A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1. 0
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1. 0
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.
2137-2159
Knorr, Wolfgang
35cccdce-d9c7-4845-81b0-51d29ea4f3e3
Williams, Matthew
66080345-cb0f-4fee-a814-7d6561d5eb66
Thum, Tea
11fdaaaf-6ad6-4547-a7fe-9c76943622ab
Zhu, Songyan
122e3311-4c1f-48e9-8aa3-09fcbe990cd9
8 April 2025
Knorr, Wolfgang
35cccdce-d9c7-4845-81b0-51d29ea4f3e3
Williams, Matthew
66080345-cb0f-4fee-a814-7d6561d5eb66
Thum, Tea
11fdaaaf-6ad6-4547-a7fe-9c76943622ab
Zhu, Songyan
122e3311-4c1f-48e9-8aa3-09fcbe990cd9
Knorr, Wolfgang, Williams, Matthew and Thum, Tea
,
et al.
(2025)
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1. 0.
Geoscientific Model Development, 18 (7), .
(doi:10.5194/gmd-18-2137-2025).
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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gmd-18-2137-2025
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Accepted/In Press date: 17 January 2025
Published date: 8 April 2025
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Local EPrints ID: 503348
URI: http://eprints.soton.ac.uk/id/eprint/503348
ISSN: 1991-9603
PURE UUID: eeb4b8f7-9f18-4fac-8ff1-a322ead9e9a5
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Date deposited: 29 Jul 2025 16:57
Last modified: 22 Aug 2025 02:45
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Author:
Wolfgang Knorr
Author:
Matthew Williams
Author:
Tea Thum
Author:
Songyan Zhu
Corporate Author: et al.
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