Assessment of climate mitigation potential of French grasslands using the land surface model ORCHIDEE-GM

There is now growing awareness that agricultural land use impacts climate not only through its GHG budget, but also through albedo-mediated changes of the surface energy budget. For instance, grasslands have higher surface albedo (i.e. more incoming solar radiation is reflected instead of being adsorbed and transferred into heat) than forage crops especially during the fallow period.

The project ALBAATRE-Systèmes focuses on reducing the climate impact of forage systems by increasing the share of grassland and by adapting land management practices to increase surface albedo. For this, extensive experimental data is collected from a network of experimental farms from IDELE across France as well as at ICOS flux tower sites. At the same time a modelling framework is being developed to upscale the experimental data at the scale of France. For this task, we use the land surface model ORCHIDEE-GM (Chang et al., 2013), which represents a branch of the global land surface model ORCHIDEE (Krinner et al., 2005) that incorporates main features of the grassland management model PaSim (Riedo et al., 1998). This model is used to study the impact on production and climate of grasslands management such as grazing, fertilization and cutting. At present, however, it has a very simplistic surface albedo description.

Therefore, this study intends to improve albedo formalisms in ORCHIDEE-GM v3.2 in order to better take into account the seasonal and structural changes of different grassland types in France. To evaluate the model, we will use the in-situ data collected over several years at the IDELE farms and at the ICOS grassland flux towers sites.

The meteorological and flux data from ICOS sites were used as input and to calibrate ORCHIDEE. The reflectance of vegetation is now described across the short wave spectrum (400 nm to 2500 nm) as a function of leaf area index, average leaf angle, leaf water content, and pigment concentration. First results show that the new albedo description has a better correlation with the observed data than with the original one but still needs to be investigated further.

This model development will allow us to better account for the albedo changes that happen in response to meteorologic conditions and management practices, thus better quantifying the mitigation potential of French grasslands (forage and natural). Moreover, future simulations will help to adapt management practices and to recommend specific grass species that have a high albedo and/or resilience to heat and drought stress, increasing both the climate change adaptation and mitigation potentials of the French forage systems.