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UCL Home  /  Geography  /  News & Events  /  News  /  News Archive  /  March 2012  /  New Data Assimilation project from the European Space Agency

New Data Assimilation project from the European Space Agency

Philip Lewis leads study to improve accuracy of carbon cycle models

New Data Assimilation project from the European Space Agency

Data assimilation (DA) is concerned with testing and improving mathematical models using measurements. The techniques are widely used in numerical weather prediction, where observations of the atmosphere are used to update models and improve their predictions. Such methods give information on the uncertainty of predictions and estimates of state.

 

Scientists led by Professor Philip Lewis in UCL Geography have been working for some time trying to use DA to test and improve how the Carbon cycle is modelled for the Earth's land surface. They use satellite measurements to constrain and test model behaviour. The interface between the land surface model and the observations is examined through 'observation operators' that predict what the satellite would see under different conditions. These are matched with actual measurements to achieve the DA.

 

In previous studies the group have worked out how to interface the ecosystem models and the data, showing how this improves estimates of carbon flows between the atmosphere and vegetation. In a recent project for the European Space Agency (ESA), a prototype software tool was developed to explore how best to carry out this type of DA and to facilitate training.

 

A new study, part of a wider Euro 3M project on DA from the ESA, will move the research on to a more detailed consideration of the model-data interface, improving the consistency of the information derived and widening the scope of what can be achieved in a land surface DA system constrained by satellite data. It will involve working closely with former colleague Dr Tristan Quaife, who recently moved to a Lectureship at the University of Reading to take part in this work.

 

Prof. Philip Lewis, UCL Geography, and NERC National Centre for Earth Observation (NCEO)

 

Further information:

 

http://www2.geog.ucl.ac.uk/~plewis/eoldas/

 

Lewis, P., Gomez--Dans, J., Kaminski, T., Settle, J., Quaife, T., Gobron, N., Styles, J., Berger, M. (2012) An Earth Observation Land Data Assimilation System (EO-LDAS). Remote Sensing of Environment. DOI: 10.1016/j.rse.2011.12.027

 

T. Quaife, P. Lewis, M. DE Kauwe, M. Williams, B. Law, M. Disney, P. Bowyer (2008), Assimilating Canopy Reflectance data into an Ecosystem Model with an Ensemble Kalman Filter, Remote Sensing of Environment, 112(4),1347-1364.


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