Chanh Kieu

1.4k total citations
66 papers, 1.0k citations indexed

About

Chanh Kieu is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Chanh Kieu has authored 66 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Atmospheric Science, 53 papers in Global and Planetary Change and 24 papers in Oceanography. Recurrent topics in Chanh Kieu's work include Tropical and Extratropical Cyclones Research (60 papers), Climate variability and models (50 papers) and Meteorological Phenomena and Simulations (44 papers). Chanh Kieu is often cited by papers focused on Tropical and Extratropical Cyclones Research (60 papers), Climate variability and models (50 papers) and Meteorological Phenomena and Simulations (44 papers). Chanh Kieu collaborates with scholars based in United States, China and Vietnam. Chanh Kieu's co-authors include Da‐Lin Zhang, Vijay Tallapragada, Quan Wang, Samuel Trahan, Qingfu Liu, Zhan Zhang, In‐Hyuk Kwon, Thanh Ngo‐Duc, Weiguo Wang and Young Cheol Kwon and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Climate and Geophysical Research Letters.

In The Last Decade

Chanh Kieu

63 papers receiving 990 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chanh Kieu United States 20 969 740 421 30 20 66 1.0k
Benoît Vannière United Kingdom 17 1.2k 1.3× 1.3k 1.7× 472 1.1× 20 0.7× 13 0.7× 26 1.4k
Anthony Wimmers United States 18 766 0.8× 599 0.8× 259 0.6× 55 1.8× 10 0.5× 34 854
Tetsuo Nakazawa Japan 26 2.0k 2.1× 2.0k 2.6× 856 2.0× 39 1.3× 30 1.5× 53 2.2k
Masahiro Sawada Japan 16 843 0.9× 724 1.0× 204 0.5× 50 1.7× 12 0.6× 42 917
Da Yang United States 14 560 0.6× 568 0.8× 179 0.4× 21 0.7× 5 0.3× 35 658
Eric A. Hendricks United States 16 1.3k 1.3× 853 1.2× 617 1.5× 101 3.4× 53 2.6× 47 1.3k
Walter M. Hannah United States 17 871 0.9× 898 1.2× 203 0.5× 56 1.9× 31 1.6× 39 995
Daniel P. Stern United States 17 1.4k 1.5× 860 1.2× 694 1.6× 79 2.6× 70 3.5× 28 1.4k
Leela M. Frankcombe Australia 16 613 0.6× 718 1.0× 440 1.0× 8 0.3× 10 0.5× 21 845
Joshua H. Cossuth United States 10 553 0.6× 477 0.6× 189 0.4× 20 0.7× 11 0.6× 17 613

Countries citing papers authored by Chanh Kieu

Since Specialization
Citations

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

Fields of papers citing papers by Chanh Kieu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chanh Kieu

This figure shows the co-authorship network connecting the top 25 collaborators of Chanh Kieu. A scholar is included among the top collaborators of Chanh Kieu 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 Chanh Kieu. Chanh Kieu 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.
Kieu, Chanh & Quan Dong Nguyen. (2024). Binary dataset for machine learning applications to tropical cyclone formation prediction. Scientific Data. 11(1). 446–446. 2 indexed citations
2.
Kieu, Chanh, et al.. (2023). A convection‐permitting dynamically downscaled dataset over the Midwestern United States. Geoscience Data Journal. 10(4). 429–446. 1 indexed citations
3.
Kieu, Chanh & Richard Rotunno. (2022). Characteristics of Tropical‐Cyclone Turbulence and Intensity Predictability. Geophysical Research Letters. 49(8). 4 indexed citations
4.
Kieu, Chanh, et al.. (2020). A Numerical Study of the Global Formation of Tropical Cyclones. Journal of Advances in Modeling Earth Systems. 13(1). 16 indexed citations
5.
Chen, Zhi‐Min, et al.. (2020). On the stability and bifurcation of the non-rotating Boussinesq equation with the Kolmogorov forcing at a low Péclet number. Communications in Nonlinear Science and Numerical Simulation. 89. 105322–105322. 5 indexed citations
6.
Wang, Quan, et al.. (2019). Large-scale dynamics of tropical cyclone formation associated with ITCZ breakdown. Atmospheric chemistry and physics. 19(13). 8383–8397. 12 indexed citations
7.
8.
Wang, Quan & Chanh Kieu. (2019). Dynamics of transverse cloud rolls in the boundary layer with the Poiseuille shear flow. Physics of Fluids. 31(9). 2 indexed citations
9.
Tang, Jie, Jun A. Zhang, Chanh Kieu, & Frank D. Marks. (2018). Sensitivity of Hurricane Intensity and Structure to Two Types of Planetary Boundary Layer Parameterization Schemes in Idealized HWRF Simulations. SHILAP Revista de lepidopterología. 11 indexed citations
10.
Kieu, Chanh & Da‐Lin Zhang. (2018). The Control of Environmental Stratification on the Hurricane Maximum Potential Intensity. Geophysical Research Letters. 45(12). 6272–6280. 22 indexed citations
11.
Zhang, Da‐Lin, et al.. (2018). On the rapid intensification of Hurricane Wilma (2005). Part IV: Inner‐core dynamics during the steady radius of maximum wind stage. Quarterly Journal of the Royal Meteorological Society. 144(717). 2508–2523. 14 indexed citations
12.
Kieu, Chanh, et al.. (2018). On the growth of intensity forecast errors in the operational hurricane weather research and forecasting (HWRF) model. Quarterly Journal of the Royal Meteorological Society. 144(715). 1803–1819. 10 indexed citations
13.
Robeson, Scott M., et al.. (2017). Large‐scale control of the lower stratosphere on variability of tropical cyclone intensity. Geophysical Research Letters. 44(9). 4313–4323. 17 indexed citations
14.
Kieu, Chanh, et al.. (2016). Hurricane Intensity Predictability. Bulletin of the American Meteorological Society. 97(10). 1847–1857. 31 indexed citations
15.
Kieu, Chanh. (2014). On the Development of Double Warm Cores in Intense Tropical Cyclones in the HWRF Model. 4 indexed citations
16.
Zhang, Zhan, Vijay Tallapragada, Chanh Kieu, Samuel Trahan, & Weiguo Wang. (2014). HWRF Based Ensemble Prediction System Using Perturbations from GEFS and Stochastic Convective Trigger Function. SHILAP Revista de lepidopterología. 3(3). 145–161. 31 indexed citations
17.
Tallapragada, Vijay & Chanh Kieu. (2014). Real-Time Forecasts of Typhoon Rapid Intensification in The North Western Pacific Basin with the NCEP Operational HWRF Model. SHILAP Revista de lepidopterología. 3(2). 63–77. 14 indexed citations
18.
Ngo‐Duc, Thanh, et al.. (2013). A study of the connection between tropical cyclone track and intensity errors in the WRF model. Meteorology and Atmospheric Physics. 122(1-2). 55–64. 21 indexed citations
19.
Kieu, Chanh, et al.. (2012). Sensitivity of the Track and Intensity Forecasts of Typhoon Megi (2010) to Satellite-Derived Atmospheric Motion Vectors with the Ensemble Kalman Filter. Journal of Atmospheric and Oceanic Technology. 29(12). 1794–1810. 26 indexed citations
20.
Kieu, Chanh & Da‐Lin Zhang. (2009). Genesis of Tropical Storm Eugene (2005) from Merging Vortices Associated with ITCZ Breakdowns. Part II: Roles of Vortex Merger and Ambient Potential Vorticity. Journal of the Atmospheric Sciences. 66(7). 1980–1996. 19 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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