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8 results for “Dust flux”
The data used for "Exploring how differences in dust particle size distribution and complex refractive indices affect dust direct radiative fluxes using the CAS-FGOALS-SPRINTARS global climate model"
<p>These data are used for " Exploring how differences in dust particle size distribution (PSD) and complex refractive indices (CRI) affect direct radiative effect (DRE) using the CAS-FGOALS-SPRINTARS global climate model ". </p> <p>(1) AS83+OPAC: The control experiment, dust PSD is the original AS83, and the generic CRI is from OPAC. </p> <p>(2) BFT22+OPAC: Same as the control experiment, but the PSD is updated to use BFT22.</p> <p>(3) BFT22+DB: Same as the experiment BFT22+OPAC, but the generic OPAC CRI is replaced by nine regionally dependent DB CRIs.</p> <p>(4) BFT22+DB strong abs: Same as the experiment BFT22+DB, but the generic CRI consists of 10% percentile real and 90% percentile imaginary parts and no regional dependencies.</p> <p>(5) BFT22+DB weak abs: Same as the experiment BFT22+DB, but the generic CRI consists of 90% percentile real and 10% percentile imaginary parts and no regional dependencies.</p> <p>All experiments mentioned above are run for 5 years (2010-2014). The annual average simulation results are stored here.</p> <p><strong>Note:</strong> AS83 represents the dust PSD scheme from d'Almeida and Schütz. (1983). BFT22 represents the new dust PSD developed by Meng et al. (2022) based on the improved brittle fragmentation theory. OPAC: the Optical Properties for Aerosols and Clouds dataset, DB: the CRIs from Di Biagio et al. (2017, 2019).</p> <p><strong>References</strong></p> <p>d'Almeida, G. A., & Schütz, L. (1983). Number, Mass and Volume Distributions of Mineral Aerosol and Soils of the Sahara. <em>Journal of Applied Meteorology and Climatology</em>,<em> 22</em>(2), 233-243. https://doi.org/https://doi.org/10.1175/1520-0450(1983)022<0233:NMAVDO>2.0.CO;2</p> <p>Di Biagio, C., Formenti, P., Balkanski, Y., Caponi, L., Cazaunau, M., Pangui, E., et al. (2019). Complex refractive indices and single-scattering albedo of global dust aerosols in the shortwave spectrum and relationship to size and iron content. <em>Atmospheric Chemistry and Physics</em>,<em> 19</em>(24), 15503-15531. https://doi.org/10.5194/acp-19-15503-2019</p> <p>Di Biagio, C., Formenti, P., Balkanski, Y., Caponi, L., Cazaunau, M., Pangui, E., et al. (2017). Global scale variability of the mineral dust long-wave refractive index: a new dataset of in situ measurements for climate modeling and remote sensing. <em>Atmospheric Chemistry and Physics</em>,<em> 17</em>(3), 1901-1929. https://doi.org/10.5194/acp-17-1901-2017</p> <p>Meng, J., Huang, Y., Leung, D. M., Li, L., Adebiyi, A. A., Ryder, C. L., et al. (2022). Improved Parameterization for the Size Distribution of Emitted Dust Aerosols Reduces Model Underestimation of Super Coarse Dust. Geophysical Research Letters, 49(8), e2021GL097287, https://doi.org/https://doi.org/10.1029/2021GL097287</p>
Orbital-controlled mid-latitude North Pacific dust flux during the late Quaternary
<p>Airborne mineral dust is sensitive to climatic changes, but its response to orbital forcing is still not fully understood. Here, we present a reconstruction of dust input to the Subarctic Pacific Ocean covering the past 190 kyr. The dust composition record is indicative of source moisture conditions, which are dominated by precessional variations. In contrast, the dust flux in marine sediments is dominated by obliquity variations, and display an out-of-phase relationship with a dust record from the mid latitude North Pacific Ocean. Climate model simulations suggest a precessional forcing likely affected the aridity and extent of the dust source regions. Meanwhile, the obliquity variations can be explained by meridional shifts in the North Pacific westerly jet, driven by changes in the meridional atmospheric temperature gradient. Our findings suggest that North Pacific dust input were primarily modulated by orbital-controlled source aridity and westerly during the late Quaternary.</p>
Data presented in Dupont et al. 2024 "Impact of dust source patchiness on the existence of a constant dust flux layer during aeolian erosion events"
<p>Meteorological and dust data used in Dupont et al. 2024. Data are based on measurements recorded above two erosive surfaces from two very different desert regions, one at a high-latitude location in Iceland and the other at a low-latitude location in Jordan. The Iceland campaign was co-organized by two projects: FRAGMENT (FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe) and HiLDA (Iceland as a model for high-latitude dust sources – a combined experimental and <br>modeling approach for characterization of dust emission and transport processes); and the Jordan campaign (J-WADI: Jordan Wind erosion And Dust Investigation) was co-organized by the FRAGMENT and Helmholtz Young Investigator Group ``A big unknown in the climate impact of atmospheric aerosol: Mineral soil dust'' projects.</p>
Influence of Dust Particles on Spatial Distributions of Particles and Fluxes in Positive Column of Glow Discharge.
<p><strong>Figures obtained from numerical simulation and discribe the influence of dust particles on spatial distributions of particles and fluxes in positive column of glow discharge. Table contain a list of reactions used in model. Dataset will be published in the article "Influence of Dust Particles on Spatial Distributions of Particles and Fluxes in Positive Column of Glow Discharge" </strong>C. Yuan, R. Tian, D. V. Bogdanov, E. A. Bogdanov, A. A. Kudryavtsev and Z. Zhou</p>
The extraterrestrial dust flux: size distribution and mass contribution estimates inferred from the Transantarctic Mountain (TAM) micrometeorite collection
<p>This study explores the long-duration (0.8-2.3Ma), time-averaged micrometeorite flux (mass and size distribution) reaching Earth, as recorded by the Transantarctic Mountain (TAM) micrometeorite collection. We investigate a single sediment trap (TAM65), performing an exhaustive recovery and characterization effort and identifying 1643 micrometeorites (between 100-2000μm). Approximately 7% of particles are unmelted or scoriaceous, of which 75% are fine-grained. Among cosmic spherules, 95.6% are silicate-dominated S-types, and further subdivided into porphyritic (16.9%), barred olivine (19.9%), cryptocrystalline (51.6%) and vitreous (7.5%). Our (rank)-size distribution is fit against a power law with a slope of -3.9 (R<sup>2</sup>=0.98) over the size range 200-700μm. However, the distribution is also bimodal, with peaks centered at ~145μm and ~250μm. Remarkably similar peak positions are observed in the Larkman Nunatak data. These observations suggest that the micrometeorite flux is composed of multiple dust sources with distinct size distributions. In terms of mass, the TAM65 trap contains 1.77g of extraterrestrial dust in 15kg of sediment (<5mm). Upscaling to a global annual estimate gives 1,555 (±753) t/yr – consistent with previous micrometeorite abundance estimates and almost identical to the previous South Pole Water Well flux estimate (~1,600 t/yr) and potentially suggesting minimal variation in the background cosmic dust flux over the Quaternary. The greatest uncertainty in our mass flux calculation is the accumulation window. A minimum age (0.8Ma) is robustly inferred from the presence of Australasian microtektites, while the upper age (~2.3Ma) is loosely constrained based on <sup>10</sup>Be exposure dating of glacial surfaces at Roberts Butte (6km from our sample site).</p>
The extraterrestrial dust flux: size distribution and mass contribution estimates inferred from the Transantarctic Mountain (TAM) micrometeorite collection
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STARDUST C/E/L DUST FLUX MONITOR INSTRUMENT-2-EDR-V1.0
Data collected by the Dust Flux Monitor Instrument (DFMI) of the Stardust satellite, taken during the early cruise phase of the mission. These data were determined by peer review to be of no scientific use.
STARDUST C/E/L DUST FLUX MONITOR INSTRUMENT-2-EDR-V1.0
Data collected by the Dust Flux Monitor Instrument (DFMI) of the Stardust satellite, taken during the early cruise phase of the mission. These data were determined by peer review to be of no scientific use.
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