Using solar-induced chlorophyll
fluorescence (SIF) to constrain global
gross primary productivity in the
process-based terrestrial biosphere model
BETHY-SCOPE
Alex Norton, Peter Rayner, Marko Scholze, Ernest Koffi
June 7, 2017
Outline
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BETHYSCOPE system;
Observations;
Information Content;
How well do we fit SIF data?
Prognostic and diagnostic LAI?
GPP estimates;
Future work.
acknowledgements
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OCO2 team especally Christian Frankenberg;
SCOPE team, Christiaan van der Tol;
BETHY team, Wolfgang Knorr, Thomas Kaminski;
System at a glance
BETHY “Biosphere, Energy Transfer Hydrology”, KNORR
2010 (doi:10.1029/2009JG001119), carbon,
energy and water balance, prognostic or
diagnostic phenology;
SCOPE “Soil-Canopy- Observation of Photosynthesis and
the Energy balance”, van der Tol et al. 2009
(doi10.5194/bg-6-3109-2009). 1d canopy
radiative transfer incl. spectrally resolved
fluorescence, mechanistic model of leaf
fluorescence;
Coupling Pass parameters from BETHY to SCOPE, use
SCOPE GPP in BETHY carbon balance.
Setup Continued
Spatial Resolution 13 PFTs, many parameters at PFT level
and some global, 2×2◦ resolution;
Key Parameters Phenological parameters, Vcmax (25C ),
chlorophyll;
Computation Jacobians calculated by finite-difference,
inner-outer loop minimisation, chlorophyll held
constant through first outer loop;
GPP Calculate GPP from optimised parameters and
uncertainties from GPP jacobians.
Data
July 2015 SIF Uncertainties
January 2015 SIF
from OCO2
Uncertainties from OCO2
I Monthly mean OCO2 SIF for 2015 aggregated to 2×2◦ ;
I Data uncertainty taken from product but aggregated
conservatively;
Information Content
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Norton et al. (2017) (doi:10.5194/gmd-2017-34);
Prior uncertainty on global GPP ≈ 13 PgC/y;
Reasonable constraint on phenological parameters, Vcmax ;
≈ 80% reduction in GPP uncertainty;
Always optimistic, especially it ignores the ability to
actually match observations.
Assimilation with Prognostic LAI
residuals of LAI for prior
model
residuals of LAI for
posterior model.
Prescribed LAI
Fit to zonal mean SIF for prior and posterior model
Seasonal Cycles
Seasonal fit to regionally
averaged SIF for North
American boreal forests:
prior (grey), optimised
(green) and (obs) dots.
Seasonal fit to regionally
averaged SIF for Amazonian
tropical forests: prior
(grey), optimised (green)
and (obs) dots.
GPP Prescribed LAI
Prior annual mean GPP
from BETHYSCOPE
Posterior annual mean GPP
from BETHYSCOPE
Notes
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global GPP increases from 82 to 100 PgC/y;
Probably still slight underestimate with failure to fit some
high SIF values;
Hybrid data product where we use SIF/GPP relationships
from BETHYSCOPE coupled to BETHY GPP produces
113 PgC/y;
The regressions from this hybrid are an interesting
emulator.
Future Work
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More interprettation;
Simultaneous assimilation of SIF and APAR;
Improving water-balance of SCOPE;
Validate or assimilate COS and CO2 .
Conclusions
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We can credibly assimilate SIF into a mechanistic
biosphere model;
We can’t do this with prognostic penology;
there still appears to be a problem matching high SIF
values;
Chlorophyll is a key nuisance variable.