Código QR (código de barras bidimensional)

Interpretable Multiscale Machine Learning‐Based Parameterizations of Convection for ICON

Abstract Machine learning (ML)‐based parameterizations have been developed for Earth System Models (ESMs) with the goal to better represent subgrid‐scale processes or to accelerate computations. ML‐based parameterizations within hybrid ESMs have successfully learned subgrid‐scale processes from shor...

תיאור מלא

שמור ב:
Principais autores: Helge Heuer, Mierk Schwabe, Pierre Gentine, Marco A. Giorgetta, Veronika Eyring
פורמט: Artigo
שפה:Inglês
יצא לאור: American Geophysical Union (AGU) 2024-08-01
סדרה:Journal of Advances in Modeling Earth Systems
נושאים:
parameterization
machine learning
convection
subgrid
climate model
XAI
גישה מקוונת:https://doi.org/10.1029/2024MS004398
תגים: הוספת תג
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!

פריטים דומים