| Current and emerging developments in subseasonal to decadal prediction WJ Merryfield, J Baehr, L Batté, EJ Becker, AH Butler, CAS Coelho, ... Bulletin of the American Meteorological Society 101 (6), E869-E896, 2020 | 202 | 2020 |
| Subseasonal forecasts of opportunity identified by an explainable neural network KJ Mayer, EA Barnes Geophysical Research Letters 48 (10), e2020GL092092, 2021 | 87 | 2021 |
| Quantifying the Effect of Climate Change on Midlatitude Subseasonal Prediction Skill Provided by the Tropics KJ Mayer, EA Barnes Geophysical Research Letters 49 (14), e2022GL098663, 2022 | 12 | 2022 |
| Subseasonal midlatitude prediction skill following quasi-biennial oscillation and Madden–Julian Oscillation activity KJ Mayer, EA Barnes Weather and Climate Dynamics 1 (1), 247-259, 2020 | 12 | 2020 |
| Identifying opportunities for skillful weather prediction with interpretable neural networks EA Barnes, K Mayer, B Toms, Z Martin, E Gordon arXiv preprint arXiv:2012.07830, 2020 | 7 | 2020 |
| Subseasonal to Decadal Prediction: Filling the Weather–Climate Gap WJ Merryfield, J Baehr, L Batté, EJ Becker, AH Butler, CAS Coelho, ... Bulletin of the American Meteorological Society 101 (9), 767-770, 2020 | 5 | 2020 |
| Assessing decadal variability of subseasonal forecasts of opportunity using explainable AI MC Arcodia, EA Barnes, KJ Mayer, J Lee, A Ordonez, MS Ahn Environmental Research: Climate 2 (4), 045002, 2023 | 4 | 2023 |
| Leveraging Interpretable Neural Networks for Scientific Discovery EA Barnes, KJ Mayer, J Rader, BA Toms, I Ebert-Uphoff AGU Fall Meeting Abstracts 2020, A069-03, 2020 | 1 | 2020 |
| Increasing the reproducibility and replicability of supervised AI/ML in the Earth systems science by leveraging social science methods CD Wirz, C Sutter, JL Demuth, KJ Mayer, WE Chapman, MG Cains, ... Earth and Space Science 11 (7), e2023EA003364, 2024 | | 2024 |
| Exploring the relative importance of the MJO and ENSO to North Pacific subseasonal predictability KJ Mayer, WE Chapman, WA Manriquez Geophysical Research Letters 51 (10), e2024GL108479, 2024 | | 2024 |
| Exploring the Relative Contribution of the MJO and ENSO to Midlatitude Subseasonal Predictability KJ Mayer, WE Chapman, WA Manriquez Authorea Preprints, 2024 | | 2024 |
| Identifying Tropical State-Dependent Biases Relevant to Midlatitude Subseasonal Predictability with Explainable Neural Networks KJ Mayer, K Dagon, MJ Molina 104th AMS Annual Meeting, 2024 | | 2024 |
| When Machine Learning Objectives Compete for Improved Subseasonal Bias Correction, Who Wins? MJ Molina, K Dagon, J Schreck, JS Perez-Carrasquilla, KJ Mayer, ... 104th AMS Annual Meeting, 2024 | | 2024 |
| Leveraging Unsupervised Machine Learning in Environmental Science KA Hilburn, KJ Mayer 104th AMS Annual Meeting, 2024 | | 2024 |
| Exploring the Relative and Combined Contribution of the MJO and ENSO to Midlatitude Subseasonal Predictability with an Interpretable Neural Network WA Manriquez, WE Chapman, KJ Mayer 104th AMS Annual Meeting, 2024 | | 2024 |
| Machine Integration and Learning for Earth Systems (MILES): Bridging Key Gaps in Machine Learning for Earth System Science DJ Gagne, J Schreck, C Becker, G Gantos, T Martin, W Petzke, W Chuang, ... 104th AMS Annual Meeting, 2024 | | 2024 |
| Quantifying Future Midlatitude Subseasonal Predictability Provided by the Tropics under Anthropogenic Warming (Invited Presentation) KJ Mayer, EA Barnes 103rd AMS Annual Meeting, 2023 | | 2023 |
| Subseasonal to Seasonal Climate Prediction, Processes, and Applications I Online Poster Discussion AW Robertson, J Infanti, KJ Mayer, F Vitart, MA Olsen Fall Meeting 2022, 2022 | | 2022 |
| Exploring Future Northern Hemisphere Winter Seasonal Variability and Predictability under Stratospheric Aerosol Injection KJ Mayer, EA Barnes, J Hurrell AGU Fall Meeting Abstracts 2022, GC22E-0638, 2022 | | 2022 |
| Clouds, Radiation, and Climate Sensitivity. Part I BEJ Rose, KJ Mayer 102nd American Meteorological Society Annual Meeting, 2022 | | 2022 |
