poster

The present generation of land surface models have difficulties in reproducing consistently the energy balances that are observed in field studies (Pitman et al., 2009; Jimenez et al., 2011; de Noblet-Ducoudré et al., 2011). This is significant because land management, as well as affecting the sequestration of atmospheric CO2, may also have unintended effects on the energy budget, and there is a need for these effects to closely investigated and quantified. The most detailed simulations of the surface layer energy budget are detailed iterative multi-layer canopy models, such as Ogeé et al. (2003), which are linked to specific measurement sites and do not interact with the atmosphere. In this current project, we aim to create a model that will implement the insights obtained in those previous studies and improve upon the present ORCHIDEE parameterisation, but will run stably and efficiently when coupled to an atmospheric model. This work involves a replacement of the existing allocation of 14 different types of vegetation within each surface tile (the 'Plant Functional Types') by a more granular scheme that can be modified to reflect changes in attributes such as vegetation density, leaf type, distribution (clumping factors), age and height of vegetation within the surface tile. It involves the implementation of more than one canopy vegetation layer to simulate the effects of scalar gradients within the canopy for determining, more accurately, the net sensible and latent heat fluxes that are passed to the atmosphere. The model includes representation of characteristics such as in-canopy transport, coupling with sensible heat flux from the soil, a multilayer radiation budget and stomatal resistance, and interaction with the bare soil flux within the canopy space (and also with snow pack). We present how the implicit coupling approach of Polcher et al. (1998) and Best et al. (2004) is extended to a multilayer scenario.