Topic: Artificial Intelligence for Clouds, Aerosol, and Precipitation Poster Session (105th AMS Annual Meeting)

Thursday, 16 January 2025: 3:00 PM-4:30 PM

Hall C (New Orleans Ernest N. Morial Convention Center)

Host: 24th Conference on Artificial Intelligence for Environmental Science

Submitters:

Kyle A. Hilburn; Christina E. Kumler, CIRA, Boulder, CO and Tiago Quintino, ECMWF, Forecast Department, Reading

Cochairs:

Ryan Lagerquist; Zhonghua Zheng, University of Illinois at Urbana-Champaign, Department of Civil and Environmental Engineering, URBANA, IL and Randy J. Chase

Clouds, aerosol, and precipitation have inherent uncertainties due to limitations in knowledge regarding physical characteristics and processes. In these situations, artificial intelligence can add value to remote sensing and modelling applications, and can aid knowledge discovery. This session is soliciting applications of artificial intelligence to observations and modelling of clouds, aerosols, and precipitation.

Papers:

951

Kayley Marie Butler, University of Southern California, Los Angeles, CA; and S. J. Silva

952

Developing a Machine Learning Model to Predict Dry Thunderstorms Associated with Haboobs

Beto L. Estrada Jr., Texas A&M University-Corpus Christi, Corpus Christi, TX; and A. Walker, J. Nachamkin, E. Krell, D. A. Peterson, C. T. Nguyen, J. R. Campbell, and P. E. Tissot

953

Impact of Dimensionality Reduction on Machine-learning-based Cloud Mask Algorithm for Infrared Hyperspectral Observations

Qikai Hu, University of Michigan, Ann Arbor, Ann Arbor, MI; and C. Fan, X. Chen, and X. Huang

954

Satellite-based Estimates of Western Pacific Tropical Cyclone Rainfall Intensity

Timothy J. Wagner, University of Wisconsin-Madison, Madison, WI; and M. J. Foster, S. Moeller, Y. L. Chen, and Y. C. Chang

- Indicates paper has been withdrawn from meeting

- Indicates an Award Winner

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