Investigation of Halley's Comet dust size distribution by Vega-2 interplanetary station visual spectra analysis

Author(s):  
Penka Stoeva ◽  
Rolf Werner ◽  
Veneta Guineva ◽  
Stoyanka Staykova
2017 ◽  
Vol 43 (2) ◽  
pp. 212-217
Author(s):  
Dong-Ning Gao ◽  
Yang Yang ◽  
Qiang Yan ◽  
Xiao-Yun Wang ◽  
Wen-Shan Duan

2019 ◽  
Author(s):  
Elena Baglaeva ◽  
Alexander Buevich ◽  
Alexander Sergeev ◽  
Andrey Shichkin ◽  
Irina Subbotina ◽  
...  

2009 ◽  
Vol 52 (3) ◽  
pp. 517-522
Author(s):  
Wei Ju-Na ◽  
Shi Yu-Ren ◽  
He Guang-Jun ◽  
Jiang Xin ◽  
Duan Wen-Shan ◽  
...  

1991 ◽  
Vol 126 ◽  
pp. 221-224
Author(s):  
I. Konno ◽  
W.F. Huebner

AbstractWe developed a 1-D hydrodynamic model of dusty gas flow with dust fragmentation in a cometary atmosphere and performed calculations for a dust-size distribution with radiia =10−4— 10 cm and densities variable with dust size. A comparison was made with Giotto observations of dust jet intensities within 100 km of the nucleus of Comet Halley. We found that dust fragmentation cannot be solely responsible for the flattening of the dust intensity near the nucleus with respect to the 1/R law. We conclude that a combination of geometric effects and grain fragmentation may explain the observed intensity profiles.


2020 ◽  
Author(s):  
Michail Mytilinaios ◽  
Lucia Mona ◽  
Francesca Barnaba ◽  
Sergio Ciamprone ◽  
Serena Trippetta ◽  
...  

<p>An advanced dust reanalysis with high spatial (at 10km x 10km) and temporal resolution is produced in the framework of DustClim project (Dust Storms Assessment for the development of user-oriented Climate Services in Northern Africa, Middle East and Europe) [1], aiming to provide reliable information on dust storms current conditions and predictions, focusing on the dust impacts on various socio-economic sectors.</p><p>This regional reanalysis is based on the assimilation of dust-related satellite observations from MODIS instrument [2], in the Multiscale Online Nonhydrostatic Atmosphere Chemistry model (NMMB-MONARCH) [3], over the region of Northern Africa, Middle East and Europe. The reanalysis is now available for a seven-year period (2011-2016) providing the following dust products: Columnar and surface concentration, distributed in 8 dust particle size bins, with effective radius ranging from 0,15μm to 7,1μm, dust load, dry and wet dust deposition, dust optical depth (DOD) and coarse dust optical depth (radius>1μm) at 550nm and profiles of dust extinction coefficient at 550nm.</p><p>A thorough evaluation of the reanalysis is in progress to assess the quality and uncertainty of the dust simulations, using dust-filtered products, retrieved from different measurement techniques, both from in-situ and remote sensing observations. The datasets considered for the DustClim reanalysis evaluation, provide observations of variables that are included in the model simulations. The DOD is provided by AERONET network [4] and by IASI [5], POLDER [6], MISR [7] and MODIS space-borne sensors; Dust extinction profiles are provided by ACTRIS/EARLINET network [8] and CALIPSO/LIVAS dataset [9]; Dust PM10 surface concentrations derived from INDAAF/SDT [10] network and estimated from PM10 measurements [11] performed within EEA/EIONET [12] network; Dust deposition measurements collected by the INDAAF/SDT and the CARAGA/DEMO [13] networks; Dust size distribution from in situ observations (ground-based and airborne); And column-averaged dust size distribution at selected stations from the AERONET network.</p><p>In this work, we present the results of the model evaluation for the year 2012. The first evaluation results will focus on dust extinction coefficient profiles from EARLINET and LIVAS, on DOD using AERONET, MISR and MODIS datasets, and on dust PM10 concentration from INDAAF/SDT network. Moreover, a DOD climatology covering the whole reanalysis period (2011-2016) will be compared with the results obtained from AERONET network.</p><p> </p><p>References</p><p>[1] https://sds-was.aemet.es/projects-research/dustclim</p><p>[2] https://modis.gsfc.nasa.gov/</p><p>[3] Di Tomaso et al., <em>Geosci. Model Dev.</em>, <strong>10</strong>, 1107-1129, doi:10.5194/gmd-10-1107-2017., 2017.</p><p>[4] https://aeronet.gsfc.nasa.gov/</p><p>[5] Cuesta et al., <em>J. Geophys. Res.</em>, <strong>120</strong>, 7099-7127, 2015.</p><p>[6] http://www.icare.univ-lille1.fr/parasol/overview/</p><p>[7] https://misr.jpl.nasa.gov/</p><p>[8] https://www.earlinet.org/</p><p>[9] Marinou et al., <em>Atmos. Chem. Phys.</em>, <strong>17</strong>, 5893–5919, https://doi.org/10.5194/acp-17-5893-2017, 2017.</p><p>[10] https://indaaf.obs-mip.fr/</p><p>[11] Barnaba et al., <em>Atmospheric environment</em>, <strong>161</strong>, 288-305, 2017.</p><p>[12] https://www.eionet.europa.eu/</p><p>[13] Laurent et al., <em>Atmos. Meas. Tech.</em>, <strong>8</strong>, 2801–2811, 2015.</p><p> </p><p> </p><p>Acknowledgement</p><p>DustClim project is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).</p>


Sign in / Sign up

Export Citation Format

Share Document