Intercomparison of multiple statistical methods in post‐processing ensemble precipitation and temperature forecasts-Reference-Cited by-同舟云学术

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Intercomparison of multiple statistical methods in post‐processing ensemble precipitation and temperature forecasts

Published:2020-07 Issue:4 Volume:27 Page:
ISSN:1350-4827
Container-title:Meteorological Applications
language:en
Short-container-title:Meteorol Appl

Author:

Li Xiangquan¹,Chen Jie¹²^ORCID,Xu Chong‐Yu³,Chen Hua¹,Guo Shenglian¹

Affiliation:

1. State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan China

2. Hubei Provincial Key Lab of Water System Science for Sponge City Construction Wuhan University Wuhan China

3. Department of Geosciences University of Oslo Oslo Norway

Funder

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/met.1935

Reference40 articles.

1. The Skill of Ensemble Prediction Systems

2. Spatial and Interannual Variability of the Reliability of Ensemble-Based Probabilistic Forecasts: Consequences for Calibration

3. Censored and shifted gamma distribution based EMOS model for probabilistic quantitative precipitation forecasting

4. The quiet revolution of numerical weather prediction

5. From ensemble forecasts to predictive distribution functions

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Probabilistic post-processing of short to medium range temperature forecasts: Implications for heatwave prediction in India;Environmental Monitoring and Assessment;2024-02-19

2. Postprocessing Ensemble Weather Forecasts for Introducing Multisite and Multivariable Correlations Using Rank Shuffle and Copula Theory;Monthly Weather Review;2022-03

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