Wenying Su

4.3k total citations · 2 hit papers
69 papers, 2.6k citations indexed

About

Wenying Su is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Wenying Su has authored 69 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Global and Planetary Change, 53 papers in Atmospheric Science and 5 papers in Oceanography. Recurrent topics in Wenying Su's work include Atmospheric aerosols and clouds (44 papers), Atmospheric Ozone and Climate (34 papers) and Atmospheric and Environmental Gas Dynamics (33 papers). Wenying Su is often cited by papers focused on Atmospheric aerosols and clouds (44 papers), Atmospheric Ozone and Climate (34 papers) and Atmospheric and Environmental Gas Dynamics (33 papers). Wenying Su collaborates with scholars based in United States, China and United Kingdom. Wenying Su's co-authors include Norman G. Loeb, Fred G. Rose, Hailan Wang, J. Corbett, Lusheng Liang, Seiji Kato, David R. Doelling, Zachary A. Eitzen, C. Mitrescu and Gregory L. Schuster and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Journal of Climate.

In The Last Decade

Wenying Su

62 papers receiving 2.6k citations

Hit Papers

Clouds and the Earth’s Radiant Energy System (CERES) Ener... 2017 2026 2020 2023 2017 2018 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wenying Su United States 23 2.3k 2.1k 229 180 119 69 2.6k
Takmeng Wong United States 21 2.5k 1.1× 2.2k 1.1× 296 1.3× 124 0.7× 103 0.9× 50 2.7k
D. Vane United States 14 3.1k 1.3× 3.2k 1.5× 119 0.5× 143 0.8× 121 1.0× 26 3.5k
Thomas P. Charlock United States 26 2.1k 0.9× 1.9k 0.9× 206 0.9× 117 0.7× 217 1.8× 76 2.4k
Kristopher M. Bedka United States 34 2.4k 1.0× 2.4k 1.2× 137 0.6× 216 1.2× 98 0.8× 86 2.9k
John M. Haynes United States 22 2.2k 1.0× 2.4k 1.1× 129 0.6× 62 0.3× 182 1.5× 41 2.8k
Bomin Sun United States 24 1.7k 0.7× 1.5k 0.7× 330 1.4× 112 0.6× 94 0.8× 39 2.1k
Hélène Chepfer France 37 4.4k 1.9× 4.4k 2.1× 150 0.7× 123 0.7× 121 1.0× 109 4.8k
Rémy Roca France 30 2.7k 1.2× 2.8k 1.3× 377 1.6× 104 0.6× 53 0.4× 93 3.2k
David A. Rutan United States 18 1.9k 0.8× 1.6k 0.8× 151 0.7× 88 0.5× 209 1.8× 57 2.0k
Yong Han United States 27 1.9k 0.8× 2.3k 1.1× 211 0.9× 504 2.8× 56 0.5× 106 2.6k

Countries citing papers authored by Wenying Su

Since Specialization
Citations

This map shows the geographic impact of Wenying Su'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 Wenying Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenying Su more than expected).

Fields of papers citing papers by Wenying Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wenying Su. 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 Wenying Su. The network helps show where Wenying Su may publish in the future.

Co-authorship network of co-authors of Wenying Su

This figure shows the co-authorship network connecting the top 25 collaborators of Wenying Su. A scholar is included among the top collaborators of Wenying Su 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 Wenying Su. Wenying Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Crimmins, Allison, Fredric Lipschultz, Kenneth E. Kunkel, et al.. (2025). Projections of future climate for U.S. national assessments: past, present, future. Climatic Change. 178(4). 84–84.
3.
Liang, Lusheng, Wenying Su, Sergio A. Sejas, Zachary A. Eitzen, & Norman G. Loeb. (2024). Next-generation radiance unfiltering process for the Clouds and the Earth's Radiant Energy System instrument. Atmospheric measurement techniques. 17(7). 2147–2163. 2 indexed citations
4.
Su, Wenying, Norman G. Loeb, Thomas H. Vonder Haar, et al.. (2021). Shortwave Radiance to Irradiance Conversion for Earth Radiation Budget Satellite Observations: A Review. Remote Sensing. 13(13). 2640–2640. 18 indexed citations
5.
Su, Wenying, Lusheng Liang, Gunnar Myhre, et al.. (2021). Understanding Top‐of‐Atmosphere Flux Bias in the AeroCom Phase III Models: A Clear‐Sky Perspective. Journal of Advances in Modeling Earth Systems. 13(9). 4 indexed citations
6.
Su, Wenying, Patrick Minnis, Lusheng Liang, et al.. (2020). Determining the daytime Earth radiative flux from National Institute of Standards and Technology Advanced Radiometer (NISTAR) measurements. Atmospheric measurement techniques. 13(2). 429–443. 21 indexed citations
7.
Yang, Yuekui, Kerry Meyer, G. Wind, et al.. (2019). Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation. Atmospheric measurement techniques. 12(3). 2019–2031. 34 indexed citations
8.
Kato, Seiji, Fred G. Rose, David A. Rutan, et al.. (2018). Surface Irradiances of Edition 4.0 Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Data Product. Journal of Climate. 31(11). 4501–4527. 334 indexed citations breakdown →
9.
Su, Wenying, Lusheng Liang, David R. Doelling, et al.. (2018). Determining the Shortwave Radiative Flux From Earth Polychromatic Imaging Camera. Journal of Geophysical Research Atmospheres. 123(20). 25 indexed citations
10.
Loeb, Norman G., David R. Doelling, Hailan Wang, et al.. (2017). Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product. Journal of Climate. 31(2). 895–918. 639 indexed citations breakdown →
11.
Wang, Hailan, Wenying Su, Norman G. Loeb, Deepthi Achuthavarier, & Siegfried D. Schubert. (2017). The role of DYNAMO in situ observations in improving NASA CERES‐like daily surface and atmospheric radiative flux estimates. Earth and Space Science. 4(4). 164–183. 1 indexed citations
13.
Loeb, Norman G., Wenying Su, & Seiji Kato. (2016). Understanding Climate Feedbacks and Sensitivity Using Observations of Earth’s Energy Budget. PubMed. 2(4). 170–178. 15 indexed citations
14.
Loeb, Norman G., Kory J. Priestley, Patrick Minnis, et al.. (2015). Towards a Seamless Global Long-Term Earth Radiation Budget Climate Data Record. 2015 AGU Fall Meeting. 2015. 1 indexed citations
15.
Corbett, J. & Wenying Su. (2015). Accounting for the effects of sastrugi in the CERES clear-sky Antarctic shortwave angular distribution models. Atmospheric measurement techniques. 8(8). 3163–3175. 15 indexed citations
16.
Su, Wenying, J. Corbett, Zachary A. Eitzen, & Lusheng Liang. (2015). Next-generation angular distribution models for top-of-atmosphere radiative flux calculation from CERES instruments: validation. Atmospheric measurement techniques. 8(8). 3297–3313. 95 indexed citations
17.
18.
Schuster, Gregory L., Mark Vaughan, David G. MacDonnell, et al.. (2012). Comparison of CALIPSO aerosol optical depth retrievals to AERONET measurements, and a climatology for the lidar ratio of dust. Atmospheric chemistry and physics. 12(16). 7431–7452. 195 indexed citations
19.
Su, Wenying. (2007). Colorimetric Characteristics for Retroreflector of Road Traffic.
20.
Su, Wenying. (2006). Retroreflection Summarize of Retro-reflective Sheeting for Traffic Signs.

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.

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