A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0

Abstract. Advances in Earth observation capabilities mean that there is now a multitude of spatially resolved data sets available that can support the quantification of water and carbon pools and fluxes at the land surface. However, such quantification ideally requires efficient synergistic exploitation of those data, which in turn requires carbon and water land-surface models with the capability to simultaneously assimilate several such data streams. The present article discusses the requirements for such a model and presents one such model based on the combination of the existing Data Assimilation Linked Ecosystem Carbon (DALEC) land vegetation carbon cycle model with the Biosphere Energy-Transfer HYdrology (BETHY) land-surface and terrestrial vegetation scheme. The resulting D&B model, made available as a community model, is presented together with a comprehensive evaluation for two selected study sites of widely varying climate. We then demonstrate the concept of land-surface modelling aided by data streams that are available from satellite remote sensing. Here we present D&B with four observation operators that translate model-derived variables into measurements available from such data streams, namely fraction of photosynthetically active radiation (FAPAR), solar-induced chlorophyll fluorescence (SIF), vegetation optical depth (VOD) at microwave frequencies and near-surface soil moisture (also available from microwave measurements). As a first step, we evaluate the combined model system using local observations and finally discuss the potential of the system presented for multi-stream data assimilation in the context of Earth observation systems.

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Publication Details

Journal
Geoscientific model development
Published
2025-04-08
DOI
https://doi.org/10.5194/gmd-18-2137-2025
Citations
2
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
2.21

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article

A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0

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2 citations
Geoscientific model development
Plant Water Relations and Carbon Dynamics
2.21
article

A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0

S. Quegan, Wolfgang Knorr, Songyan Zhu, Gaétan Pique, Tarek S. El‐Madany, Mike Schwank, Anna Kontu, Tristan Quaife, Tuuli Miinalainen, Alexandre Bouvet, Matthias Drusch, Sönke Zaehle, Susan Steele‐Dunne, Pablo Reyes-Muñoz, Mika Aurela, Hannakaisa Lindqvist, Tea Thum, Yann H. Kerr, Timothy R. Green, Dirk Schuettemeyer, Arnaud Mialon, Emanuel Bueechi, Mariëtte Vreugdenhil, Wouter Dorigo, P. J. Rayner, Amanda Ojasalo, Jochem Verrelst, Juha Lemmetyinen, Mirco Migliavacca, T. Luke Smallman, Nemesio Rodríguez-Fernández, Marko Scholze, Michael Voßbeck, Marika Honkanen, Thomas Kaminski, Matthew Williams
article en
2 citations

Abstract

Abstract. Advances in Earth observation capabilities mean that there is now a multitude of spatially resolved data sets available that can support the quantification of water and carbon pools and fluxes at the land surface. However, such quantification ideally requires efficient synergistic exploitation of those data, which in turn requires carbon and water land-surface models with the capability to simultaneously assimilate several such data streams. The present article discusses the requirements for such a model and presents one such model based on the combination of the existing Data Assimilation Linked Ecosystem Carbon (DALEC) land vegetation carbon cycle model with the Biosphere Energy-Transfer HYdrology (BETHY) land-surface and terrestrial vegetation scheme. The resulting D&B model, made available as a community model, is presented together with a comprehensive evaluation for two selected study sites of widely varying climate. We then demonstrate the concept of land-surface modelling aided by data streams that are available from satellite remote sensing. Here we present D&B with four observation operators that translate model-derived variables into measurements available from such data streams, namely fraction of photosynthetically active radiation (FAPAR), solar-induced chlorophyll fluorescence (SIF), vegetation optical depth (VOD) at microwave frequencies and near-surface soil moisture (also available from microwave measurements). As a first step, we evaluate the combined model system using local observations and finally discuss the potential of the system presented for multi-stream data assimilation in the context of Earth observation systems.

Geoscientific model developmentVol. 18(7)
Finnish Meteorological Institute (FI), Université Toulouse III - Paul Sabatier (FR), TU Wien (AT), Universitat de València (ES), Lund University (SE), Centre National d'Études Spatiales (FR), Swiss Federal Institute for Forest, Snow and Landscape Research (CH), Centre d'Études Spatiales de la Biosphère (FR), Joint Research Centre (IT), Max Planck Institute for Biogeochemistry (DE), European Space Research and Technology Centre (NL), University of Reading (GB), University of Sheffield (GB), Delft University of Technology (NL), University of Edinburgh (GB)
European Space Agency, Academy of Finland, European Research Council, Horizon 2020
Openalex Percentile: Top 14%
Plant Water Relations and Carbon Dynamics
2.21
DOIOpen Access PDFOpenAlex
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