In JGCRI/HIRM: A Hybrid Impulse Response Model for Hector

This vignette provides a basic introduction for running HIRM. Here we will show how to use HIRM with its built-in inputs derived from Hector. HIRM could however be set up use inputs from any process-based model.

RCP 4.5 Run

First, load the hirm package and other helpful packages.

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(HIRM)
library(ggplot2)  # For plotting

Then load the built-in HIRM inputs.

# This is Hector's general impulse response function (IRF). The relationship between global mean temperature and radiative forcing is the same for all aerosols and ghgs. 
irf_input <- Hector_IRF

# This is a list of radiative forcing pathways (RF) for different aerosols and ghgs for different RCP scenarios. 
rf_inputs <- Hector_RF

# The configuration matrix  will be used to pair IRFs with RF pathways.
config_matrix <- Hector_ConfigMatrix

Get an idea of what the configuration matrix looks like.

# In this matrix each row represents a different RF pathway and the columns represent different IRFs. (Hector has a single general IRF while other process-based models have multiple). Currently all of the entries in the matrix are set to 0, meaning that non of the RF pathways are paried with the IRF. 
head(config_matrix)

Now all of the HIRM inputs are loaded modify the configuration matrix to set HIRM up for a specific run. For this example let's set HIRM up to run the rcp45 scenario.

# Figure out which RF pathways have a pattern that matches our scenario name. 
scenario_name <- 'rcp45' 
rf_indices    <- which(grepl(pattern = scenario_name, x = row.names(config_matrix)))

# For each rcp45 RF pathway change the entry from a 0 to 1 so that HIRM will pair Hector's general IRF with the RF pathway input. 
config_matrix[rf_indices, 1] <- 1

Use the inputs in the impulse respose model (IRM).

rslt <- core_IRM(config_matrix = config_matrix, 
                 rf_list = rf_inputs, 
                 irf_list = irf_input)

Plot the temperature results.

ggplot(data = rslt$total_temp) + 
  geom_line(aes(year, value)) + 
  theme_bw() + 
  labs(title = "HIRM RCP 4.5 Global Mean Temp", y = expression(degree~'C'), x = 'Year')

Plot the temperature contribution of each radiative forcing agent.

ggplot(data = rslt$temp_contributions) + 
  geom_line(aes(year, value, color = RF_agent)) + 
  theme_bw() + 
  labs(title = "HIRM RCP 4.5 RF Agent Temperarure Contributions", 
       y = expression(degree~'C'), x = 'Year')