IPCC AR6 Chapter 3 (selected figures)
Overview
This recipe collects selected diagnostics used in IPCC AR6 WGI Chapter 3: Human influence on the climate system. Plots from IPCC AR6 can be readily reproduced and compared to previous versions. The aim is to be able to start with what was available now the next time allowing us to focus on developing more innovative analysis methods rather than constantly having to “re-invent the wheel”.
The plots are produced collecting the diagnostics from individual recipes. The following figures from Eyring et al. (2021) can currently be reproduced:
Figure 3.3 a,b,c,d: Surface Air Temperature - Model Bias
Figure 3.4: Anomaly Of Near-Surface Air Temperature
Figure 3.5: Temporal Variability Of Near-Surface Air Temperature
Figure 3.13: Precipitation - Model Bias
Figure 3.15: Precipitation Anomaly
Available recipes and diagnostics
Recipes are stored in esmvaltool/recipes/ipccwg1ar6ch3/
recipe_ipccwg1ar6ch3_atmosphere.yml
Diagnostics are stored in esmvaltool/diag_scripts/
Fig. 3.3:
ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl: See here:.
ipcc_ar6/model_bias.ncl
Fig. 3.4:
ipcc_ar6/tas_anom.ncl
ipcc_ar6/tsline_collect.ncl
Fig. 3.5:
ipcc_ar6/zonal_st_dev.ncl
Fig. 3.13:
ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl: See here:.
ipcc_ar6/model_bias.ncl
Fig. 3.15:
ipcc_ar6/precip_anom.ncl
User settings in recipe
Script ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl
See here.
Script ipcc_ar6/model_bias.ncl
Optional settings (scripts)
plot_abs_diff: additionally also plot absolute differences (true, false)
plot_rel_diff: additionally also plot relative differences (true, false)
plot_rms_diff: additionally also plot root mean square differences (true, false)
projection: map projection, e.g., Mollweide, Mercator
timemean: time averaging, i.e. “seasonalclim” (DJF, MAM, JJA, SON), “annualclim” (annual mean)
Required settings (variables)
reference_dataset: name of reference dataset
Color tables
variable “tas” and “tos”: diag_scripts/shared/plot/rgb/ipcc-ar6_temperature_div.rgb, diag_scripts/shared/plot/rgb/ipcc-ar6_temperature_10.rgb, diag_scripts/shared/plot/rgb/ipcc-ar6_temperature_seq.rgb
variable “pr”: diag_scripts/shared/plots/rgb/ipcc-ar6_precipitation_seq.rgb, diag_scripts/shared/plot/rgb/ipcc-ar6_precipitation_10.rgb
variable “sos”: diag_scripts/shared/plot/rgb/ipcc-ar6_misc_seq_1.rgb, diag_scripts/shared/plot/rgb/ipcc-ar6_misc_div.rgb
Script ipcc_ar6/tas_anom.ncl
Required settings for script
styleset: as in diag_scripts/shared/plot/style.ncl functions
Optional settings for script
blending: if true, calculates blended surface temperature
ref_start: start year of reference period for anomalies
ref_end: end year of reference period for anomalies
ref_value: if true, right panel with mean values is attached
ref_mask: if true, model fields will be masked by reference fields
region: name of domain
plot_units: variable unit for plotting
y-min: set min of y-axis
y-max: set max of y-axis
header: if true, region name as header
volcanoes: if true, adds volcanoes to the plot
write_stat: if true, write multi model statistics in nc-file
Optional settings for variables
reference_dataset: reference dataset; REQUIRED when calculating anomalies
Color tables
e.g. diag_scripts/shared/plot/styles/cmip5.style
Script ipcc_ar6/tsline_collect.ncl
Optional settings for script
blending: if true, then var=”gmst” otherwise “gsat”
ref_start: start year of reference period for anomalies
ref_end: end year of reference period for anomalies
region: name of domain
plot_units: variable unit for plotting
y-min: set min of y-axis
y-max: set max of y-axis
order: order in which experiments should be plotted
stat_shading: if true: shading of statistic range
ref_shading: if true: shading of reference period
Optional settings for variables
reference_dataset: reference dataset; REQUIRED when calculating anomalies
Script ipcc_ar6/zonal_st_dev.ncl
Required settings for script
styleset: as in diag_scripts/shared/plot/style.ncl functions
Optional settings for script
plot_legend: if true, plot legend will be plotted
plot_units: variable unit for plotting
multi_model_mean: if true, multi-model mean and uncertaintiy will be plotted
Optional settings for variables
reference_dataset: reference dataset; REQUIRED when calculating anomalies
Script ipcc_ar6/precip_anom.ncl
Required settings for script
panels: list of variables plotted in each panel
start_year: start of time coordinate
end_year: end of time coordinate
Optional settings for script
anomaly: true if anomaly should be calculated
ref_start: start year of reference period for anomalies
ref_end: end year of reference period for anomalies
ref_mask: if true, model fields will be masked by reference fields
region: name of domain
plot_units: variable unit for plotting
header: if true, region name as header
stat: statistics for multi model nc-file (MinMax,5-95,10-90)
y_min: set min of y-axis
y_max: set max of y-axis
Variables
pr (atmos, monthly mean, longitude latitude time)
tas (atmos, monthly mean, longitude latitude time)
tasa (atmos, monthly mean, longitude latitude time)
Observations and reformat scripts
BerkeleyEarth (tasa - esmvaltool/cmorizers/data/formatters/datasets/berkeleyearth.py)
CRU (pr - esmvaltool/cmorizers/data/formatters/datasets/cru.py)
ERA5 (tas - ERA5 data can be used via the native6 project)
GHCN (pr - esmvaltool/cmorizers/data/formatters/datasets/ghcn.ncl)
GPCP-SG (pr - obs4MIPs)
HadCRUT5 (tasa - esmvaltool/cmorizers/data/formatters/datasets/hadcrut5.py)
Kadow2020 (tasa - esmvaltool/cmorizers/data/formatters/datasets/kadow2020.py)
NOAAGlobalTemp (tasa - esmvaltool/cmorizers/data/formatters/datasets/noaaglobaltemp.py)
References
Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press.