Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations

• Published in: Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences Vol. 373; no. 2054; p. 20140424
• Main Authors: Braconnot, Pascale, Kageyama, Masa
• Format: Journal Article
• Language: English
• Published: England The Royal Society Publishing 13.11.2015; Royal Society, The
• Subjects: Cloud And Surface Albedo Feedbacks; Continental interfaces, environment; Ice-Sheet And Insolation Forcing; Last Glacial Maximum And Mid-Holocene Climates; Ocean, Atmosphere; Sciences of the Universe; Last Glacial Maximum and Mid-Holocene climates; ice-sheet and insolation forcing; cloud and surface albedo feedbacks
• ISSN: 1364-503X; 1471-2962
• DOI: 10.1098/rsta.2014.0424

Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results.