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David Hall authored and/or contributed to the following articles/publications.
Machine Learning for Targeted Assimilation of Satellite Data
Optimizing the utilization of huge data sets is a challenging problem for weather prediction. To a significant degree, prediction accuracy is determined by the data used in model initialization, assimilated from a variety of observational platforms. At present, the volume of weather data collected in a given day greatly exceeds the ability of as...
Institution National Oceanic and Atmospheric Administration - NOAA
Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences
Promising new opportunities to apply artificial intelligence (AI) to the Earth and environmental sciences are identified, informed by an overview of current efforts in the community. Community input was collected at the first National Oceanic and Atmospheric Administration (NOAA) workshop on “Leveraging AI in the Exploitation of Satellite Earth ...
Institution National Oceanic and Atmospheric Administration - NOAA
Tropical and Extratropical Cyclone Detection Using Deep Learning
Extracting valuable information from large sets of diverse meteorological data is a time-intensive process. Machine-learning methods can help to improve both speed and accuracy of this process. Specifically, deep-learning image-segmentation models using the U-Net structure perform faster and can identify areas that are missed by more restrictive...
Institution National Oceanic and Atmospheric Administration - NOAA
The intensity of a tropical cyclone is correlated strongly to the damage it causes when it makes landfall. Most of the time, tropical cyclones are located over the open ocean, where direct intensity measurements are difficult to obtain. An alternative approach is to estimate the tropical cyclone intensity indirectly from satellite images. In thi...
Institution National Oceanic and Atmospheric Administration - NOAA