Norske meteorittkratre @realfagsbiblioteket

UiO Realfagsbiblioteket | Norske meteorittkratre @realfagsbiblioteket | Uploaded March 2020 | Updated October 2024, 13 hours ago.
Velkommen til mars utgaven av Geo-onsdag! Denne gangen er det foredrag ved Henning Dypvik, Professor ved Seksjon for geologi og geofysikk.
Meteorittkratre dannes ved kollisjoner mellom planeter (f.eks. Jorden), og kometer eller asteroider. På Jorden er det til nå funnet 190 store kratre, mens vi i Norge har tre; Mjølnir, Gardnoskrateret og Ritlandskrateret. De blir alle tre presentert i foredraget; hvordan de ble dannet og funnet, har de noen som helst betydning og hva vi kan forvente av tilsvarende aktivitet i fremtiden? Prof. Henning Dypvik er bl.a. involvert i utforskingen av de tre norske kratrene.
https://www.ub.uio.no/kurs-arrangement/arrangementer/ureal/2020/200311geoonsdag.html

$Exploring System Dynamics in the Natural World with AI - John M. Aiken John M. Aiken (University of Oslo, Expert Analytics) - Welcome Talk William Gilpin (UT Austin) - Model scale versus domain knowledge in long-term forecasting of chaos Welcome to a conference on discovery and prediction in complex geo systems. AI/ML shows promise for accelerating Bayesian inversions, is able to capture and identify controlling features of high fidelity models, and appears to improve complex system analysis, including extending predictive horizons, for reasons that are not fully understood. This conference focuses on efforts to advance the use of AI/ML to understand physical processes in the geosciences and adjacent fields. AI/ML shows promise for accelerating Bayesian inversions, is able to capture and identify aspects of the dynamics of high fidelity models, and appears to improve complex system analysis, including extending predictive horizons, for reasons that are not fully understood. This has been demonstrated across the physical sciences including for geophysical modeling, fracture mechanics, and climate and weather prediction. This conference focuses on efforts to advance the use of AI/ML to understand physical processes in the geosciences and adjacent fields, and brings together practitioners and theorists from academia and industry for an open exchange of current results and discussions of future strategies. A central goal is to encourage diversity and collaboration between different disciplines, all through AI/ML practice, and to identify new connections between applications in fields, from networks to earthquakes, and turbulence to chaos. https://www.ub.uio.no/english/courses-events/events/mednat/ureal/2024/240930conference.html$

Atmosphere - biosphere changes through time: Evidence from weathering and paleosol formation