University of Florida Homepage

Assessing the Impacts of Falling Ice Radiative Effects on the Seasonal Variation of Land Surface Properties

Kisembe, J., Li, J. L. F., Wen, Y., Lee, W. L., Qian, W., Li, Z., & Jiang, J. H. (2024). Assessing the impacts of falling ice radiative effects on the seasonal variation of land surface properties. Journal of Geophysical Research: Atmospheres, 129(15), e2024JD040991. DOI: https://doi.org/10.1029/2024JD040991 Article first published online: 05 August 2024 in JGR Atmospheres ABSTRACT: The […]

B.S. in Meteorology Starting in Fall 2024

The Department of Geography is excited to announce the Bachelor of Science program in Meteorology has been fully approved, and will officially begin in Fall 2024. Our program provides broader geographic training and aims to build skills that crosscut from meteorology to applied climate science, geospatial analysis, hydrology, business, economics, communications, and Al as required […]

Future Heavy rainfall and flood risks for Native America under climate and demographic changes: A case study in Oklahoma

WEN – Future Heavy rainfall and flood risks for Native America under climate and demographic changes: A case study in Oklahoma Zhi Li, Theresa Wsoodle, Mengye Chen, Shang Gao, Jiaqi Zhang, Yixin Wen, Tiantian Yang, Farina King, Yang Hong Article first published online: 9 October 2023 DOI: https://doi.org/10.1175/WCAS-D-23-0005.1 ABSTRACT: Climate change has posed inequitable risks […]

A decadal review of the CREST model family: Developments, applications, and outlook

WEN – A decadal review of the CREST model family: Developments, applications, and outlook Zhi Li, Xianwu Xue, Robert Clark, Humberto Vergara, Jonathan Gourley, Guogiang Tang, Xinyi Shen, Guangyuan Kan, Ke Zhang, Jiahu Wang, Mengye Chen, Shang Gao, Jiagi Zhang, Tiantian Yang, Yixin Wen, Pierre Kirstetter, Yang Hong Article first published online: 26 August 2023 […]

Fall Course: GEO4938 GEO6938 Machine Learning in Meteorology

GEO4938 GEO6938 Machine Learning in Meteorology Hands-on experiences with machine learning (ML) from a series of practical case-studies in meteorology. Regression, classification, clustering and retrieval, and deep learning to solve research questions by identifying potential applications of ML, selecting the appropriate ML models, representing data as features to serve as input to ML models, and […]

Fall Course: MET4410 Radar and Satellite Meteorology

MET4410 Radar and Satellite Meteorology Learn the principles and practices of satellite and radar remote sensing as used in the atmospheric sciences. Apply the principles of remote sensing meteorology to process, visualize and interpret radar and satellite data for various weather events. Part of the GeoAI Certificate You will learn to: * operate a weather […]

Joint collaboration on comparing NOAA’s ground-based weather radar and NASA-JAXA’s spaceborne radar

WEN – Joint collaboration on comparing NOAA’s ground-based weather radar and NASA-JAXA’s spaceborne radar Zhi Li, Yixin Wen, Liang Liao, David Wolff, Robert Meneghini, Terry Schuur Article first published online: 9 March 2023 DOI: https://doi.org/10.1175/BAMS-D-22-0127.1 ABSTRACT: The National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA) have a long and successful […]

Focus Area 7: Geospatial Analysis & Techniques

Modeling, Measurement, Visualization and Computation: techniques for the collection, analysis, interpretation and display of geospatial data, using tools such as GeoAI, GIS, Remote Sensing, GPS, and Spatial Statistics. Sub Areas GEOAI: Geographic Artificial Intelligence Geographic Information Systems (GIS) Remote Sensing Spatio-temporal analysis Geospatial Modeling Courses GIS2002: The Digital Earth GIS2114: Geographic Artificial Intelligence & Big […]

Dr. Berry Wen

Dr. Yixin ‘Berry’ Wen Assistant Professor she/her/hers yixin.wen@ufl.edu Curriculum Vita Focus Areas Earth System Science Sustainability & Global Environmental Change Research Statement My motivation to pursue more accurate remote sensing precipitation retrievals at global scale is powered by the massive precipitation observations and the advanced machine learning (ML) technologies. During my 10-year work on the […]