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Comparing Area Probability Forecasts of (Extreme) Local Precipitation Using Parametric and Machine Learning Statistical Postprocessing Methods
Probabilistic forecasts, which communicate forecast uncertainties, enable users to make better we...
KRP Whan, MJ Schmeits | Status: published | Journal: Mon. Wea. Rev. | Volume: 146 | Year: 2018 | First page: 3651 | Last page: 3673 | doi: 10.1175/MWR-D-17-0290.1
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Aerosol Absorption over Land Derived from the Ultra-Violet Aerosol Index by Deep Learning.
Quantitative measurements of aerosol absorptive properties, e.g., the absorbing aerosol optical d...
J. Sun, P. Veefkind, P. Van Velthoven, P. Levelt | Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Volume: 14 | Year: 2021 | First page: 9692 | Last page: 9710 | doi: 10.1109/JSTARS.2021.3108669
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Deep Learning for Solar Irradiance Nowcasting: A Comparison of a Recurrent Neural Network and Two Traditional Methods
This paper aims to improve short-term forecasting of clouds to accelerate the usability of solar ...
Dennis Knol, Fons de Leeuw, Jan Fokke Meirink, Valeria V. Krzhizhanovskaya | Year: 2021
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Using Explainable Machine Learning Forecasts to Discover Subseasonal Drivers of High Summer Temperatures in Western and Central Europe
Reliable subseasonal forecasts of high summer temperatures would be very valuable for society. Al...
Chiem van Straaten, Kirien Whan, Dim Coumou, Bart van den Hurk, and Maurice Schmeits | Journal: Monthly Weather Review | Volume: 150 | Year: 2022 | First page: 1115 | Last page: 1134 | doi: https://doi.org/10.1175/MWR-D-21-0201.1
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Short-Term Forecasting of High-Impact Weather with Physics-Guided Machine Learning : Technical Report
Extreme weather events such as heavy storms and heavy precipitation have a large impact on our so...
C. A. Severijns & G. A. Pagani
| Year: 2023 | Pages: 12
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