Publications per year
Publications per year
Personal profile
Related documents
Education/Academic qualification
Atmospheric Science, PhD, Colorado State University
Atmospheric Science, MS, Colorado State University
Atmospheric Science, BS
Fingerprint
Dive into the research topics where Kirsten Mayer is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
Investigating Western North America Atmospheric Rivers with Machine Learning-Based Detection
Dagon, K., King, T., Shields, C., Truesdale, J., Kim, S., Mayer, K., Graubner, A., Greiner, A., Kapp-Schwoerer, L. & Kashinath, K., 2026, In: Machine Learning: Earth.Research output: Contribution to journal › Article › peer-review
Open Access -
MJO Predictability: Its Sources and Limits
Krouma, M., R. Jauregui, Y., Khouider, B., Kerns, B., Kim, D., Kim, H., Mayer, K., Ray, P., Shen, B., Vitart, F., Wei, Y. & Zhang, C., 2026, In: Bulletin of the American Meteorological Society.Research output: Contribution to journal › Article › peer-review
-
CAMulator: Fast Emulation of the Community Atmosphere Model
Chapman, W. E., Schreck, J., Sha, K., Gagne, D. J., Kimpara, D., Zanna, L., Mayer, K. & Berner, J., 2025, (E-pub ahead of print) In: arXiv.Research output: Contribution to journal › Article
-
Can Transfer Learning be Used to Identify Tropical State-Dependent Bias Relevant to Midlatitude Subseasonal Predictability?
Mayer, K. J., Dagon, K. & Molina, M. J., Oct 2025, In: Artificial Intelligence for the Earth Systems. 4, 4, 14 p., e240091.Research output: Contribution to journal › Article › peer-review
-
Controllable Probabilistic Forecasting with Stochastic Decomposition Layers
Schreck, J., Chapman, W., Becker, C., Gagne II, D. J., Kimpara, D., Cherukuru, N., Berner, J., Mayer, K. & Sobhani, N., 2025, In: arXiv.Research output: Contribution to journal › Article
Activities
-
Investigating Subseasonal Predictability with Earth System Models and Machine Learning
Mayer, K. (Invited speaker)
Oct 2026Activity: Give a talk or presentation › Invited talk
-
An Introduction to Artificial Neural Networks
Mayer, K. (Lecturer)
May 2026Activity: Teaching/Mentoring › Teaching or Training at Workshops/Tutorials/Colloquia
-
Learning from machine learning for improved Earth system understanding
Mayer, K. (Invited speaker)
Apr 2026Activity: Give a talk or presentation › Invited talk
-
Future Seasonal Surface Temperature Predictability with and without ARISE – Stratospheric Aerosol Injection-1.5
Mayer, K. (Invited speaker)
Mar 2026Activity: Give a talk or presentation › Invited talk
-
Machine Learning for S2S Prediction and Research at NSF NCAR
Mayer, K. (Invited speaker)
Mar 2026Activity: Give a talk or presentation › Invited talk
Press/Media
Datasets
-
Data for Exploring the Relative Contribution of the MJO and ENSO to Mid-latitude Subseasonal Predictability
Mayer, K. (Creator) & Chapman, W. (Contributor), NSF NCAR - National Center for Atmospheric Research, Feb 12 2024
DOI: 10.5065/f21v-ya03
Dataset