Statistical Modeling Of Effective Temperature With Cosmic Ray Flux

The increasing frequency of sporadic weather patterns in the last decade, especially major winter storms, demands improvements in current weather forecasting techniques. Recently, there are growing interests in stratospheric forecasting because of its potential enhancements of weather forecasts. The dominating factors of northern hemisphere wintertime variation of the general circulation in the stratosphere is a phenomenon called stratospheric sudden warming (SSW) events. It is shown in multiple studies that SSW and cosmic ray muon flux variations are strongly correlated with the effective atmospheric temperature changes, which suggests that cosmic ray detectors could be potentially used as meteorological applications, especially for monitoring SSW events. A method for determining the effective temperature with cosmic ray flux measurements is studied in this work by using statistical modeling techniques, such as k-fold cross validation and partial least square regression. This method requires the measurement of the vertical profile of the atmospheric temperature, typically measured by radiosonde, for training the model. In this study, cosmic ray flux measured in Atlanta and Yakutsk are chosen for demonstrating this novel technique. The results of this study show the possibility of realtime monitoring on effective temperature by simultaneous measurement of cosmic ray muon and neutron flux. This technique can also be used for studying the historical SSW events using the past world wide cosmic