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@INPROCEEDINGS{Schultz:905400,
author = {Schultz, Martin},
title = {{D}eep {L}earning for {W}eather {F}orecasting and {C}limate
{P}rediction},
reportid = {FZJ-2022-00652},
year = {2022},
note = {Publication website includes recorded streaming. AI4Good
website: https://aiforgood.itu.int/},
abstract = {AI methods are rapidly taking hold in almost any aspect of
our lives. In some specialized application areas, computers
are outperforming humans with respect to image or audio
analysis, speech recognition, and controlled movements.
Nevertheless, weather and climate prediction still uses
humongous computer codes, which solve thousands of
differential equations on the fastest supercomputers.
Everywhere along the workflow of such prediction systems
researchers are trying out how AI could transform or even
revolutionize weather and climate forecasting. While there
are some promising research pathways, several scientific and
technical challenges have to be overcome before we might see
a widespread adaptation of such methods in weather centres
and research organisations. I will discuss recent
achievements and ongoing activities and I may be tempted to
speculate about fundamental, inherent limitations of AI
concepts in this application area.},
month = {Jan},
date = {2022-01-12},
organization = {AI4Good, virtual (Switzerland), 12 Jan
2022 - 12 Jan 2022},
subtyp = {Invited},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / Earth System Data
Exploration (ESDE)},
pid = {G:(DE-HGF)POF4-5111 / G:(DE-Juel-1)ESDE},
typ = {PUB:(DE-HGF)6},
url = {https://juser.fz-juelich.de/record/905400},
}