Modelling framework for asynchronous land-atmosphere coupling using NASA GISS ModelE and LPJ-LMfire: Design, Application and Evaluation for the 2.5ka period

Abstract. While paleoclimate simulations have been a priority for Earth system modelers over the past three decades, little attention has been paid to the period between the mid-Holocene and the Last Millennium, although this is an important period for the emergence of complex societies. Here, we consider the climate of 2500 BP (550 BCE), a period when compared to late preindustrial time, greenhouse gas concentrations were slightly lower, and orbital forcing led to a stronger seasonal cycle in high latitude insolation. To capture the influence of land cover on climate, we asynchronously coupled the NASA GISS ModelE Earth system model with the LPJ-LMfire dynamic global vegetation model. We simulated global climate and assessed our results in the context of independent paleoclimate reconstructions. We also explored a set of combinations of model performance parameters (bias and variability) and demonstrated their importance for the asynchronous coupling framework. The coupled model system shows substantial vegetation albedo feedback to climate. In the absence of a bias correction, while driving LPJ-LMfire in the coupling process, ModelE drifts towards colder conditions in the high latitudes of the Northern Hemisphere in response to land cover simulated by LPJ-LMfire. A regional precipitation response is also prominent in the various combinations of the coupled model system, with a substantial intensification of the Summer Indian Monsoon and a drying pattern over Europe. Evaluation of the simulated climate against reconstructions of temperature from multiple proxies and the isotopic composition of precipitation (δ¹⁸O_p) from speleothems demonstrated the skill of ModelE in simulating past climate. A regional analysis of the simulated vegetation-climate response further confirmed the validity of this approach. The coupled model system is sensitive to the representation of shrubs and this land cover type requires particular attention as a potentially important driver of climate in regions where shrubs are abundant. Our results further demonstrate the importance of bias correction in coupled paleoclimate simulations.