Footprint-weighted tile approach for a spruce forest and a nearby patchy clearing using the ACASA model

The ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) model, with a higher-order closure for tall vegetation, has already been successfully tested and validated for homogeneous spruce forests. The aim of this paper is to test the model using a footprint-weighted tile approach for a clearing with a heterogeneous structure of the underlying surface. The comparison with flux data shows a good agreement with a footprint-aggregated tile approach of the model. However, the results of a comparison with a tile approach on the basis of the mean land use classification of the clearing is not significantly different. It is assumed that the footprint model is not accurate enough to separate small-scale heterogeneities. All measured fluxes are corrected by forcing the energy balance closure of the test data either by maintaining the measured Bowen ratio or by the attribution of the residual depending on the fractions of sensible and latent heat flux to the buoyancy flux. The comparison with the model, in which the energy balance is closed, shows that the buoyancy correction for Bowen ratios > 1.5 better fits the measured data. For lower Bowen ratios, the correction probably lies between the two methods, but the amount of available data was too small to make a conclusion. With an assumption of similarity between water and carbon dioxide fluxes, no correction of the net ecosystem exchange is necessary for Bowen ratios > 1.5

Il Modello ACASA per la stima degli scambi di carbonio negli ecosistemi mediterranei

L’attività di ricerca finalizzata allo sviluppo e alla validazione di modellistica avanzata per la contabilizzazione del bilancio del carbonio nei sistemi agrari e forestali nasce da una intensa collaborazione con l’Università della California. In particolare è in fase di studio il modello ACASA (Advanced Canopy-Atmosphere-Soil Algorithm), che è attualmente uno dei modelli del tipo soil-vegetation-atmosphere transfer (SVAT) più sofisticati. ACASA contiene equazioni differenziali di terzo ordine per simulare i flussi di energia e materia nella canopy (10 strati atmosferici all’interno e 10 al di sopra), mentre il suolo è suddiviso in 15 strati. Una combinazione delle equazioni di Ball-Berry e Farquhar è utilizzata per stimare il flusso di CO2. Il modello considera gli effetti dello stress idrico sulla traspirazione e sull’assimilazione della vegetazione

Advanced-Canopy-Atmosphere-Soil Algorithm (ACASA model) for estimating mass and energy fluxes

There is a recognized need to improve land surface models that simulate mass and energy fluxes between terrestrial ecosystems and atmosphere. In particular, long-term land planning strategies at local and regional scales require better understanding of agricultural ecosystem capacity to exchange CO2 and water. One of the more elaborate models for flux modelling is the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) model (Pyles et al., 2000), which provides micro-scale and regional-scale fluxes. The ACASA model allows for characterization of energy and carbon fluxes. It is a higher-order closure model used to estimate fluxes and profiles of heat, water vapor, carbon and momentum within and above canopy using third-order closure equations. It also estimates turbulent profiles of velocity, temperature, humidity within and above canopy. The ACASA model estimates CO2 fluxes using a combination of Ball-Berry and Farquhar equations. In addition, the effects of water stress on stomata, transpiration and CO2 assimilation are considered. The model was mainly used over dense canopies (Pyles et al. 2000, 2003) in the past, so the aim of this work was to test the ACASA model over a sparse canopy for estimating mass and energy fluxes, comparing model output with field measurements taken over a vineyard located in Montalcino, Tuscany, Italy

Urban metabolism and climate change: a planning support system

Patterns of urban development influence flows of material and energy within urban settlements and exchanges with its surrounding. In recent years the quantitative estimation of the components of the so-called urban metabolism has increasingly attracted the attention of researchers from different fields. To contribute to this effort we developed a modelling framework for estimating the carbon exchanges together with sensible and latent heat fluxes and air temperature in relation to alternative land-use scenarios. The framework bundles three components: (i) a Cellular Automata model for the simulation of the urban land-use dynamics; (ii) a transportation model for estimating the variation of the transportation network load and (iii) the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) model tightly coupled with the mesoscale weather forecasting model WRF. We present and discuss the results of an example application on the City of Florence

Towards a planning decision support system for low-carbon urban development

The flows of carbon and energy produced by urbanized areas represent one of the aspects of urban sustainability that can have an important impact on climate change. For this reason, in recent years the quantitative estimation of the so-called urban metabolism components has increasingly attracted the attention of researchers from different fields. On the other hand, it has been well recognized that the structure and design of future urban development can significantly affect the flows of material and energy exchanged by an urban area with its surroundings. In this context, the paper discusses a software framework able to estimate the carbon exchanges accounting for alternative scenarios which can influence urban development. The modelling system is based on four main components: (i) a Cellular Automata model for the simulation of the urban land-use dynamics; (ii) a transportation model, able to estimate the variation of the transportation network load and (iii) the ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) model which was tightly coupled with the (iv) mesoscale weather model WRF for the estimation of the relevant urban metabolism components. An in-progress application to the city of Florence is presented and discussed

Impact of canopy representations on regional modeling of evapotranspiration using the WRF-ACASA coupled model

In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model, to investigate the impact of canopy representation on regional evapotranspiration. The WRF-ACASA model uses a multilayer structure to represent the canopy, consequently allowing microenvironmental variables such as leaf area index (LAI), air and canopy temperature, wind speed and humidity to vary both horizontally and vertically. The improvement in canopy representation and canopy-atmosphere interaction allow for more realistic simulation of evapotranspiration on both regional and local scales. The coupled WRF-ACASA model is compared with the widely used intermediate complexity Noah land surface model in WRF (WRF-Noah) for both potential (ETo) and actual evapotranspiration (ETa). Two LAI datasets (USGS and MODIS) are used to study the model responses to surface conditions. Model evaluations over a diverse surface stations from the CIMIS and AmeriFlux networks show that an increase surface representations increase the model accuracy in ETa more so than ETo. Overall, while the high complexity of WRF-ACASA increases the realism of plant physiological processes, the model sensitivity to surface representation in input data such as LAI also increases. Keywords: Land surface modeling; WRF; Canopy representation; Regional modeling; Reference evapotranspiration; Actual evapotranspirationNational Science Foundation (U.S.) (Award ATM-0619139 and EF-1137306