chillR (version 0.75)

step_model: Calculation of cumulative temperature metric according to a user-defined stepwise weight function

Description

This function calculates heat for temperate trees according to a stepwise model provided by the user.

Usage

step_model(
  HourTemp,
  df = data.frame(lower = c(-1000, 1.4, 2.4, 9.1, 12.4, 15.9, 18), upper = c(1.4, 2.4,
    9.1, 12.4, 15.9, 18, 1000), weight = c(0, 0.5, 1, 0.5, 0, -0.5, -1)),
  summ = TRUE
)

Value

Vector of length length(HourTemp) containing the cumulative temperature metric over the entire duration of HourTemp.

Arguments

HourTemp

Vector of hourly temperatures.

df

data.frame with three columns: lower, upper and weight. lower should contain the lower boundary of a chilling weight interval and upper should contain the upper boundary. weight indicates the weighting to be applied to the respective temperature interval.

summ

Boolean parameter indicating whether calculated metrics should be provided as cumulative values over the entire record (TRUE) or as the actual accumulation for each hour (FALSE).

Author

Eike Luedeling

Details

Temperature-based metric calculated according to the user-defined model.

Examples

weather<-fix_weather(KA_weather[which(KA_weather$Year>2006),])

stack<-stack_hourly_temps(weather,latitude=50.4)

df=data.frame(
  lower=c(-1000,1,2,3,4,5,6),
  upper=c(1,2,3,4,5,6,1000),
  weight=c(0,1,2,3,2,1,0))

custom<-function(x) step_model(x,df)

custom(stack$Temp)

models<-list(Chilling_Hours=Chilling_Hours,Utah_Chill_Units=Utah_Model,
Chill_Portions=Dynamic_Model,GDH=GDH,custom=custom)

tempResponse(stack,Start_JDay = 305,End_JDay = 60,models)