Examples of Machine Learning Applications of Climate and Weather Data in Python for ATMS597 class - Data Science for Weather and Climate..
Project 3: Analysis of climate anomalies over Jakarta, Indonesia ground station observations.
Project 4 : Use sets of prior weather station data and meteorological observations in ML Regression Models to predict future
Project 5 : Download, clean, regularize and sift through weather station (Metar) data to select and collate required precipitation dataset. Then use Logistic Regression to create predictions for precipitation types.
Project 6: Analysis of MOD08_M3 (Monthly Mean MODIS Cloud Data) and ERA5 Reanalysis to build optimized ANN models to predict future cloud-top height, cloud liquid droplet effective radius and cloud ice fraction anomalies.
I acknowledge my collaborators (names included in each report) on these projects.