activity
20192024
most citedDeep reinforcement learning in World-Earth system models to discover sustainable management strategies

26 citations · 71 across the 6 of their papers we have counts for

collaborators

6 papers

physics.ao-ph2024

Intraseasonal synchronization of extreme rainfalls between North India and the Sahel

Felix Strnad, Kieran M. R. Hunt, Niklas Boers +1

The Indian Summer Monsoon (ISM) and the West African Monsoon (WAM) are dominant drivers of boreal summer precipitation variability in tropical and subtropical regions. Although the…

physics.ao-ph2023★ 1 cited

Contributions of El Niño Southern Oscillation (ENSO) Diversity to Low-Frequency Changes in ENSO Variance

Jakob Schlör, Felix Strnad, Antonietta Capotondi +1

El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical…

physics.ao-ph2023★ 26 cited

Extreme rainfall propagation within Boreal Summer Intraseasonal Oscillation modulated by Pacific sea surface temperature

Felix M. Strnad, Jakob Schloer, Ruth Geen +2

Intraseasonal variations of the South Asian Summer Monsoon (SASM) contain alternating extreme rainfall (active) and low rainfall (break) phases impacting agriculture and economies.…

physics.ao-ph2022★ 3 cited

Physically Constrained Generative Adversarial Networks for Improving Precipitation Fields from Earth System Models

Philipp Hess, Markus Drüke, Stefan Petri +2

Precipitation results from complex processes across many scales, making its accurate simulation in Earth system models (ESMs) challenging. Existing post-processing methods can impr…

physics.ao-ph2022★ 15 cited

Teleconnection patterns of different El Niño types revealed by climate network curvature

Felix M. Strnad, Jakob Schlör, Christian Fröhlich +1

The diversity of El Niño events is commonly described by two distinct flavors, the Eastern Pacific (EP) and Central Pacific (CP) types. While the remote impacts, i.e. teleconnectio…

physics.soc-ph2019★ 26 cited

Deep reinforcement learning in World-Earth system models to discover sustainable management strategies

Felix M. Strnad, Wolfram Barfuss, Jonathan F. Donges +1

Increasingly complex, non-linear World-Earth system models are used for describing the dynamics of the biophysical Earth system and the socio-economic and socio-cultural World of h…