library:external:posters
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision | |||
|
library:external:posters [2026/03/30 12:30] mcosta [2026] |
library:external:posters [2026/03/30 12:30] (current) mcosta [2026] |
||
|---|---|---|---|
| Line 10: | Line 10: | ||
| - CERTAINTY Annual Meeting (Helsinki, Finland, 17-19 March 2026), Updates and Improvements to EC-Earth4: Mineral Dust Scheme and Cold Cloud Processes, M. Chatziparaschos et al. (CERTAINTY). {{ : | - CERTAINTY Annual Meeting (Helsinki, Finland, 17-19 March 2026), Updates and Improvements to EC-Earth4: Mineral Dust Scheme and Cold Cloud Processes, M. Chatziparaschos et al. (CERTAINTY). {{ : | ||
| - | - CERTAINTY Annual Meeting (Helsinki, Finland, 17-19 March 2026), From prescribed to interactive aerosols: implications for | + | - CERTAINTY Annual Meeting (Helsinki, Finland, 17-19 March 2026), From prescribed to interactive aerosols: implications for decadal prediction, L. Garcia-Oliva et al. (CERTAINTY, RES AECT-2025-3-0044). {{library: |
| - | decadal prediction, L. Garcia-Oliva et al. (CERTAINTY, RES AECT-2025-3-0044). {{library: | + | |
| - Ellis Winter School 2026 AI for Earth Hazards & Climate Extremes (Athens, Greece, March 15th, 2026). Deep learning dust forecasting from observations using partial convolutions. M. Hortelano et al. {{ : | - Ellis Winter School 2026 AI for Earth Hazards & Climate Extremes (Athens, Greece, March 15th, 2026). Deep learning dust forecasting from observations using partial convolutions. M. Hortelano et al. {{ : | ||
| - CMIP Community Workshop 2026 (Online, March 9th-13th, 2026), Quantifying the Scientific Skill of High-Resolution Models with pyhanami, M. Alerany Solé et al. (HANAMI) {{ : | - CMIP Community Workshop 2026 (Online, March 9th-13th, 2026), Quantifying the Scientific Skill of High-Resolution Models with pyhanami, M. Alerany Solé et al. (HANAMI) {{ : | ||
library/external/posters.txt · Last modified: 2026/03/30 12:30 by mcosta
Page Tools
