Luke Madaus
Meteorologist | Cloud-based weather and climate analytics
Primary areas of research include data assimilation methods, crowdsourced observations, mesoscale dynamic meteorology and forecast verification
Curriculum Vitae LinkedIn Twitter: @lmadaus
Currently working as a Staff Scientist and Geophysical Solutions Engineer at Jupiter
Recent Research and Projects
Crowdsourced Weather Observations
The explosion of connected devices in recent years has opened up new opportunities for weather observations at scales and frequencies previously unthinkable. I am exploring crowdsourced and non-traditional observation platforms (such as backyard weather stations or smartphone pressure observations) for their use in weather forecasting and verification.
Data Assimilation for Short-Term Prediction
Frequently-updating, convection-allowing operational ensemble forecasts are right around the corner, but much work is needed to determine how to efficiently maximize the value of dense observations to support these high-resolution modeling efforts. I have ongoing work developing four-dimensional (4D) and object based data assimilation methods to address these needs.
Surface Observations and Convective Initiation
My PhD thesis work investigates how assimilating standard surface weather observations at high spatial and temporal frequency may improve short-term storm-scale forecasts of convective initation.