Erb, Michael P.McKay, Nicholas P.Steiger, NathanDee, SylviaHancock, ChrisIvanovic, Ruza F.Gregoire, Lauren J.Valdes, Paul2023-01-272023-01-272022Erb, Michael P., McKay, Nicholas P., Steiger, Nathan, et al.. "Reconstructing Holocene temperatures in time and space using paleoclimate data assimilation." <i>Climate of the Past,</i> 18, no. 12 (2022) Copernicus Publications: 2599-2629. https://doi.org/10.5194/cp-18-2599-2022.https://hdl.handle.net/1911/114271Paleoclimatic records provide valuable information about Holocene climate, revealing aspects of climate variability for a multitude of sites around the world. However, such data also possess limitations. Proxy networks are spatially uneven, seasonally biased, uncertain in time, and present a variety of challenges when used in concert to illustrate the complex variations of past climate. Paleoclimatic data assimilation provides one approach to reconstructing past climate that can account for the diverse nature of proxy records while maintaining the physics-based covariance structures simulated by climate models. Here, we use paleoclimate data assimilation to create a spatially complete reconstruction of temperature over the past 12 000 years using proxy data from the Temperature 12k database and output from transient climate model simulations. Following the last glacial period, the reconstruction shows Holocene temperatures warming to a peak near 6400 years ago followed by a slow cooling toward the present day, supporting a mid-Holocene which is at least as warm as the preindustrial. Sensitivity tests show that if proxies have an overlooked summer bias, some apparent mid-Holocene warmth could actually represent summer trends rather than annual mean trends. Regardless, the potential effects of proxy seasonal biases are insufficient to align the reconstructed global mean temperature with the warming trends seen in transient model simulations.engThis work is distributed under the Creative Commons Attribution 4.0 License.Reconstructing Holocene temperatures in time and space using paleoclimate data assimilationJournal articlecp-18-2599-2022https://doi.org/10.5194/cp-18-2599-2022