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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:

Evaluation of Subseasonal-to-Seasonal (S2S) precipitation forecast from the North American Multi-Model ensemble phase II (NMME-2) over the contiguous U.S.
Lujun Zhang, Taereem Kim, Tiantian Yang, et al.
Journal of Hydrology (2021) Vol. 603, pp. 127058-127058
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Near real-time hurricane rainfall forecasting using convolutional neural network models with Integrated Multi-satellitE Retrievals for GPM (IMERG) product
Taereem Kim, Tiantian Yang, Lujun Zhang, et al.
Atmospheric Research (2022) Vol. 270, pp. 106037-106037
Open Access | Times Cited: 28
Subseasonal prediction of weekly precipitation anomalies over Southern China during early summer based on predictability analysis and machine learning
Yang Lyu, Xiefei Zhi, Shoupeng Zhu, et al.
Atmospheric Research (2025), pp. 107927-107927
Closed Access
A seven-parameter Bernoulli-Gamma-Gaussian model to calibrate subseasonal to seasonal precipitation forecasts
Zeqing Huang, Tongtiegang Zhao, Weixin Xu, et al.
Journal of Hydrology (2022) Vol. 610, pp. 127896-127896
Open Access | Times Cited: 25
Adaptive bias correction for improved subseasonal forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 14
Adapting subseasonal-to-seasonal (S2S) precipitation forecast at watersheds for hydrologic ensemble streamflow forecasting with a machine learning-based post-processing approach
Lujun Zhang, Shang Gao, Tiantian Yang
Journal of Hydrology (2024) Vol. 631, pp. 130643-130643
Closed Access | Times Cited: 4
Investigating the streamflow simulation capability of a new mass-conserving long short-term memory (MC-LSTM) model across the contiguous United States
Y Wang, Lujun Zhang, N. Benjamin Erichson, et al.
Journal of Hydrology (2025), pp. 133161-133161
Closed Access
Improving subseasonal forecast of precipitation in Europe by combining a stochastic weather generator with dynamical models
Meriem Krouma, Damien Specq, Linus Magnusson, et al.
Quarterly Journal of the Royal Meteorological Society (2024) Vol. 150, Iss. 762, pp. 2744-2764
Open Access | Times Cited: 3
Understanding China's industrialization driven water pollution stress in 2002–2015—A multi-pollutant based net gray water footprint analysis
Zhongwen Yang, Bin Li, Rui Xia, et al.
Journal of Environmental Management (2022) Vol. 310, pp. 114735-114735
Closed Access | Times Cited: 12
Evaluation of subseasonal precipitation forecasts in the Uruguay River basin
Juan Badagian, Marcelo Barreiro, Ramiro I. Saurral
International Journal of Climatology (2024) Vol. 44, Iss. 14, pp. 5233-5247
Closed Access | Times Cited: 2
The characterization, mechanism, predictability, and impacts of the unprecedented 2023 Southeast Asia heatwave
Yang Lyu, Jingyu Wang, Xiefei Zhi, et al.
npj Climate and Atmospheric Science (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 2
Improving Subseasonal-to-Seasonal forecasts in predicting the occurrence of extreme precipitation events over the contiguous U.S. using machine learning models
Lujun Zhang, Tiantian Yang, Shang Gao, et al.
Atmospheric Research (2022) Vol. 281, pp. 106502-106502
Open Access | Times Cited: 11
Assessment of subseasonal-to-seasonal (S2S) ensemble extreme precipitation forecast skill over Europe
Pauline Rivoire, Olivia Martius, Philippe Naveau, et al.
Natural hazards and earth system sciences (2023) Vol. 23, Iss. 8, pp. 2857-2871
Open Access | Times Cited: 6
Improving Global Subseasonal to Seasonal Precipitation Forecasts Using a Support Vector Machine‐Based Method
Gaohong Yin, Takao Yoshikane, Ryo Kaneko, et al.
Journal of Geophysical Research Atmospheres (2023) Vol. 128, Iss. 17
Open Access | Times Cited: 5
Analyses on the Multimodel Wind Forecasts and Error Decompositions over North China
Yang Lyu, Xiefei Zhi, Hong Wu, et al.
Atmosphere (2022) Vol. 13, Iss. 10, pp. 1652-1652
Open Access | Times Cited: 9
Assessment of Subseasonal-to-Seasonal (S2S) Precipitation Forecast Skill for Reservoir Operation in the Yaque Del Norte River, Dominican Republic
Norman Pelak, Eylon Shamir, Theresa Modrick Hansen, et al.
Water (2024) Vol. 16, Iss. 14, pp. 2032-2032
Open Access | Times Cited: 1
Lessons learned from the co-development of operational climate forecast services for vineyards management
Núria Pérez-Zañón, Victòria Agudetse, Eulàlia Baulenas, et al.
Climate Services (2024) Vol. 36, pp. 100513-100513
Open Access | Times Cited: 1
Advanced Rule-Based System for Rainfall Occurrence Forecasting by Integrating Machine Learning Techniques
Vikas Kumar Vidyarthi, Ashu Jain
Journal of Water Resources Planning and Management (2022) Vol. 149, Iss. 1
Closed Access | Times Cited: 4
Advancing subseasonal reservoir inflow forecasts using an explainable machine learning method
Ming Fan, Siyan Liu, Dan Lu
Journal of Hydrology Regional Studies (2023) Vol. 50, pp. 101584-101584
Open Access | Times Cited: 2
How to choose credible ensemble members for the sub-seasonal to seasonal prediction of precipitation?
Weihua Jie, Tongwen Wu, Frédéric Vitart, et al.
Climate Dynamics (2022) Vol. 61, Iss. 3-4, pp. 1257-1276
Open Access | Times Cited: 3
Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1–4 over South Africa
Steven Phakula, Willem A. Landman, Christien J. Engelbrecht
Meteorological Applications (2024) Vol. 31, Iss. 1
Open Access
Evaluation of Subseasonal-to-Seasonal (S2S) precipitation forecast performance from NMME-2 over Indonesia
Dimas Adi Nugraha, Muhammad Ridho Syahputra, Muhammad Rais Abdillah, et al.
IOP Conference Series Earth and Environmental Science (2024) Vol. 1350, Iss. 1, pp. 012006-012006
Open Access
Improving the Skill of Subseasonal to Seasonal (S2S) Wind Speed Forecasts Over India Using Statistical and Machine Learning Methods
Aheli Das, Dondeti Pranay Reddy, Somnath Baidya Roy
Journal of Geophysical Research Machine Learning and Computation (2024) Vol. 1, Iss. 4
Open Access
A robust skill verification of hindcast decadal experiments on streamflow regimes using CMIP6 data
Venkatesh Budamala, Tirthankar Roy, Rajarshi Das Bhowmik
Journal of Hydrology (2024), pp. 132525-132525
Closed Access
Enhancing monthly precipitation forecasting by integrating multi-source data with machine learning models: a study in the Upper Blue Nile Basin
Juhar Mohammed, Yenesew Mengiste, Mekonnen Gebremichael
Modeling Earth Systems and Environment (2024) Vol. 11, Iss. 1
Closed Access
Evaluation on the Forecast Skills of Precipitation and Its Influencing Factors in the Flood Season in Liaoning Province of China
Yihe Fang, Dakai Jiang, Chenghan Liu, et al.
Atmosphere (2023) Vol. 14, Iss. 4, pp. 668-668
Open Access | Times Cited: 1
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