gen_rel_change_scenario

Takes the extracted CMIP6 data and returns climate change scenarios, which
can then be used to generate weather data.

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

Lars Caspersen

Eduardo Fernandez

gen_rel_change_scenario function

<dl><dt>downloaded_list</dt>
<dd>list of data.frames, generated using the
extract_cmip6_data function. Elements are named after the shared socioeconomic
pathway ('SSP') and global climate model ('GCM')</dd>
<dt>scenarios</dt>
<dd>numeric vector, states the future years, for which the climate
change scenarios should be generated. By default set to c(2050, 2085).</dd>
<dt>reference_period</dt>
<dd>numeric vector specifying the years to be used as the
reference period. Defaults to c(1986:2014).</dd>
<dt>future_window_width</dt>
<dd>numeric, sets the window width of the running mean
calculation for the mean temperatures of the years indicated by scenarios</dd></dl>

Arguments

Author

Generates relative climate change scenarios based on extracted CMIP6 data — gen_rel_change_scenario

<dl>

<dt>downloaded_list</dt>
<dd>list of data.frames, generated using the
extract_cmip6_data function. Elements are named after the shared socioeconomic
pathway ('SSP') and global climate model ('GCM')</dd>


<dt>scenarios</dt>
<dd>numeric vector, states the future years, for which the climate
change scenarios should be generated. By default set to c(2050, 2085).</dd>


<dt>reference_period</dt>
<dd>numeric vector specifying the years to be used as the
reference period. Defaults to c(1986:2014).</dd>


<dt>future_window_width</dt>
<dd>numeric, sets the window width of the running mean
calculation for the mean temperatures of the years indicated by scenarios</dd>

</dl>

gen_rel_change_scenario: Generates relative climate change scenarios based on extracted CMIP6 data

Description

Usage

Value

Arguments

Author