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Modeling and simulating spatial extremes by combining extreme value theory with generative adversarial networks
Modeling dependencies between climate extremes is important for climate risk assessment, for inst...
Y Boulaguiem, J Zschleischler, E Vignotto, K van der Wiel, S Engelke | Journal: Environmental Data Science | Volume: 1 | Year: 2022 | First page: e5 | doi: 10.1017/eds.2022.4
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Preparing local climate change scenarios for the Netherlands using resampling of climate model output.
A method to prepare a set of four climate scenarios for the Netherlands is presented. These scena...
G Lenderink, BJJM van den Hurk, AMG Klein Tank, GJ van Oldenborgh, E van Meijgaard, H de Vries, JJ Beersma | Status: published | Journal: Environmental Research Letters | Volume: 9 | Year: 2014 | First page: 115008 | doi: 10.1088/1748-9326/9/11/115008
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Comparison of parallel wind measurement with Sonic and Cup-Vane at nine locations for climatological applications
The instrument replacement of cup/vane wind measurements to sonic (THIES 2D) has a negligibly sma...
G Groen | Year: 2011 | Pages: 15
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The response of the African summer monsoon to remote and local forcing due to precession and obliquity
In this paper we examine the orbital signal in Earth's climate with a coupled model of intermedia...
E Tuenter, SL Weber, FJ Hilgen, LJ Lourens | Status: published | Journal: Global and Planetary Change | Volume: 36 | Year: 2003 | First page: 219 | Last page: 235 | doi: 10.1016/S0921-8181(02)00196-0
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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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