |
thetaFm |
input forward direction of TC |
Rlam |
two columns for distances and direction from grid points to TC centre in km |
V |
velocity profile |
f |
coriolis parameter at the centre of TC in hz |
surface |
equals one if winds are reduced from the gradient level to the surface, otherwise gradient winds. |
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))
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.
NewHollandWindProfile(f, rMax, rMax2, dP, rho, R, vMax, beta)NewHollandWindProfile(f, rMax, rMax2, dP, rho, R, vMax, beta)
f |
single coriolis parameter at the centre of TC in hz |
rMax |
radius of maximum winds in km |
rMax2 |
radius of outer 17.5ms winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
rho |
density of air in Kg/m3 |
R |
vector of distances from grid points to TC centre in km |
vMax |
maximum wind velocity calculation in m/s |
beta |
exponential term for Holland vortex |
array with two columns for velocity and then vorticity. //@example NewHollandWindProfile(-1e-4,20,20,1.15,-14,50,1.3)
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.
NewHollandWindProfilePi(f, rMax, rMax2, dP, rho, R, vMax, beta)NewHollandWindProfilePi(f, rMax, rMax2, dP, rho, R, vMax, beta)
f |
single coriolis parameter at the centre of TC in hz |
rMax |
radius of maximum winds in km |
rMax2 |
radius of outer 17ms winds in km |
dP |
pressure differential, environmental less TC central pressure in hPa |
rho |
density of air in Kg/m3 |
R |
vector of distances from grid points to TC centre in km |
vMax |
maximum wind velocity calculation in m/s |
beta |
exponential term for Holland vortex |
array with two columns for velocity and then vorticity. //@example NewHollandWindProfilePi(-1e-4,20,20,1.15,-14,50,1.3)
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.
predict_rmax(rMax175ms, vMax, TClats)predict_rmax(rMax175ms, vMax, TClats)
rMax175ms |
Numeric. A vector of radius of 17.5 m/s winds (in km). |
vMax |
Numeric. A vector of maximum wind speeds (m/s). |
TClats |
Numeric. A vector of latitudes of tropical cyclones (in degrees). |
A vector of predicted rmax values (in km).
rMax175ms <- c(100, 120, 140) vMax <- c(50, 55, 60) TClats <- c(20, 25, 30) predict_rmax(rMax175ms, vMax, TClats)rMax175ms <- c(100, 120, 140) vMax <- c(50, 55, 60) TClats <- c(20, 25, 30) predict_rmax(rMax175ms, vMax, TClats)
wind profile time series at a grid point
RankineWindProfilePi(f, vMax, rMax, R)RankineWindProfilePi(f, vMax, rMax, R)
f |
single coriolis parameter at the centre of TC in hz |
vMax |
maximum wind velocity calculation in m/s |
rMax |
radius of maximum winds in km |
R |
vector of distances from grid points to TC centre in km |
array with two columns for velocity and then vorticity. //@example RankineWindProfilePi(-1e-4,20,20,50)
Grid points distance and direction to TC.
Rdist(Gridlon, Gridlat, TClon, TClat)Rdist(Gridlon, Gridlat, TClon, TClat)
Gridlon |
vector of Grid point longitudes |
Gridlat |
vector of Grid point latitudes |
TClon |
single TC longitude |
TClat |
single TC latitude |
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)
Grid point time series of TC distance and direction.
RdistPi(Gridlon, Gridlat, TClon, TClat)RdistPi(Gridlon, Gridlat, TClon, TClat)
Gridlon |
single Grid point longitude |
Gridlat |
single Grid point latitude |
TClon |
vector of TC longitudes |
TClat |
vector of TC latitudes |
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))
Return the Bearing for Line Segments
returnBearing(x)returnBearing(x)
x |
spatial vector with line segments (two connected points) |
array of bearings see geosphere::bearing, i.e the Forward direction of the storm geographic bearing, positive clockwise from true north
### 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)### 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)
Compute the Tropical Cyclone Radius of Maximum Winds
rMax_modelsR( rMaxModel, TClats, cPs, eP, R175ms = 150, dPdt = NULL, vFms = NULL, rho = 1.15 )rMax_modelsR( rMaxModel, TClats, cPs, eP, R175ms = 150, dPdt = NULL, vFms = NULL, rho = 1.15 )
rMaxModel |
0=Powell et.al.(2005),1=McInnes et.al.(2014),2=Willoughby & Rahn (2004), 3=Vickery & Wadhera (2008), 4=Takagi & Wu (2016), 5 = Chavas & Knaff (2022) |
TClats |
Tropical cyclone central latitude (nautical degrees) |
cPs |
Tropical cyclone central pressure (hPa) |
eP |
Background environmental pressure (hPa) |
R175ms |
radius of 17.5m/s wind speeds (km) |
dPdt |
rate of change in central pressure over time, hPa per hour from Holland 2008 |
vFms |
Forward speed of the storm m/s |
rho |
density of air |
radius of maximum winds (km)
rMax_modelsR(0,-14,950,1013,200,0,0,1.15)rMax_modelsR(0,-14,950,1013,200,0,0,1.15)
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.
rMax175ms_solver(rMax175ms_m, vMax, rmax_predict_m, TClats)rMax175ms_solver(rMax175ms_m, vMax, rmax_predict_m, TClats)
rMax175ms_m |
Numeric. Guessed radius of 17.5 m/s winds in meters. |
vMax |
Numeric. Maximum wind speed (m/s). |
rmax_predict_m |
Numeric. Target radius of maximum winds in meters. |
TClats |
Numeric. Latitude of the tropical cyclone in degrees. |
The difference between the guessed rmax and the target rmax.
rMax175ms_solver(100000, 50, 36000, 20)rMax175ms_solver(100000, 50, 36000, 20)
Numerically solves for the radius of 17.5 m/s winds (rMax175ms) using the Chavas and Knaff (2022) model and 'uniroot'.
rMax2_modelsR(rMax2Model, rMax, vMax, TClats)rMax2_modelsR(rMax2Model, rMax, vMax, TClats)
rMax2Model |
TC outer radius of 17.5m/s winds model ('150km'=1,'CK22'=2) |
rMax |
Numeric. A vector of radius of maximum winds (km). |
vMax |
Numeric. A vector of maximum wind speeds (m/s). |
TClats |
Numeric. A vector of latitudes of tropical cyclone cwntre in degrees. |
A vector of predicted rMax175ms values (in km).
rMax <- c(30, 36, 40) vMax <- c(50, 55, 60) TClats <- c(20, 25, 30) rMax2_modelsR(2,rMax, vMax, TClats)rMax <- c(30, 36, 40) vMax <- c(50, 55, 60) TClats <- c(20, 25, 30) rMax2_modelsR(2,rMax, vMax, TClats)
Compute the Wind and Pressure Spatial Hazards Field Associated with TCs Single Time Step.
TCHazaRdsWindField(GEO_land, TC, paramsTable, returnWaves = FALSE)TCHazaRdsWindField(GEO_land, TC, paramsTable, returnWaves = FALSE)
GEO_land |
SpatVector or dataframe hazard geometry generated with land_geometry |
TC |
SpatVector or data.frame of Tropical cyclone track parameters for a single time step. |
paramsTable |
Global parameters to compute TC Hazards. |
returnWaves |
Return ocean wave parameters (default = FALSE) |
SpatRaster with the following attributes
| abbreviated attribute | description | units |
| P | Atmospheric pressure | hPa |
| Uw | Meridional wind speed | m/s |
| Vw | Zonal wind speed | m/s |
| Sw | Wind speed | m/s |
| Dw | The direction from which wind originates | deg clockwise from true north. |
| Hs0 | Deep water significant wave height | m |
| Tp0 | Deep water Peak wave period | s |
| Dp0 | The peak direction in which wave are heading | deg clockwise from true north. |
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$BOM_PRES TCi = TC[47] plot(dem);lines(TCi,lwd = 4,col=2) paramsTable = read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds")) #calculate the wind hazard HAZ = TCHazaRdsWindField(GEO_land,TCi,paramsTable) plot(HAZ) #require(rasterVis) #pretty spatial vector plot #ats = seq(0, 80, length=9) #UV = as(c(HAZ["Uw"],HAZ["Vw"]),"Raster") #need to convert back to raster #vectorplot(UV, isField='dXY', col.arrows='white', aspX=0.002,aspY=0.002,at=ats , #colorkey=list( at=ats), par.settings=viridisTheme)require(terra) dem <- rast(system.file("extdata/DEMs/YASI_dem.tif", package="TCHazaRds")) land <- dem; land[land > 0] = 0 inland_proximity = distance(land,target = 0) GEO_land = land_geometry(dem,inland_proximity) TCi = vect(cbind(c(154,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment TCi$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.
TCHazaRdsWindFields( outdate = NULL, GEO_land, TC, paramsTable, outfile = NULL, overwrite = FALSE, returnWaves = FALSE )TCHazaRdsWindFields( outdate = NULL, GEO_land, TC, paramsTable, outfile = NULL, overwrite = FALSE, returnWaves = FALSE )
outdate |
array of POSITx date times to linearly interpolate TC track |
GEO_land |
SpatVector or dataframe hazard geometry generated with land_geometry |
TC |
SpatVector of Tropical cyclone track parameters for a single time step |
paramsTable |
Global parameters to compute TC Hazards |
outfile |
character. Output netcdf filename |
overwrite |
TRUE/FALSE, option to overwrite outfile |
returnWaves |
Return ocean wave parameters (default = FALSE) |
SpatRasterDataset with the following attributes.
| abbreviated attribute | description | units |
| P | Atmospheric pressure | hPa |
| Uw | Meridional wind speed | m/s |
| Vw | Zonal wind speed | m/s |
| Sw | Wind speed | m/s |
| Dw | The direction from which wind originates | deg clockwise from true north |
| Hs0 | Deep water significant wave height | m |
| Tp0 | Deep water Peak wave period | s |
| Dp0 | The peak direction in which wave are heading | deg clockwise from true north. |
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))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.
TCHazaRdsWindProfile(GEO_land, TC, paramsTable)TCHazaRdsWindProfile(GEO_land, TC, paramsTable)
GEO_land |
SpatVector or dataframe hazard geometry generated with land_geometry |
TC |
SpatVector or data.frame of Tropical cyclone track parameters for a single time step. |
paramsTable |
Global parameters to compute TC Hazards. |
SpatRaster with the following attributes
| abbreviated attribute | description | units |
| P | Atmospheric pressure | hPa |
| Uw | Meridional wind speed | m/s |
| Vw | Zonal wind speed | m/s |
| Sw | Wind speed | m/s |
| Dw | Wind direction | deg clockwise from true north |
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$Sw,type="l",xlab = "Radial distance [km]",ylab = "Wind speed [m/s]");grid() #plot(HAZ,"Sw",type="continuous")require(terra) dem <- rast(system.file("extdata/DEMs/YASI_dem.tif", package="TCHazaRds")) land <- dem; land[land > 0] = 0 inland_proximity = distance(land,target = 0) GEO_land = land_geometry(dem,inland_proximity) TCi = vect(cbind(c(154,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment TCi$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
TCHazaRdsWindTimeSereies( outdate = NULL, GEO_land = NULL, TC, paramsTable, returnWaves = FALSE )TCHazaRdsWindTimeSereies( outdate = NULL, GEO_land = NULL, TC, paramsTable, returnWaves = FALSE )
outdate |
array of POSITx date times to linearly interpolate TC track,optional. |
GEO_land |
dataframe hazard geometry generated with land_geometry |
TC |
SpatVector of Tropical cyclone track parameters |
paramsTable |
Global parameters to compute TC Hazards. |
returnWaves |
Return ocean wave parameters (default = FALSE) |
The function calculates wind speed and direction time series from a tropical cyclone track using various wind profile models.
list() containing a timeseries
| abbreviated attribute | description | units |
| date | POSIX data time object of TC or outdate if provided | as.POSIX |
| P | Atmospheric pressure | hPa |
| Uw | Meridional wind speed | m/s |
| Vw | Zonal wind speed | m/s |
| Sw | Wind speed | m/s |
| R | distance to TC centre | m |
| rMax | radius of maximum wind | km |
| vMax | TC maximum velocity | m/s |
| b | TC wind profile exponent | - |
| CP | TC central Pressure | hPa |
| dPdt | change in TC CP per hour | hPa/hr |
| vFm | velocity of TC forward motion | m/s |
| Hs0 | Deep water significant wave height | m |
| Tp0 | Deep water Peak wave period | s |
| Dp0 | The peak direction in which wave are heading | deg clockwise from true north. |
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]"))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]"))
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.
TCpoints2lines(pts_v)TCpoints2lines(pts_v)
pts_v |
A 'SpatVector' of points (from the 'terra' package). |
A 'SpatVector' containing line geometries created from the input points.
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)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)
Transect points from a origin through a point or with a bearing and to the opposite side.
TCProfilePts( TC_line, Through_point = NULL, bear = NULL, length = 200, step = 2 )TCProfilePts( TC_line, Through_point = NULL, bear = NULL, length = 200, step = 2 )
TC_line |
origin of the transect |
Through_point |
a point to pass through |
bear |
the bearing |
length |
the length of the transect in Km |
step |
the spacing of the transect in Km |
spatial vector of transect profile points with distances in Km (negative for left hand side)
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$thetaFm+90,length =100,step=10) plot(pp,"radialdist",type="continuous") lines(TCi,col=2)require(terra) TCi <- vect(cbind(c(154.1,154),c(-26.1,-26)),"lines",crs="epsg:4283") #track line segment TCi$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)
Temporally Interpolate Along a Tropical Cyclone Track And Compute Along-Track Parameters
TCvectInterp(outdate = NULL, TC, paramsTable)TCvectInterp(outdate = NULL, TC, paramsTable)
outdate |
POSIX times to be interpolated to. The output date in "YYYY-MM-DD" format. Default is NULL. |
TC |
SpatVector of Tropical cyclone track parameters |
paramsTable |
Global parameters to compute TC Hazards. |
SpatVector of Tropical cyclone track parameters
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)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)
Update Parameter List to Calibrated Values
tunedParams( paramsTable, infile = system.file("extdata/tuningParams/QLD_modelSummaryTable.csv", package = "TCHazaRds") )tunedParams( paramsTable, infile = system.file("extdata/tuningParams/QLD_modelSummaryTable.csv", package = "TCHazaRds") )
paramsTable |
Global parameters to compute TC Hazards. |
infile |
File containing tuning parameters in a .csv. Default for QLD calibration. |
list of params with updated tuning wind parameters.
paramsTable <- read.csv(system.file("extdata/tuningParams/defult_params.csv",package = "TCHazaRds")) tunedParams(paramsTable)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
update_Track( outdate = NULL, indate, TClons, TClats, vFms, thetaFms, cPs, rMaxModel, vMaxModel, betaModel, rMax2Model, eP, rho = NULL, RMAX, VMAX, B, RMAX2 )update_Track( outdate = NULL, indate, TClons, TClats, vFms, thetaFms, cPs, rMaxModel, vMaxModel, betaModel, rMax2Model, eP, rho = NULL, RMAX, VMAX, B, RMAX2 )
outdate |
POSIX times to be interpolated to |
indate |
POSIX input times |
TClons |
input central TC longitude |
TClats |
input central TC latitude |
vFms |
input forward velocity of TC |
thetaFms |
input forward direction |
cPs |
central pressure |
rMaxModel |
empirical model for radius of maximum wind calculation (rMax in km) |
vMaxModel |
empirical model for maximum wind velocity calculation (vMax in m/s) |
betaModel |
empirical model for TC shape parameter beta (dimensionless Beta) |
rMax2Model |
empirical model for radius of outer 17.5ms wind calculation (rMax2 in km) |
eP |
background environmental pressure (hPa) |
rho |
air density |
RMAX |
If params rMaxModel value is NA, use input TC$RMAX |
VMAX |
If params rMaxModel value is NA, use input TC$VMAX |
B |
If params rMaxModel value is NA, use input TC$B |
RMAX2 |
If params rMax2Model value is NA, use input TC$RMAX2 |
list of track data inclining the rMax vMax and Beta.
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 )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
vMax_modelsR( vMaxModel, cPs, eP, vFms = NULL, TClats = NULL, dPdt = NULL, beta = 1.3, rho = 1.15 )vMax_modelsR( vMaxModel, cPs, eP, vFms = NULL, TClats = NULL, dPdt = NULL, beta = 1.3, rho = 1.15 )
vMaxModel |
0=Arthur (1980),1=Holland (2008),2=Willoughby & Rahn (2004).3=Vickery & Wadhera (2008),4=Atkinson and Holliday (1977) |
cPs |
Tropical cyclone central pressure (hPa) |
eP |
Background environmental pressure (hPa) |
vFms |
Forward speed of the storm m/s |
TClats |
Tropical cyclone central latitude |
dPdt |
rate of change in central pressure over time, hPa per hour from Holland 2008 |
beta |
exponential term for Holland vortex |
rho |
density of air |
maximum wind speed m/s.
vMax_modelsR(vMaxModel=1,cPs=950,eP=1010,vFms = 1,TClats = -14,dPdt = .1)vMax_modelsR(vMaxModel=1,cPs=950,eP=1010,vFms = 1,TClats = -14,dPdt = .1)