Paul Roebber, University of Wisconsin-Milwaukee, will give the lecture "Applications of Machine Learning to Atmospheric Science"
Multiple linear regression (MLR) has seen wide use in economics and affiliated fields, as it is a useful technique for assessing the relationships between variables and thereby developing understanding from data. MLR represents an early, simple application of data analytics to weather prediction in the form of Model Output Statistics (MOS), which seeks to map numerical weather prediction model output to observations. More sophisticated techniques, like artificial neural networks (ANN), including its extension to Deep Learning, or various other machine-learning approaches such as Evolutionary Programming, are now gaining currency in many fields, and have excellent potential for use in atmospheric sciences.