Empirical_daily_temperature_curve

data.frame containing hourly temperatures. Must contain columns
<code>Year</code> (year of observation), <code>Month</code> (month of observation), <code>Day</code> (day of 
observation), <code>Hour</code> (hour of observation) and <code>Temp</code> (Observed temperature).
If multiple observations within an hour are available, these are averaged.

Thourly

This function derives an empirical daily temperature curve from observed hourly
temperature data. The mean temperature during each hour of the day is expressed
as a function of the daily minimum and maximum temperature. This is done
separately for each month of the year. The output is a data.frame that can then
be used with the
<code><a rd-options="=Empirical_hourly_temperatures" href="/link/Empirical_hourly_temperatures?package=chillR&version=0.72.2&to=%3DEmpirical_hourly_temperatures" data-mini-rdoc="=Empirical_hourly_temperatures::Empirical_hourly_temperatures">Empirical_hourly_temperatures</a></code>
function to generate hourly temperatures from data on daily minimum (<code>Tmin</code>)
and maximum (<code>Tmax</code>) temperatures.

utility

The phenology of plants (i.e. the timing of their annual life
phases) depends on climatic cues. For temperate trees and many other plants,
spring phases, such as leaf emergence and flowering, have been found to result
from the effects of both cool (chilling) conditions and heat. Fruit tree
scientists (pomologists) have developed some metrics to quantify chilling
and heat (e.g. see Luedeling (2012) <doi:10.1016/j.scienta.2012.07.011>).
'chillR' contains functions for processing temperature records into
chilling (Chilling Hours, Utah Chill Units and Chill Portions) and heat units
(Growing Degree Hours). Regarding chilling metrics, Chill Portions are often
considered the most promising, but they are difficult to calculate. This package
makes it easy. 'chillR' also contains procedures for conducting a PLS analysis
relating phenological dates (e.g. bloom dates) to either mean temperatures or
mean chill and heat accumulation rates, based on long-term weather and phenology
records (Luedeling and Gassner (2012) <doi:10.1016/j.agrformet.2011.10.020>).
As of version 0.65, it also includes functions for generating weather
scenarios with a weather generator, for conducting climate change analyses
for temperature-based climatic metrics and for plotting results from such
analyses. Since version 0.70, 'chillR' contains a function for interpolating
hourly temperature records.

Eike Luedeling

chillR

Statistical Methods for Phenology Analysis in Temperate Fruit
Trees

Empirical_daily_temperature_curve function

This function derives an empirical daily temperature curve from observed hourly
temperature data. The mean temperature during each hour of the day is expressed
as a function of the daily minimum and maximum temperature. This is done
separately for each month of the year. The output is a data.frame that can then
be used with the
<code><a rd-options='=Empirical_hourly_temperatures' href='Empirical_hourly_temperatures'>Empirical_hourly_temperatures</a></code>
function to generate hourly temperatures from data on daily minimum (<code>Tmin</code>)
and maximum (<code>Tmax</code>) temperatures.

Empirical_daily_temperature_curve: Empirical daily temperature curve

Description

Usage

Arguments

Value

Examples