kjmayer
Project Scientist at the National Center for Atmospheric Research
National Center for Atmospheric Research
Pinned Repositories
actm-sai-csu
AI to detect, attribute, and quantify solar radiation management (SRM) effects and risks under a range of geopolitical scenarios. Project funded by DARPA‐PA‐21‐04‐02.
ats655-coursematerial
Course material for ATS 655: Objective Analysis with Prof. Elizabeth Barnes, Dept. of Atmospheric Science, Colorado State University.
ENSOvsMJO
Use interpretable NN to explore relative contributions of ENSO and MJO to midlatitude S2S predictability
PhD_Chapter4_SAISeasonalPrediction
impact of stratospheric aerosol injection on seasonal predictability
S2SPred-EarthSystem
SeasonalTempPred_ARISE-SAI-1.5
Associated code for paper "Future Seasonal Surface Temperature Predictability with and without ARISE-Stratospheric Aerosol Injection-1.5"
TL-XAI_E3SM
Use explainable NNs and transfer learning to identify state-dependent bias in tropical sources of subseasonal predictability
SubX
Kathy's Codes for Accessing and Processing SubX Data from the IRI Data Library
ML-for-S2S
Repository for subseasonal-to-seasonal prediction and predictability projects using machine learning.
ML_workshop2023
kjmayer's Repositories
kjmayer/S2SPred-EarthSystem
kjmayer/ats655-coursematerial
Course material for ATS 655: Objective Analysis with Prof. Elizabeth Barnes, Dept. of Atmospheric Science, Colorado State University.
kjmayer/ENSOvsMJO
Use interpretable NN to explore relative contributions of ENSO and MJO to midlatitude S2S predictability
kjmayer/PhD_Chapter4_SAISeasonalPrediction
impact of stratospheric aerosol injection on seasonal predictability
kjmayer/SeasonalTempPred_ARISE-SAI-1.5
Associated code for paper "Future Seasonal Surface Temperature Predictability with and without ARISE-Stratospheric Aerosol Injection-1.5"
kjmayer/TL-XAI_E3SM
Use explainable NNs and transfer learning to identify state-dependent bias in tropical sources of subseasonal predictability