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Abstract:This paper describes the HISTALP database, consisting of monthly homogenised records of temperature, pressure, precipitation, sunshine and cloudiness for the 'Greater Alpine Region' (GAR,(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(43)(44)(45)(46)(47)(48)(49). The longest temperature and air pressure series extend back to 1760, precipitation to 1800, cloudiness to the 1840s and sunshine to the 1880s. A systematic QC procedure has been applied to the series and a high number of inhomogeneities (more than 2500) and outliers (more than 5000) have been detected and removed. The 557 HISTALP series are kept in different data modes: original and homogenised, gap-filled and outlier corrected station mode series, grid-1 series (anomaly fields at 1°× 1°, lat × long) and Coarse Resolution Subregional (CRS) mean series according to an EOF-based regionalisation. The leading climate variability features within the GAR are discussed through selected examples and a concluding linear trend analysis for 100, 50 and 25-year subperiods for the four horizontal and two altitudinal CRSs. Among the key findings of the trend analysis is the parallel centennial decrease/increase of both temperature and air pressure in the 19th/20th century. The 20th century increase (+1.2°C/+1.1 hPa for annual GAR-means) evolved stepwise with a first peak near 1950 and the second increase (1.3°C/0.6hPa per 25 years) starting in the 1970s. Centennial and decadal scale temperature trends were identical for all subregions. Air pressure, sunshine and cloudiness show significant differences between low versus high elevations. A long-term increase of the high-elevation series relative to the low-elevation series is given for sunshine and air pressure. Of special interest is the exceptional high correlation near 0.9 between the series on mean temperature and air pressure difference (high-minus low-elevation). This, further developed via some atmospheric statics and thermodynamics, allows the creation of 'barometric temperature series' without use of the measures of temperature. They support the measured temperature trends in the region. Precipitation shows the most significant regional and seasonal differences with, e.g., remarkable opposite 20th century evolution for NW (9% increase) versus SE (9% decrease). Other long-and short-term features are discussed and indicate the promising potential of the new database for further analyses and applications.

Palaeoclimatology provides our only means of assessing climatic variations before the beginning of instrumental records. The various proxy variables used, however, have a number of limitations which must be adequately addressed and understood. Besides their obvious spatial and seasonal limitations, different proxies are also potentially limited in their ability to represent climatic variations over a range of different timescales. Simple correlations with instrumental data over the period since ad 1881 give some guide to which are the better proxies, indicating that coral- and ice-core-based reconstructions are poorer than tree-ring and historical ones. However, the quality of many proxy time series can deteriorate during earlier times. Suggestions are made for assessing proxy quality over longer periods than the last century by intercomparing neighbouring proxies and, by comparisons with less temporally resolved proxies such as borehole temperatures. We have averaged 17 temperature reconstructions (representing various seasons of the year), all extending back at least to the mid-seventeenth century, to form two annually resolved hemispheric series (NH10 and SH7). Over the 1901–91 period, NH10 has 36% variance in common with average NH summer (June to August) temperatures and 70% on decadal timescales. SH7 has 16% variance in common with average SH summer (December to February) temperatures and 49% on decadal timescales, markedly poorer than the reconstructed NH series. The coldest year of the millennium over the NH is ad 1601, the coldest decade 1691–1700 and the seventeenth is the coldest century. A Principal Components Analysis (PCA) is performed on yearly values for the 17 reconstructions over the period ad 1660–1970. The correlation between PC1 and NH10 is 0.92, even though PC1 explains only 13.6% of the total variance of all 17 series. Similar PCA is performed on thousand-year-long General Circulation Model (GCM) data from the Geophysical Fluid Dynamics Laboratory (GFDL) and the Hadley Centre (HADCM2), sampling these for the same locations and seasons as the proxy data. For GFDL, the correlation between its PC1 and its NH10 is 0.89, while for HADCM2 the PCs group markedly differently. Cross-spectral analyses are performed on the proxy data and the GFDL model data at two different frequency bands (0.02 and 0.03 cycles per year). Both analyses suggest that there is no large-scale coherency in the series on these timescales. This implies that if the proxy data are meaningful, it should be relatively straightforward to detect a coherent near-global anthropogenic signal in surface temperature data.

Cooling Recent Warming Reverses Long-Term Arctic www.sciencemag.org (this information is current as of September 25, 2009 ):The following resources related to this article are available online at

An atlas of megadroughts in Europe and in the Mediterranean Basin during the Common Era provides insights into climate variability.