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Tellus A: Dynamic Meteorology and Oceanography Volume 63, 2011 - Issue 5
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Original Articles

Calibrating probabilistic forecasts from an NWP ensemble

Thomas NipenUniversity of British Columbia, Vancouver, CanadaCorrespondencee-mail: [email protected]
&
Roland StullUniversity of British Columbia, Vancouver, Canada
Pages 858-875 | Received 12 Dec 2010, Accepted 21 Jun 2011, Published online: 15 Dec 2016

Citations (14)

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Read on this site (1)

Dominique R. Bourdin, Sean W. Fleming & Roland B. Stull. (2012) Streamflow Modelling: A Primer on Applications, Approaches and Challenges. Atmosphere-Ocean 50:4, pages 507-536.
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Articles from other publishers (13)

Nibedita Samal, R. Ashwin, Akshay Singhal, Sanjeev Kumar Jha & David E. Robertson. (2023) Using a Bayesian joint probability approach to improve the skill of medium-range forecasts of the Indian summer monsoon rainfall. Journal of Hydrology: Regional Studies 45, pages 101284.
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Elizabeth A. Barnes, Randal J. Barnes & Mark DeMaria. (2023) Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts. Environmental Data Science 2.
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Tae-Ho Kang, Ashish Sharma & Lucy Marshall. (2021) Assessing Goodness of Fit for Verifying Probabilistic Forecasts. Forecasting 3:4, pages 763-773.
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Masoud Zaerpour, Simon Michael Papalexiou & Ali Nazemi. (2021) Informing Stochastic Streamflow Generation by Large-Scale Climate Indices at Single and Multiple Sites. Advances in Water Resources 156, pages 104037.
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Qichun Yang, Quan J. Wang & Kirsti Hakala. (2021) Achieving effective calibration of precipitation forecasts over a continental scale. Journal of Hydrology: Regional Studies 35, pages 100818.
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Ashkan Zarnani, Soheila Karimi & Petr Musilek. (2019) Quantile Regression and Clustering Models of Prediction Intervals for Weather Forecasts: A Comparative Study. Forecasting 1:1, pages 169-188.
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André Gensler, Bernhard Sick & Stephan Vogt. (2018) A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies. Renewable and Sustainable Energy Reviews 96, pages 352-379.
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Yixuan Zhong, Shenglian Guo, Huanhuan Ba, Feng Xiong, Fi-John Chang & Kairong Lin. (2018) Evaluation of the BMA probabilistic inflow forecasts using TIGGE numeric precipitation predictions based on artificial neural network. Hydrology Research 49:5, pages 1417-1433.
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David M. Siuta & Roland B. Stull. (2018) Benefits of a multimodel ensemble for hub-height wind prediction in mountainous terrain. Wind Energy 21:9, pages 783-800.
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David Siuta, Gregory West, Roland Stull & Thomas Nipen. (2017) Calibrated Probabilistic Hub-Height Wind Forecasts in Complex Terrain. Weather and Forecasting 32:2, pages 555-577.
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Ashkan Zarnani, Petr Musilek & Jana Heckenbergerova. (2014) Clustering numerical weather forecasts to obtain statistical prediction intervals. Meteorological Applications 21:3, pages 605-618.
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Dominique R. Bourdin, Thomas N. Nipen & Roland B. Stull. (2014) Reliable probabilistic forecasts from an ensemble reservoir inflow forecasting system. Water Resources Research 50:4, pages 3108-3130.
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Dominique R. Bourdin & Roland B. Stull. (2013) Bias-corrected short-range Member-to-Member ensemble forecasts of reservoir inflow. Journal of Hydrology 502, pages 77-88.
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