Schedule

22 April 2024

23 April 2024

24 April 2024

CI2024 will take place 22-24 April 2024, in BMA House, London, UK and online.

Please visit The Alan Turing Institute event page to register by 17 April 2024.

Monday 22 April 2024

UTC+1	DAY 1
09:30-10:30	Registration and networking with welcome refreshments
10:30-11:00	Welcome remarks (Scott Hosking)
11:00-12:00	How uncertain is future sea level rise? (Tamsin Edwards)
12:00-12:30	Morning break with refreshments
12:30-13:35	On Societal-relevant Applications (Chair Alden Conner) Mapping Housing Stock Characteristics from Drone Images for Climate Resilience in the CaribbeanAnnotations via NIDM-Terms Fosters Improved Search of OpenNeuro Datasets (Isabelle Tingzon) Envisioning Digital Twins for Instrumented Farms of the Future (Paul Harris) Using a large language model to create a chatbot companion for a major climate report (Arjun Biswas)
13:35-14:50	Lunch
16:45-15:55	On Hydrology modelling (Chair Kenza Tazi) Sensitivity analysis of causal discovery on simulated river flood data using non-linear conditional independence testing (Peter Miersch) Gaussian & Neural Processes in Hydrology (Robert Rouse) Hybrid climate simulation including machine-learnt subgrid variability from kilometre-scale weather simulation (James Briant)
15:55-16:25	Afternoon break with refreshments
16:25-17:25	Progress and challenges in ensemble weather forecasting with machine learning (Ilan Price)
17:25-17:35	Closing remarks for Day 1 (Scott Hosking)
18:15-onwards	“Climate Quizformatics” at Impact Hub, Euston (in-person attendees only, Hosts (Katy Thompson and Andrew McDonald)

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Tuesday 23 April 2024

UTC+1	DAY 2
09:00-09:30	Registration with welcome refreshments
09:30-09:35	Welcome back (Orlando Timmerman and Andrew McDonald)
09:35-10:35	The digital revolution of Earth system modelling (Peter Dueben)
10:40-11:45	On Weather & climate modeling (Chair Douglas Rao) Scalable Data Assimilation with Message Passing (Oscar Key) Will a climate simulation run? (Doug McNeall) Machine Learning for Stochastic Parametrisation (Hannah Christensen)
11:45-12:15	Morning break with refreshments
12:15-13:15	Panel: Perspectives on Practical Reproducibility in Climate Science (Marion Weinzierl, Dominic Orchard, Alejandro Coca-Castro, Chair Cassandra Gould van Praag)
13:15-14:30	Lunch
14:30-15:45	Virtual poster exhibition and afternoon refreshments
15:45-16:45	Lightning talks (Chair Meghna Asthana) Precipitation prediction from large-scale climatic features over the Upper Indus Basin using Gaussian Processes (Kenza Tazi) Spatially-Coherent Probabilistic Downscaling of Daily Precipitation in Ungauged Mountain Locations: A Transfer Learning Study in the Swiss Alps and the Langtang Valley, Nepal (Marc Girona-Mata) AI-assisted Climate Downscaling of the ERA5 Reanalysis for Rapid Assessment (Ilenia Manco) ~~Predicting visible ship tracks (Peter Manshausen) (moved to day 3)~~ Deep Learning for Lagrangian Drift Simulation on Sea Surface (Daria Botvynko)
16:50-17:50	Role of AI in tackling climate change (Anima Anandkumar)
17:50-18:00	Closing remarks for Day 2 (Orlando Timmerman and Andrew McDonald)
18:30-onwards	CI2024 Dinner at BMA House (in-person attendees only)

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Wednesday 24 April 2024

UTC+1	DAY 3
09:00-09:30	Registration with welcome refreshements
09:30-09:35	Welcome back (Cassandra Gould van Praag)
09:35-10:40	Lightning talks (Chair Guillaume Couairon Building probabilistic projections of the Antarctic contribution to global sea level rise using a random forest emulator (Fiona Turner) Reconstruction of Arctic sea ice thickness (1992-2010) based on a hybrid machine learning and data assimilation approach (Léo Edel) Modeling Snow on Sea Ice using Physics Guided Machine Learning (Ayush Prasad) Estimating high-resolution profiles of wind speeds from a global reanalysis dataset using TabNet (Harish Baki) Estimating global ocean POC fluxes through machine learning and data fusion on heterogeneous and sparse in-situ observations (Abhiraami Navaneethanathan) Improving ocean model generalisation by including water type classification as pre-processing to the satellite image (Solomon White) Predicting visible ship tracks (Peter Manshausen)
10:40-11:10	Morning break with refreshments
11:10-12:10	Panel: Ethics and Explainability in Climate AI: From Theory to Practice (Elizabeth Barnes , David-John Gagne, Galen McKinley, Savannah Thais, Chair Viviana Acquaviva)
12:10-13:10	Lunch
13:10-14:15	On Aerosol & Atmospheric Applications (Chair Ricardo Barros Lourenço) Accelerating GHG emissions inference using Graph Neural Networks (Elena Fillola) Untangling Aerosol Processes: Exploiting Explainable Machine Learning Techniques in a Lagrangian Framework (Eliza Duncan) Towards probabilistic aerosol retrievals with invertible neural networks (Paolo Pelucchi)
14:20-15:20	How We are Building Trustworthy AI for Weather and Climate in AI2ES (Amy McGovern and David-John Gagne)
15:20-15:50	Closing remarks for Day 3 and conference close (Cassandra Gould van Praag)
15:50-16:45	Farewell refreshments

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