Ty Dickinson
Climate Scientist
Tulsa, Oklahoma, United States
Summary
👤
Senior🎓
Top SchoolTy Dickinson is a climate scientist with eight years of experience specializing in subseasonal-to-seasonal (S2S) predictability and extreme precipitation events. Currently at Salient Predictions, he translates research-grade methods into applied forecasting insights, building on a PhD track in meteorology from the University of Oklahoma. His doctoral work produced an algorithmic database of 14–90 day extreme precipitation events across CONUS and used deep convolutional networks in an object-oriented framework to validate extremes—bridging traditional climatology with modern machine learning. Prior roles include operationally focused internships and outreach work that informed impact-based climatologies and stakeholder-facing communication. Based in Tulsa, he combines hands-on model development with an eye for making complex forecast information actionable for decision makers.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Meteorology, Doctor of Philosophy - PhD, Meteorology at University of Oklahoma
Github Skills (9)
prediction7
python4
toolbox4
deep-learning3
machine-learning3
pytorch3
tensorflow2
neural-network2
latex1
Programming languages (2)
Github contributions (5)
tydickinson29/PRES2iPpy
Jul 2019 - Sep 2021
Prediction of Rainfall Extremes at Subseasonal to Seasonal Periods in Python
Contributions:1 release, 128 commits, 2 PRs in 2 years 2 months
extremespythonpredictionseasonalperiods
tydickinson29/Impact-Based-Seasonal-Outlooks
Jul 2017 - Nov 2017
Contributions:2 PRs, 190 pushes, 3 branches in 4 months
seasonal
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