Chin–Tzu Fong

473 total citations
15 papers, 372 citations indexed

About

Chin–Tzu Fong is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Chin–Tzu Fong has authored 15 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Atmospheric Science, 10 papers in Global and Planetary Change and 4 papers in Oceanography. Recurrent topics in Chin–Tzu Fong's work include Meteorological Phenomena and Simulations (10 papers), Climate variability and models (10 papers) and Tropical and Extratropical Cyclones Research (9 papers). Chin–Tzu Fong is often cited by papers focused on Meteorological Phenomena and Simulations (10 papers), Climate variability and models (10 papers) and Tropical and Extratropical Cyclones Research (9 papers). Chin–Tzu Fong collaborates with scholars based in Taiwan, United States and Australia. Chin–Tzu Fong's co-authors include Jing‐Shan Hong, Ling‐Feng Hsiao, Ying‐Hwa Kuo, Tien-Chiang Yeh, Cheng‐Shang Lee, Yong-run Guo, Xiang‐Yu Huang, Zhiquan Liu, Craig S. Schwartz and Ta‐Kang Yeh and has published in prestigious journals such as Monthly Weather Review, Journal of Hydrometeorology and Weather and Forecasting.

In The Last Decade

Chin–Tzu Fong

15 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chin–Tzu Fong Taiwan	11	303	242	87	48	46	15	372
Kirsti Salonen Finland	11	327 1.1×	279 1.2×	86 1.0×	70 1.5×	98 2.1×	21	437
Shu‐Chih Yang United States	9	289 1.0×	274 1.1×	99 1.1×	48 1.0×	12 0.3×	23	353
Brett Candy United Kingdom	14	483 1.6×	359 1.5×	110 1.3×	81 1.7×	80 1.7×	25	573
Jordan Gerth United States	6	194 0.6×	184 0.8×	33 0.4×	38 0.8×	29 0.6×	12	277
Paytsar Muradyan United States	10	216 0.7×	166 0.7×	40 0.5×	37 0.8×	61 1.3×	26	278
James A. Jung United States	14	660 2.2×	580 2.4×	88 1.0×	54 1.1×	59 1.3×	31	705
Kenneth A. Campana United States	9	431 1.4×	434 1.8×	87 1.0×	46 1.0×	17 0.4×	13	532
Alison Pamment United Kingdom	8	259 0.9×	240 1.0×	33 0.4×	27 0.6×	24 0.5×	9	348
Hirotaka Nakatsuka Japan	5	408 1.3×	216 0.9×	50 0.6×	161 3.4×	46 1.0×	26	471
Cristina Lupu United Kingdom	8	580 1.9×	509 2.1×	67 0.8×	58 1.2×	47 1.0×	12	642

Countries citing papers authored by Chin–Tzu Fong

Since Specialization

Citations

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

Fields of papers citing papers by Chin–Tzu Fong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chin–Tzu Fong. 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 Chin–Tzu Fong. The network helps show where Chin–Tzu Fong may publish in the future.

Co-authorship network of co-authors of Chin–Tzu Fong

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

All Works

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15 of 15 papers shown

Peng, Melinda S., et al.. (2024). Evaluation of five global AI models for predicting weather in Eastern Asia and Western Pacific. npj Climate and Atmospheric Science. 7(1). 11 indexed citations

Tóth, Zoltán, et al.. (2024). Statistical Postprocessing of Week-1 and Week-2 Precipitation Forecasts over Taiwan. Journal of Hydrometeorology. 25(10). 1481–1499. 1 indexed citations

Hsiao, Ling‐Feng, Melinda S. Peng, Chin–Tzu Fong, et al.. (2021). Impacts of assimilating dual-Doppler radar-retrieval winds on the TWRF predictions of Typhoon Nesat (2017). Terrestrial Atmospheric and Oceanic Sciences. 32(5.1). 2 indexed citations

Hsiao, Ling‐Feng, et al.. (2020). Improve Tropical Cyclone Prediction of TWRF with the Application of Advanced Observation Data. 1 indexed citations

Hsiao, Ling‐Feng, et al.. (2020). Improvement of the Numerical Tropical Cyclone Prediction System at the Central Weather Bureau of Taiwan: TWRF (Typhoon WRF). Atmosphere. 11(6). 657–657. 20 indexed citations

Chen, I‐Han, et al.. (2020). Improving Afternoon Thunderstorm Prediction over Taiwan through 3DVar-Based Radar and Surface Data Assimilation. Weather and Forecasting. 35(6). 2603–2620. 12 indexed citations

Berner, Judith, et al.. (2019). The Taiwan WRF Ensemble Prediction System: Scientific Description, Model-Error Representation and Performance Results. Asia-Pacific Journal of Atmospheric Sciences. 56(1). 1–15. 25 indexed citations

Yeh, Ta‐Kang, et al.. (2016). Determining the precipitable water vapor with ground-based GPS and comparing its yearly variation to rainfall over Taiwan. Advances in Space Research. 57(12). 2496–2507. 33 indexed citations

Hsiao, Ling‐Feng, Huang Xiangyu, Ying‐Hwa Kuo, et al.. (2015). Blending of Global and Regional Analyses with a Spatial Filter: Application to Typhoon Prediction over the Western North Pacific Ocean. Weather and Forecasting. 30(3). 754–770. 32 indexed citations

10.

Hong, Jing‐Shan, et al.. (2014). Ensemble Typhoon Quantitative Precipitation Forecasts Model in Taiwan. Weather and Forecasting. 30(1). 217–237. 38 indexed citations

11.

Yeh, Ta‐Kang, et al.. (2014). Applying the Water Vapor Radiometer to Verify the Precipitable Water Vapor Measured by GPS. Terrestrial Atmospheric and Oceanic Sciences. 25(2). 189–189. 12 indexed citations

12.

Schwartz, Craig S., Zhiquan Liu, Xiang‐Yu Huang, Ying‐Hwa Kuo, & Chin–Tzu Fong. (2013). Comparing Limited-Area 3DVAR and Hybrid Variational-Ensemble Data Assimilation Methods for Typhoon Track Forecasts: Sensitivity to Outer Loops and Vortex Relocation. Monthly Weather Review. 141(12). 4350–4372. 47 indexed citations

13.

Hsiao, Ling‐Feng, Ying‐Hwa Kuo, Yong-run Guo, et al.. (2012). Application of WRF 3DVAR to Operational Typhoon Prediction in Taiwan: Impact of Outer Loop and Partial Cycling Approaches. Weather and Forecasting. 27(5). 1249–1263. 86 indexed citations

14.

Chen, Jau‐Ming, et al.. (1999). Climate Characteristics of the CWB Global Forecast System:Hydrological Processes and Atmospheric Circulation. Terrestrial Atmospheric and Oceanic Sciences. 10(4). 737–737. 1 indexed citations

15.

Fong, Chin–Tzu, et al.. (1997). The Second–Generation Global Forecast System at the Central Weather Bureau in Taiwan. Weather and Forecasting. 12(3). 653–663. 51 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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