Session SC2.23

SC2.23 | Using Machine Learning to downscale climate scenarios

Using Machine Learning to downscale climate scenarios

Co-organized by AS6/CL6/CR8/ESSI6/HS11/NH15/SSS13

Convener: Christian Pagé | Co-conveners: Irida LazicECSECS, Milica TosicECSECS

Mon, 04 May, 08:30–10:15 (CEST)

Room -2.82

This short course will train you how to use robust Machine Learning methods to do statistical downscaling of coarse climate model scenarios. A sample dataset will be used: daily surface temperature from one Global Climate Model of the CMIP6 database (historical and future climate time periods), along with a high resolution reanalysis.
Introduction on climate statistical downscaling
Methodology: classical and Machine-Learning based
Steps to perform downscaling
Sample datasets
Results
All material will be made available online, and a sample Jupyter Notebook will be provided.

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.