OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods
Yao Tong, Xuejie Gao, Zhenyu Han, et al.
Climate Dynamics (2020) Vol. 57, Iss. 5-6, pp. 1425-1443
Open Access | Times Cited: 148

Showing 1-25 of 148 citing articles:

Future changes in precipitation and temperature over the Yangtze River Basin in China based on CMIP6 GCMs
Yanlin Yue, Dan Yan, Qun Yue, et al.
Atmospheric Research (2021) Vol. 264, pp. 105828-105828
Closed Access | Times Cited: 104

Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change
Qigen Lin, Stefan Steger, Massimiliano Pittore, et al.
The Science of The Total Environment (2022) Vol. 850, pp. 158049-158049
Closed Access | Times Cited: 87

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China
Zizheng Guo, Joaquin V. Ferrer, Marcel Hürlimann, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 4, pp. 101542-101542
Open Access | Times Cited: 68

On deep learning-based bias correction and downscaling of multiple climate models simulations
Fang Wang, Di Tian
Climate Dynamics (2022) Vol. 59, Iss. 11-12, pp. 3451-3468
Closed Access | Times Cited: 62

Deep Learning for Improving Numerical Weather Prediction of Heavy Rainfall
Philipp Hess, Niklas Boers
Journal of Advances in Modeling Earth Systems (2022) Vol. 14, Iss. 3
Open Access | Times Cited: 61

Physically constrained generative adversarial networks for improving precipitation fields from Earth system models
Philipp Hess, Markus Drüke, Stefan Petri, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 10, pp. 828-839
Open Access | Times Cited: 46

A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Huajin Lei, Hongyu Zhao, Tianqi Ao
Hydrology and earth system sciences (2022) Vol. 26, Iss. 11, pp. 2969-2995
Open Access | Times Cited: 42

Customized deep learning for precipitation bias correction and downscaling
Fang Wang, Di Tian, Mark Carroll
Geoscientific model development (2023) Vol. 16, Iss. 2, pp. 535-556
Open Access | Times Cited: 25

Performance assessment of bias correction methods using observed and regional climate model data in different watersheds, Ethiopia
Habtamu Daniel
Journal of Water and Climate Change (2023) Vol. 14, Iss. 6, pp. 2007-2028
Open Access | Times Cited: 22

Estimations of potential evapotranspiration from CMIP6 multi-model ensemble over Africa
Ibrahim Yahaya, Zhenjie Li, Jian Zhou, et al.
Atmospheric Research (2024) Vol. 300, pp. 107255-107255
Closed Access | Times Cited: 8

Impacts of Climate Change on Extreme Climate Indices in Türkiye Driven by High-Resolution Downscaled CMIP6 Climate Models
Berkin Gümüş, Sertaç Oruç, İsmail Yücel, et al.
Sustainability (2023) Vol. 15, Iss. 9, pp. 7202-7202
Open Access | Times Cited: 20

Precipitation Bias Correction: A Novel Semi‐parametric Quantile Mapping Method
Chandra Rupa Rajulapati, Simon Michael Papalexiou
Earth and Space Science (2023) Vol. 10, Iss. 4
Open Access | Times Cited: 18

Improving Subseasonal‐To‐Seasonal Prediction of Summer Extreme Precipitation Over Southern China Based on a Deep Learning Method
Yang Lyu, Shoupeng Zhu, Xiefei Zhi, et al.
Geophysical Research Letters (2023) Vol. 50, Iss. 24
Open Access | Times Cited: 17

A warming-induced glacier reduction causes lower streamflow in the upper Tarim River Basin
Lina Liu, Liping Zhang, Qin Zhang, et al.
Journal of Hydrology Regional Studies (2024) Vol. 53, pp. 101802-101802
Open Access | Times Cited: 6

Projecting Health Impacts of Future Temperature: A Comparison of Quantile-Mapping Bias-Correction Methods
Weijia Qian, Howard H. Chang
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 4, pp. 1992-1992
Open Access | Times Cited: 32

Comparison of different quantile delta mapping schemes in frequency analysis of precipitation extremes over mainland Southeast Asia under climate change
Xiaosheng Qin, Chao Dai
Journal of Hydrology (2022) Vol. 606, pp. 127421-127421
Open Access | Times Cited: 23

Classification of extreme heatwave events in the Northern Hemisphere through a new method
Yuqing Wang, Chunzai Wang
Climate Dynamics (2023) Vol. 61, Iss. 3-4, pp. 1947-1969
Closed Access | Times Cited: 13

Deep Learning for Bias‐Correcting CMIP6‐Class Earth System Models
Philipp Hess, Stefan Lange, Christof Schötz, et al.
Earth s Future (2023) Vol. 11, Iss. 10
Open Access | Times Cited: 13

Using Copula functions to predict climatic change impacts on floods in river source regions
Tingxing Chen, Haishen Lyu, Robert Horton, et al.
Advances in Climate Change Research (2024) Vol. 15, Iss. 3, pp. 406-418
Open Access | Times Cited: 4

Assessing the impact of bias correction approaches on climate extremes and the climate change signal
Hong Zhang, Sarah Chapman, Ralph Trancoso, et al.
Meteorological Applications (2024) Vol. 31, Iss. 3
Open Access | Times Cited: 4

Future changes in extremes across China based on NEX-GDDP-CMIP6 models
Yang Bao-gang, Linxiao Wei, Hongyu Tang, et al.
Climate Dynamics (2024) Vol. 62, Iss. 10, pp. 9587-9617
Open Access | Times Cited: 4

Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood
Ling Zhang, Zhongshi Zhang, Lu Li, et al.
npj Climate and Atmospheric Science (2025) Vol. 8, Iss. 1
Open Access

Comparative analysis of bias correction methods for projecting extreme precipitation and temeprature indices in Pakistan
Zulfiqar Ali, Mohd Khairul Idlan Muhammad, Mansour Almazroui, et al.
Atmospheric Research (2025), pp. 107957-107957
Closed Access

Quantile-based bias-correction of extreme rainfall: Pros & cons of popular methods for climate signal preservation
Roberta Padulano, L.A. Gomez-Mogollon, L. G. Napolitano, et al.
Journal of Hydrology (2025), pp. 132814-132814
Closed Access

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