Hui-Ya Chuang

6.6k total citations
11 papers, 216 citations indexed

About

Hui-Ya Chuang is a scholar working on Global and Planetary Change, Atmospheric Science and Health. According to data from OpenAlex, Hui-Ya Chuang has authored 11 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Global and Planetary Change, 7 papers in Atmospheric Science and 1 paper in Health. Recurrent topics in Hui-Ya Chuang's work include Atmospheric and Environmental Gas Dynamics (5 papers), Meteorological Phenomena and Simulations (5 papers) and Climate variability and models (4 papers). Hui-Ya Chuang is often cited by papers focused on Atmospheric and Environmental Gas Dynamics (5 papers), Meteorological Phenomena and Simulations (5 papers) and Climate variability and models (4 papers). Hui-Ya Chuang collaborates with scholars based in United States, United Kingdom and China. Hui-Ya Chuang's co-authors include Jeffery T. McQueen, Geoff DiMego, M. Tsidulko, Jonathan Pleim, David C. Wong, Rohit Mathur, Pius C. S. Lee, Nelson L. Seaman, Paula M. Davidson and Tanya L. Otte and has published in prestigious journals such as Monthly Weather Review, Bulletin of the American Meteorological Society and Frontiers in Psychology.

In The Last Decade

Hui-Ya Chuang

10 papers receiving 201 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hui-Ya Chuang United States	7	196	132	82	66	9	11	216
Zhongjing Jiang China	9	233 1.2×	137 1.0×	130 1.6×	94 1.4×	14 1.6×	22	310
Hyunkwang Lim South Korea	9	252 1.3×	227 1.7×	92 1.1×	59 0.9×	9 1.0×	21	302
Yingli Yu China	10	261 1.3×	199 1.5×	103 1.3×	43 0.7×	8 0.9×	13	276
Lindong Dai China	8	249 1.3×	187 1.4×	140 1.7×	65 1.0×	9 1.0×	12	272
Yafei Wang China	5	214 1.1×	130 1.0×	154 1.9×	68 1.0×	18 2.0×	9	241
Alan C. Czarnetzki United States	8	160 0.8×	105 0.8×	69 0.8×	58 0.9×	11 1.2×	12	193
Jesús Yus-Díez Spain	8	157 0.8×	103 0.8×	81 1.0×	42 0.6×	19 2.1×	19	188
Hyunkee Hong South Korea	10	258 1.3×	199 1.5×	85 1.0×	88 1.3×	13 1.4×	32	295
Jinghui Lian France	7	163 0.8×	226 1.7×	60 0.7×	78 1.2×	9 1.0×	21	255
Anna Protonotariou Greece	8	222 1.1×	198 1.5×	87 1.1×	30 0.5×	7 0.8×	12	240

Countries citing papers authored by Hui-Ya Chuang

Since Specialization

Citations

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

Fields of papers citing papers by Hui-Ya Chuang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hui-Ya Chuang. 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 Hui-Ya Chuang. The network helps show where Hui-Ya Chuang may publish in the future.

Co-authorship network of co-authors of Hui-Ya Chuang

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

All Works

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11 of 11 papers shown

1.

Fung, Sai-fu, et al.. (2025). Revisiting the bi-factor structure of the short version of the Warwick–Edinburgh mental well-being scale with samples in China. Frontiers in Psychology. 16. 1422065–1422065. 1 indexed citations

2.

Rose, Neil L., et al.. (2025). MoistureMapper: An Autonomous Mobile Robot for High-Resolution Soil Moisture Mapping at Scale. 3268–3274.

3.

Chuang, Hui-Ya, et al.. (2018). R2O Transition of NCAR’s Icing and Turbulence Algorithms into NCEP’s Operations. Pure and Applied Geophysics. 176(5). 2057–2079. 3 indexed citations

4.

Lu, Cheng‐Hsuan, Arlindo da Silva, Jun Wang, et al.. (2016). The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP. Geoscientific model development. 9(5). 1905–1919. 26 indexed citations

5.

Lu, Cheng‐Hsuan, Arlindo da Silva, Mian Chin, et al.. (2013). The NEMS GFS aerosol component; NCEP's global aerosol forecast system. 6 indexed citations

6.

Du, Jun, Geoff DiMego, Zoltán Tóth, et al.. (2009). 4A.4 NCEP Short Range Ensemble Forecast (SREF) System Upgrade in 2009. 16 indexed citations

7.

Bernardet, Lígia, Louisa Nance, Meral Demirtaş, et al.. (2008). The Developmental Testbed Center and its Winter Forecasting Experiment. Bulletin of the American Meteorological Society. 89(5). 611–628. 21 indexed citations

8.

Otte, Tanya L., George Pouliot, Jonathan Pleim, et al.. (2005). Linking the Eta Model with the Community Multiscale Air Quality (CMAQ) Modeling System to Build a National Air Quality Forecasting System. Weather and Forecasting. 20(3). 367–384. 123 indexed citations

9.

Chuang, Hui-Ya & Peter J. Sousounis. (2003). The Impact of the Prevailing Synoptic Situation on the Lake-Aggregate Effect. Monthly Weather Review. 131(5). 990–1010. 8 indexed citations

10.

Chuang, Hui-Ya, et al.. (2001). The NCEP Eta model post processor, a documentation. 4 indexed citations

11.

Chuang, Hui-Ya & Peter J. Sousounis. (2000). A Technique for Generating Idealized Initial and Boundary Conditions for the PSU–NCAR Model MM5. Monthly Weather Review. 128(8). 2875–2884. 8 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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