Journal
CLIMATE DYNAMICS
Volume 34, Issue 7-8, Pages 1115-1128Publisher
SPRINGER
DOI: 10.1007/s00382-009-0577-9
Keywords
Sea level pressure; Climate field reconstructions; Logbooks; Instrumental pressure series; Europe; Principal component regression
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Funding
- Swiss National Science Foundation (SNSF) through its National Center of Competence in Research
- European Science Foundation (ESF)
- EU [036961, 212250]
- MILLENNIUM Project [IP 017008-2]
- U.S. Department of Energy [DE-FG02-98ER62601]
- international ACRE (atmospheric circulation reconstructions over the Earth) initiative
- Foundation Marchese Francesco Medici del Vascello
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Local to regional climate anomalies are to a large extent determined by the state of the atmospheric circulation. The knowledge of large-scale sea level pressure (SLP) variations in former times is therefore crucial when addressing past climate changes across Europe and the Mediterranean. However, currently available SLP reconstructions lack data from the ocean, particularly in the pre-1850 period. Here we present a new statistically-derived 5A degrees A xA 5A degrees resolved gridded seasonal SLP dataset covering the eastern North Atlantic, Europe and the Mediterranean area (40A degrees W-50A degrees E; 20A degrees N-70A degrees N) back to 1750 using terrestrial instrumental pressure series and marine wind information from ship logbooks. For the period 1750-1850, the new SLP reconstruction provides a more accurate representation of the strength of the winter westerlies as well as the location and variability of the Azores High than currently available multiproxy pressure field reconstructions. These findings strongly support the potential of ship logbooks as an important source to determine past circulation variations especially for the pre-1850 period. This new dataset can be further used for dynamical studies relating large-scale atmospheric circulation to temperature and precipitation variability over the Mediterranean and Eurasia, for the comparison with outputs from GCMs as well as for detection and attribution studies.
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