DE
Member Since 2012
Dr Enrico Camporeale Camporeale
Research Associate, University of Colorado Boulder
AGU Research
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Local enhancements of the turbulent energy transfer by extreme vertical velocity drafts in stratified geophysical flows
GEOPHYSICAL FLUID DYNAMICS: PHYSICS-INFORMED MACHINE LEARNING III POSTER
nonlinear geophysics | 14 december 2023
Raffaele Marino, Raffaello Foldes, Silvio Sergio C...
Statistical analysis of the output of numerical simulations performed in a certain range of values of the Froude number (Feraco et al., 2018), as well...
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Low-dimensional representation of large-scale intermittency in stratified geophysical flows
GEOPHYSICAL FLUID DYNAMICS: PHYSICS-INFORMED MACHINE LEARNING III POSTER
nonlinear geophysics | 14 december 2023
Raffaello Foldes, Enrico Camporeale, Raffaele Mari...
We introduce a novel machine learning approach designed to reduce the dimensionality of state variables in direct numerical simulations of stratified ...
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One Hour Ahead Horizontal Geoelectric Fields Forecast Using a Multi-Fidelity Machine Learning method
UNDERSTANDING GEOMAGNETICALLY INDUCED CURRENTS AND THEIR IMPACT ON TECHNOLOGY I POSTER
spa-magnetospheric physics | 13 december 2023
Andong Hu, Enrico Camporeale, Greg Lucas
Geomagnetically Induced Currents (GICs) are electrical currents induced at the Earth's surface by rapid changes in the geomagnetic field caused by spa...
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Space weather information architecture and innovative solutions: progress report
SPACE WEATHER COLLABORATION, COOPERATION, AND COORDINATION II ORAL
spa-solar and heliospheric physics | 13 december 2023
Arnaud Masson, Shing F. Fung, Enrico Camporeale, M...
Over the past decade, radical changes have happened in the world of science and information technology. Open science is now recommended by the United ...
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Space Weather modeling at the University of Colorado Deep Learning Laboratory
SPACE WEATHER COLLABORATION, COOPERATION, AND COORDINATION I POSTER
spa-solar and heliospheric physics | 12 december 2023
Enrico Camporeale, Andong Hu, Greg Lucas, Brian M....
We give an overview on a number of models developed by our team at the University of Colorado, Boulder. As a result of a large investment in AI/ML, we...
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Physics-Informed Machine Learning Prediction of Ambient Solar Wind Speed
MACHINE LEARNING IN SPACE WEATHER III POSTER
nonlinear geophysics | 11 december 2023
Enrico Camporeale, Andong Hu
Forecasting the ambient solar wind several days in advance still proves extremely difficult. In fact, state-of-the-art models (either physics-based or...
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Validating ML Model: Enhancing Solar Wind Classification for Forecaster Awareness
MACHINE LEARNING IN SPACE WEATHER III POSTER
nonlinear geophysics | 11 december 2023
Lois Landwer, Hazel M. Bain, Mark S. Miesch, Geor...
The NOAA Space Weather Prediction Center (SWPC) aims to enhance forecaster situational awareness by implementing a machine learning (ML) model that ut...
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Proboost Multi-fidelity Machine Learning Method for Extreme Space Weather Events
MACHINE LEARNING IN SPACE WEATHER I ORAL
nonlinear geophysics | 11 december 2023
Andong Hu, Enrico Camporeale
We introduce an innovative ensemble machine learning (ML) method designed for forecasting extreme space weather events, called proboost (probabilistic...
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