WFRF:(Chevallier Frédéric)
Sökning: WFRF:(Chevallier Frédéric) > Consistent assimila...
LIBRIS Formathandbok (Information om MARC21)
| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 03892naa a2200361 4500 | |
| 001 | oai:lup.lub.lu.se:283998f0-e37d-4980-be6d-cb6b5fec7965 | |
| 003 | SwePub | |
| 008 | 161021s2016 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://lup.lub.lu.se/record/283998f0-e37d-4980-be6d-cb6b5fec79652 URI |
| 024 | 7 | a https://doi.org/10.5194/gmd-9-3569-20162 DOI |
| 040 | a (SwePub)lu | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a art2 swepub-publicationtype |
| 072 | 7 | a ref2 swepub-contenttype |
| 100 | 1 | a MacBean, Natashau University of Paris-Saclay4 aut |
| 245 | 1 0 | a Consistent assimilation of multiple data streams in a carbon cycle data assimilation system |
| 264 | c 2016-10-04 | |
| 264 | 1 | b Copernicus GmbH,c 2016 |
| 300 | a 20 s. | |
| 520 | a Data assimilation methods provide a rigorous statistical framework for constraining parametric uncertainty in land surface models (LSMs), which in turn helps to improve their predictive capability and to identify areas in which the representation of physical processes is inadequate. The increase in the number of available datasets in recent years allows us to address different aspects of the model at a variety of spatial and temporal scales. However, combining data streams in a DA system is not a trivial task. In this study we highlight some of the challenges surrounding multiple data stream assimilation for the carbon cycle component of LSMs. We give particular consideration to the assumptions associated with the type of inversion algorithm that are typically used when optimising global LSMs-namely, Gaussian error distributions and linearity in the model dynamics. We explore the effect of biases and inconsistencies between the observations and the model (resulting in non-Gaussian error distributions), and we examine the difference between a simultaneous assimilation (in which all data streams are included in one optimisation) and a step-wise approach (in which each data stream is assimilated sequentially) in the presence of non-linear model dynamics. In addition, we perform a preliminary investigation into the impact of correlated errors between two data streams for two cases, both when the correlated observation errors are included in the prior observation error covariance matrix, and when the correlated errors are ignored. We demonstrate these challenges by assimilating synthetic observations into two simple models: the first a simplified version of the carbon cycle processes represented in many LSMs and the second a non-linear toy model. Finally, we provide some perspectives and advice to other land surface modellers wishing to use multiple data streams to constrain their model parameters. | |
| 650 | 7 | a NATURVETENSKAPx Geovetenskap och miljövetenskapx Klimatforskning0 (SwePub)105012 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Earth and Related Environmental Sciencesx Climate Research0 (SwePub)105012 hsv//eng |
| 700 | 1 | a Peylin, Philippeu University of Paris-Saclay4 aut |
| 700 | 1 | a Chevallier, Frédéricu University of Paris-Saclay4 aut |
| 700 | 1 | a Scholze, Markou Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science4 aut0 (Swepub:lu)nate-mks |
| 700 | 1 | a Schürmann, Gregoru Max Planck Institute for Biogeochemistry4 aut |
| 710 | 2 | a University of Paris-Saclayb Institutionen för naturgeografi och ekosystemvetenskap4 org |
| 773 | 0 | t Geoscientific Model Developmentd : Copernicus GmbHg 9:10, s. 3569-3588q 9:10<3569-3588x 1991-959Xx 1991-9603 |
| 856 | 4 | u http://dx.doi.org/10.5194/gmd-9-3569-2016x freey FULLTEXT |
| 856 | 4 | u https://www.geosci-model-dev.net/9/3569/2016/gmd-9-3569-2016.pdf |
| 856 | 4 8 | u https://lup.lub.lu.se/record/283998f0-e37d-4980-be6d-cb6b5fec7965 |
| 856 | 4 8 | u https://doi.org/10.5194/gmd-9-3569-2016 |
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