Heliophysics is producing an incredible amount of data that are beyond human capability to process. Advanced techniques of machine learning will enhance significantly our capability of finding new things in our data.
Magnetic structures visible on the surface of the Sun are both tracers of, and critical contributors to the progression of the solar cycle. Identifying and cataloging them greatly enhances solar cycle research.
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, as well as theircontribution to the cycle.
Long observational surveys and cross-callibration across instruments is of vital importance for studying the solar cycle. Given that the solar cycle evolves over decadal and centenial time scales, this means workign with 400 years worth of observational surveys.
The prediction of the solar cycle and its characteristics is one of the main practical goals of solar physics. Tt hinges on understanding the collective contribution of thousands of magnetic regions and the evolution of the polar fields.
- • How many active regions are necessary to predict the solar dipole moment?
- • Parameter optimization for surface flux transport models.
- • Using the dipolar and quadrupolar moments to improve solar-cycle predictions based on the polar magnetic fields.
- • Solar cycle propagation, memory, and prediction: Insights from a century of magnetic proxies.
Dynamo simulations are a very powerful tool for studying the solar cycle and understanding observations. A new generation of dynamo simulations is critical for predicting the characteristics of future solar cycles.
- • Kinematic active region formation in a three-dimensional solar dynamo model
- • Helioseismic perspective of the solar dynamo.
- • The unusual minimum of sunspot cycle 23 caused by meridional plasma flow variations.
- • Magnetic quenching of turbulent diffusivity: reconciling mixing-length theory estimates with kinematic dynamo models of the solar cycle.
- • A double-ring algorithm for modeling solar active regions: Unifying kinematic dynamo models and surface flux-transport simulations.
- • Helioseismic data assimilation in solar dynamo models.
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.