Influence of solar variability, CO<sub>2</sub> and orbital forcing between 1000 and 1850 AD in the IPSLCM4 model

Abstract

Abstract. Studying the climate of the last millennium gives the possibility to deal with a relatively well-documented climate essentially driven by natural forcings. We have performed two simulations with the IPSLCM4 climate model to evaluate the impact of Total Solar Irradiance (TSI), CO 2 and orbital forcing on secular temperature variability during the preindustrial part of the last millennium. The Northern Hemisphere (NH) temperature of the simulation reproduces the amplitude of the NH temperature reconstructions over the last millennium. Using a linear statistical decomposition we evaluated that TSI and CO 2 have similar contributions to secular temperature variability between 1425 and 1850 AD. They generate a temperature minimum comparable to the Little Ice Age shown by the temperature reconstructions. Solar forcing explains ∼80% of the NH temperature variability during the first part of the millennium (1000-1425 AD) including the Medieval Climate Anomaly (MCA). It is responsible for a warm period which occurs two centuries later than in the reconstructions. This mismatch implies that the secular variability during the MCA is not fully explained by the response of the model to the TSI reconstruction.With a signal-noise ratio (SNR) estimate we found that the temperature signal of the forced simulation is significantly different from internal variability over area wider than ∼5.10 6 km 2 , i.e. approximately the extent of Europe. Orbital forcing plays a significant role in latitudes higher than 65 • N in summer and supports the conclusions of a recent study Correspondence to: J. Servonnat (jerome.servonnat@lsce.ipsl.fr) on an Arctic temperature reconstruction over past two millennia. The forced variability represents at least half of the temperature signal on only ∼30% of the surface of the globe. This study suggests that regional reconstructions of the temperature between 1000 and 1850 AD are likely to show weak signatures of solar, CO 2 and orbital forcings compared to internal variability.

Simulated climate variability in the region of Rapa Nui during the last millennium

“…Only very few simulations of the last millennium using comprehensive coupled climate models are available to address this topic (e.g. Ammann et al, 2007;Servonnat et al, 2010;Swingedouw et al, 2010). Therefore, the following analyses of the millennium ensemble simulations with the comprehensive Earth system models ECHAM5/MPIOM and ECHO-G (González-Rouco et al, 2006) are an important contribution for understanding pre-industrial climate variability in the Pacific region.…”

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 3: Practical considerations, relaxed assumptions, and using tree-ring data to address the amplitude of solar forcing

“…In combination with a lack of information from winter, this might cause internal unforced variability to dominate too much over the response to external forcings. A model study by Servonnat et al (2010) suggested that the responses to external forcings are only detectable within regions larger than approximately the size of Europe, thus pointing to the importance of not using regions that are too small in studies like this. On the other hand, the pseudoproxy study by suggested that annual-mean temperature data, with realistic proxy noise levels, from at least 40 randomly distributed single grid-boxes are needed to clearly separate between the two sets of multiple forcings used here.…”

“…Moreover, unforced temperature variability will have a larger influence in a single grid box as compared to an average of several grid boxes, where the forced part of the temperature variation will be more easily detected (e.g. Servonnat et al, 2010). Thus, as we are here primarily inter- ested in seeing how well the model simulates the externally forced temperature variation, it appears recommendable to select an area that is large enough to detect the forced simulated temperature response but small enough that the actual proxy record provides a meaningful approximation of the true temperature variability.…”

Assessing reconstruction techniques of the Atlantic Ocean circulation variability during the last millennium

“…Rahmstorf et al (2015), for example, showed instead an AMOC weakening during the industrial period as compared to the LIA, in agreement with results from instrumental records (Dima and Lohmann 2010) and CMIP5 historical model simulations (Drijfhout et al 2012;Cheng et al 2013;Jungclaus et al 2014). These latter however generally disagree on the mechanisms underlying the AMOC variability, as well as on the AMOC sensitivity to external forcing (e.g., Servonnat et al 2010;Ortega et al 2012;Hofer et al 2011). Thus, both AMOC variability and its influence on the climate of the last millennium are still far from being clear.…”

“…The relative abundance of high resolution proxy data for this period with respect to earlier ones has facilitated reconstructions of relevant climate variables-most notably temperature and hydroclimate parameters-on different spatial scales (e.g., Mann et al 2008;Cook et al 2010;Pages 2k Consortium 2013). Estimations of past forcing factors have additionally allowed simulating the climate evolution of this period with models of different complexity (e.g., Crowley 2000;Bauer et al 2003;González-Rouco et al 2003b;Servonnat et al 2010;Jungclaus et al 2010), thus making systematic comparisons between simulations Abstract We assess the use of the meridional thermalwind transport estimated from zonal density gradients to reconstruct the oceanic circulation variability during the last millennium in a forced simulation with the ECHO-G coupled climate model. Following a perfect-model approach, model-based pseudo-reconstructions of the Atlantic meridional overturning circulation (AMOC) and the Florida Current volume transport (FCT) are evaluated against their true simulated variability.…”