ALBERT

Description: The development of a daily historical European–North Atlantic mean sea level pressure dataset (EMSLP) for 1850–2003 on a 5° latitude by longitude grid is described. This product was produced using 86 continental and island stations distributed over the region 25°–70°N, 70°W–50°E blended with marine data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The EMSLP fields for 1850–80 are based purely on the land station data and ship observations. From 1881, the blended land and marine fields are combined with already available daily Northern Hemisphere fields. Complete coverage is obtained by employing reduced space optimal interpolation. Squared correlations (r 2) indicate that EMSLP generally captures 80%–90% of daily variability represented in an existing historical mean sea level pressure product and over 90% in modern 40-yr European Centre for Medium-Range Weather Forecasts Re-Analyses (ERA-40) over most of the region. A lack of sufficient observations over Greenland and the Middle East, however, has resulted in poorer reconstructions there. Error estimates, produced as part of the reconstruction technique, flag these as regions of low confidence. It is shown that the EMSLP daily fields and associated error estimates provide a unique opportunity to examine the circulation patterns associated with extreme events across the European–North Atlantic region, such as the 2003 heat wave, in the context of historical events.

Description: Reconstructed daily mean sea level pressure patterns of the North Atlantic–European region are classified for the period 1850 to 2003 to explore long-term changes of the atmospheric circulation and its impact on long-term temperature variability in the central European region. Commonly used k-means clustering algorithms resulted in classifications of low quality because of methodological deficiencies leading to local optima by chance for complex datasets. In contrast, a newly implemented clustering scheme combining the concepts of simulated annealing and diversified randomization (SANDRA) is able to reduce substantially the influence of chance in the cluster assignment, leading to partitions that are noticeably nearer to the global optimum and more stable. The differences between conventional cluster analysis and the SANDRA scheme are significant for subsequent analyses of single clusters—in particular, for trend analysis. Conventional indices used to determine the appropriate number of clusters failed to provide clear guidance, indicating that no distinct separation between clusters of circulation types exists in the dataset. Therefore, the number of clusters is determined by an external indicator, the so-called dominance criteria for t-mode principal component analysis. Nevertheless, the resulting partitions are stable for certain numbers of clusters and provide meaningful and reproducible clusters. The resulting types of pressure patterns reveal pronounced long-term variability and various significant trends of the time series of seasonal cluster frequency. Tentative estimations of central European temperature changes based solely on seasonal cluster frequencies can explain between 33.9% (summer) and 59.0% (winter) of temperature variance on the seasonal time scale. However, the signs of long-term changes in temperature are correctly reproduced even on multidecadal–centennial time scales. Moreover, linear warming trends are reproduced, implying from one-third up to one-half of the observed temperature increase between 1851/52 and 2003 (except for summer, but with significant trends for spring and autumn), indicating that changes in daily circulation patterns contribute to the observed overall long-term warming in the central European region.

Description: The authors estimate the change in extreme winter weather events over Europe that is due to a long-term change in the North Atlantic Oscillation (NAO) such as that observed between the 1960s and 1990s. Using ensembles of simulations from a general circulation model, large changes in the frequency of 10th percentile temperature and 90th percentile precipitation events over Europe are found from changes in the NAO. In some cases, these changes are comparable to the expected change in the frequency of events due to anthropogenic forcing over the twenty-first century. Although the results presented here do not affect anthropogenic interpretation of global and annual mean changes in observed extremes, they do show that great care is needed to assess changes due to modes of climate variability when interpreting extreme events on regional and seasonal scales. How changes in natural modes of variability, such as the NAO, could radically alter current climate model predictions of changes in extreme weather events on multidecadal time scales is also discussed.

Description: There has been considerable recent interest in paleoclimate reconstructions of the temperature history of the last millennium. A wide variety of techniques have been used. The interrelation among the techniques is sometimes unclear, as different studies often use distinct data sources as well as distinct methodologies. Here recent work is reviewed and some new calculations performed with an aim to clarifying the consequences of the different approaches used. A range of proxy data collections introduced by different authors is used to estimate Northern Hemispheric annual mean temperatures with two reconstruction algorithms: (1) inverse regression and, (2) compositing followed by variance matching (CVM). It is found that inverse regression tends to give large weighting to a small number of proxies and that the second approach (CVM) is more robust to varying proxy input. The choice of proxy records is one reason why different reconstructions show different ranges. A reconstruction using 13 proxy records extending back to AD 1000 shows a maximum pre-industrial temperature of 0.25 K (relative to the 1866 to 1970 mean). The standard error on this estimate, based on the residual in the calibration period, is 0.14 K. Instrumental temperatures for two recent years (1998 and 2005) have exceeded the pre-industrial estimated maximum by more than 4 standard deviations of the calibration period residual.

Description: There has been considerable recent interest in paleoclimate reconstructions of the temperature history of the last millennium. A wide variety of techniques have been used. The interrelation between the techniques is sometimes unclear, as different studies often use distinct data sources as well as distinct methodologies. Recent work is reviewed with an aim to clarifying the import of the different approaches. A range of proxy data collections used by different authors are passed through two reconstruction algorithms: firstly, inverse regression and, secondly, compositing followed by variance matching. It is found that the first method tends to give large weighting to a small number of proxies and that the second approach is more robust to varying proxy input. A reconstruction using 18 proxy records extending back to AD 1000 shows a maximum pre-industrial temperature of 0.25 K (relative to the 1866 to 1970 mean). The standard error on this estimate, based on the residual in the calibration period is 0.149 K. Two recent years (1998 and 2005) have exceeded the estimated pre-industrial maximum by more than 4 standard errors.

Description: In this paper we try to develop a quantitative understanding of the absolute change in climate between the mid-Holocene ~6000 yr BP (6 ka) and the preindustrial period ~1750 AD (0 ka) in the northern high latitudes. This has been performed using available quantitative reconstructions of temperature and precipitation from proxy data. The main reason for comparing these two periods is that the summer insolation in the northern high latitudes was higher at 6 ka than 0 ka due to orbital forcing. Another reason is that it gives us the opportunity to quantitatively compare results from proxy data with results from several climate model simulations for the same periods by using data from the Palaeoclimate Modelling Intercomparison Project. Another aim has been to try and quantify the uncertainties in the proxy data reconstructions. The reconstructions indicate that the northern high latitudes were 0.96±0.42°C warmer in summer, 1.71±1.70°C warmer in winter and 2.02±0.72 warmer in the annual mean temperature at 6 ka compared to 0 ka. The warmer climate in summer around 6 ka BP was most likely directly related to the higher summer insolation whereas the warmer climate in annual mean and winter temperature may possibly be explained by internal physical mechanisms such as heat stored in the oceans during summer and released during the cold season or by changes in the vegetation causing albedo changes that may affect seasonal temperatures differentially. For the future there is a great need to reduce the errors of the predictions as well as improving our understanding of how a proxys respond to changes in environmental variables.

Description: The solar orbital forcing induced changes in insolation at the mid-Holocene compared to the late Holocene, which causes an amplification of the seasonal cycle in the Northern Hemisphere in the earlier period. The climate response over northern high latitudes, to this change in forcing has been investigated in three types of PMIP (Paleoclimate Modelling Intercomparison Project) simulations with different complexity of the climate system. The model results have also been compared with available reconstructions from temperature proxy data. Both the reconstructions and the PMIP2 models show a warm response in annual mean temperature, as well as in summer and winter temperature. The model-model comparisons indicate the importance of including the different physical feedbacks (ocean, sea-ice, vegetation) in the climate model. An objective selection method is applied in the model-data comparison to evaluate the capability of the climate model in reproducing the spatial response pattern. The comparisons between the reconstructions and the best-fit selected simulations show that over the northern high latitudes, summer temperature change follows closely to the insolation and shows a common feature with strong warming over land and relatively weak warming over ocean. A pronounced warming centre is found over Barents Sea in winter in model simulations, which is also supported by the nearby northern Eurasian continental reconstructions. The warming over Barents Sea corresponds to a positive North Atlantic Oscillation (NAO). The strengthened sea level pressure gradient may have caused a northward shift of the Atlantic storm track. It results in enhanced westerlies towards the northern Eurasia, which may be responsible for the winter warming over northern Fennoscandia and northern Siberia.