Soyoung Ha

997 total citations
23 papers, 729 citations indexed

About

Soyoung Ha is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Soyoung Ha has authored 23 papers receiving a total of 729 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Atmospheric Science, 17 papers in Global and Planetary Change and 5 papers in Environmental Engineering. Recurrent topics in Soyoung Ha's work include Meteorological Phenomena and Simulations (14 papers), Climate variability and models (11 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Soyoung Ha is often cited by papers focused on Meteorological Phenomena and Simulations (14 papers), Climate variability and models (11 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Soyoung Ha collaborates with scholars based in United States and South Korea. Soyoung Ha's co-authors include Chris Snyder, Joshua P. Hacker, Judith Berner, A. Fournier, Zhiquan Liu, Craig S. Schwartz, Kathryn R. Fossell, Matthew Pocernich, William C. Skamarock and J. L. Schramm and has published in prestigious journals such as Geophysical Research Letters, Monthly Weather Review and Atmospheric chemistry and physics.

In The Last Decade

Soyoung Ha

18 papers receiving 711 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Soyoung Ha United States 12 668 600 118 77 41 23 729
Kristian Horvath Croatia 14 475 0.7× 360 0.6× 98 0.8× 104 1.4× 48 1.2× 42 573
Peter Weston United Kingdom 7 583 0.9× 510 0.8× 93 0.8× 94 1.2× 28 0.7× 11 660
Louisa Nance United States 13 673 1.0× 482 0.8× 120 1.0× 66 0.9× 21 0.5× 24 726
Per Undén United Kingdom 15 792 1.2× 764 1.3× 87 0.7× 120 1.6× 26 0.6× 19 867
Hisaki Eito Japan 8 574 0.9× 468 0.8× 60 0.5× 101 1.3× 20 0.5× 14 636
Patricia M. Pauley United States 13 538 0.8× 447 0.7× 89 0.8× 86 1.1× 58 1.4× 22 633
Radmila Brožková Czechia 10 404 0.6× 366 0.6× 70 0.6× 102 1.3× 71 1.7× 18 501
Zhengkun Qin China 15 696 1.0× 548 0.9× 89 0.8× 65 0.8× 35 0.9× 59 746
Cécilien Charette Canada 10 887 1.3× 830 1.4× 181 1.5× 93 1.2× 19 0.5× 12 925
Damian R. Wilson United Kingdom 10 1.1k 1.6× 1.0k 1.7× 54 0.5× 62 0.8× 38 0.9× 14 1.1k

Countries citing papers authored by Soyoung Ha

Since Specialization
Citations

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

Fields of papers citing papers by Soyoung Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soyoung Ha

This figure shows the co-authorship network connecting the top 25 collaborators of Soyoung Ha. A scholar is included among the top collaborators of Soyoung Ha 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 Soyoung Ha. Soyoung Ha 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.
Ha, Soyoung & Juanzhen Sun. (2024). Impact of Soil Moisture Updates on Temperature Forecasting. Geophysical Research Letters. 51(15).
2.
Ha, Soyoung, et al.. (2024). Development of AI Convergence Picture Book Creation Class Program to Improve Creativity and AI Value Recognition for Elementary School Students. Korean Association For Learner-Centered Curriculum And Instruction. 24(24). 811–838.
3.
4.
Kim, Hyun Mee, et al.. (2024). Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula. Journal of Meteorological Research. 38(2). 262–284.
5.
Ha, Soyoung, Rajesh Kumar, Gabriele Pfister, et al.. (2024). Chemical Data Assimilation With Aqueous Chemistry in WRF‐Chem Coupled With WRFDA (V4.4.1). Journal of Advances in Modeling Earth Systems. 16(2). 2 indexed citations
6.
Ha, Soyoung. (2022). Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme. Geoscientific model development. 15(4). 1769–1788. 6 indexed citations
7.
8.
Ha, Soyoung, et al.. (2020). Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period. Atmospheric chemistry and physics. 20(10). 6015–6036. 22 indexed citations
9.
10.
Klemp, Joseph B., William C. Skamarock, & Soyoung Ha. (2018). Damping Acoustic Modes in Compressible Horizontally Explicit Vertically Implicit (HEVI) and Split-Explicit Time Integration Schemes. Monthly Weather Review. 146(6). 1911–1923. 11 indexed citations
11.
Skamarock, William C., Michael Duda, Soyoung Ha, & Sang‐Hun Park. (2018). Limited-Area Atmospheric Modeling Using an Unstructured Mesh. Monthly Weather Review. 146(10). 3445–3460. 26 indexed citations
12.
Ha, Soyoung, Chris Snyder, William C. Skamarock, J. G. Anderson, & Nancy Collins. (2017). Ensemble Kalman Filter Data Assimilation for the Model for Prediction Across Scales (MPAS). Monthly Weather Review. 145(11). 4673–4692. 24 indexed citations
13.
Ha, Soyoung, Judith Berner, & Chris Snyder. (2015). A Comparison of Model Error Representations in Mesoscale Ensemble Data Assimilation. Monthly Weather Review. 143(10). 3893–3911. 22 indexed citations
14.
Ha, Soyoung & Chris Snyder. (2013). Influence of Surface Observations in Mesoscale Data Assimilation Using an Ensemble Kalman Filter. Monthly Weather Review. 142(4). 1489–1508. 41 indexed citations
15.
Liu, Zhiquan, Craig S. Schwartz, Chris Snyder, & Soyoung Ha. (2012). Impact of Assimilating AMSU-A Radiances on Forecasts of 2008 Atlantic Tropical Cyclones Initialized with a Limited-Area Ensemble Kalman Filter. Monthly Weather Review. 140(12). 4017–4034. 102 indexed citations
16.
Hacker, Joshua P., Chris Snyder, Soyoung Ha, & Matthew Pocernich. (2011). Linear and non-linear response to parameter variations in a mesoscale model. Tellus A Dynamic Meteorology and Oceanography. 63(3). 429–429. 40 indexed citations
17.
Hacker, Joshua P., Soyoung Ha, Chris Snyder, et al.. (2010). The U.S. Air ForceWeather Agency’s mesoscale ensemble: scientific description and performance results. Tellus A Dynamic Meteorology and Oceanography. 63(3). 625–625. 78 indexed citations
18.
Berner, Judith, Soyoung Ha, Joshua P. Hacker, A. Fournier, & Chris Snyder. (2010). Model Uncertainty in a Mesoscale Ensemble Prediction System: Stochastic versus Multiphysics Representations. Monthly Weather Review. 139(6). 1972–1995. 205 indexed citations
19.
Ha, Soyoung, Ying-Hwa Kuo, Yong-run Guo, & Gyu‐Ho Lim. (2003). Variational Assimilation of Slant-Path Wet Delay Measurements from a Hypothetical Ground-Based GPS Network. Part I: Comparison with Precipitable Water Assimilation. Monthly Weather Review. 131(11). 2635–2655. 26 indexed citations
20.
Ha, Soyoung, et al.. (2002). Comparison of GPS slant wet delay measurements with model simulations during the passage of a squall line. Geophysical Research Letters. 29(23). 13 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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