SURFATM-NH3: a model combining the surface energy balance and bi-directional exchanges of ammonia applied at the field scale

Abstract

Abstract.A new biophysical model SURFATM-NH3, simulating the ammonia (NH 3 ) exchange between terrestrial ecosystems and the atmosphere is presented. SURFATM-NH3 consists of two coupled models: (i) an energy budget model and (ii) a pollutant exchange model, which distinguish the soil and plant exchange processes. The model describes the exchanges in terms of adsorption to leaf cuticles and bi-directional transport through leaf stomata and soil. The results of the model are compared with the flux measurements over grassland during the GRAMINAE Integrated Experiment at Braunschweig, Germany. The dataset of GRAMINAE allows the model to be tested in various meteorological and agronomic conditions: prior to cutting, after cutting and then after the application of mineral fertilizer. The whole comparison shows close agreement between model and measurements for energy budget and ammonia fluxes. The major controls on the ground and plant emission potential are the physicochemical parameters for liquid-gas exchanges which are integrated in the compensation points for live leaves, litter and the soil surface. Modelled fluxes are highly sensitive to soil and plant surface temperatures, highlighting the importance of accurate estimates of these terms. The model suggests that the net flux depends not only on the foliar (stomatal) compensation point but also that of leaf litter. SURFATM-NH3 represents a comprehensive approach to studying pollutant exchanges and its link with plant and soil functioning. It also provides a simplified generalised approach (SVAT model) applicable for atmospheric transport models.Correspondence to: E. Personne

Dry deposition of nitrogen compounds (NO<sub>2</sub>, HNO<sub>3</sub>, NH<sub>3</sub>), sulfur dioxide and ozone in west and central African ecosystems using the inferential method

“…Due to the lack of data for typical tropical savanna sites, we chose a range of lower-end values reported for grass or unfertilized ecosystems in the literature. Thus, we have chosen values of 100 (low scenario) and 200 (high scenario) for st (Spindler et al, 2001;Horvath et al, 2005;Trebs et al, 2006;Personne et al, 2009) and values of 200 (low scenario) and 360 (high scenario) for g (Massad et al, 2010;Zhang et al, 2010). Figure 3 presents the mean diurnal variation of X cp (NH 3 ) for a Sahelian site (Banizoumbou) and a wet Guinean savanna site (Lamto) in the dry season (January 2006).…”

Predicting and partitioning ozone fluxes to maize crops from sowing to harvest: the Surfatm-O<sub>3</sub> model

“…The Surfatm-O 3 model is a one dimensional soil-vegetationatmosphere-transfer model, elaborated upon the model described in Personne et al (2009), which includes (i) an energy budget model accounting for the latent (LE) and sensible (H ) heat fluxes and (ii) a pollutant exchange model simulating ozone fluxes between the surface and the atmosphere. It includes one vegetation layer and one soil compartment.…”

“…The energy balance model, its input parameters and the transfer resistances (aerodynamic resistance (R a ), in-canopy aerodynamic resistance (R ac ), leaf quasi-laminar boundary layer resistance (R bl ) and soil quasi-laminar boundary layer resistance (R bs )) are fully described in Personne et al (2009) and will not be detailed in the following. The resistive scheme for O 3 is shown in Fig.…”

Intercomparison and assessment of turbulent and physiological exchange parameters of grassland

“…However, the accuracy with which R n can be measured is important for the interpretation of the energy balance closure at this site. In addition, R n was needed to drive some of the numerical models, which incorporated their own heat balance calculation (Personne et al, 2009). The CEH and FRI radiometers in particular showed a very tight relationship, while the INRA instrument shows some more variability.…”

“…to describe how the measurements are used to derive a robust "consensus" micrometeorological datasets, with error estimates and data quality flags, which is used in the companion papers for the calculation of gradient fluxes and to drive SVAT models for reactive trace gases (Burkhardt et al, 2009;Loubet et al, 2009;Mészáros et al, 2009;Milford et al, 2009;Personne et al, 2009;Sutton et al, 2009a, b).…”