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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-267
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-267
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model experiment description paper 14 Oct 2020

Submitted as: model experiment description paper | 14 Oct 2020

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This preprint is currently under review for the journal GMD.

How to reconstruct diffuse radiation scenario for simulating GPP in land surface models?

Yuan Zhang1,2, Olivier Boucher3, Philippe Ciais1, Laurent Li2, and Nicolas Bellouin4 Yuan Zhang et al.
  • 1Laboratoire des Sciences du Climat et de l’Environnement (LSCE), IPSL, CEA/CNRS/UVSQ, Gif sur Yvette, France
  • 2Laboratoire de Météorologie Dynamique, IPSL, Sorbonne Université/CNRS, Paris, France
  • 3Institut Pierre–Simon Laplace, CNRS/Sorbonne Université, Paris, France
  • 4Department of Meteorology, University of Reading, Reading, RG6 6BB, UK

Abstract. The impact of diffuse radiation on photosynthesis has been widely documented in field measurements. This impact may have evolved over time during the last century due to changes in cloudiness, increased anthropogenic aerosol loads over polluted regions, and to sporadic volcanic eruptions curtaining the stratosphere with sulfate aerosols. The effect of those changes in diffuse light on large-scale photosynthesis (GPP) are difficult to quantify, and land surface models have been designed to simulate them. Investigating how anthropogenic aerosols have impacted GPP through diffuse light in those models requires carefully designed factorial simulations and a reconstruction of background diffuse light levels during the pre-industrial period. Currently, it remains poorly understood how diffuse radiation reconstruction methods can affect GPP estimation and what fraction of GPP changes can be attributed to aerosols. In this study, we investigate different methods to reconstruct spatio-temporal distribution of the fraction of diffuse radiation (Fdf) under pre-industrial aerosol emission conditions using a land surface model with a two-stream canopy light transmission scheme that resolves diffuse light effects on photosynthesis in a multi-layered canopy, ORCHIDEE_DF. We show that using a climatologically-averaged monthly Fdf, as has been done by earlier studies, can bias the global GPP by up to 13 Pg C yr−1 because this reconstruction method dampens the variability of Fdf and produces Fdf that is inconsistent with short-wave incoming surface radiation. In order to correctly simulate pre-industrial GPP modulated by diffuse light, we thus recommend that the Fdf forcing field should be calculated consistently with synoptic, monthly and inter-annual aerosol and cloud variability for pre-industrial years. In the absence of aerosol and cloud data, alternative reconstructions need to retain the full variability in Fdf. Our results highlight the importance of keeping consistent Fdf and radiation for land surface models in future experimental designs that seek to investigate the impacts of diffuse radiation on GPP and other carbon fluxes.

Yuan Zhang et al.

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Yuan Zhang et al.

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Short summary
We investigated different methods to reconstruct spatio-temporal distribution of the fraction of diffuse radiation (Fdf) to qualtify the aerosol impacts on GPP using ORCHIDEE_DF land surface model. We find that climatologically-averaging methods which dampens the variability of Fdf can cause significant bias in the modeled diffuse radiation impacts on GPP. Better methods to do the reconstruction of Fdf are recommended.
We investigated different methods to reconstruct spatio-temporal distribution of the fraction of...
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