Understanding Solar Weather

Solar Weather is a challenge impacting multiple areas of our lives: telecommunications and computing, climate, and human space activities. This can pose a threat to much of our infrastructure, ranging from immediate effects on GPS systems, satellite communication, and aircraft communication to larger scale. Better understanding and prediction of these complex phenomena can help to limit these impacts. This poster reports on an independent study investigation extending a class study of solar weather in studying programming, sensor networks, data analysis, artificial intelligence, and machine learning. Our vision for this project is to gain a better understanding of solar weather data, and to look for patterns in that data. Our goal has been to codify the structure for analyzing solar weather data and to create an application to do so. Two specific areas we are investigating involve using a low-cost microcontroller to simulate a satellite and running a predictive algorithm to forecast future solar weather cycles. Future work will investigate the accuracy of our model by performing hold-back analyses, predicting the results of a past cycle or pair of cycles (which we will omit) based on the remaining data.