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dc.contributor.authorMiller, Steven
dc.coverage.spatialArabian Peninsula of Southwest Asia region
dc.coverage.temporal2016-08-03-2016-08-05
dc.date2019
dc.date.accessioned2019-08-13T22:38:13Z
dc.date.available2019-08-13T22:38:13Z
dc.identifier.urihttps://hdl.handle.net/10217/196351
dc.identifier.urihttp://dx.doi.org/10.25675/10217/196351
dc.descriptionSUPP_MOVIE_1_WRFCHEM_INTDUST.gif: Animated gif image displaying Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of column-integrated dust in units of grams per square-meter, scaled over values 0.1 to 3.4, over the Arabian Peninsula of Southwest Asia. A 97-frame animated sequence rendered at 30 min temporal resolution over the period 2016-08-03 0000 UTC to 2016-08-05 0000 UTC. SUPP_MOVIE_2_DEBRA_msg_s20160804_0000_e20160804_1000.gif:Animated gif image displaying Meteosat Second Generation-3 (Meteosat-8) satellite imagery of lofted dust over the Arabian Peninsula of Southwest Asia. A 39-frame animated sequence rendered at 15 min temporal resolution over the time period 2016-08-04 0000 UTC to 2016-08-04 1000 UTC. Lofted dust shown in yellow, using the Dynamic Enhancement Background Reduction Algorithm (DEBRA) of Miller et al., 2017: Miller, S. D., R. L. Bankert, J. E. Solbrig, J. M. Forsythe, and Y.-J. Noh, 2017: A Dynamic Enhancement with Background Reduction Algorithm: Overview and Application to Satellite-Based Dust Storm Detection. JGR-Atmospheres, 122(23), 12,938–12,959, doi.org/10.1002/2017JD027365. SUPP_MOVIE_3_WRFCHEM_TPW.gif:Animated gif image displaying Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of Total Precipitable Water (TPW) over the Arabian Peninsula of Southwest Asia. A 97-frame animated sequence rendered at 30 min temporal resolution over the time period 2016-08-03 0000 UTC to 2016-08-5 0000 UTC.
dc.descriptionThese supplemental files are referred to as S1, S2, and S3 in the associated Miller et al. (2019) paper.
dc.description.abstractLofted mineral dust over data-sparse regions presents considerable challenges to satellite-based remote sensing methods and numerical weather prediction alike. The Southwest Asia domain is replete with such examples, with its diverse array of dust sources, dust mineralogy, and meteorologically-driven lofting mechanisms on multiple spatial and temporal scales. A microcosm of these challenges occurred over 3-4 August 2016 when two dust plumes, one lofted within an inland dry air mass and another embedded within a moist air mass, met over the Southern Arabian Peninsula. Whereas conventional infrared-based techniques readily detected the dry air mass dust plume, they experienced marked difficulties in detecting the moist air mass dust plume, which only became apparent when visible reflectance revealed it crossing over an adjacent dark water background. In combining information from numerical modelling, multi-satellite/multi-sensor observations of lofted dust and moisture profiles, and idealized radiative transfer simulations, we develop a better understanding of the environmental controls of this event, characterizing the sensitivity of infrared-based dust detection to column water vapor, dust vertical extent, and dust optical properties. Differences in assumptions of dust complex refractive index translate to variations in the sign and magnitude of the split-window brightness temperature difference commonly used for detecting mineral dust. A multi-sensor technique for mitigating the radiative masking effects of water vapor via modulation of the split-window dust-detection threshold, predicated on idealized simulations tied to these driving factors, is proposed and demonstrated. The new technique, indexed to an independent description of the surface-to-500 hPa atmospheric column moisture, reveals parts of the missing dust plume embedded in the moist air mass, with best performance over land surfaces.
dc.description.sponsorshipOffice of Naval Research under grant N00014-16-1-2040
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofData - Colorado State University
dc.relation.isreferencedbyMiller, S. D., L. D. Grasso, Q. Bian, S. M. Kreidenweis, J. F. Dostalek, J. E. Solbrig, J. Bukowski, S. C. van den Heever, Y. Wang, X. Xu, J. Wang, A. L. Walker, T.-C. Wu, M. Zupanski, C. Chiu, and J. S. Reid, 2019: A Tale of Two Dust Storms: Analysis of a Complex Dust Event in the Middle East. Atmospheric Measurement Techniques, In press. https://doi.org/10.5194/amt-2019-82.
dc.titleDataset associated with "A Tale of Two Dust Storms: Analysis of a Complex Dust Event in the Middle East"
dc.typeDataset


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