Downscaling Climate Models with Physics-informed Machine Learning to tackle the Energy Transition: Presentation of the EnergAIze project at the internal AI4Green networking event.

Jasmin Lampert; Pascal Léon Thiele; Marianne Bügelmayer-Blaschek; Kristofer Hasel; Theresa Schellander-Gorgas; Irene Schicker

Downscaling Climate Models with Physics-informed Machine Learning to tackle the Energy Transition: Presentation of the EnergAIze project at the internal AI4Green networking event.

Jasmin Lampert (Speaker), Pascal Léon Thiele, Marianne Bügelmayer-Blaschek, Kristofer Hasel, Theresa Schellander-Gorgas, Irene Schicker

Geological Survey of Austria

Research output: Poster presentation without proceedings

Translated title of the contribution	Downscaling von Klimamodellen mit physikalisch informiertem maschinellem Lernen zur Bewältigung der Energiewende: Präsentation des EnergAIze Projekts auf einem internen AI4Green Networking Event.
Original language	English
Number of pages	1
Publication status	Published - 26 Jun 2024
Event	AI for Green - Vienna, Austria Duration: 26 Jun 2024 → 26 Jun 2024

Other

Other	AI for Green
Country/Territory	Austria
City	Vienna
Period	26/06/24 → 26/06/24

Research Field

Multimodal Analytics
Climate Resilient Pathways

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

@conference{2abe46ebd8bc40d1b5476f5dcf30f85c,

title = "Downscaling Climate Models with Physics-informed Machine Learning to tackle the Energy Transition: Presentation of the EnergAIze project at the internal AI4Green networking event.",

keywords = "Physics-informed Machine Learning, Climate Change, Energy Meteorology, Energy transition, Downscaling",

author = "Jasmin Lampert and Thiele, {Pascal L{\'e}on} and Marianne B{\"u}gelmayer-Blaschek and Kristofer Hasel and Theresa Schellander-Gorgas and Irene Schicker",

year = "2024",

month = jun,

day = "26",

language = "English",

note = "AI for Green ; Conference date: 26-06-2024 Through 26-06-2024",

}

Downscaling Climate Models with Physics-informed Machine Learning to tackle the Energy Transition: Presentation of the EnergAIze project at the internal AI4Green networking event. / Lampert, Jasmin (Speaker); Thiele, Pascal Léon ; Bügelmayer-Blaschek, Marianne et al.
2024. Paper presented at AI for Green, Vienna, Austria.

Research output: Poster presentation without proceedings

TY - CONF

T1 - Downscaling Climate Models with Physics-informed Machine Learning to tackle the Energy Transition

T2 - AI for Green

AU - Thiele, Pascal Léon

AU - Bügelmayer-Blaschek, Marianne

AU - Hasel, Kristofer

AU - Schellander-Gorgas, Theresa

AU - Schicker, Irene

A2 - Lampert, Jasmin

PY - 2024/6/26

Y1 - 2024/6/26

KW - Physics-informed Machine Learning

KW - Climate Change

KW - Energy Meteorology

KW - Energy transition

KW - Downscaling

M3 - Poster presentation without proceedings

Y2 - 26 June 2024 through 26 June 2024

ER -

Downscaling Climate Models with Physics-informed Machine Learning to tackle the Energy Transition: Presentation of the EnergAIze project at the internal AI4Green networking event.

Other

Research Field

UN SDGs

Other files and links

Cite this