Impact Of Grid Resolution In Meteorological Models On Dynamical Calculation Of Ammonia Emissions

Skjøth, C. ORCID: https://orcid.org/0000-0001-5992-9568, Werner, Malgorzata and Geels, C. (2014) Impact Of Grid Resolution In Meteorological Models On Dynamical Calculation Of Ammonia Emissions. In: ECLAIRE Open Science Conference: Integrating Impacts of Air Pollution and Climate Change on Ecosystems, 1st-2nd October 2014, Budapest, Hungary.

Abstract

In the ÉCLAIRE project a central strategy is related to improving the simulations of ammonia emissions. Fixed emission factors and fixed temporal profiles are replaced with a dynamical approach that rely on a) weather, b) vegetation status c) farming practice d) activity status and e) feedback processes between chemistry and the vegetation. A central element in this strategy is a direct coupling between weather/climate models and the dynamical calculation of these ammonia emissions using a process based approach. This process based approach relies on an accurate description of both the weather (short term) and climate (long term). However, weather and climate models are grid based models that also include a number of parameterizations that describe the processes that cannot be fully resolved within a model. This will cause spatial and temporal uncertainty on both climate and weather in the meteorological output from the models. This uncertainty will have a cascade of effects on the calculation of ammonia emissions and must be quantified. In this study, we will quantify the spatial uncertainty on calculated ammonia emissions by using meteorological results from the WRF model. We use results from a nested setup with three different spatial resolutions (36km, 12km and 4km) to simulate the dynamical calculation of ammonia emissions during spring from several different agricultural sectors. The study area covers the United Kingdom and the results show both short term effects and long term effects on weather and climate due to the grid resolution. This effect on meteorology has subsequently a cascade of effects on different parameterisations that impacts the calculations of ammonia emissions: timing as well as amount. The study shows that the spatial uncertainty is particularly pronounced near coastal or mountainous regions. The meteorological model and its spatial representativity over the study domain must therefore be considered, when ammonia emissions are dynamically calculated for air quality studies.

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