Baoxiang Pan

1.1k total citations
36 papers, 701 citations indexed

About

Baoxiang Pan is a scholar working on Global and Planetary Change, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Baoxiang Pan has authored 36 papers receiving a total of 701 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Global and Planetary Change, 20 papers in Atmospheric Science and 8 papers in Environmental Engineering. Recurrent topics in Baoxiang Pan's work include Meteorological Phenomena and Simulations (18 papers), Climate variability and models (16 papers) and Hydrological Forecasting Using AI (7 papers). Baoxiang Pan is often cited by papers focused on Meteorological Phenomena and Simulations (18 papers), Climate variability and models (16 papers) and Hydrological Forecasting Using AI (7 papers). Baoxiang Pan collaborates with scholars based in China, United States and United Kingdom. Baoxiang Pan's co-authors include Soroosh Sorooshian, Kuolin Hsu, Amir AghaKouchak, Qingyun Duan, Hao Wang, Jiangjiang Xia, Wentao Li, Zhenji Zhang, Alexander Ihler and Gemma J. Anderson and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Remote Sensing of Environment.

In The Last Decade

Baoxiang Pan

32 papers receiving 687 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Baoxiang Pan China 14 430 376 257 138 42 36 701
Pertti Nurmi Finland 13 504 1.2× 537 1.4× 157 0.6× 82 0.6× 73 1.7× 30 879
Georgy Ayzel Russia 13 449 1.0× 433 1.2× 225 0.9× 260 1.9× 25 0.6× 36 760
Donglai Jiao China 9 278 0.6× 180 0.5× 94 0.4× 120 0.9× 26 0.6× 36 448
James Correia United States 16 982 2.3× 956 2.5× 176 0.7× 79 0.6× 48 1.1× 31 1.2k
Andrés Navarro Spain 14 473 1.1× 523 1.4× 88 0.3× 102 0.7× 20 0.5× 42 757
Jan D. Keller Germany 14 442 1.0× 459 1.2× 117 0.5× 45 0.3× 95 2.3× 25 720
Jiayong Liang United States 8 269 0.6× 151 0.4× 83 0.3× 103 0.7× 32 0.8× 16 484
Negin Hayatbini United States 8 302 0.7× 296 0.8× 117 0.5× 103 0.7× 27 0.6× 10 484
Tao-Chang Yang Taiwan 13 424 1.0× 173 0.5× 290 1.1× 263 1.9× 71 1.7× 18 697
Akshara Kaginalkar India 12 453 1.1× 476 1.3× 294 1.1× 22 0.2× 20 0.5× 27 787

Countries citing papers authored by Baoxiang Pan

Since Specialization
Citations

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

Fields of papers citing papers by Baoxiang Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baoxiang Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Baoxiang Pan. A scholar is included among the top collaborators of Baoxiang Pan 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 Baoxiang Pan. Baoxiang Pan 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.
2.
Zhang, Wei, et al.. (2025). RadarDiT: An advanced radar echo extrapolation model for three gorges reservoir area via diffusion transformer. Journal of Hydrology Regional Studies. 61. 102703–102703.
3.
Pan, Baoxiang, et al.. (2025). Fusion of multi-source precipitation records via coordinate-based generative models. Nature Communications. 17(1). 1227–1227. 1 indexed citations
4.
Zhu, Tao, Mengqian Lu, Jing Yang, et al.. (2025). Enhancing Ready-to-Implementation subseasonal crop growth predictions in central Southwestern Asia: A machine learning-climate dynamical hybrid strategy. Agricultural and Forest Meteorology. 370. 110582–110582. 2 indexed citations
5.
Ou, Zhonghong, Baoxiang Pan, Yi Zheng, et al.. (2025). Probabilistic Diffusion Models Advance Extreme Flood Forecasting. Geophysical Research Letters. 52(15).
6.
Zhang, Feng, Baoxiang Pan, Yannian Zhu, et al.. (2025). High-resolution ensemble retrieval of cloud properties for all-day based on geostationary satellite. npj Climate and Atmospheric Science. 8(1). 1 indexed citations
7.
Pan, Baoxiang, Tiejian Li, Zhaoxi Li, et al.. (2025). Latent diffusion model for quantitative precipitation estimation and forecast at km scale. Environmental Modelling & Software. 194. 106701–106701. 1 indexed citations
8.
Xue, Yu, et al.. (2025). Feedback control of a heterogeneous lattice hydrodynamic model with multi-visual field effect under cyber-attacks. Physica A Statistical Mechanics and its Applications. 674. 130781–130781. 1 indexed citations
9.
Pan, Baoxiang, et al.. (2025). Fast, scale-adaptive and uncertainty-aware downscaling of Earth system model fields with generative machine learning. Nature Machine Intelligence. 7(3). 363–373. 9 indexed citations
10.
Pan, Baoxiang, Quanliang Chen, Jingnan Wang, et al.. (2025). Learning to Infer Weather States Using Partial Observations. SHILAP Revista de lepidopterología. 2(1). 2 indexed citations
11.
Chen, Xi, et al.. (2025). Boosting weather forecast via generative superensemble. npj Climate and Atmospheric Science. 8(1). 1 indexed citations
12.
Ling, Fenghua, Jing‐Jia Luo, Lei Bai, et al.. (2024). Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction. npj Climate and Atmospheric Science. 7(1). 14 indexed citations
13.
Wang, Ya, Gang Huang, Baoxiang Pan, et al.. (2024). Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks: Climatology, Interannual Variability, and Extremes. Advances in Atmospheric Sciences. 41(7). 1299–1312. 6 indexed citations
14.
Sun, Ruochen, Baoxiang Pan, & Qingyun Duan. (2024). Learning Distributed Parameters of Land Surface Hydrologic Models Using a Generative Adversarial Network. Water Resources Research. 60(7). 5 indexed citations
15.
Sun, Ruochen, Baoxiang Pan, & Qingyun Duan. (2023). A surrogate modeling method for distributed land surface hydrological models based on deep learning. Journal of Hydrology. 624. 129944–129944. 20 indexed citations
16.
Li, Jingwei, et al.. (2023). The Deep‐Learning‐Based Fast Efficient Nighttime Retrieval of Thermodynamic Phase From Himawari‐8 AHI Measurements. Geophysical Research Letters. 50(11). 13 indexed citations
17.
Pan, Baoxiang, Gemma J. Anderson, André Gonçalves, et al.. (2021). Learning to Correct Climate Projection Biases. Journal of Advances in Modeling Earth Systems. 13(10). 41 indexed citations
18.
Zhao, Tongtiegang, Baoxiang Pan, Lei Ye, et al.. (2021). Correspondence relationship between ENSO teleconnection and anomaly correlation for GCM seasonal precipitation forecasts. Climate Dynamics. 58(3-4). 633–649. 8 indexed citations
19.
Pan, Baoxiang, Kuolin Hsu, Amir AghaKouchak, & Soroosh Sorooshian. (2017). The Use of Convolutional Neural Network in Relating Precipitation to Circulation. AGU Fall Meeting Abstracts. 2017. 2 indexed citations
20.
Ma, Yi‐Wei, et al.. (2017). Attributing Crop Production in the United States Using Artificial Neural Network. AGU Fall Meeting Abstracts. 2017. 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Pertti Nurmi Breakdown of academic impact, for papers by Georgy Ayzel Breakdown of academic impact, for papers by Donglai Jiao Breakdown of academic impact, for papers by James Correia Breakdown of academic impact, for papers by Andrés Navarro Breakdown of academic impact, for papers by Jan D. Keller Breakdown of academic impact, for papers by Jiayong Liang Breakdown of academic impact, for papers by Negin Hayatbini Breakdown of academic impact, for papers by Tao-Chang Yang Breakdown of academic impact, for papers by Akshara Kaginalkar
Rankless by CCL
2026