Huan Meng

1.5k total citations
33 papers, 1.0k citations indexed

About

Huan Meng is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Huan Meng has authored 33 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Atmospheric Science, 11 papers in Global and Planetary Change and 9 papers in Environmental Engineering. Recurrent topics in Huan Meng's work include Precipitation Measurement and Analysis (25 papers), Meteorological Phenomena and Simulations (23 papers) and Soil Moisture and Remote Sensing (9 papers). Huan Meng is often cited by papers focused on Precipitation Measurement and Analysis (25 papers), Meteorological Phenomena and Simulations (23 papers) and Soil Moisture and Remote Sensing (9 papers). Huan Meng collaborates with scholars based in United States, Italy and Germany. Huan Meng's co-authors include Ralph Ferraro, Cezar Kongoli, Fuzhong Weng, Paul Pellegrino, Norman C. Grody, Banghua Yan, Limin Zhao, Charles Dean, Jun Dong and Shuang Qiu and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Geophysical Research Letters and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Huan Meng

28 papers receiving 997 citations

Peers

Huan Meng

GPC

OCEAN

Kinji Furukawa Japan

Thomas Schwitalla Germany

Leo Pio D’Adderio Italy

Anne C. Wilber United States

Jacopo Grazioli Switzerland

M. D. Chou United States

Daniel Leuenberger Switzerland

Mircea Grecu United States

David Hudak Canada

Éva Borbás United States

Kinji Furukawa Japan

Huan Meng

749 ×0.8

382 ×0.6

GPC

208 ×1.2

100 ×1.4

OCEAN

38 ×0.6

Citations per year, relative to Huan Meng Huan Meng (= 1×) peers Kinji Furukawa

Countries citing papers authored by Huan Meng

Since Specialization

Citations

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

Fields of papers citing papers by Huan Meng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huan Meng

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

All Works

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20 of 20 papers shown

Yin, Jifu, Xiwu Zhan, Michael Barlage, et al.. (2023). Refinement of NOAA AMSR-2 Soil Moisture Data Product—Part 2: Development With the Optimal Machine Learning Model. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–11.

Yin, Jifu, Xiwu Zhan, Michael Barlage, et al.. (2023). Refinement of NOAA AMSR-2 Soil Moisture Data Product: 1. Intercomparisons of the Commonly Used Machine-Learning Models. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–10.

Yang, John Xun, Yalei You, William J. Blackwell, et al.. (2023). SatERR: A Community Error Inventory for Satellite Microwave Observation Error Representation and Uncertainty Quantification. Bulletin of the American Meteorological Society. 105(1). E1–E20. 7 indexed citations

Gorooh, Vesta Afzali, Kuolin Hsu, Ralph Ferraro, et al.. (2023). Advances in Precipitation Retrieval and Applications from Low-Earth-Orbiting Satellite Information. Bulletin of the American Meteorological Society. 104(10). E1764–E1771. 5 indexed citations

Petković, Veljko, et al.. (2023). Precipitation Vertical Structure Characterization: A Feature-Based Approach. Journal of Hydrometeorology. 24(12). 2281–2297.

You, Yalei, Huan Meng, Jun Dong, et al.. (2022). A Snowfall Detection Algorithm for ATMS Over Ocean, Sea Ice, and Coast. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 15. 1411–1420. 6 indexed citations

Yang, Wenze, Huan Meng, Ralph Ferraro, & Yong Chen. (2020). Inter-Calibration of AMSU-A Window Channels. Remote Sensing. 12(18). 2988–2988. 3 indexed citations

Kongoli, Cezar, Huan Meng, Jun Dong, & Ralph Ferraro. (2020). Ground-based Assessment of Snowfall Detection over Land Using Polarimetric High Frequency Microwave Measurements. Remote Sensing. 12(20). 3441–3441. 3 indexed citations

You, Yalei, Huan Meng, Jun Dong, & Scott D. Rudlosky. (2019). Time‐Lag Correlation Between Passive Microwave Measurements and Surface Precipitation and Its Impact on Precipitation Retrieval Evaluation. Geophysical Research Letters. 46(14). 8415–8423. 15 indexed citations

10.

Meng, Huan, Jun Dong, Ralph Ferraro, et al.. (2017). A 1DVAR‐based snowfall rate retrieval algorithm for passive microwave radiometers. Journal of Geophysical Research Atmospheres. 122(12). 6520–6540. 33 indexed citations

11.

DeMaria, Mark, Ralph Ferraro, John L. Beven, et al.. (2015). Satellite tools to monitor and predict Hurricane Sandy (2012): Current and emerging products. Atmospheric Research. 166. 165–181. 5 indexed citations

12.

Kongoli, Cezar, Huan Meng, Jun Dong, & Ralph Ferraro. (2015). A snowfall detection algorithm over land utilizing high‐frequency passive microwave measurements—Application to ATMS. Journal of Geophysical Research Atmospheres. 120(5). 1918–1932. 31 indexed citations

13.

Moradi, Isaac, et al.. (2012). Developing climate data records from microwave satellite data. AGU Fall Meeting Abstracts. 2012. 1 indexed citations

14.

Yang, Wenze, et al.. (2012). Cross-Scan Asymmetry of AMSU-A Window Channels: Characterization, Correction, and Verification. IEEE Transactions on Geoscience and Remote Sensing. 51(3). 1514–1530. 11 indexed citations

15.

Sen, Sumit, Puneet Srivastava, T. Prabhakar Clement, J. H. Dane, & Huan Meng. (2011). Simulating hydrologic response of a pasture hillslope in North Alabama using the Hortonian Infiltration and Runoff/On model. Journal of Soil and Water Conservation. 66(6). 411–422. 2 indexed citations

16.

Waliser, Duane E., Jui‐Lin F. Li, Christopher P. Woods, et al.. (2009). Cloud ice: A climate model challenge with signs and expectations of progress. Journal of Geophysical Research Atmospheres. 114(D8). 320 indexed citations

17.

Meng, Huan, Timothy R. Green, José D. Salas, & Lajpat R. Ahuja. (2008). Development and testing of a terrain-based hydrologic model for spatial Hortonian Infiltration and Runoff/On. Environmental Modelling & Software. 23(6). 794–812. 15 indexed citations

18.

Yan, Banghua, Fuzhong Weng, & Huan Meng. (2008). Retrieval of snow surface microwave emissivity from the advanced microwave sounding unit. Journal of Geophysical Research Atmospheres. 113(D19). 29 indexed citations

19.

Kongoli, Cezar, Ralph Ferraro, Paul Pellegrino, Huan Meng, & Charles Dean. (2007). Utilization of the AMSU high frequency measurements for improved coastal rain retrievals. Geophysical Research Letters. 34(17). 13 indexed citations

20.

Meng, Huan, José D. Salas, Timothy R. Green, & Lajpat R. Ahuja. (2005). Scaling analysis of space–time infiltration based on the universal multifractal model. Journal of Hydrology. 322(1-4). 220–235. 20 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.

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