Level-Shift Failures in Spatiotemporal Kriging with Target-Node History: Diagnosis and Repair

We study level-shift failures in spatiotemporal kriging when target nodes' current values are masked but their histories remain available. KRIN subtracts each node's recent mean and restores it after prediction. Under a common reconstruction protocol, it reduces MAE in 37 of 40 configurations using released implementations. However, none of the centred released implementations outperforms seasonal persistence with current common-mode correction (+CM) on Chicago or Subway under Shock. Controlled experiments examine how recovery varies with the location and timing of available level information. Holding targets and observation counts fixed, moving observations outside a shifted region increases SPIN-s MAE from 194.6 to 598.4 on Subway, while SPIN-s + KRIN changes from 121.2 to 123.9. Immediately after a uniform shift, +CM achieves lower error than the learned configurations, while shift alarms identify failures after centring only imprecisely. These findings distinguish broad error reduction from conditional gains over a strong baseline and highlight sensitivity to observation location and transition timing in the evaluated settings.