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followers: 276.0 following: 72.0 repos: 32.0 gists: 0.0

Name: Zachary Labe

Type: User

Company: NOAA Geophysical Fluid Dynamics Laboratory (GFDL)

Bio: I’m a climate scientist trying to visualize the signal from a lot of noise.

Twitter: ZLabe

Location: Princeton, NJ

Blog: https://zacklabe.com/

About

👋 Hi, I’m Zack!
👨‍💻 Working on climate prediction and projection, especially for disentangling patterns of climate change from climate variability using data-driven methods at NOAA GFDL
👀 Interested in...
- Large-scale climate variability
- Atmospheric teleconnections
- Decadal climate prediction
- Stratosphere-troposphere coupling
- Arctic sea ice
- Extreme events
- Science communication
🔨 Using methods like...
- Climate model large ensembles
- Machine learning
- Explainable AI
- Data visualization
💻 Research website at https://zacklabe.com/
- Institutional website at https://www.gfdl.noaa.gov/zachary-labe/
✨ Passionate about telling data-driven stories to improve communication of climate change [Visit my climate visualizations page!]

Contact

📄 CV/Resume
📫 Email
🐦 @ZLabe
🐘 @[email protected]
🌤️ @zlabe.bsky.social

Zachary Labe's Projects

aa

(Non)linear atmospheric response to Arctic Amplification forcing

amip_simu

AMIP experiments for surface forcings (sea ice, SST, QBO, Eurasian snow)

antseaicevari

Large-scale atmospheric response to Antarctic sea ice loss

arcticseaice

Sea ice parameters

attribution_springna

Climate drivers of the springtime North America cooling pattern

beringseaice2018

Historical sea ice in the Bering Sea

bibtexlibrary

Personal library of BibTeX references

caathickness

Canadian Arctic Archipelago - sea ice thickness

climatepython

📈 Series of workshops and lectures using Python in the climate/atmospheric sciences 📉

datavizstudies

Repository for studies on data visualization in weather/climate science

detectmitigate

Using neural networks to detect effects of rapid climate mitigation

earlyspringonset

Evaluating anomalously early spring onsets in the 21st century

ess-python-tutorial

extremeevents

Using ANN's to reveal changes in extreme events and internal variability in climate models

icevarfigs

🌀 Weather and climate graphics for science communication 🌀

internalsignal

ANN detecting signal from internal variability

intpart

lim

Code and data for building linear inverse model (LIM) in Matlab

maps_2018

MAPS fellowship presentation - May 2018 - Global Warming Hiatus Statistics

modelbiasesann

Investigation of model biases in historical internal variability using explainable AI

predictgmstrate

Using a neural network to predict changes in the rate of global mean surface temperature warming

sai

Using explainable to identify regional climate signals to stratospheric aerosol injection

seaiceqbo

Assessing the influence of the QBO in Arctic sea ice perturbation experiments

seaicethickness

UCI Data Science Initiative Fellowship

seaicevariability

Arctic sea ice interannual variability and change

sstresponse

PAMIP simulations to understand role of sea surface temperatures on polar amplifications

stratovari

Large ensemble to explore robustness of stratospheric response to Arctic sea-ice loss

thicknesssensitivity

Arctic sea ice thickness sensitivity experiments

toe_tmin-tmax

Timing of emergence of CONUS summertime temperatures

zlabe_cv

Curriculum Vitae (CV)

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