Mid-Holocene climate change in Europe: a data-model comparison

Abstract

Abstract. We present here a comparison between the outputs of 25 General Circulation Models run for the midHolocene period (6 ka BP) with a set of palaeoclimate reconstructions based on over 400 fossil pollen sequences distributed across the European continent. Three climate parameters were available (moisture availability, temperature of the coldest month and growing degree days), which were grouped together using cluster analysis to provide regions of homogenous climate change. Each model was then investigated to see if it reproduced 1) similar patterns of change and 2) the correct location of these regions. A fuzzy logic distance was used to compare the output of the model with the data, which allowed uncertainties from both the model and data to be taken into account. The models were compared by the magnitude and direction of climate change within the region as well as the spatial pattern of these changes. The majority of the models are grouped together, suggesting that they are becoming more consistent. A test against a set of zero anomalies (no climate change) shows that, although the models are unable to reproduce the exact patterns of change, they all produce the correct signs of change observed for the mid-Holocene.

The influence of atmospheric circulation on the mid-Holocene climate of Europe: a data–model comparison

“…Neither the ensemble nor individual PMIP3/CMIP5 models show the pattern of winter temperature anomalies shown by the reconstruction, which indicates a more extensive and relatively strong warming extending over much of northern and central Europe, together with a strong but somewhat less extensive cooling over southern Europe. This pattern of high-latitude warming and low-latitude cooling is comparable with previous midHolocene winter temperature reconstructions (Cheddadi et al, 1997;Brewer et al, 2007;Wu et al, 2007). Precipitation changes in winter in the model ensemble are limited, as it is in all of the model simulations (Fig.…”

“…Previous data-model comparisons have shown that climate models fail to simulate the summer cooling observed by proxy data over Southern Europe that is contrary to the increase in summer insolation in the MH (Davis and Brewer, 2009), and the strong winter warming observed over parts of northern Europe (Masson et al, 1999;Bonfils et al, 2004;Brewer et al, 2007) that is also contrary to the decrease in winter insolation in the MH. Nevertheless, models have still been able to demonstrate high-latitude winter warming through the action of local feedbacks such as sea ice and vegetation (Wohlfahrt et al, 2004;Braconnot et al, 2007b;Otto et al, 2009).…”

“…This data set represents a substantial improvement compared with data sets used in previous data-model comparisons. Our fossil pollen data set includes 48 % more sites compared with Davis et al (2003) and used by Brewer et al (2007), and 143 % more sites compared to Cheddadi et al (1997), with this improvement in data coverage spread throughout Europe (Fig. 1).…”

Spatial variations of effective moisture in the western United States

“…Cluster analysis is a useful tool in assessing climate mechanisms [Bonfils et al, 2004a] and data-model comparisons [Brewer et al, 2007]. Here we use the Ward [1963] method of hierarchical clustering with a Euclidian distance measure to maximize within-cluster similarities among objects (i.e., stations) and minimize between-cluster similarities [Balling, 1984].…”

Climate change between the mid and late Holocene in northern high latitudes – Part 2: Model-data comparisons

“…The mid-Holocene is one of the noticed warm periods that is well documented by proxy data and is often used to evaluate how models respond to a change primarily in insolation. Most of these data-model comparisons focus on proxy data rich areas such as southern and mid-latitude Europe (Liao et al, 1994;Harrison et al, 1998;Masson et al, 1999;Prentice et al, 1998;Guiot et al, 1999;Joussaume et al, 1999;Bonfils et al, 2004;Gladstone et al, 2005;Masson-Delmotte et al, 2006;Brewer et al, 2007). The high-latitude region is less often addressed due to the relative lack of proxy data compared to some other regions.…”