fireIndexKBDI: Fire weather indices based on cumulative weather observations

In EcoFire/firebehavioR: Prediction of Wildland Fire Behavior and Hazard

Description

Methods to estimate daily fire weather indices using dynamic weather observations.

Usage

fireIndexKBDI(temp, precip, map, rh, u)

Arguments

temp	a numeric vector of daily air temperatures (C)
precip	a numeric vector of daily precipitations (mm)
map	a single numeric value of mean annual precipitation (mm)
rh	a numeric vector of relative humidities (%)
u	a numeric vector of daily wind speeds (km/hr)

Details

This function computes up to 8 methods to estimate dynamic fire weather indices. These methods are dynamic in that they take prior days' weather into consideration. Therefore the inputs must be ordered by day (i.e., weather observations for a given day are followed by weather observations for the next day.) The number of computed methods depends on the supplied arguments. If requisite arguments for specific methods are not supplied, fireIndexKBDI will not output results for those specific methods (i.e., there will be fewer than 8 columns). The requisite arguments for each method:

kbdi

'temp', 'precip', 'map'

drought factor

'temp', 'precip', 'map'

forestMark5

'temp', 'precip', 'map','u', 'rh'

fosbergKBDI

'temp', 'precip', 'map','u', 'rh'

fuelMoistureKBDI

'temp', 'precip', 'map','u', 'rh'

nesterov

'temp', 'precip', 'rh'

nesterovMod

'temp', 'precip', 'rh'

zdenko

'temp', 'precip', 'rh'

Value

a data frame of fire weather index values with a column for each valid method

Author(s)

Justin P Ziegler, [e-mail]

References

Sharples, J.J., McRae, R.H.D., Weber, R.O. and Gill, A.M., 2009. A simple index for assessing fuel moisture content. Environmental Modelling & Software, 24(5):637-646.
Goodrick, S.L., 2002. Modification of the Fosberg fire weather index to include drought. International Journal of Wildland Fire, 11(4), pp.205-211.
Sharples, J.J., McRae, R.H.D., Weber, R.O. and Gill, A.M., 2009. A simple index for assessing fire danger rating. Environmental Modelling & Software. 24(6):764-774.
Keetch, J.J., Byram, G.M., 1968. A drought index for forest fire control. RP-SE-68, US Department of Agriculture, Forest Service, Southeastern Forest Experiment Station.
Groisman, P.Y., Sherstyukov, B.G., Razuvaev, V.N., Knight, R.W., Enloe, J.G., Stroumentova, N.S., Whitfield, P.H., F<c3><b8>rland, E., Hannsen-Bauer, I., Tuomenvirta, H. and Aleksandersson, H., 2007. Potential forest fire danger over Northern Eurasia: changes during the 20th century. Global and Planetary Change, 56(3-4):371-386.
Skvarenina, J., Mindas, J., Holecy, J. and Tucek, J., 2003, May. Analysis of the natural and meteorological conditions during two largest forest fire events in the Slovak Paradise National Park. In Proceedings of the International Scientific Workshop on Forest Fires in the Wildland<e2><80><93>Urban Interface and Rural Areas in Europe: an integral planning and management challenge.

Examples

#Example using RAWS meteorological station data
data(rrRAWS)
ff = rbind(
data.frame(ffm = ffm('simard', rrRAWS$rh, rrRAWS$temp_c)$fm1hr, method = 'simard'),
data.frame(ffm = ffm('wagner', rrRAWS$rh, rrRAWS$temp_c)$fm1hr, method = 'wagner'),
data.frame(ffm = ffm('anderson', rrRAWS$rh, rrRAWS$temp_c)$fm1hr, method = 'anderson')
)
ff$dateTime = rep(rrRAWS$dateTime, 3)

#NOT RUN

#par(mfrow=c(3,1))
#hist(ff$ffm[ff$method=="simard"])
#hist(ff$ffm[ff$method=="wagner"])
#hist(ff$ffm[ff$method=="anderson"])

EcoFire/firebehavioR documentation built on May 17, 2019, 3:01 p.m.