Marlene Kretschmer

Check out our new PNAS paper (on changes of the SH eddy driven jet) led by Julia Mindlin 🌎🌍🌏

Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks Abstract. Atlantic hurricane activity varies substantially from year to year and so does the associated damage. Longer-term forecasting of hurricane risks is a key element to reduce damage and societa...

The methodology of our forecast is documented here:

wcd.copernicus.org/articles/1/3...

@marleneclimate.bsky.social @carlschleussner.bsky.social @TobiasGeiger

"Using causal networks to constrain regional drought projections" by Marina Friedel

session CL3.1.1 - Synoptic and Large-Scale Circulation Dynamics: Impacts on Regional Extremes, Climate Variability, and Change, room 0.14 on Friday, 14:32

"Disentangling reduced representations of teleconnections using variational autoencoders" by Fiona Spuler

session CL4.15 - Unravelling Climate Variability and Teleconnections Across Timescales, room 0.14 on Friday, 10:05

"Subseasonal and seasonal windows of forecast opportunity of extreme European winter weather"
by Fiona Spuler

session AS1.7 - Subseasonal-to-Seasonal Prediction, Processes and Applications, room 0.11/12 on Thursday, 09:00

"A Forensic Investigation of Climate Model Biases in Teleconnections: The Case of the Relationship BetweenENSO and the Northern Stratospheric Polar Vortex" by Xiaocen Shen

poster Hall X5 at board number X5.187. Thursday, 10:45-12:30.

"StoryPy: A Python-based package to compute climate storylines" by Richard Alawode et al.

poster Hall X5 at board number X5.188. Thursday, 10:45-12:30.

"Causal Pathways connecting Indian summer monsoon to the Arctic sea ice decline" by Sujata kulkarni

session CL2.6 - Climate variability and extremes through ocean, atmosphere and ice interactions: from model simulations to long time series observations, room 0.49/50 on Wednesday, 14:15

"High energy shortfall across 28 European countries during the winter: Investigation of the role of the Madden-Julian Oscillation and stratospheric polar vortex"
by Emmanuel Rouges

session ERE2.1 - Energy Meteorology, room -2.41/42 on Tuesday, 09:55:

"Combining spatio-temporal neural networks with mechanistic interpretability to investigate teleconnections in S2S forecasts" by Philine Bommer;

session ITS1.1/CL0.9 - Machine Learning for Climate Science, room C on Tuesday, 09:50:

"Quantifying the influence of Barents-Kara Sea ice loss on Ural blocking" by Ernest Agyemang-Oko;

poster Hall X5 at board number X5.73. Monday, 10:45-12:30.

EGU-FOMO? Here's a little thread with contributions from my group:

Can we predict euro weather regimes on S2S timescales with machine learning?
When including spatiotemporal information of stratospheric winds and tropical olr, our model shows competitive skill 👇

‪According to recent @wcrpclimate.bsky.social research, some regional shifts—like amplified Arctic warming—match predictions. However, climate model ensembles do not well simulate others, such as tropical sea surface temperatures and monsoon rainfall. Why?

We discuss 4 challenges, posing a high risk-high gain situation for ECRs: 1) working with impact scientists, 2) analysing big climate data, 3) applying machine learning, 4) engaging with stakeholders

Hope you enjoy reading it 👩‍💻🧑‍💻

Late to the party, but I also want to promote this new paper which will hopefully spark discussions in the conmunity: "A shifiting climate: New paradigms and challenges for (early career) scientists in extreme weather research"

rmets.onlinelibrary.wiley.com/doi/10.1002/...

Join us @UniLeipzig!

Three open positions in the climate causality research group (phd, postdoc, data scientist) on drivers of extreme events ❄️🌡🌧

Details here: speicherwolke.uni-leipzig.de/index.php/s/...