Simultaneous Assimilation of Remotely Sensed Soil Moisture and FAPAR for Improving Terrestrial Carbon Fluxes at Multiple Sites Using CCDAS

Mousong Wu,Marko Scholze,Michael Voßbeck,Georg Hoffmann,Thomas Kaminski

doi:10.3390/rs11010027

Mousong Wu, Marko Scholze + Show 3 more

Open Access

https://doi.org/10.3390/rs11010027

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Journal: Remote sensing	Publication Date: Dec 25, 2018
Citations: 12	License type: CC BY 4.0

Affiliation: Lund University, Hamburg Institut (Germany)

Abstract

The carbon cycle of the terrestrial biosphere plays a vital role in controlling the global carbon balance and, consequently, climate change. Reliably modeled CO2 fluxes between the terrestrial biosphere and the atmosphere are necessary in projections of policy strategies aiming at constraining carbon emissions and of future climate change. In this study, SMOS (Soil Moisture and Ocean Salinity) L3 soil moisture and JRC-TIP FAPAR (Joint Research Centre—Two-stream Inversion Package Fraction of Absorbed Photosynthetically Active Radiation) data with respective original resolutions at 10 sites were used to constrain the process-based terrestrial biosphere model, BETHY (Biosphere, Energy Transfer and Hydrology), using the carbon cycle data assimilation system (CCDAS). We find that simultaneous assimilation of these two datasets jointly at all 10 sites yields a set of model parameters that achieve the best model performance in terms of independent observations of carbon fluxes as well as soil moisture. Assimilation in a single-site mode or using only a single dataset tends to over-adjust related parameters and deteriorates the model performance of a number of processes. The optimized parameter set derived from multi-site assimilation with soil moisture and FAPAR also improves, when applied at global scale simulations, the model-data fit against atmospheric CO2. This study demonstrates the potential of satellite-derived soil moisture and FAPAR when assimilated simultaneously in a model of the terrestrial carbon cycle to constrain terrestrial carbon fluxes. It furthermore shows that assimilation of soil moisture data helps to identity structural problems in the underlying model, i.e., missing management processes at sites covered by crops and grasslands.

Highlights

The terrestrial biosphere plays a vital role in the global carbon, water, and energy cycles [1,2].Exchanges of carbon between the land surface and the atmosphere directly influence atmospheric carbon dioxide concentrations
We investigate the potential of such a simultaneous assimilation of remotely sensed surface soil moisture and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) data to constrain the terrestrial carbon cycle both in single-site and in multi-site setups
The questions addressed are: What are the advantages of combining soil moisture and FAPAR data in constraining parameters of Biosphere Energy Transfer HYdrology (BETHY) in a multiple sites approach? What do the posterior parameter values obtained by the assimilation experiments tell us about the mechanistic processes represented in the model? We address the question whether an optimal parameter set obtained from site scale assimilation experiments improves global scale simulations

Summary

Introduction

The terrestrial biosphere plays a vital role in the global carbon, water, and energy cycles [1,2]. Exchanges of carbon between the land surface and the atmosphere directly influence atmospheric carbon dioxide concentrations. The interactions of these three cycles result in a climate-carbon cycle feedback, which is a major source of uncertainty in climate change projections [2]. Large uncertainties exist in estimates of the terrestrial carbon balance both in observations and in model simulations [2,3,4,5]. A better understanding of the response of the terrestrial biosphere to climate variability is both necessary and fundamental for improving projections of future climate change.

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