Comparing Hector & AR6 total RF

1 Set Up

library(data.table)
library(dplyr)
library(tidyr)
library(ggplot2)

BASE_DIR <- here::here()

theme_set(theme_bw())

1.1 Objective

Here we are comparing the difference between total halocarbon RF from Hector and also from AR6.

ar6_data <- read.csv(file.path(BASE_DIR, "ar6_results.csv"))
hector_data <- read.csv(file.path(BASE_DIR, "hector_results.csv"))


rbind(ar6_data, hector_data) %>% 
    as.data.table() %>% 
    .[year <= 2100 & year >= 1850, ] %>% 
    .[scenario %in% hector_data$scenario] -> 
    data

2 Compare

ggplot(data) + 
    geom_line(aes(year, value, color = source, groupby = scenario)) + 
    facet_wrap("scenario", scales = "free") + 
    labs(y = NULL)

Warning: Ignoring unknown aesthetics: groupby

Mean difference between halocarbon RF

dcast(data, year + scenario + variable ~ source, value.var = "value") %>% 
    .[ , dif := ((AR6 - Hector))] %>%
    .[ , .(value = mean(dif)), by = .(scenario)] %>% 
    knitr::kable()

scenario	value
ssp119	0.0068486
ssp126	0.0065934
ssp245	0.0075620
ssp370	0.0082600
ssp434	0.0075293
ssp460	0.0099985
ssp534-over	0.0065813
ssp585	0.0071673

library(hector)
system.file("input", package = "hector") %>% 
    list.files(pattern = "ini", full.names = TRUE) %>% 
    lapply(function(f){
        name <- gsub(x = basename(f), pattern = "hector_|.ini", replacement = "")
        core <- newcore(f, name = name)
        run(core)
        fetchvars(core, dates = 1850:2100, vars = RF_TOTAL()) 
    }) %>% 
    do.call(what = "rbind") %>%  
    as.data.table() %>% 
    .[ , .(value = mean(value)), by = .(scenario)] %>% 
    knitr::kable()

scenario	value
ssp119	1.055222
ssp126	1.242896
ssp245	1.438486
ssp370	1.834509
ssp434	1.342277
ssp460	1.660491
ssp534-over	1.478971
ssp585	2.175404

NA
NA
NA
NA
NA
NA