Abstract
Abstract. Land surface models (LSMs) are pushing towards improved realism owing to an increasing number of observations at the local scale, constantly improving satellite data sets and the associated methodologies to best exploit such data, improved computing resources, and in response to the user community. As a part of the trend in LSM development, there have been ongoing efforts to improve the representation of the land surface processes in the interactions between the soil–biosphere–atmosphere (ISBA) LSM within the EXternalized SURFace (SURFEX) model platform. The force–restore approach in ISBA has been replaced in recent years by multi-layer explicit physically based options for sub-surface heat transfer, soil hydrological processes, and the composite snowpack. The representation of vegetation processes in SURFEX has also become much more sophisticated in recent years, including photosynthesis and respiration and biochemical processes. It became clear that the conceptual limits of the composite soil–vegetation scheme within ISBA had been reached and there was a need to explicitly separate the canopy vegetation from the soil surface. In response to this issue, a collaboration began in 2008 between the high-resolution limited area model (HIRLAM) consortium and Météo-France with the intention to develop an explicit representation of the vegetation in ISBA under the SURFEX platform. A new parameterization has been developed called the ISBA multi-energy balance (MEB) in order to address these issues. ISBA-MEB consists in a fully implicit numerical coupling between a multi-layer physically based snowpack model, a variable-layer soil scheme, an explicit litter layer, a bulk vegetation scheme, and the atmosphere. It also includes a feature that permits a coupling transition of the snowpack from the canopy air to the free atmosphere. It shares many of the routines and physics parameterizations with the standard version of ISBA. This paper is the first of two parts; in part one, the ISBA-MEB model equations, numerical schemes, and theoretical background are presented. In part two (Napoly et al., 2016), which is a separate companion paper, a local scale evaluation of the new scheme is presented along with a detailed description of the new forest litter scheme.
Highlights
Land surface models (LSMs) are based upon fundamental mathematical laws and physics applied within a theoretical framework
LSMs were originally implemented in numerical weather prediction (NWP) and global climate models (GCMs) in order to provide interactive lower boundary conditions for the atmospheric radiation and turbulence parameterization schemes over continental land surfaces
A growing number of state-of-the-art LSMs, which are used in coupled atmospheric models for operational numerical weather prediction (Ek et al, 2003; Boussetta et al, 2013), climate modeling (Oleson et al, 2010; Zhang et al, 2015), or both (Best et al, 2011; Masson et al, 2013), represent most or all of the following processes: photosynthesis and the associated carbon fluxes, multi-layer soil water and heat transfer, vegetation phenology and dynamics, sub-grid lateral water transfer, river routing, atmosphere–lake exchanges, snowpack dynamics, and near-surface urban meteorology
Summary
Land surface models (LSMs) are based upon fundamental mathematical laws and physics applied within a theoretical framework. Additional modifications were made to this scheme over the last decade to include soil freezing (Boone et al, 2000; Giard and Bazile, 2000), which improved hydrological processes (Mahfouf and Noilhan, 1996; Boone et al, 1999; Decharme and Douville, 2006) This scheme was based on the pioneering work of Deardorff (1977) and it has proven its value for coupled land–atmosphere research and applications since its inception. It is currently used for research within the mesoscale non-hydrostatic research model (Meso-NH) (Lafore et al, 1998) It is used within the operational high-resolution short-term numerical weather prediction at Météo-France within the limited area model AROME (Seity et al, 2011) and by HIRLAM countries within the ALADIN– HIRLAM system as the HARMONIE–AROME model configuration (Bengtsson et al, 2017). It is used for climate research within the global climate model (GCM) Action de Researche Petite Echelle Grande Echelle (ARPEGEclimat; Voldoire et al, 2013) and by HIRLAM countries within the ALADIN–HIRLAM system as HARMONIE– AROME and HARMONIE–ALARO Climate configurations (Lind et al, 2016)
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