Detecting hotspots of atmosphere–vegetation interaction via slowing down – Part 2: Application to a global climate model

Abstract

Early warning signals (EWS) have become a popular statistical tool to infer stability properties of the climate system. In Part 1 of this two-part paper we have presented a diagnostic method to find the hotspot of a sudden transition as opposed to regions that experience an externally induced tipping as a mere response. Here, we apply our method to the atmosphere–vegetation model PlanetSimulator (PlaSim) – VECODE using a regression model. For each of two vegetation collapses in PlaSim-VECODE, we identify a hotspot of one particular grid cell. We demonstrate with additional experiments that the detected hotspots are indeed a particularly sensitive region in the model and give a physical explanation for these results. The method can thus provide information on the causality of sudden transitions and may help to improve the knowledge on the vulnerability of certain subsystems in climate models.