Simulating surface warming in Earth's three polar regions during the Middle Miocene Climatic Optimum using isotopic and non-isotopic versions of the Community Earth System Model

The Earth's North and South Poles and the Tibetan Plateau — collectively referred to as the ‘three poles’ — are regions that are very sensitive to climate changes and are known to amplify shifts in global temperature. In the case of the polar regions this effect is well known as polar amplification. The climate patterns during the Middle Miocene Climatic Optimum (MMCO) are considered a past analog to future climate, which could develop patterns and characteristics bearing similarity to MMCO by the end of the century. Therefore, analyzing MMCO environmental conditions in these regions in comparison to a pre-Industrial reference state provides valuable insights into possible future surface temperature changes at the Earth's three poles. We conducted simulations of the MMCO, focusing on surface temperature anomalies at the Earth's three poles. As a modelling tool we employed two versions of the Community Earth System Model (CESM), one of them equipped with model dynamics to simulate stable water isotopes. During the MMCO, we show 1) temperature anomalies at the three poles exceeded global averages, with Antarctica warming most, followed by the Tibetan Plateau and the Arctic, highlighting the role of the Tibetan Plateau as a key factor in global climate change often overlooked; 2) temperature anomalies at the Tibetan Plateau are higher in boreal winter (DJF), while in the Arctic and Antarctic temperature anomalies are larger in boreal summer (JJA), highlighting a seasonal shift between the maximum of climate change signals at the third pole; 3) Changes in clear-sky surface downwelling longwave radiation fluxes (∆Trlds_clearsky) and changes in surface albedo forcing (∆TSAF) constitute the primary and secondary mechanisms driving the annual surface temperature anomaly at the Earth's three poles. In contrast, the leading physical processes governing the seasonal cycle are subject to regional variation.