Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales
Terrestrial biosphere models are indispensable tools for analyzing the Biosphere-atmosphere exchange of carbon and water. Evaluation of these models using site level observations scrutinizes our current understanding of biospheric responses to meteorological variables. Here we propose a novel model-data comparison strategy considering that CO2 and H2O exchanges fluctuate on a wide range of timescales. Decomposing simulated and observed time series into subsignals allows to quantify model performance as a function of frequency, and to localize model-data disagreement in time. This approach is illustrated using site level predictions from two models of different complexity, Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and Lund-Potsdam-Jena (LPJ), at four eddy covariance towers in different climates. Frequency-dependent errors reveal substantial model-data disagreement in seasonal?annual and high-frequency net CO2 fluxes. By localizing these errors in time we can trace these back, for example, to overestimations of seasonal-annual periodicities of ecosystem respiration during spring greenup and autumn in both models. In the same frequencies, systematic misrepresentations of CO2 uptake severely affect the performance of LPJ, which is a consequence of the parsimonious representation of phenology. ORCHIDEE shows pronounced model-data disagreements in the high-frequency fluctuations of evapotranspiration across the four sites. We highlight the advantages that our novel methodology offers for a rigorous model evaluation compared to classical model evaluation approaches. We propose that ongoing model development will benefit from considering model-data (dis)agreements in the time-frequency domain.
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dig-cirad-fr-5577732024-01-28T18:48:33Z http://agritrop.cirad.fr/557773/ http://agritrop.cirad.fr/557773/ Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales. Mahecha Miguel D., Reichstein Markus, Jung Martin, Seneviratne Sonia I., Zaehle Sönke, Beer Christian, Braakhekke M.C., Carvalhais Nuno, Lange Holger, Le Maire Guerric, Moors Eddy J.. 2010. Journal of Geophysical Research. Biogeosciences, 115 (G2), 21 p.https://doi.org/10.1029/2009JG001016 <https://doi.org/10.1029/2009JG001016> Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales Mahecha, Miguel D. Reichstein, Markus Jung, Martin Seneviratne, Sonia I. Zaehle, Sönke Beer, Christian Braakhekke, M.C. Carvalhais, Nuno Lange, Holger Le Maire, Guerric Moors, Eddy J. eng 2010 Journal of Geophysical Research. Biogeosciences U10 - Informatique, mathématiques et statistiques P40 - Météorologie et climatologie 000 - Autres thèmes P01 - Conservation de la nature et ressources foncières écologie eau modélisation environnementale cycle du carbone dioxyde de carbone cycle hydrologique évapotranspiration écosystème modèle de simulation atmosphère météorologie climatologie http://aims.fao.org/aos/agrovoc/c_2467 http://aims.fao.org/aos/agrovoc/c_8309 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_17299 http://aims.fao.org/aos/agrovoc/c_1302 http://aims.fao.org/aos/agrovoc/c_11670 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_8994 http://aims.fao.org/aos/agrovoc/c_4783 http://aims.fao.org/aos/agrovoc/c_1671 Terrestrial biosphere models are indispensable tools for analyzing the Biosphere-atmosphere exchange of carbon and water. Evaluation of these models using site level observations scrutinizes our current understanding of biospheric responses to meteorological variables. Here we propose a novel model-data comparison strategy considering that CO2 and H2O exchanges fluctuate on a wide range of timescales. Decomposing simulated and observed time series into subsignals allows to quantify model performance as a function of frequency, and to localize model-data disagreement in time. This approach is illustrated using site level predictions from two models of different complexity, Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and Lund-Potsdam-Jena (LPJ), at four eddy covariance towers in different climates. Frequency-dependent errors reveal substantial model-data disagreement in seasonal?annual and high-frequency net CO2 fluxes. By localizing these errors in time we can trace these back, for example, to overestimations of seasonal-annual periodicities of ecosystem respiration during spring greenup and autumn in both models. In the same frequencies, systematic misrepresentations of CO2 uptake severely affect the performance of LPJ, which is a consequence of the parsimonious representation of phenology. ORCHIDEE shows pronounced model-data disagreements in the high-frequency fluctuations of evapotranspiration across the four sites. We highlight the advantages that our novel methodology offers for a rigorous model evaluation compared to classical model evaluation approaches. We propose that ongoing model development will benefit from considering model-data (dis)agreements in the time-frequency domain. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/557773/1/document_557773.pdf application/pdf Cirad license info:eu-repo/semantics/openAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1029/2009JG001016 10.1029/2009JG001016 http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=209675 info:eu-repo/semantics/altIdentifier/doi/10.1029/2009JG001016 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1029/2009JG001016 |
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U10 - Informatique, mathématiques et statistiques P40 - Météorologie et climatologie 000 - Autres thèmes P01 - Conservation de la nature et ressources foncières écologie eau modélisation environnementale cycle du carbone dioxyde de carbone cycle hydrologique évapotranspiration écosystème modèle de simulation atmosphère météorologie climatologie http://aims.fao.org/aos/agrovoc/c_2467 http://aims.fao.org/aos/agrovoc/c_8309 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_17299 http://aims.fao.org/aos/agrovoc/c_1302 http://aims.fao.org/aos/agrovoc/c_11670 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_8994 http://aims.fao.org/aos/agrovoc/c_4783 http://aims.fao.org/aos/agrovoc/c_1671 U10 - Informatique, mathématiques et statistiques P40 - Météorologie et climatologie 000 - Autres thèmes P01 - Conservation de la nature et ressources foncières écologie eau modélisation environnementale cycle du carbone dioxyde de carbone cycle hydrologique évapotranspiration écosystème modèle de simulation atmosphère météorologie climatologie http://aims.fao.org/aos/agrovoc/c_2467 http://aims.fao.org/aos/agrovoc/c_8309 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_17299 http://aims.fao.org/aos/agrovoc/c_1302 http://aims.fao.org/aos/agrovoc/c_11670 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_8994 http://aims.fao.org/aos/agrovoc/c_4783 http://aims.fao.org/aos/agrovoc/c_1671 |
spellingShingle |
U10 - Informatique, mathématiques et statistiques P40 - Météorologie et climatologie 000 - Autres thèmes P01 - Conservation de la nature et ressources foncières écologie eau modélisation environnementale cycle du carbone dioxyde de carbone cycle hydrologique évapotranspiration écosystème modèle de simulation atmosphère météorologie climatologie http://aims.fao.org/aos/agrovoc/c_2467 http://aims.fao.org/aos/agrovoc/c_8309 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_17299 http://aims.fao.org/aos/agrovoc/c_1302 http://aims.fao.org/aos/agrovoc/c_11670 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_8994 http://aims.fao.org/aos/agrovoc/c_4783 http://aims.fao.org/aos/agrovoc/c_1671 U10 - Informatique, mathématiques et statistiques P40 - Météorologie et climatologie 000 - Autres thèmes P01 - Conservation de la nature et ressources foncières écologie eau modélisation environnementale cycle du carbone dioxyde de carbone cycle hydrologique évapotranspiration écosystème modèle de simulation atmosphère météorologie climatologie http://aims.fao.org/aos/agrovoc/c_2467 http://aims.fao.org/aos/agrovoc/c_8309 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_17299 http://aims.fao.org/aos/agrovoc/c_1302 http://aims.fao.org/aos/agrovoc/c_11670 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_8994 http://aims.fao.org/aos/agrovoc/c_4783 http://aims.fao.org/aos/agrovoc/c_1671 Mahecha, Miguel D. Reichstein, Markus Jung, Martin Seneviratne, Sonia I. Zaehle, Sönke Beer, Christian Braakhekke, M.C. Carvalhais, Nuno Lange, Holger Le Maire, Guerric Moors, Eddy J. Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
description |
Terrestrial biosphere models are indispensable tools for analyzing the Biosphere-atmosphere exchange of carbon and water. Evaluation of these models using site level observations scrutinizes our current understanding of biospheric responses to meteorological variables. Here we propose a novel model-data comparison strategy considering that CO2 and H2O exchanges fluctuate on a wide range of timescales. Decomposing simulated and observed time series into subsignals allows to quantify model performance as a function of frequency, and to localize model-data disagreement in time. This approach is illustrated using site level predictions from two models of different complexity, Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and Lund-Potsdam-Jena (LPJ), at four eddy covariance towers in different climates. Frequency-dependent errors reveal substantial model-data disagreement in seasonal?annual and high-frequency net CO2 fluxes. By localizing these errors in time we can trace these back, for example, to overestimations of seasonal-annual periodicities of ecosystem respiration during spring greenup and autumn in both models. In the same frequencies, systematic misrepresentations of CO2 uptake severely affect the performance of LPJ, which is a consequence of the parsimonious representation of phenology. ORCHIDEE shows pronounced model-data disagreements in the high-frequency fluctuations of evapotranspiration across the four sites. We highlight the advantages that our novel methodology offers for a rigorous model evaluation compared to classical model evaluation approaches. We propose that ongoing model development will benefit from considering model-data (dis)agreements in the time-frequency domain. |
format |
article |
topic_facet |
U10 - Informatique, mathématiques et statistiques P40 - Météorologie et climatologie 000 - Autres thèmes P01 - Conservation de la nature et ressources foncières écologie eau modélisation environnementale cycle du carbone dioxyde de carbone cycle hydrologique évapotranspiration écosystème modèle de simulation atmosphère météorologie climatologie http://aims.fao.org/aos/agrovoc/c_2467 http://aims.fao.org/aos/agrovoc/c_8309 http://aims.fao.org/aos/agrovoc/c_9000056 http://aims.fao.org/aos/agrovoc/c_17299 http://aims.fao.org/aos/agrovoc/c_1302 http://aims.fao.org/aos/agrovoc/c_11670 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_8994 http://aims.fao.org/aos/agrovoc/c_4783 http://aims.fao.org/aos/agrovoc/c_1671 |
author |
Mahecha, Miguel D. Reichstein, Markus Jung, Martin Seneviratne, Sonia I. Zaehle, Sönke Beer, Christian Braakhekke, M.C. Carvalhais, Nuno Lange, Holger Le Maire, Guerric Moors, Eddy J. |
author_facet |
Mahecha, Miguel D. Reichstein, Markus Jung, Martin Seneviratne, Sonia I. Zaehle, Sönke Beer, Christian Braakhekke, M.C. Carvalhais, Nuno Lange, Holger Le Maire, Guerric Moors, Eddy J. |
author_sort |
Mahecha, Miguel D. |
title |
Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
title_short |
Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
title_full |
Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
title_fullStr |
Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
title_full_unstemmed |
Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
title_sort |
comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales |
url |
http://agritrop.cirad.fr/557773/ http://agritrop.cirad.fr/557773/1/document_557773.pdf |
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