Reconstruction of sea level pressure fields over the Eastern North Atlantic and Europe back to 1500
- Cite this article as:
- Luterbacher, J., Xoplaki, E., Dietrich, D. et al. Climate Dynamics (2002) 18: 545. doi:10.1007/s00382-001-0196-6
Spatially and temporally high-resolution estimates of past natural climate variability are important to assess recent significant climate trends. The mid-latitude atmospheric circulation is the dominant factor for regional changes in temperature, rainfall, and other climatic variables. Here we present reconstructions of gridded monthly sea level pressure (SLP) fields back to 1659 and seasonal reconstructions from 1500-1658 for the eastern North Atlantic-European region (30°W to 40°E; 30°N to 70°N). These were developed using principal component regression analysis based on the combination of early instrumental station series (pressure, temperature and precipitation) and documentary proxy data from Eurasian sites. The relationships were derived over the 1901-1960 calibration period and verified over 1961-1990. Under the assumption of stationarity in the statistical relationships, a transfer function derived over the 1901-1990 period was used to reconstruct the 500-year large-scale SLP fields. Systematic quality testing indicated reliable winter reconstructions throughout the entire period. Lower skill was obtained for the other seasons, although meaningful monthly reconstructions were available from around 1700 onwards, when station pressure series became available. The quality and the reconstructed SLP fields for two exceptionally cold years (1573, 1740) are discussed and climatologically interpreted. An EOF analysis of the 1500-1999 winter SLP revealed, firstly, a zonal flow pattern with pronounced decadal to centenial time scale variations, secondly, a monopole pattern over northwest Europe and thirdly, a pattern modulating the meridional flow component over Europe. These 500-year SLP reconstructions should be useful for modelling studies, particulary for analyses of low-frequency atmospheric variability and for circulation dynamics.