U. S. Nair

6.0k total citations · 3 hit papers
76 papers, 4.1k citations indexed

About

U. S. Nair is a scholar working on Global and Planetary Change, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, U. S. Nair has authored 76 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Global and Planetary Change, 40 papers in Atmospheric Science and 11 papers in Environmental Engineering. Recurrent topics in U. S. Nair's work include Climate variability and models (30 papers), Atmospheric aerosols and clouds (20 papers) and Meteorological Phenomena and Simulations (20 papers). U. S. Nair is often cited by papers focused on Climate variability and models (30 papers), Atmospheric aerosols and clouds (20 papers) and Meteorological Phenomena and Simulations (20 papers). U. S. Nair collaborates with scholars based in United States, Australia and United Kingdom. U. S. Nair's co-authors include Roger A. Pielke, Ronald M. Welch, Robert O. Lawton, Dev Niyogi, Rezaul Mahmood, Souleymane Fall, Clive McAlpine, Adriana Beltrán‐Przekurat, Sundar A. Christopher and Aaron Kaulfus and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and Journal of Geophysical Research Atmospheres.

In The Last Decade

U. S. Nair

67 papers receiving 4.0k citations

Hit Papers

Climatic Impact of Tropical Lowland Deforestation on Near... 2001 2026 2009 2017 2001 2011 2013 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
U. S. Nair United States 25 2.6k 1.5k 742 515 406 76 4.1k
Xiaofeng Wang China 37 1.3k 0.5× 1.1k 0.7× 293 0.4× 635 1.2× 167 0.4× 204 5.9k
Ronald M. Welch United States 33 2.4k 0.9× 2.0k 1.3× 355 0.5× 433 0.8× 408 1.0× 128 4.1k
Dieter Wolf‐Gladrow Germany 48 1.6k 0.6× 1.7k 1.1× 524 0.7× 2.2k 4.3× 365 0.9× 135 8.8k
M. Sato Japan 28 5.1k 1.9× 4.6k 3.0× 588 0.8× 788 1.5× 352 0.9× 98 7.8k
Fang Li China 33 2.7k 1.0× 1.8k 1.2× 245 0.3× 667 1.3× 97 0.2× 163 4.3k
S. R. Arnold United Kingdom 40 3.0k 1.1× 3.2k 2.1× 599 0.8× 365 0.7× 72 0.2× 139 5.4k
Lin Liu China 40 953 0.4× 2.9k 1.9× 499 0.7× 345 0.7× 493 1.2× 228 5.3k
David Jones United Kingdom 48 4.1k 1.6× 2.2k 1.4× 476 0.6× 2.1k 4.0× 240 0.6× 246 7.7k
David J. Lary United States 31 1.7k 0.6× 2.0k 1.3× 676 0.9× 347 0.7× 111 0.3× 127 3.7k
Wolfgang Knorr Germany 39 5.1k 1.9× 3.0k 2.0× 573 0.8× 1.6k 3.0× 153 0.4× 87 7.2k

Countries citing papers authored by U. S. Nair

Since Specialization
Citations

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

Fields of papers citing papers by U. S. Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by U. S. Nair. 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 U. S. Nair. The network helps show where U. S. Nair may publish in the future.

Co-authorship network of co-authors of U. S. Nair

This figure shows the co-authorship network connecting the top 25 collaborators of U. S. Nair. A scholar is included among the top collaborators of U. S. Nair 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 U. S. Nair. U. S. Nair 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
1.
Nair, U. S., et al.. (2025). An investigation of the impact of Canadian wildfires on US air quality using model, satellite, and ground measurements. Atmospheric chemistry and physics. 25(11). 5497–5517.
2.
Pielke, Roger A., et al.. (2025). Land use land cover change, irrigation and their impacts on Bi-hourly evolution of convective environments during GRAINEX. Journal of Hydrology Regional Studies. 62. 102884–102884.
3.
Mahmood, Rezaul, et al.. (2025). Impacts of Irrigated and Nonirrigated Land Uses on Convective Environments and Related Diagnostic Variables during GRAINEX in Nebraska, United States. Journal of Hydrometeorology. 26(5). 501–519. 1 indexed citations
4.
Nair, U. S., et al.. (2023). Impact of growth of a medium-sized Indian coastal city on urban climate: A case study using data fusion and analytics. Urban Climate. 49. 101525–101525. 4 indexed citations
5.
Nair, U. S., et al.. (2020). Analogy-based Assessment of Domain-specific Word Embeddings. NASA STI Repository (National Aeronautics and Space Administration). 1–6. 3 indexed citations
6.
Miller, Jeffrey J., U. S. Nair, Rahul Ramachandran, & Manil Maskey. (2018). Detection of transverse cirrus bands in satellite imagery using deep learning. Computers & Geosciences. 118. 79–85. 21 indexed citations
7.
Gong, Xi, Aaron Kaulfus, U. S. Nair, & Daniel A. Jaffe. (2017). Quantifying O3 Impacts in Urban Areas Due to Wildfires Using a Generalized Additive Model. Environmental Science & Technology. 51(22). 13216–13223. 78 indexed citations
8.
Nair, U. S., Yuling Wu, Christopher D. Holmes, et al.. (2013). Cloud-resolving simulations of mercury scavenging and deposition in thunderstorms. Atmospheric chemistry and physics. 13(19). 10143–10157. 17 indexed citations
9.
Ramachandran, Rahul, Xiang Li, Sara Graves, et al.. (2013). Data Prospecting–A Step Towards Data Intensive Science. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6(3). 1233–1241.
10.
McNider, Richard T., Gert‐Jan Steeneveld, Roger A. Pielke, et al.. (2012). Response and Sensitivity of the Nocturnal Boundary Layer Over Land to Added Longwave Radiative Forcing. AGUFM. 2012. 2 indexed citations
11.
Lyons, T.J., et al.. (2008). Clearing enhances dust devil formation. Journal of Arid Environments. 72(10). 1918–1928. 19 indexed citations
12.
Kala, Jatin, et al.. (2008). Validation of a Simple Steady-State Forecast of Minimum Nocturnal Temperatures. Journal of Applied Meteorology and Climatology. 48(3). 624–633. 8 indexed citations
13.
Pielke, Roger A., Adriana Beltrán‐Przekurat, C. A. Hiemstra, et al.. (2006). Impacts of regional land use and land cover on rainfall : an overview. IAHS-AISH publication. 325–331. 10 indexed citations
14.
Asefi, S., et al.. (2005). An integrated hydrological and atmospheric model to predict malaria epidemics. 1591–1596. 1 indexed citations
15.
Christopher, S. A., et al.. (2004). The Effect of Central American Smoke Aerosols on the Air Quality and Climate over the Southeastern United States: First Results from RAMS-AROMA. AGUFM. 2004. 1 indexed citations
16.
Nair, U. S., Robert O. Lawton, Ronald M. Welch, & Roger A. Pielke. (2003). Impact of land use on Costa Rican tropical montane cloud forests: Sensitivity of cumulus cloud field characteristics to lowland deforestation. Journal of Geophysical Research Atmospheres. 108(D7). 102 indexed citations
17.
Nair, U. S., et al.. (2002). Climatic impact of lowland deforestation on tropical montane cloud forests in Costa Rica. Open MIND. 1 indexed citations
18.
Nair, U. S.. (2001). Impact of land surface heterogeneity on the spatial organization of cumulus clouds. 3 indexed citations
19.
Berendes, Todd, et al.. (2001). Interactive Visualizer and Image Classifier for Satellites (IVICS). AGUSM. 2001. 3 indexed citations
20.
Nair, U. S.. (2000). The CAPE climatology for continental United States: Sensitivity to perturbations in temperature and dewpoint.

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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