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| Titel |
Improving carbon cycle models using inverse modelling techniques with in-situ measurements and satellite observations |
| VerfasserIn |
Sylvain Delahaies, Ian Roulstone, Nancy Nichols |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250095214
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| Publikation (Nr.) |
 EGU/EGU2014-10664.pdf |
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| Zusammenfassung |
| Improving our understanding of the carbon cycle is an important component of modelling
climate and the Earth system, and a variety of inverse modelling techniques have been used to
combine process models with different types of observational data. Model data fusion,
or inverse modelling, is the process of best combining our under- standing of the
dynamics of a system, observations and our prior knowledge of the state of the
system.
We consider a simple model for the carbon budget allocation for terrestrial ecosystems,
the Data Assimilation-Linked Ecosystem model (DALEC). DALEC is a box model
simulating a large range of processes occurring at different time scales from days to
millennia. Eddy covariance measurements of net ecosystem exchange of CO2 have been used
intensively for over a decade to confront DALEC with real data to estimate model
parameters and quantify uncertainty of the model predictions. The REgional FLux
Estimation eXperiment (REFLEX), compared the strengths and weaknesses of
various inverse modelling strategies (MCMC, ENKF) to estimate parameters and
initial stocks for DALEC; most results agreed on the fact that parameters and initial
stocks directly related to fast processes were best estimated with narrow confidence
intervals, whereas those related to slow processes were poorly estimated with very large
uncertainties. While other studies have tried to overcome this difficulty by adding
complementary data streams or by considering longer observation windows no systematic
analysis has been carried out so far to explain the large differences among results of
REFLEX.
One of the merits of DALEC is its simplicity that facilitates close mathematical scrutiny.
Using variational techniques we quantify the ill-posedness of the inverse problem and we
discuss various regularisation techniques. Using the tangent linear model we study the
information content of multiple data sources and show how these multiple data sources help
constraining initial carbon stocks and parameters. |
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