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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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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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The impact of the COVID-19 pandemic on air pollution: A global assessment using machine learning techniques
In response to the COVID-19 pandemic, most countries implemented public health ordinances that re...
Jasper S. Wijnands, Kerry A. Nice, Sachith Seneviratne, Jason Thompson, Mark Stevenson | Journal: Atmospheric Pollution Research | Volume: 13 | Year: 2022 | doi: https://doi.org/10.1016/j.apr.2022.101438
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Support vector machine tropical wind speed retrieval in the presence of rain for Ku-band wind scatterometry
Wind retrieval parameters, i.e. quality indicators and the two-dimensional variational ambiguity ...
Xingou Xu, Ad Stoffelen
| Journal: Atmospheric Measurement Techniques | Volume: 14 | Year: 2021 | doi: https://doi.org/10.5194/amt-14-7435-2021
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