Roberto San José

Sources and sinks of ammonia within an oilseed rape canopy.

Within-canopy profiles of ammonia (NH 3) and measurements of the canopy turbulence characteristics were used to calculate the vertical source/sink density profile of NH 3 and sensible heat in a mature oilseed rape (Brassica napus) canopy. For the analysis, the inverse Lagrangian technique (ILT) based on localized near-field theory was used. Turbulence was measured with a standard ultrasonic anemometer, which, although not ideal for in-canopy work, is estimated to lead to a parameterization of the normalized standard deviation of the vertical wind component .w=u/, which is 11% accurate for heights >0.16 m during the day. The NH3 profiles in the canopy consistently show largest concentrations at the ground caused by NH 3 release from decomposing litter leaves on the ground surface with values of up to 150 ng m 2 s 1 predicted by the ILT. The inverse Lagrangian source/sink analysis performs well for both sensible heat and NH3, although it proves to be sensitive to the choice of the source/sink layers and becomes uncertain at the ground. Despite the large estimated ground level emission (26 gN H 3-N ha 1 per day), the analysis indicates that for the runs considered all NH 3 is recaptured by the lowest 0.7 m of the 1.38 m tall canopy, and that the bi-directional net exchange with the atmosphere is governed by the top 0.5 m, leading to a net emission from the canopy of 12 g NH3-N ha 1 per day. Since measurements of apoplastic [NH4 C ] and pH indicate that no significant stomatal emission from foliage should have occurred, this suggests that the siliques were a further source of NH3.

Advanced Numerical Methods for Complex Environmental Models: Needs and Availability

The understanding of lakes physical dynamics is crucial to provide scientifically credible information foron lakes ecosystem management. We show how the combination of in-situ dataobservations, remote sensing observationsdata and three15 dimensional hydrodynamic (3D) numerical simulations is capable of deliveringresolving various spatio-temporal scales involved in lakes dynamics. This combination is achieved through data assimilation (DA) and uncertainty quantification. In this study, we presentdevelop a flexible framework forby incorporating DA into lakes three-dimensional3D hydrodynamic lake models. Using an Ensemble Kalman Filter, our approach accounts for model and observational uncertainties. We demonstrate the framework by assimilating in-situ and satellite remote sensing temperature data into a three-dimensional3Dl hydrodynamic 20 model of Lake Geneva. Results show that DA effectively improves model performance over a broad range of spatio-temporal scales and physical processes. Overall, temperature errors have been reduced by 54 %. With a localization scheme, an ensemble size of 20 members is found to be sufficient to derive covariance matrices leading to satisfactory results. The entire framework has been developed for the constraintswith a goal of near real-time operational systems and near real-time operations (e.g. integration into meteolakes.ch). 25

Implementation of energy fluxes in EULAG with a new 3D shadow model

Micro urban simulations require high detail information. In order to take into account the building morphology, we have used a computational fluid dynamics (CFD) model named EULAG (UCAR) driven by the Weather and Research Forecasting System (WRF) through boundary conditions. A new three-dimensional urban solar radiation model (SHAMO) has been developed by the authors. We present results of the simulation obtained by using a modified version of the EULAG model which includes an energy balance equation to obtain the urban atmosphere/canopy energy exchange with the new 3D shadow model. The radiation model is coupled with the heat transfer equations from urban canopy model (UCM). The data produced by the urban solar radiation model has been used in large scale numerical experiments to simulate turbulent fluxes for urban areas; in this contribution over Madrid (Spain) city. Results of the micro scale simulations and sensitivity analysis will be presented in this paper.

From top-down land use planning intelligence to bottom-up stakeholder engagement for smart cities - a case study: DECUMANUS service products

Intelligence delivered by earth observation (EO) satellites performs a vital role in supporting ICT enabled urban governance, and the creation of decision making tools delivering integrated urban planning. This paper reviews the DECUMANUS project experience, detailing the development of the EO derived tools, and evaluating the service products that facilitate the deployment of top-down expertise in land use planning. The central purpose of the paper is to assess the potential for use of these DECUMANUS high resolution EO images and data, also to support bottom-up participatory planning, promoting co-design. It is concluded: 1) EO derived images and associated data offer great opportunity to deliver top-down decision making tools, which combined with auxiliary data, including participatory sensing data, effectively support integrated urban planning; 2) EO derived images also offer substantial potential as communication tools, enabling citizens to make more informed and responsible choices and participate in co-designed urban planning.

Analysis of fire behaviour simulations over Spain with WRF-FIRE

Wildland fire spread and behaviour are complex phenomena owing to both the number of involved physico-chemical factors, and the non-linear relationship between variables. Spain is plagued by forest and brush fires every summer, when the extremely dry weather sets in along with high temperatures. The use of fire behaviour models requires the availability of high resolution environmental and fuel data; in the absence of real data, errors on the simulated fire spread can be compounded to affect the spatial and temporal accuracy of predicted data. The effect of input values on the accuracy of WRF-FIRE simulations was evaluated to assess the capabilities of the new system for wildland fire in accurately forecasting fire behaviour. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behaviour.

Comparison between different dynamical downscaling methods using WRF-Chem for urban applications: Madrid case study

The European Centre for Medium-Range Weather Forecasts is used to provide boundary conditions for the mesoscale model WRF-Chem that has been run over Europe with 23 km spatial resolution. We have used a full one-way nesting approach to produce simulations centred over the city of Madrid (Spain) with 4.6 km spatial resolution, 0.92 km spatial resolution and 0.184 km spatial resolution. In last level, we have run the CMAQ (full chemistry) model to produce chemical pollution data. This is called the control reference simulation. The simplified and faster downscaling procedure used in this experiment is the CALMET-CMAQL (linear chemistry) model. Both downscaling techniques are compared using meteorological and air pollution monitoring station. The comparison between both downscaling techniques shows that the CALMET-CMAQL model is much faster and computationally cheap; the results are good enough to consider this tool for climate purposes.

Climate Downscaling Processes Using WRF/Chem and CALMET Modelling Systems: Madrid Case Study

Downscaling techniques are very important to assure the robustness and credibility of climate modelling exercises. Regional climate simulations use boundary conditions and initial conditions from global climate and meteorological models. The regional climate simulations (WRF/chem model) have much higher spatial resolution and using nesting approaches can be used to derive climate indicators at urban level. Dynamical nesting approaches -- also known as dynamical downscaling procedures -- use a substantial amount of computer power, particularly for urban applications, other alternatives such as CALMET diagnostic model (for meteorological applications) and CMAQ model (with linear chemistry) produce results faster and can be used for climate applications with reasonable required computer power. In this contribution, we are using the European Centre for Medium-Range Weather Forecasts (ECMWF) model data sets to provide boundary conditions for the mesoscale model WRF/Chem (NOAA, US) that has been ran over Europe with 23 km spatial resolution and 33 vertical levels up to 50 hPa. We have used the full nesting approach defined into WRF model to produce simulations centered over the city of Madrid (Spain) with 4.6 km spatial resolution (nesting level 1, l1), 0.92 km spatial resolution (nesting level 2, l2) and 0.184 km spatial resolution (nesting level 3, l3). In l3, we have run the CMAQ (full chemistry) model (EPA, US) to produce chemical pollution data. We have applied both downscaling techniques over Madrid area using Retiro meteorological and air pollution monitoring station as observational station. The comparison between both downscaling techniques shows that CALMET-CMAQL (linear chemistry) model is much faster and the results are good enough (compared with other simulations results) to consider this tool, when the number of simulations for climate purposes is very high (due to many years and several climate scenarios) and the application of the WRF/chem model (dynamical downscaling) is prohibited computationally.

Operational short term health impact assessment of air pollution modelling system over Europe

The last decade, scientific studies have indicated an association between air pollution to which people are exposed and wide range of adverse health outcomes. We have developed a tool which is based on a model (MM5-CMAQ) running over Europe with 50 km spatial resolution, based on EMEP annual emissions, to produce a short-term forecast of the impact on health. In order to estimate the mortality change (forecasted for the next 24 hours) we have chosen a log-linear (Poisson) regression form to estimate the concentration-response function. The parameters involved in the C-R function have been estimated based on epidemiological studies, which have been published. Finally, we have derived the relationship between concentration change and mortality change from the C-R function which is the final health impact function.