A GCM comparison of Pleistocene super-interglacial periods in relation to Lake El'gygytgyn, NE Arctic Russia

Abstract

Abstract. Until now, the lack of time-continuous, terrestrial paleoenvironmental data from the Pleistocene Arctic has made model simulations of past interglacials difficult to assess. Here, we compare climate simulations of four warm interglacials at Marine Isotope Stages (MISs) 1 (9 ka), 5e (127 ka), 11c (409 ka) and 31 (1072 ka) with new proxy climate data recovered from Lake El'gygytgyn, NE Russia. Climate reconstructions of the mean temperature of the warmest month (MTWM) indicate conditions up to 0.4, 2.1, 0.5 and 3.1 • C warmer than today during MIS 1, 5e, 11c and 31, respectively. While the climate model captures much of the observed warming during each interglacial, largely in response to boreal summer (JJA) orbital forcing, the extraordinary warmth of MIS 11c compared to the other interglacials in the Lake El'gygytgyn temperature proxy reconstructions remains difficult to explain. To deconvolve the contribution of multiple influences on interglacial warming at Lake El'gygytgyn, we isolated the influence of vegetation, sea ice and circum-Arctic land ice feedbacks on the modeled climate of the Beringian interior. Simulations accounting for climate-vegetation-land-surface feedbacks during all four interglacials show expanding boreal forest cover with increasing summer insolation intensity. A deglaciated Greenland is shown to have a minimal effect on northeast Asian temperature during the warmth of stages 11c and 31 (Melles et al., 2012). A prescribed enhancement of oceanic heat transport into the Arctic Ocean does have some effect on Lake El'gygytgyn's regional climate, but the exceptional warmth of MIS l1c remains enigmatic compared to the modest orbital and greenhouse gas forcing during that interglacial.

Oceanic response to changes in the WAIS and astronomical forcing during the MIS31 superinterglacial

“…Analyses have been carried out for the last 100 years of these 1000-year simulations. The astronomical forcing is assumed to represent 1072 ka based on the warmest summer month in the Lake El'gygytgyn reconstruction (Coletti et al, 2015;Melles et al, 2012; Table S1 in the Supplement):…”

“…This epoch has been characterized by warmer global air temperatures and substantial melting of polar glaciers compared to today (Melles et al, 2012;Wet et al, 2016). However, paleoreconstructions and modeling results disagree with respect to the North Hemisphere (NH) warming during MIS31, suggesting the need for a better understanding of this interglacial and other warmer climates as discussed by Melles et al (2012) and Coletti et al (2015).…”

“…This is especially true when evaluating the climate response to potential changes in the meridional overturning circulation (MOC) and the oceanic heat transport (OHT; . Increased OHT from the Pacific into the Arctic associated with changes in Antarctic ice volume has been argued to affect the Beringian climate during interglacial epochs (Coletti et al, 2015) and maintain warm high-latitude oceanic surface temperatures in many intervals throughout the geologic past (Comeau et al, 2016).…”

“…Others have taken advantage of simplified climate models using an atmospheric general circulation model (GCM) coupled to a slab mixed-layer ocean model (Lunt et al, 2017;Coletti et al, 2015;Roychowdhury and DeConto, 2016). Though valid, this modeling approach reduces oceanatmosphere feedbacks that are crucial for the reorganization of atmospheric flow on long timescales.…”

“…It has been emphasized by coupled modeling studies that oceanic dynamical changes related to orbital fluctuations are the primary forcing in determining large-scale atmospheric flow patterns (Erb et al, 2015;Tomas et al, 2016). Because oceanic dynamical changes during interglacial intervals are important for determining the large-scale atmospheric circulation and temperature distribution (Coletti et al, 2015), solutions to these issues are pursued here by employing the International Centre for Theoretical Physics Coupled Global Climate Model (ICTP-CGCM; Kucharski et al, 2015).…”