🌀 Weather and climate graphics for science communication 🌀
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Updated
Dec 20, 2022 - Python
🌀 Weather and climate graphics for science communication 🌀
📈 Series of workshops and lectures using Python in the climate/atmospheric sciences 📉
Code used to identify and analyze drought clusters from gridded data.
Assessing the influence of the QBO in Arctic sea ice perturbation experiments
(Non)linear atmospheric response to Arctic Amplification forcing
Large ensemble to explore robustness of stratospheric response to Arctic sea-ice loss
Using neural networks to detect effects of rapid climate mitigation
Evaluating anomalously early spring onsets in the 21st century
ANN detecting signal from internal variability
Using a neural network to predict changes in the rate of global mean surface temperature warming
Large-scale atmospheric response to Antarctic sea ice loss
Historical sea ice in the Bering Sea
Timing of emergence of CONUS summertime temperatures
Using explainable to identify regional climate signals to stratospheric aerosol injection
AMIP experiments for surface forcings (sea ice, SST, QBO, Eurasian snow)
PAMIP simulations to understand role of sea surface temperatures on polar amplifications
Climate drivers of the springtime North America cooling pattern
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