Evaluate water vapor short wave radiance absorption schemes of ESMs with the observations.#
Overview#
The recipe reproduces figures from DeAngelis et al. (2015): Figure 1b to 4 from the main part as well as extended data figure 1 and 2. This paper compares models with different schemes for water vapor short wave radiance absorption with the observations. Schemes using pseudo-k-distributions with more than 20 exponential terms show the best results.
Available recipes and diagnostics#
Recipes are stored in recipes/
recipe_deangelis15nat.yml
Diagnostics are stored in diag_scripts/
deangelis15nat/deangelisf1b.py
deangelis15nat/deangelisf2ext.py
deangelis15nat/deangelisf3f4.py
User settings in recipe#
The recipe can be run with different CMIP5 and CMIP6 models. deangelisf1b.py: Several flux variables (W m-2) and up to 6 different model exeriements can be handeled. Each variable needs to be given for each model experiment. The same experiments must be given for all models. In DeAngelis et al. (2015) 150 year means are used but the recipe can handle any duration.
deangelisf2ext.py:
deangelisf3f4.py: For each model, two experiments must be given: a pre industrial control run, and a scenario with 4 times CO2. Possibly, 150 years should be given, but shorter time series work as well.
Variables#
deangelisf1b.py: Tested for:
rsnst (atmos, monthly, longitude, latitude, time)
rlnst (atmos, monthly, longitude, latitude, time)
lvp (atmos, monthly, longitude, latitude, time)
hfss (atmos, monthly, longitude, latitude, time)
any flux variable (W m-2) should be possible.
deangelisf2ext.py:
rsnst (atmos, monthly, longitude, latitude, time)
rlnst (atmos, monthly, longitude, latitude, time)
rsnstcs (atmos, monthly, longitude, latitude, time)
rlnstcs (atmos, monthly, longitude, latitude, time)
lvp (atmos, monthly, longitude, latitude, time)
hfss (atmos, monthly, longitude, latitude, time)
tas (atmos, monthly, longitude, latitude, time)
deangelisf3f4.py: * rsnstcs (atmos, monthly, longitude, latitude, time) * rsnstcsnorm (atmos, monthly, longitude, latitude, time) * prw (atmos, monthly, longitude, latitude, time) * tas (atmos, monthly, longitude, latitude, time)
Observations and reformat scripts#
deangelisf1b.py: * None
deangelisf2ext.py: * None
deangelisf3f4.py:
- rsnstcs:
CERES-EBAF
- prw
ERA-Interim, SSMI
References#
DeAngelis, A. M., Qu, X., Zelinka, M. D., and Hall, A.: An observational radiative constraint on hydrologic cycle intensification, Nature, 528, 249, 2015.