Traffic Engineering (TE) has become a challenging mechanism for network management and resources optimization due to uncertain and difficult to predict traffic patterns. Recent works have proposed robust optimization techniques to deal with traffic uncertainty, computing a stable routing configuration that is immune to traffic variations within certain uncertainty set. While this robust approach achieves routing reliability at low optimality loss, using a single routing configuration for long-time periods can be inefficient. Based on expected traffic patterns, we show that it is possible to adapt the uncertainty set and build a multi-temporal yet robust routing scheme that outperforms the stable approach. This work presents the study of robust routing in a real network topology, exploring the tradeoffs between stable and multi-temporal robust routing