Ling‐Feng Hsiao

829 total citations
25 papers, 653 citations indexed

About

Ling‐Feng Hsiao is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Ling‐Feng Hsiao has authored 25 papers receiving a total of 653 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Atmospheric Science, 17 papers in Global and Planetary Change and 5 papers in Oceanography. Recurrent topics in Ling‐Feng Hsiao's work include Meteorological Phenomena and Simulations (18 papers), Tropical and Extratropical Cyclones Research (17 papers) and Climate variability and models (15 papers). Ling‐Feng Hsiao is often cited by papers focused on Meteorological Phenomena and Simulations (18 papers), Tropical and Extratropical Cyclones Research (17 papers) and Climate variability and models (15 papers). Ling‐Feng Hsiao collaborates with scholars based in Taiwan, United States and Japan. Ling‐Feng Hsiao's co-authors include Tien-Chiang Yeh, Jing‐Shan Hong, Chin–Tzu Fong, Takahisa Maeda, Cheng‐Shang Lee, Ying‐Hwa Kuo, Yong-run Guo, Kangning Huang, Ming‐Jen Yang and Zifa Wang and has published in prestigious journals such as Journal of Hydrology, Monthly Weather Review and Environmental Modelling & Software.

In The Last Decade

Ling‐Feng Hsiao

24 papers receiving 633 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ling‐Feng Hsiao Taiwan 14 546 390 151 127 87 25 653
Jinfang Yin China 16 875 1.6× 823 2.1× 135 0.9× 91 0.7× 44 0.5× 75 996
Honglong Yang China 14 403 0.7× 309 0.8× 305 2.0× 134 1.1× 42 0.5× 51 616
Yerong Feng China 14 468 0.9× 341 0.9× 133 0.9× 111 0.9× 59 0.7× 43 549
M. D. Chou United States 7 1.0k 1.9× 961 2.5× 120 0.8× 77 0.6× 106 1.2× 9 1.1k
Thara Prabhakaran India 14 757 1.4× 760 1.9× 209 1.4× 131 1.0× 14 0.2× 58 957
Yue Ying United States 12 545 1.0× 465 1.2× 93 0.6× 146 1.1× 90 1.0× 17 597
Xingxiu Deng Canada 9 479 0.9× 388 1.0× 173 1.1× 80 0.6× 39 0.4× 12 538
Tianmeng Chen China 15 679 1.2× 645 1.7× 185 1.2× 187 1.5× 22 0.3× 34 818
Mariano Sastre Spain 16 532 1.0× 440 1.1× 340 2.3× 162 1.3× 37 0.4× 43 768
Jeffery T. McQueen United States 13 529 1.0× 424 1.1× 177 1.2× 234 1.8× 31 0.4× 21 654

Countries citing papers authored by Ling‐Feng Hsiao

Since Specialization
Citations

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

Fields of papers citing papers by Ling‐Feng Hsiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling‐Feng Hsiao. 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 Ling‐Feng Hsiao. The network helps show where Ling‐Feng Hsiao may publish in the future.

Co-authorship network of co-authors of Ling‐Feng Hsiao

This figure shows the co-authorship network connecting the top 25 collaborators of Ling‐Feng Hsiao. A scholar is included among the top collaborators of Ling‐Feng Hsiao 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 Ling‐Feng Hsiao. Ling‐Feng Hsiao 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.
Chan, Pak Wai, et al.. (2025). Historical rainstorm in Hong Kong on 7–8 September 2023: Diagnosis, forecasting and nowcasting. Atmospheric Science Letters. 26(1). 2 indexed citations
2.
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
3.
4.
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
5.
6.
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
7.
Liu, Hui, Ying‐Hwa Kuo, Sergey Sokolovskiy, et al.. (2018). A Quality Control Procedure Based on Bending Angle Measurement Uncertainty for Radio Occultation Data Assimilation in the Tropical Lower Troposphere. Journal of Atmospheric and Oceanic Technology. 35(10). 2117–2131. 24 indexed citations
8.
Wu, Ming‐Chang, et al.. (2017). Effective Use of Ensemble Numerical Weather Predictions in Taiwan by Means of a SOM-Based Cluster Analysis Technique. Water. 9(11). 836–836. 9 indexed citations
9.
Hsiao, Ling‐Feng, et al.. (2015). Systematic evaluation of the impacts of GPSRO data on the prediction of typhoons over the northwestern Pacific in 2008–2010. Atmospheric measurement techniques. 8(6). 2531–2542. 28 indexed citations
10.
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
11.
Huang, Ching-Yuang, et al.. (2015). An Impact Study of GPS Radio Occultation Observations on Frontal Rainfall Prediction with a Local Bending Angle Operator. Weather and Forecasting. 31(1). 129–150. 22 indexed citations
12.
Zhang, Xin, et al.. (2014). Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model. Journal of Atmospheric and Oceanic Technology. 31(9). 2008–2014. 2 indexed citations
13.
Hong, Jing‐Shan, et al.. (2014). Ensemble Typhoon Quantitative Precipitation Forecasts Model in Taiwan. Weather and Forecasting. 30(1). 217–237. 38 indexed citations
14.
Hsiao, Ling‐Feng, Ming‐Jen Yang, Cheng‐Shang Lee, et al.. (2013). Ensemble forecasting of typhoon rainfall and floods over a mountainous watershed in Taiwan. Journal of Hydrology. 506. 55–68. 80 indexed citations
15.
Lee, Cheng‐Shang, Kwan Tun Lee, Yu‐Chi Wang, et al.. (2012). Assessment of sewer flooding model based on ensemble quantitative precipitation forecast. Journal of Hydrology. 506. 101–113. 31 indexed citations
16.
Hsiao, Ling‐Feng, et al.. (2010). A Vortex Relocation Scheme for Tropical Cyclone Initialization in Advanced Research WRF. Monthly Weather Review. 138(8). 3298–3315. 65 indexed citations
17.
Hsiao, Ling‐Feng, et al.. (2009). Sensitivity of Typhoon Track Predictions in a Regional Prediction System to Initial and Lateral Boundary Conditions. Journal of Applied Meteorology and Climatology. 48(9). 1913–1928. 15 indexed citations
18.
Hsiao, Ling‐Feng, et al.. (2004). A Composite Comparative Study of the Dust Events in Taipei and Beijing. Terrestrial Atmospheric and Oceanic Sciences. 15(5). 983–983. 2 indexed citations
19.
Wang, Zifa, et al.. (2002). A modeling of the sea breeze and its impacts on ozone distribution in northern Taiwan. Environmental Modelling & Software. 17(1). 21–27. 31 indexed citations
20.
Maeda, Takahisa, et al.. (2001). A Nested Air Quality Prediction Modeling System for Urban and Regional Scales: Application for High-Ozone Episode in Taiwan. Water Air & Soil Pollution. 130(1-4). 391–396. 126 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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