Data assimilation and numerical modelling of atmospheric composition

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Title: Data assimilation and numerical modelling of atmospheric composition
Author: Vira, Julius
Belongs to series: Finnish Meteorological Institute Contributions 130
ISSN: 0782-6117
ISBN: 978-952-336-012-9
Abstract: Atmospheric chemistry and transport models are used for a wide range of applications which include predicting dispersion of a hazardous pollutants, forecasting regional air quality, and modelling global distribution of aerosols and reactive gases. However, any such prediction is uncertain due to inaccuracies in input data, model parametrisations and lack of resolution. This thesis studies methods for integrating remote sensing and in-situ observations into atmospheric chemistry models with the aim of improving the predictions. Techniques of data assimilation, originally developed for numerical weather prediction, are evaluated for improving regional-scale predictions in two forecast experiments, one targeting the photochemical pollutants ozone (O3) and nitrogen dioxide (NO2), the other targeting sulphur dioxide (SO2). In both cases, assimilation of surface-based air quality monitoring data is found to initially improve the forecast when assessed on monitoring stations not used in assimilation. However, as the forecast length increased, the forecast converged towards the reference simulations where no data assimilation was used. The relaxation time was 6-12 hours for SO2 and NO2 and about 24 hours for O3. An alternative assimilation scheme was tested for SO2. In addition to the initial state of the forecast, the scheme adjusted the gridded emission fluxes based on the observations within the last 24 hours. The improvements due to adjustment of emissions were generally small but, where observed, the improvements persisted throughout the 48 hour forecast. The assimilation scheme was further adapted for estimating emission fluxes in volcanic eruptions. Assimilating retrievals of the Infrared Atmospheric Sounding Interferometer (IASI) instrument allowed reconstructing both the vertical and horizontal profile of SO2 emissions during the 2010 eruption of Eyjafjallaj¨okull in Iceland. As a novel feature, retrievals of plume height were assimilated in addition to the commonly used column density retrievals. The results for Eyjafjallaj¨okull show that the plume height retrievals provide a useful additional constraint in conditions where the vertical distribution would otherwise remain ambiguous. Finally, the thesis presents a rigorous description and evaluation of a numerical scheme for solving the advection equation. The scheme conserves tracer mass and non-negativity, and is therefore suitable for regional and global atmospheric chemistry models. The scheme is particularly adapted for handling discontinuous solutions; for smooth solutions, the scheme is nevertheless found to perform comparably to other state-of-art schemes used in atmospheric models.
Date: 2017-02
Subject: dispersion models
air quality
data assimilation
inverse modelling
numerical methods

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