ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set
<p>Monitoring and describing the spatiotemporal variability in dust aerosols is crucial for understanding their multiple effects, related feedbacks, and impacts within the Earth system. This study describes the development of the ModIs Dust AeroSol (MIDAS) data set. MIDAS provides columnar dai...
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doaj-4f2646e6717245e4851be0b0d8f2059e2021-01-15T08:58:04ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482021-01-011430933410.5194/amt-14-309-2021ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data setA. Gkikas0E. Proestakis1V. Amiridis2S. Kazadzis3S. Kazadzis4E. Di Tomaso5A. Tsekeri6E. Marinou7N. Hatzianastassiou8C. Pérez García-Pando9C. Pérez García-Pando10Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens, GreeceInstitute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens, GreeceInstitute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens, GreecePhysikalisch-Meteorologisches Observatorium Davos, World Radiation Center, Davos, SwitzerlandInstitute of Environmental Research and Sustainable Development, National Observatory of Athens, Athens, GreeceBarcelona Supercomputing Center, Barcelona, SpainInstitute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens, GreeceDeutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyLaboratory of Meteorology, Department of Physics, University of Ioannina, Ioannina, GreeceBarcelona Supercomputing Center, Barcelona, SpainICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Spain<p>Monitoring and describing the spatiotemporal variability in dust aerosols is crucial for understanding their multiple effects, related feedbacks, and impacts within the Earth system. This study describes the development of the ModIs Dust AeroSol (MIDAS) data set. MIDAS provides columnar daily dust optical depth (DOD) at 550 nm at a global scale and fine spatial resolution (0.1<span class="inline-formula"><sup>∘</sup></span> <span class="inline-formula">×</span> 0.1<span class="inline-formula"><sup>∘</sup></span>) over a 15-year period (2003–2017). This new data set combines quality filtered satellite aerosol optical depth (AOD) retrievals from MODIS-Aqua at swath level (Collection 6.1; Level 2), along with DOD-to-AOD ratios provided by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis to derive DOD on the MODIS native grid. The uncertainties of the MODIS AOD and MERRA-2 dust fraction, with respect to the AEronet RObotic NETwork (AERONET) and LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS), respectively, are taken into account for the estimation of the total DOD uncertainty. MERRA-2 dust fractions are in very good agreement with those of LIVAS across the dust belt in the tropical Atlantic Ocean and the Arabian Sea; the agreement degrades in North America and the Southern Hemisphere, where dust sources are smaller. MIDAS, MERRA-2, and LIVAS DODs strongly agree when it comes to annual and seasonal spatial patterns, with colocated global DOD averages of 0.033, 0.031, and 0.029, respectively; however, deviations in dust loading are evident and regionally dependent. Overall, MIDAS is well correlated with AERONET-derived DODs (<span class="inline-formula"><i>R</i>=0.89</span>) and only shows a small positive bias (0.004 or 2.7 %). Among the major dust areas of the planet, the highest <span class="inline-formula"><i>R</i></span> values (<span class="inline-formula"><i>></i>0.9</span>) are found at sites of North Africa, the Middle East, and Asia. MIDAS expands, complements, and upgrades the existing observational capabilities of dust aerosols, and it is suitable for dust climatological studies, model evaluation, and data assimilation.</p>https://amt.copernicus.org/articles/14/309/2021/amt-14-309-2021.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Gkikas E. Proestakis V. Amiridis S. Kazadzis S. Kazadzis E. Di Tomaso A. Tsekeri E. Marinou N. Hatzianastassiou C. Pérez García-Pando C. Pérez García-Pando |
spellingShingle |
A. Gkikas E. Proestakis V. Amiridis S. Kazadzis S. Kazadzis E. Di Tomaso A. Tsekeri E. Marinou N. Hatzianastassiou C. Pérez García-Pando C. Pérez García-Pando ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set Atmospheric Measurement Techniques |
author_facet |
A. Gkikas E. Proestakis V. Amiridis S. Kazadzis S. Kazadzis E. Di Tomaso A. Tsekeri E. Marinou N. Hatzianastassiou C. Pérez García-Pando C. Pérez García-Pando |
author_sort |
A. Gkikas |
title |
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set |
title_short |
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set |
title_full |
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set |
title_fullStr |
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set |
title_full_unstemmed |
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set |
title_sort |
modis dust aerosol (midas): a global fine-resolution dust optical depth data set |
publisher |
Copernicus Publications |
series |
Atmospheric Measurement Techniques |
issn |
1867-1381 1867-8548 |
publishDate |
2021-01-01 |
description |
<p>Monitoring and describing the spatiotemporal variability in dust aerosols is crucial for understanding their multiple effects, related feedbacks, and impacts within the Earth system. This study describes the development of the ModIs Dust AeroSol (MIDAS) data set. MIDAS provides columnar daily dust optical depth (DOD) at 550 nm at a global scale and fine spatial resolution (0.1<span class="inline-formula"><sup>∘</sup></span> <span class="inline-formula">×</span> 0.1<span class="inline-formula"><sup>∘</sup></span>) over a 15-year period (2003–2017). This new data set combines quality filtered satellite aerosol optical depth (AOD) retrievals from MODIS-Aqua at swath level (Collection 6.1; Level 2), along with DOD-to-AOD ratios provided by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis to derive DOD on the MODIS native grid. The uncertainties of the MODIS AOD and MERRA-2 dust fraction, with respect to the AEronet RObotic NETwork (AERONET) and LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS), respectively, are taken into account for the estimation of the total DOD uncertainty. MERRA-2 dust fractions are in very good agreement with those of LIVAS across the dust belt in the
tropical Atlantic Ocean and the Arabian Sea; the agreement degrades in North America and the Southern Hemisphere, where dust sources are smaller. MIDAS, MERRA-2, and LIVAS DODs strongly agree when it comes to annual and seasonal spatial patterns, with colocated global DOD averages of 0.033, 0.031, and 0.029, respectively; however, deviations in dust loading are evident and regionally dependent. Overall, MIDAS is well correlated with AERONET-derived DODs (<span class="inline-formula"><i>R</i>=0.89</span>) and only shows a small positive bias (0.004 or 2.7 %). Among the major dust areas of the planet, the highest <span class="inline-formula"><i>R</i></span> values (<span class="inline-formula"><i>></i>0.9</span>) are found at sites of North Africa, the Middle East, and Asia. MIDAS expands, complements, and upgrades the existing observational capabilities of dust aerosols, and it is suitable for dust climatological studies, model evaluation, and data assimilation.</p> |
url |
https://amt.copernicus.org/articles/14/309/2021/amt-14-309-2021.pdf |
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