Time-varying or regime-switching CTRW extensions

Develop time-varying parameterizations or regime-switching extensions of the Coupled Continuous Time Random Walk (CTRW) model for the All India Annual Maximum Temperature Series (1901–2017) to allow the model to adapt to structural changes in temperature dynamics over time, and implement Bayesian inference for these extensions.

Background

The paper models annual maximum temperatures in India using a coupled Continuous Time Random Walk (CTRW) with stationary jump-size and waiting-time distributions. While effective for capturing episodic jump–wait behavior, the authors note limitations in reflecting evolving climate dynamics over the 117-year span.

In the conclusion, the authors explicitly state that several avenues remain open and specify the need to explore time-varying CTRW parameters or regime-switching mechanisms to better capture structural changes in temperature dynamics.