ALBERT

Description: Current earthquake forecasting approaches are mainly based on probabilistic assumptions, as earthquakes seem to occur randomly. Such apparent randomness can however be caused by deterministic chaos, rendering deterministic short‐term forecasts possible. Due to the short historical and instrumental record of earthquakes, chaos detection has proven challenging, but more frequently occurring slow slip events (SSE) are promising candidates to probe for determinism. Here, we characterize the SSE signatures obtained from GNSS position time series in the Hikurangi Subduction Zone (New Zealand) to investigate whether the seemingly random SSE occurrence is governed by chaotic determinism. We find evidence for deterministic chaos for stations recording shallow SSEs, suggesting that short‐term deterministic forecasting of SSEs, similar to weather forecasts, might indeed be possible over timescales of a few weeks. We anticipate that our findings could open the door for next‐generation SSE forecasting, adding new tools to existing probabilistic approaches. Plain Language Summary Since earthquakes appear to occur randomly, the currently available probabilistic predictions are based on past earthquake records. These predictions estimate the likelihood of an earthquake of a given magnitude occurring within a defined time period. In contrast to such probabilistic approaches, deterministic systems are fully predictable, albeit often confined to short time scales due to their potential chaotic behavior. Probing for deterministic predictability in the earthquake cycle is intractable due to the limited historical instrumental record. However, frequently occurring slow slip events ‐ captured by transient GNSS displacements that can last several weeks ‐ provide a unique opportunity to explore deterministic predictability in these types of slow earthquakes. By studying GNSS time series from various stations on New Zealand’s North Island, we have discovered evidence suggesting that these irregularly occurring slow slip events might be governed by chaotic determinism. This implies the potential to forecast both timing and magnitude of slow slip events a few weeks in advance using deterministic methods, much like we predict weather patterns. Consequently, our theoretical findings could therefore pave the way for innovative approaches to short‐term slow slip forecasting. Key Points Nonlinear analysis of GNSS displacement time series unveils evidence for deterministic chaos in slow slip events in New Zealand Our theoretical findings imply that irregularly occurring slow slip events could potentially be forecasted a few weeks in advance