| 7 | | Aerosol and cloud-induced changes in diffuse light have important impacts on the global land carbon cycle by changing light distribution and photosynthesis in vegetation canopies. However, this effect remains poorly represented in current land surface models. Here we add a light partitioning module and a new canopy light transmission module to the ORCHIDEE land surface model (trunk version, v5453) and use the revised model, ORCHIDEE_DF, to estimate the fraction of diffuse light and its effect on gross primary production (GPP) in a multi-layer canopy. We evaluate the new parameterizations using flux observations from 159 eddy covariance sites over the globe. Our results show that compared to the original model, ORCHIDEE_DF improves the GPP simulation under sunny conditions and captures the observed higher photosynthesis under cloudier conditions in most plant functional types (PFTs). Our results also indicate that the larger GPP under cloudy conditions compared to sunny conditions is mainly driven by increased diffuse light in the morning and in the afternoon, and by decreased VPD and air temperature at midday. The observations show strongest positive effects of diffuse light on photosynthesis are found in the range 5-20 °C and VPD<1 kPa. This effect is found to decrease when VPD becomes too large, or temperature falls outside that range likely because of increasing stomatal resistance to leaf CO2 uptake. ORCHIDEE_DF underestimates the diffuse light effect at low temperature in all PFTs and overestimates this effect at high temperature and high VPD in grasslands and croplands. The new model has the potential to better investigate the impact of large-scale aerosol changes on the terrestrial carbon budget, both in the historical period and in the context of future air quality policies and/or climate engineering. |
| | 7 | 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 PgC 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. |
