The last interglaciation (-130 to 116 ka) is a time period with a strong astronomically induced seasonal forcing of insolation compared to the present. Proxy records indicate a significantly different climate to that of the modern, in particular Arctic summer warming and higher eustatic sea level. Because the forcings are relatively well constrained, it provides an opportunity to test numerical models which are used for future climate prediction. In this paper we compile a set of climate model simulations of the early last interglaciation (130 to 125 ka), encompassing a range of model complexities. We compare the simulations to each other and to a recently published compilation of last interglacial temperature estimates.We show that the annual mean response of the models is rather small, with no clear signal in many regions. However, the seasonal response is more robust, and there is significant agreement amongst models as to the regions of warming vs cooling. However, the quantitative agreement of the model simulations with data is poor, with the models in general underestimating the magnitude of response seen in the proxies. Taking possible seasonal biases in the proxies into account improves the agreement, but only marginally. However, a lack of uncertainty estimates in the data does not allow us to draw firm conclusions. Instead, this paper points to several ways in which both modelling and data could be improved, to allow a more robust model-data comparison. © Author(s) 2013

Recent evidence shows that wind‐driven ocean currents, like the western boundary currents, are strongly affected by global warming. However, due to insufficient observations both on temporal and spatial scales, the impact of climate change on large‐scale ocean gyres is still not clear. Here, based on satellite observations of sea surface height and sea surface temperature, we find a consistent poleward shift of the major ocean gyres. Due to strong natural variability, most of the observed ocean gyre shifts are not statistically significant, implying that natural variations may contribute to the observed trends. However, climate model simulations forced with increasing greenhouse gases suggest that the observed shift is most likely to be a response of global warming. The displacement of ocean gyres, which is coupled with the poleward shift of extratropical atmospheric circulation, has broad impacts on ocean heat transport, regional sea level rise, and coastal ocean circulation.

Abstract. Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980–2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr−1 due to large discrepancies in modelled snowfall accumulation.

Abstract. There is a growing number of proxy-based reconstructions detailing the climatic changes that occurred during the last interglacial period (LIG). This period is of special interest, because large parts of the globe were characterized by a warmer-than-present-day climate, making this period an interesting test bed for climate models in light of projected global warming. However, mainly because synchronizing the different palaeoclimatic records is difficult, there is no consensus on a global picture of LIG temperature changes. Here we present the first model inter-comparison of transient simulations covering the LIG period. By comparing the different simulations, we aim at investigating the common signal in the LIG temperature evolution, investigating the main driving forces behind it and at listing the climate feedbacks which cause the most apparent inter-model differences. The model inter-comparison shows a robust Northern Hemisphere July temperature evolution characterized by a maximum between 130–125 ka BP with temperatures 0.3 to 5.3 K above present day. A Southern Hemisphere July temperature maximum, −1.3 to 2.5 K at around 128 ka BP, is only found when changes in the greenhouse gas concentrations are included. The robustness of simulated January temperatures is large in the Southern Hemisphere and the mid-latitudes of the Northern Hemisphere. For these regions maximum January temperature anomalies of respectively −1 to 1.2 K and −0.8 to 2.1 K are simulated for the period after 121 ka BP. In both hemispheres these temperature maxima are in line with the maximum in local summer insolation. In a number of specific regions, a common temperature evolution is not found amongst the models. We show that this is related to feedbacks within the climate system which largely determine the simulated LIG temperature evolution in these regions. Firstly, in the Arctic region, changes in the summer sea-ice cover control the evolution of LIG winter temperatures. Secondly, for the Atlantic region, the Southern Ocean and the North Pacific, possible changes in the characteristics of the Atlantic meridional overturning circulation are crucial. Thirdly, the presence of remnant continental ice from the preceding glacial has shown to be important when determining the timing of maximum LIG warmth in the Northern Hemisphere. Finally, the results reveal that changes in the monsoon regime exert a strong control on the evolution of LIG temperatures over parts of Africa and India. By listing these inter-model differences, we provide a starting point for future proxy-data studies and the sensitivity experiments needed to constrain the climate simulations and to further enhance our understanding of the temperature evolution of the LIG period.

The greening of Arabia: multiple opportunities for human occupation of the Arabian peninsula during the Late Pleistocene inferred from an ensemble of climate model simulations. Quaternary International, 382. pp. 181199.