Using the SARIMAX model to understand the effect of teleconnection of climate indices on seasonal rainfall in Rwanda and provide long-term forecast of extreme rainfall events.

 An Overview
What is SARIMAX?

SARIMAX, or Seasonal Autoregressive Integrated Moving Average with eXogenous factors, is a statistical method aimed at predicting the future behavior of time series. In this case, my dependant variable is the daily/weekly rainfall anomaly. Exogenous factors implies incorporating the influence of other factors, better known as predictors, into the model.

Teleconnection, ENSO, IOD? 

Teleconnection refers to climate phenomena being related to each other at large distances (typically thousands of kilometers).


ENSO, IOD, ITCZ, MJO, and various monsoon systems are zonal temperature gradients over oceans and seasonal wind flows that can potentially affect the climate of far away countries. In the case of the IOD (Indian Ocean Dipole) and the ENSO (El Nino Southern Oscillation), their strength is represented by a climate index which is typically a SSTA (Sea Surface Temperature Anomaly) which captures how strong the event is. 

Why are all these important? 
The IOD and ENSO have major seasonal impacts on rainfall in Rwanda, and with global warming leading to more extreme temperatures, these temperature phenomena will only grow stronger, leading to more extreme rainfall. These climate indices are the predictors I have chosen to use.