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Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0 : Model description and information content

Norton, Alexander J. ; Rayner, Peter J. ; Koffi, Ernest N. and Scholze, Marko LU (2018) In Geoscientific Model Development 11(4). p.1517-1536
Abstract

The synthesis of model and observational information using data assimilation can improve our understanding of the terrestrial carbon cycle, a key component of the Earth's climate-carbon system. Here we provide a data assimilation framework for combining observations of solar-induced chlorophyll fluorescence (SIF) and a process-based model to improve estimates of terrestrial carbon uptake or gross primary production (GPP). We then quantify and assess the constraint SIF provides on the uncertainty in global GPP through model process parameters in an error propagation study. By incorporating 1 year of SIF observations from the GOSAT satellite, we find that the parametric uncertainty in global annual GPP is reduced by 73ĝ€% from ±19.0 to... (More)

The synthesis of model and observational information using data assimilation can improve our understanding of the terrestrial carbon cycle, a key component of the Earth's climate-carbon system. Here we provide a data assimilation framework for combining observations of solar-induced chlorophyll fluorescence (SIF) and a process-based model to improve estimates of terrestrial carbon uptake or gross primary production (GPP). We then quantify and assess the constraint SIF provides on the uncertainty in global GPP through model process parameters in an error propagation study. By incorporating 1 year of SIF observations from the GOSAT satellite, we find that the parametric uncertainty in global annual GPP is reduced by 73ĝ€% from ±19.0 to ±5.2ĝ€Pgĝ€†Cĝ€†yrĝ-1. This improvement is achieved through strong constraint of leaf growth processes and weak to moderate constraint of physiological parameters. We also find that the inclusion of uncertainty in shortwave down-radiation forcing has a net-zero effect on uncertainty in GPP when incorporated into the SIF assimilation framework. This study demonstrates the powerful capacity of SIF to reduce uncertainties in process-based model estimates of GPP and the potential for improving our predictive capability of this uncertain carbon flux.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Geoscientific Model Development
volume
11
issue
4
pages
20 pages
publisher
Copernicus GmbH
external identifiers
  • scopus:85045566821
ISSN
1991-959X
DOI
10.5194/gmd-11-1517-2018
language
English
LU publication?
yes
id
c7d952e9-784c-477d-ae0d-e5dc1b7e85de
date added to LUP
2018-04-26 08:50:41
date last changed
2022-04-25 07:09:18
@article{c7d952e9-784c-477d-ae0d-e5dc1b7e85de,
  abstract     = {{<p>The synthesis of model and observational information using data assimilation can improve our understanding of the terrestrial carbon cycle, a key component of the Earth's climate-carbon system. Here we provide a data assimilation framework for combining observations of solar-induced chlorophyll fluorescence (SIF) and a process-based model to improve estimates of terrestrial carbon uptake or gross primary production (GPP). We then quantify and assess the constraint SIF provides on the uncertainty in global GPP through model process parameters in an error propagation study. By incorporating 1 year of SIF observations from the GOSAT satellite, we find that the parametric uncertainty in global annual GPP is reduced by 73ĝ€% from ±19.0 to ±5.2ĝ€Pgĝ€†Cĝ€†yrĝ-1. This improvement is achieved through strong constraint of leaf growth processes and weak to moderate constraint of physiological parameters. We also find that the inclusion of uncertainty in shortwave down-radiation forcing has a net-zero effect on uncertainty in GPP when incorporated into the SIF assimilation framework. This study demonstrates the powerful capacity of SIF to reduce uncertainties in process-based model estimates of GPP and the potential for improving our predictive capability of this uncertain carbon flux.</p>}},
  author       = {{Norton, Alexander J. and Rayner, Peter J. and Koffi, Ernest N. and Scholze, Marko}},
  issn         = {{1991-959X}},
  language     = {{eng}},
  month        = {{04}},
  number       = {{4}},
  pages        = {{1517--1536}},
  publisher    = {{Copernicus GmbH}},
  series       = {{Geoscientific Model Development}},
  title        = {{Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0 : Model description and information content}},
  url          = {{http://dx.doi.org/10.5194/gmd-11-1517-2018}},
  doi          = {{10.5194/gmd-11-1517-2018}},
  volume       = {{11}},
  year         = {{2018}},
}