FATES calibration update
Rosie Fisher, Jessie Needham, Charlie Koven, Jennifer Holm, Adrianna Foster, Daniel Kennedy, Katie Dagon, Ryan Knox, Keith Oleson, Kjetil Aas, Marcos Longo, Jackie Shuman, Greg Lemieux & the FATES team (and the CLM team! etc. etc. )
Background
FATES has a ‘default’ set of parameters, but these are largely derived from CLM defaults and are not widely trusted
Calibration Cascade
Use a set of reduced complexity modes of FATES to divide up parameter space into manageable chunks…
Calibration Cascade
Sat Phenology
NOCOMP
Fixed Biogeography
Full-fat-FATES
Albedo bias
Default FATES
One at a time ensemble
One at a time ensemble
This looks about right! (trade off of time vs bias correction
Albedo bias
Default
Thin layers
Albedo bias
Albedo bias
Thin layers + no clumping
So far so good, but what now?
So far so good, but what now?
So far so good, but what now?
We need to compare output to (at least) all relevant ILAMB data products
We need to run in ensemble mode
We need to do this -a lot-
FATES calibration repo
https://github.com/adrifoster/fates-global-cal
Respiration / carbon use efficiency / productivity assessment
Ryan vs Atkin vs growth respiration
https://github.com/adrifoster/fates-global-cal/blob/main/jupyter_ppe_scripts/FATES_mainenance_respiration_ensemble.ipynb
‘mega-ensemble script’
outlook
Leaf layer thickness vs. increase factor vs. albedo (CERES product)
Leaf layer thickness vs. increase factor vs. albedo (GEWEX.SRB product)
CERES albedo bias with one at a time changes in RTM parameters per Majasalmi and Bright ranges
Leaf layer thickness vs. increase factor:: SurfaceNetSWRadiation (CERES product)
Vcmax vs Ball Berry slope: latent heat flux bias (GBAF product)
Vcmax vs Ball Berry slope: GPP bias (GBAF product)
outlook
To Do
Write code to multiply FATES-SP LAI by 1/clumping.
Acquire new ILAMB scoring system
Debug scoring w/ Nate
Make priors from LHC from M&B and leaf angle papers. DONE
Make different rtm grid,