Magnetic structures visible on the surface of the Sun are both tracers of, and critical contributors to the progression of the solar cycle. Computer vision is a very powerful tool for detecting and cataloging them in a ways that greatly enhance solar cycle research. This image shows the output of our Bipolar Active Region Detection (BARD) code, applied to SOHO/MDI data.
The solar magnetic field arranges itself into self-similar structures spanning a wide range of spatial scales. Their demographics give valuable insight into their origin and life-cycle. I'm particularly interested in how the statistical properties of magnetic regions are modulated by the solar cycle, and on using this information to better solar dynamo modeling and cycle prediction.
Dynamo simulations are a very powerful tool for studying the solar cycle and understanding observations. One of my main interests is to develop a new generation of dynamo simulations that can be used for predicting the characteristics of the solar cycle. The figure shows one of our latest simulations that better captures emergence of the magnetic structures associated with sunspots.
The prediction of the solar cycle and its characteristics is one of the main practical goals of solar physics. My expertise in both data analysis and dynamo simulations puts me in a privileged position to tackle this problem. The figure shows the observed location, time and size of sunspots, as well as a synthetic set of sunspots created using only cycle amplitude information.
In order to development useful solar cycle predictions, we need to be able to predict quantities that affect human technological activities and the Earth's climate. For this purpose, I'm actively working to interface our dynamo simulations with heliospheric models. The figure shows coupled dynamo and solar wind simulations performed in collaboration with NASA's CCMC.
When it comes to study the solar cycle, long observational surveys and cross-callibration across instruments is of vital importance. I'm working to ensure that valuable observational surveys are not lost to the new generations as critical personnel retires. The figure shows work I'm doing to fix outstanding geometry problems in data from the Kitt Peak Vacuum Telescope.
My passion for history, cartography, and data analysis (coupled with my love for computer gaming), have led me to become heavily involved in fan-made game modifications (commonly known as "Mods"). My contribution has always been the assimilation of geophysical data to create realistic game assets, and the development of information-rich, user-friendly interfaces. My main projects have been:
The most popular mod for Europa Universalis III (more than the original game itself). My role was to assimilate shoreline, hydrography, topography, land coverage, and color data to create the most detailed and realistic world map in a Paradox game at that point in time. Our mod was so popular that Paradox decided to turn it into a commercial game. Unfortunately, it was later canceled.
An ambitious historical seafaring game, set in the Age of Sail, being developed by the PiratesAhoy! community. My role is to assimilate sea wind speed, pressure, and temperature data to create realistic in-game weather systems. These systems, (including tropical storms, hurricanes, and squalls) will have seasonal variations based on their observed statistical properties.