DUST-GLASS · Improving global dust prediction and monitoring through data assimilation of satellite-based dust aerosol optical depth

Improving global dust prediction and monitoring through data assimilation of satellite-based dust aerosol optical depth

Across the arid and semi-arid regions of the planet, massive amounts of desert dust aerosols (or mineral particles) are emitted in the atmosphere under the impact of winds. Among aerosol species, dust is the most abundant component, in terms of mass, contributing more than half to the global aerosol amount. Dust aerosols play a key role in several aspects of the Earth system, thus explaining the huge scientific efforts on the description of their spatiotemporal features and the investigation of the induced impacts on weather and climate, on marine and terrestrial ecosystems, on humans’ health and on several anthropogenic activities (transportation, agriculture, solar energy production). Given the scientific importance of dust in the Earth system as well as the numerous socioeconomic impacts, it is clearly reflected the imperative need for optimizing dust monitoring and forecasting. For this purpose, contemporary satellite observations, ground-based platforms and atmospheric-dust models have been employed. Considering the advantages and drawbacks of the above-mentioned approaches, the best practice is the synergistic implementation of all the available “tools” for dust research. Aligned to these daunting and demanding challenges in the relevant scientific field, the research activities of the DUST-GLASS project (Improving global dust prediction and monitoring through data assimilation of satellite-based dust aerosol optical depth) have been designed appropriately in order to fulfil and advance the methodologies for dust monitoring and forecasting. To realize, satellite observations obtained by passive and active remote sensors, reanalysis datasets and a sophisticated chemical weather prediction system, with focus on mineral dust, have been utilized. DUST-GLASS is composed by three key research objectives (ROs), spanning in a wide range of activities, including the development of a multi-year global dust optical depth (DOD) dataset, its integration in a data assimilation (DA) system suitable for global/regional dust simulations and the assessment of DA impact on dust forecasts.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз