Posters II

Tuesday, 30 January 2024: 3:00 PM-4:30 PM
Hall E (The Baltimore Convention Center)
Host: 23rd Conference on Artificial Intelligence for Environmental Science

Papers:
399
A Purely Data-Driven Transformer Model for Real-Time Predictions of the 2023-24 Climate Condition in the Tropical Pacific
Rong-Hua Zhang, School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China; and C. Gao

398
A Transformer-Based Deep Learning Model for Successful Predictions of the 2021 Second-Year La Niña Condition

400
Geocenter: A New Deep-Learning Ensemble for Determining Tropical-Cyclone Center Locations from Geostationary Satellite Data
Ryan A. Lagerquist, CIRA and NOAA/ESRL/GSL, Boulder, CO; and G. Chirokova, M. DeMaria, R. DeMaria, I. Ebert-Uphoff, J. Knaff, and C. Slocum

401
Development of a Machine Learning-Based Tropical Cyclone Track Prediction Scheme over the Western North Pacific
You-Hyun Baek, KMA, Seogwipo-si, Jeju-do, South korea; and H. Lee, J. R. Lee, S. Won, and S. H. Kim

402
Improving Ensemble Model Tropical Cyclone Track Forecast Using Machine Learning
Nikita Agrawal, Whitney M. Young Magnet High School, Chicago, IL; and B. A. Colle

403
How Far in Advance Can Deep Learning Predict Tropical Cyclone Formation?
Chanh Kieu, Indiana University Bloomington, Bloomington, IN; and Q. Nguyen and N. Tri

405
Machine Learning Quality Control of Lightning Data for Tropical Cyclone Intensity Forecasting
Kyle A. Hilburn, ; and S. N. Stevenson, K. Musgrave, and B. C. Trabing

406
Exploring Tropical Cyclone Structure and Evolution with AI-based Synthetic Passive Microwave Data
Marie McGraw, CIRA, Fort Collins, CO; and K. Haynes, K. D. Musgrave, I. Ebert-Uphoff, C. Slocum, and J. Knaff

407
Towards Global Fire Radiative Power (FRP) Retrievals from METImage Measurements Using Regional Radiance Machine Learning Models
Yingxin Gu, IMSG at NOAA/NESDIS/STAR, College Park, MD; and I. A. Csiszar, M. Tsidulko, and W. Guo

408
Toward Prediction of Pyrocumulonimbus with Machine Learning
Chuyen T Nguyen, Naval Research Laboratory, Monterey, CA; and E. A. Krell, J. Nachamkin, D. A. Peterson, E. J. Hyer, P. E. Tissot, S. A. King, B. Estrada Jr., and K. J. Tory

404
A Spatially-Aware North Atlantic Tropical Cyclogenesis Index Using Machine Learning

409
Using Grouped Features to Improve Explainable AI Results for Atmospheric AI Models that use Gridded Spatial Data and Complex Machine Learning Techniques
Evan Andrew Krell, Texas A&M Univ. - Corpus Christi, Corpus Christi, TX; and H. Kamangir, W. G. Collins, S. A. King, and P. Tissot

410
Automatic Fog Detection and Visibility Estimation From Camera Images Using Deep Learning Features For Aviation Operations Involving Uncrewed Aircraft Systems (UAS)
Marwa Majdi, Univ. of North Dakota, Grand Forks, ND; and D. Delene and M. Chrit

411
Predicting Winter Fog over Complex Terrain Using Deep Learning
Grace Liu, University of Utah, Salt Lake City, UT; and Z. Pu

412
Transfer Learning for the Canadian Airspace: Leveraging a Globally-Trained UNet Model to Create Enhanced Radar Depictions in Regional Domains
Kiley L. Yeakel, MIT Lincoln Laboratory, Lexington, MA; and P. M. Lamey, D. Morse, H. Iskenderian, and M. S. Veillette

413
Improved Composite Reflectivity Mosaics in Mountain Terrain for Air Traffic Management
William J. Dupree, MIT, Lexington, MA; MIT Lincoln Laboratory, Lexington, MA; and J. Y. N. Cho, M. S. Veillette, and H. Iskenderian

414
Development of Localized Aviation MOS Program for Main Airports in South Korea
Jeonghoe Kim, Seoul National University, Seoul, South korea; and J. H. Kim

415
Utilizing Neural Networks to Predict Water Temperatures in a Thermal Refuge
Andrew DeSimone, Texas A&M University-Corpus Christi, Corpus Christi, TX; and A. Beasley, A. Anand, B. Colburn, S. Dasu, P. E. Tissot, and H. M. Marrero Colominas

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
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