North American paleoclimate reconstructions for the Last Glacial Maximum using an inverse modeling through iterative forward modeling approach applied to pollen data. Issue 20 (30th October 2016)

• Record Type: Journal Article
• Authors: Izumi, Kenji; Bartlein, Patrick J.
• Is Part Of: Geophysical research letters. Volume 43:Issue 20(2016)
• Page Start: 10, 965
• Page End: 10, 972
• Publication Date: 2016-10-30
• Subjects: pollen‐based climate reconstruction -- inverse‐vegetation modeling -- the Last Glacial Maximum; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2016GL070152
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The inverse modeling through iterative forward modeling (IMIFM) approach was used to reconstruct Last Glacial Maximum (LGM) climates from North American fossil pollen data. The approach was validated using modern pollen data and observed climate data. While the large‐scale LGM temperature IMIFM reconstructions are similar to those calculated using conventional statistical approaches, the reconstructions of moisture variables differ between the two approaches. We used two vegetation models, BIOME4 and BIOME5‐beta, with the IMIFM approach to evaluate the effects on the LGM climate reconstruction of differences in water use efficiency, carbon use efficiency, and atmospheric CO2 concentrations. Although lower atmospheric CO2 concentrations influence pollen‐based LGM moisture reconstructions, they do not significantly affect temperature reconstructions over most of North America. This study implies that the LGM climate was very cold but not very much drier than present over North America, which is inconsistent with previous studies. Key Points: We demonstrate pollen‐based climate reconstruction using an inverse‐vegetation modeling approach North America's Last Glacial Maximum climate may have been more mesic than previous studies suggest Reconstructed temperatures are similar using classical statistical and inverse‐modeling approaches