Auflistung nach Mitwirkenden "Eyring, Veronika"
Anzeige der Dokumente 1-5 von 5
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Constraining Uncertainty in Projected Gross Primary Production With Machine Learning
; ; Camps‐Valls, Gustau; Friedlingstein, Pierre; ; (Journal of Geophysical Research: Biogeosciences, 2020-11-21)
The terrestrial biosphere is currently slowing down global warming by absorbing about 30% of human emissions of carbon dioxide (CO2). The largest flux of the terrestrial carbon uptake is gross primary production (GPP) ... -
Deep Learning Based Cloud Cover Parameterization for ICON
; ; ; ; ; (Journal of Advances in Modeling Earth Systems, 2022-12-14)
A promising approach to improve cloud parameterizations within climate models and thus climate projections is to use deep learning in combination with training data from storm‐resolving model (SRM) simulations. The ICOsahedral ... -
Detecting Extreme Temperature Events Using Gaussian Mixture Models
; ; ; ; ; (Journal of Geophysical Research: Atmospheres, 2023-09-22)
Abstract Extreme temperature events have traditionally been detected assuming a unimodal distribution ...
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Do Emergent Constraints on Carbon Cycle Feedbacks Hold in CMIP6?
; ; ; ; (Journal of Geophysical Research: Biogeosciences, 2022-12-05)
Emergent constraints on carbon cycle feedbacks in response to warming and increasing atmospheric CO2 concentration have previously been identified in Earth system models participating in the Coupled Model ... -
Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models
; ; ; ; ; (Journal of Advances in Modeling Earth Systems, 2022-08-13)
Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal ...
