Periodic Reporting for period 1 - DUST-GLASS (Improving global dust prediction and monitoring through data assimilation of satellite-based dust aerosol optical depth)
Reporting period: 2017-05-01 to 2019-04-30
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.
Based on MODIS DOD, the regime of dust loads is described through the reproduction of annual (Figure 1) and seasonal (Figure 2) climatological global maps as well as by analyzing the interannual and intra-annual variation of DOD at planetary, hemispherical and regional level. Moreover, the derived DOD has been compared against CALIOP and MERRA-2 DODs showing a satisfactory level of agreement, despite the different techniques applied for the quantification of mineral particles’ amount. Likewise, the MODIS-DOD is highly consistent with AERONET observations, which have been treated appropriately in order to minimize, as much as possible, the “contamination” of other aerosol types (Figure 3).
At the second phase of DUST-GLASS, the developed DOD dataset is utilized in the DA scheme of the NMMB-MONARCH model, operating at the Barcelona Supercomputing Center (BSC). The data assimilation scheme is the Local Ensemble Transform Kalman filter (LETKF), an ensemble-based technique using flow-dependent model error amplitudes and structures which evolve during forecast. A “prognostic” uncertainty model is constructed for the estimation of DOD error, which is expressed by the MODIS-AERONET absolute DOD departures, multiplied with the geometric air mass factor, as a function of MODIS DOD.
The implementation of the ensemble forecast for NMMB-MONARCH is relied on 12 members, generated by applying multi-parameters, multi-physics and multi-meteorological initial and boundary conditions perturbations. High resolution numerical simulations (0.1° x 0.1°) have been performed for two experiments consisting of an ensemble first-guess (FG), and an ensemble analysis (AN), where a first-guess is an analysis-initialized forecast. The domain of interest covers the North Africa, the Middle East and Europe and the simulation period spans from 1st Jan 2012 to 31st Jan 2012, with a spin-up run (without assimilation) for one month (December 2011). In Figure 4, are illustrated the geographical distributions of DOD based on the FG (upper panel) and AN (middle panel) runs while in the bottom panel are depicted the increments (AN-FG). For the assessment of the potential positive impact of DA on short-term (24 hours) dust forecasts, the FG and AN DODs have been compared against coarse AODs obtained by AERONET stations. Overall, the representation of dust fields is improved when the MODIS DOD observations are assimilated in the NMMB-MONARCH model (Figure 5).
Besides the research activities of DUST-GLASS, the developed DOD product has been utilized in the FINDING (“ForecastINg Dust Impact on solar eNergy in EGypt”) project while it will be exploited in the DustClim project (https://bit.ly/2Kj7zBE) which focus on the production of a dust regional model reanalysis for North Africa, Middle East and Europe and the development of dust-related services tailored to specific socio-economic sectors. During the project period, the obtained findings have been presented (7 announcements) at international conferences/workshops while the preparation of two scientific manuscripts (i.e. global dust climatology, updated results for DA by performing numerical simulations for a full year cycle) is in progress. Finally, in order to enhance the dissemination and exploitation actions, the global DOD dataset will be included in the dust observations inventory developed in the framework of the inDust (“International Network to Encourage the Use of Monitoring and Forecasting Dust Products”) COST Action (https://cost-indust.eu/).