scholarly journals Comments on “Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model”by Norton et al.

2019 ◽  
Author(s):  
Anonymous
2015 ◽  
Vol 12 (13) ◽  
pp. 4067-4084 ◽  
Author(s):  
E. N. Koffi ◽  
P. J. Rayner ◽  
A. J. Norton ◽  
C. Frankenberg ◽  
M. Scholze

Abstract. Simulations of carbon fluxes with terrestrial biosphere models still exhibit significant uncertainties, in part due to the uncertainty in model parameter values. With the advent of satellite measurements of solar induced chlorophyll fluorescence (SIF), there exists a novel pathway for constraining simulated carbon fluxes and parameter values. We investigate the utility of SIF in constraining gross primary productivity (GPP). As a first test we assess whether SIF simulations are sensitive to important parameters in a biosphere model. SIF measurements at the wavelength of 755 nm are simulated by the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. Idealized sensitivity tests of the SCOPE model stand-alone indicate strong sensitivity of GPP to the carboxylation capacity (Vcmax) and of SIF to the chlorophyll AB content (Cab) and incoming short wave radiation. Low sensitivity is found for SIF to Vcmax, however the relationship is subtle, with increased sensitivity under high radiation conditions and lower Vcmax ranges. CCDAS simulates well the patterns of satellite-measured SIF suggesting the combined model is capable of ingesting the data. CCDAS supports the idealized sensitivity tests of SCOPE, with SIF exhibiting sensitivity to Cab and incoming radiation, both of which are treated as perfectly known in previous CCDAS versions. These results demonstrate the need for careful consideration of Cab and incoming radiation when interpreting SIF and the limitations of utilizing SIF to constrain Vcmax in the present set-up in the CCDAS system.


2018 ◽  
Author(s):  
Alexander J. Norton ◽  
Peter J. Rayner ◽  
Ernest N. Koffi ◽  
Marko Scholze ◽  
Jeremy D. Silver ◽  
...  

Abstract. This paper presents the assimilation of solar-induced chlorophyll fluorescence (SIF) into a terrestrial biosphere model to estimate the gross uptake of carbon through photosynthesis (GPP). We use the BETHY-SCOPE model to simulate both GPP and SIF in a process-based manner, going beyond a simple linear scaling between the two. We then use satellite SIF data from the Orbiting Carbon Observatory-2 (OCO-2) for 2015 in the data assimilation system to constrain model GPP. The assimilation results in considerable improvement between model and observed SIF, despite difficulties in simulating large SIF values due partly to uncertainties in the prescribed LAI. SIF-optimized global GPP increases by 7 % to 137 ± 6 PgCyr−1 and shows improvement in its global distribution relative to independent estimates. This change in global GPP is driven by an overall decline in APAR and increase in the light-use efficiency of photosynthesis across almost all ecosystems. This process-based data assimilation opens up new pathways to the effective utilization of satellite SIF data that will improve our understanding of the global carbon cycle.


2015 ◽  
Vol 12 (1) ◽  
pp. 707-749 ◽  
Author(s):  
E. N. Koffi ◽  
P. J. Rayner ◽  
A. J. Norton ◽  
C. Frankenberg ◽  
M. Scholze

Abstract. We investigate the utility of satellite measurements of chlorophyll fluorescence (Fs) in constraining gross primary productivity (GPP). We ingest Fs measurements into the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. CCDAS simulates well the patterns of Fs suggesting the combined model is capable of ingesting these measurements. However simulated Fs is insensitive to the key parameter controlling GPP, the carboxylation capacity (Vcmax). Simulated Fs is sensitive to both the incoming absorbed photosynthetically active radiation (aPAR) and leaf chlorophyll concentration both of which are treated as perfectly known in previous CCDAS versions. Proper use of Fs measurements therefore requires enhancement of CCDAS to include and expose these variables.


2019 ◽  
Author(s):  
Alexander J. Norton ◽  
Peter J. Rayner ◽  
Ernest N. Koffi ◽  
Marko Scholze ◽  
Jeremy D. Silver ◽  
...  

Abstract. This paper presents the assimilation of solar-induced chlorophyll fluorescence (SIF) into a terrestrial biosphere model to estimate the gross uptake of carbon through photosynthesis (GPP). We use the BETHY-SCOPE model to simulate both GPP and SIF using a process-based formulation, going beyond a simple linear scaling between the two. We then use satellite SIF data from the Orbiting Carbon Observatory-2 (OCO-2) for 2015 in the data assimilation system to constrain model biophysical parameters and GPP. The assimilation results in considerable improvement in the fit between model and observed SIF, despite a limited capability to fit regions with large seasonal variability in SIF. The SIF assimilation increases global GPP by 31 % to 167 ± 5 Pg C yr−1 and shows an improvement in the global distribution of productivity relative to independent estimates, but a large difference in magnitude. This change in global GPP is driven by an overall increase in photosynthetic light-use efficiency across almost all biomes and more minor, regionally distinct changes in APAR. This process-based data assimilation opens up new pathways to the effective utilization of satellite SIF data to improve our understanding of the global carbon cycle.


2019 ◽  
Vol 16 (15) ◽  
pp. 3069-3093 ◽  
Author(s):  
Alexander J. Norton ◽  
Peter J. Rayner ◽  
Ernest N. Koffi ◽  
Marko Scholze ◽  
Jeremy D. Silver ◽  
...  

Abstract. This paper presents the assimilation of solar-induced chlorophyll fluorescence (SIF) into a terrestrial biosphere model to estimate the gross uptake of carbon through photosynthesis (GPP). We use the BETHY-SCOPE model to simulate both GPP and SIF using a process-based formulation, going beyond a simple linear scaling between the two. We then use satellite SIF data from the Orbiting Carbon Observatory-2 (OCO-2) for 2015 in the data assimilation system to constrain model biophysical parameters and GPP. The assimilation results in considerable improvement in the fit between model and observed SIF, despite a limited capability to fit regions with large seasonal variability in SIF. The SIF assimilation increases global GPP by 31 % to 167±5 Pg C yr−1 and shows an improvement in the global distribution of productivity relative to independent estimates, but a large difference in magnitude. This change in global GPP is driven by an overall increase in photosynthetic light-use efficiency across almost all biomes and more minor, regionally distinct changes in APAR. This process-based data assimilation opens up new pathways to the effective utilization of satellite SIF data to improve our understanding of the global carbon cycle.


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