Community Research and Development Information Service - CORDIS

FP5

CAMELS Report Summary

Project ID: EVK2-CT-2002-00151
Funded under: FP5-EESD
Country: Germany

D4.1 Report on design of now casting carbon data assimilation system

Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models.
Bottom up integration using MOSES/JULES and Spatial Data
Top down Methods based on the Inversion of Atmospheric Concentrations
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models
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Develop inverse models for the TEMS and the atmospheric transport model (ATM) use these within an offline Carbon Cycle Data Assimilation System (CCDAS), to adjust TEM parameters and prior flux estimates based on a 20-25 year simulation period.

Implement in an AGCM, using existing Numerical Weather Prediction (NWP) data assimilation system where possible to nudge internal model variables (e.g. respiring carbon) to optimally fit the observations.

Carry-out a prototype online CCDAS experiment to infer the European carbon balance from 1990 onwards.

Atmospheric CO2 data and remotely sensed biophysical parameters (WP1)
Improved TEMs and parameters based on model validation (WP2)
Initial carbon stores and model parameters based on 20th century land carbon balance (WP3).

P3).

FORWARD MODELLING
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models.
Bottom up integration using MOSES/JULES and Spatial Data
Top down Methods based on the Inversion of Atmospheric Concentrations
Dual observation and modelling approach, based inversion of atmospheric observations and on the use of satellite data and ecosystem models
ls

INVERSE MODELLING
Method: Use atmospheric transport model to infer CO2 sources and sinks most consistent with atmospheric CO2 measurements.

Advantages: a) Large-scale; b) Data based (transparency).

Disadvantages:
a) Uncertain (network too sparse);
b) not constrained by eco-physiological understanding;
c) net CO2 flux only (cannot isolate land management).

The Kyoto Protocol (and any subsequent agreements designed to curb global warming) will require monitoring of carbon emissions and uptake.

Modelling and measurement techniques have been developed which can estimate land-atmosphere exchange (i.e. Kyoto sinks) at various time and space scales.

A carbon data assimilation system is required to optimally combine these approaches and to make best use of future CO2 measurements from satellite.

Related information

Reported by

MAX-PLANCK-GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V., MAX PLANCK INSTITUTE OF BIOCHEMISTRY
Carl-Zeiss-Promenade 10
07745 JENA
Germany
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