Abstract

Abstract Regional climate and environmental variability in response to orbital forcing during interglacial events within the mid-Piacenzian (Pliocene) Warm Period (mPWP; 3.264–3.025 Ma) has been rarely studied using climate and vegetation models. Here we use climate and vegetation model simulations to predict changes in regional vegetation patterns in response to orbital forcing for four different interglacial events within the mPWP (Marine Isotope Stages (MIS) G17, K1, KM3 and KM5c). The efficacy of model-predicted changes in regional vegetation is assessed by reference to selected high temporal resolution palaeobotanical studies that are theoretically capable of discerning vegetation patterns for the selected interglacial stages. Annual mean surface air temperatures for the studied interglacials are between 0.4 °C to 0.7 °C higher than a comparable Pliocene experiment using modern orbital parameters. Increased spring/summer and reduced autumn/winter insolation in the Northern Hemisphere during MIS G17, K1 and KM3 enhances seasonality in surface air temperature. The two most robust and notable regional responses to this in vegetation cover occur in North America and continental Eurasia, where forests are replaced by more open-types of vegetation (grasslands and shrubland). In these regions our model results appear to be inconsistent with local palaeobotanical data. The orbitally driven changes in seasonal temperature and precipitation lead to a ~ 30% annual reduction in available deep soil moisture (2.0 m from surface), a critical parameter for forest growth, and subsequent reduction in the geographical coverage of forest-type vegetation; a phenomenon not seen in comparable simulations of Pliocene climate and vegetation run with a modern orbital configuration. Our results demonstrate the importance of examining model performance under a range of realistic orbital forcing scenarios within any defined time interval (e.g. mPWP). Additional orbitally resolved records of regional vegetation are needed to further examine the validity of model-predicted regional climate and vegetation responses in greater detail.

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