Olga V. Kalashnikova

Global and Planetary Change · 2002–2025

A researcher in the Science corpus: 5 papers; trusts 4 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Global and Planetary Change — 21 citations into it; #2,652 of 10,225 by trust here, #4,701 by citations
• Atmospheric Science — 20 citations into it; #1,316 of 4,804 by trust here, #1,916 by citations
• Earth-Surface Processes — 12 citations into it

Whom Olga V. Kalashnikova trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. I. Sokolik
2. Oleg Dubovik
3. J. Heintzenberg
4. Ralph A. Kahn
5. Alexander Smirnov
6. Yoram J. Kaufman
7. Jean-Luc Deuze

Who trusts Olga V. Kalashnikova overall

1. Oleg Dubovik
2. Ralph A. Kahn
3. Christopher Cattrall
4. D. Winker
5. Alexander Sinyuk
6. Hans Moosmüller
7. Ping Yang
8. Tatyana Lapyonok
9. I. Sokolik
10. John A. Reagan

Papers from Olga V. Kalashnikova's perspective

Ordered by how strongly the researchers Olga V. Kalashnikova trusts endorse each paper. Same corpus, a different order for every researcher.

1. Accuracy assessments of aerosol optical properties retrieved from Aerosol Robotic Network (AERONET) Sun and sky radiance measurements
2. Importance of shapes and compositions of wind‐blown dust particles for remote sensing at solar wavelengths
3. Radiative heating rates and direct radiative forcing by mineral dust in cloudy atmospheric conditions
4. Estimate of the aerosol properties over the ocean with POLDER
5. Comparison of size and morphological measurements of coarse mode dust particles from Africa
6. Absorption of sunlight by dust as inferred from satellite and ground‐based remote sensing
7. Introduction to special section: Outstanding problems in quantifying the radiative impacts of mineral dust
8. Sensitivity of multiangle imaging to natural mixtures of aerosols over ocean
9. Modeling the radiative properties of nonspherical soil-derived mineral aerosols
10. Shape of atmospheric mineral particles collected in three Chinese arid‐regions

Their papers

• Development and Application of Self-Supervised Machine Learning for Smoke Plume and Active Fire Identification from the FIREX-AQ Datasets (2025)
• The Earth Surface Mineral Dust Source Investigation: An Earth Science Imaging Spectroscopy Mission (2020) — 148 citations
• Ability of multiangle remote sensing observations to identify and distinguish mineral dust types : Optical models and retrievals of optically thick plumes : Quantifying the radiative and biogeochemical impacts of mineral dust (2005) — 162 citations
• Modeling the radiative properties of nonspherical soil-derived mineral aerosols (2004) — 142 citations
• Importance of shapes and compositions of wind‐blown dust particles for remote sensing at solar wavelengths (2002) — 159 citations