Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Incorporation of mineralogical composition into models of the radiative properties of mineral aerosol from UV to IR wavelengths
This map shows the geographic impact of I. N. Sokolik's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by I. N. Sokolik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites I. N. Sokolik more than expected).
This network shows the impact of papers produced by I. N. Sokolik. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by I. N. Sokolik. The network helps show where I. N. Sokolik may publish in the future.
Co-authorship network of co-authors of I. N. Sokolik
This figure shows the co-authorship network connecting the top 25 collaborators of I. N. Sokolik.
A scholar is included among the top collaborators of I. N. Sokolik based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with I. N. Sokolik. I. N. Sokolik is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Karydis, Vlassis A., Prashant Kumar, Donifan Barahona, et al.. (2010). On the effect of insoluble dust particles on global CCN and droplet number. AGU Fall Meeting Abstracts. 2010.3 indexed citations
Kurosaki, Yasunori, M. Shinoda, I. N. Sokolik, & Masato Mikami. (2009). Inter-annual variation of threshold wind speed for dust emission in Mongolia. EGUGA. 10326.1 indexed citations
11.
Prados, A. I., et al.. (2007). Assessing U.S Air Quality Using CALIPSO and MODIS Data via Giovanni. AGU Fall Meeting Abstracts. 2007.1 indexed citations
12.
Kurosaki, Yasunori, I. N. Sokolik, & V. N. Razuvaev. (2007). Analyses of Ground-based and Satellite Observations for Developing a Dust Climatology in Central and East Asia. AGUFM. 2007.
13.
Groisman, Pavel, I. N. Sokolik, Kathy Hibbard, Guy Brasseur, & John Katzenberger. (2007). Northern Eurasia in the global Earth system. Eos. 88(46). 487–487.2 indexed citations
14.
Sokolik, I. N., Robert E. Dickinson, & Yongjiu Dai. (2006). Impact of Atmospheric Mineral Dust on the Surface Energy Balance and PAR in the NEESPI Study Domain. AGU Fall Meeting Abstracts. 2006.
15.
Darmenov, Anton & I. N. Sokolik. (2004). Testing MODIS Dust Detection Capabilities Over the Ocean Using Visible and IR Channels. AGUSM. 2004.1 indexed citations
16.
Lafon, Sandra, Jean‐Louis Rajot, I. N. Sokolik, et al.. (2004). Comprehensive Characterization of Size-resolved Composition and Morphology of Mineral Dust Particles for Radiative Forcing Studies. AGU Fall Meeting Abstracts. 2004.1 indexed citations
17.
Калашникова, О. В., Ralph A. Kahn, & I. N. Sokolik. (2003). Retrieving mineral dust composition, size and shape (CSS) properties from multi-angle remote sensing observations.. AGUFM. 2003.
18.
Sokolik, I. N., et al.. (2003). New Techniques For Predicting Optical Properties Of Nonspherical Multicomponent Aerosols Using Single Particle Measurements. AGU Fall Meeting Abstracts. 2003.1 indexed citations
19.
Sokolik, I. N., et al.. (2002). Integrated Analysis of Satellite and Ground-based Meteorological Observations of Asian Dust Outbreaks in Spring of 2001. AGUFM. 2002.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.