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- Chen, Deliang, 1961, et al.
(författare)
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European Trend Atlas of Extreme Temperature and Precipitation Records
- 2015
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- This Atlas presents records of climatic variability and change in Europe starting before 1901 and focuses especially on trends of extreme temperatures and precipitation. The authors have used software developed within EMULATE (European and North Atlantic daily to MULtidecadal climATE variability) to obtain the extremes indices and temporal trends. The trend atlas provides an easy way to identify spatial patterns for a given time period, region, season, and index. The Atlas clearly shows that climate in Europe has changed over the last 100 to 150 years, such that the occurrence and intensity of warm temperature extremes have increased. Precipitation extremes have also changed, but with a less clear pattern compared to the temperature extremes.
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| 2. |
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| 3. |
- Luterbacher, Jürg, et al.
(författare)
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Circulation dynamics and its influence on European and Mediterranean January–April climate over the past half millennium : results and insights from instrumental data,documentary evidence and coupled climate models
- 2010
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Ingår i: Climatic Change. - Netherlands : Springer. - 0165-0009 .- 1573-1480. ; 101:1-2, s. 201-234
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Tidskriftsartikel (refereegranskat)abstract
- We use long instrumental temperature series together with available field reconstructions of sea-level pressure (SLP) and three-dimensional climate modelsimulations to analyze relations between temperature anomalies and atmospheric circulation patterns over much of Europe and the Mediterranean for the late winter/early spring (January–April, JFMA) season. A Canonical Correlation Analysis(CCA) investigates interannual to interdecadal covariability between a new gridded SLP field reconstruction and seven long instrumental temperature series covering the past 250 years. We then present and discuss prominent atmospheric circulation patterns related to anomalous warm and cold JFMA conditions within different European areas spanning the period 1760–2007. Next, using a data assimilation technique, we link gridded SLP data with a climate model (EC-Bilt-Clio) for a better dynamical understanding of the relationship between large scale circulationand European climate. We thus present an alternative approach to reconstruct climate for the pre-instrumental period based on the assimilated model simulations.Furthermore, we present an independent method to extend the dynamic circulation analysis for anomalously cold European JFMA conditions back to the sixteenth century. To this end, we use documentary records that are spatially representative for the long instrumental records and derive, through modern analogs, large-scale SLP, surface temperature and precipitation fields. The skill of the analog method is tested in the virtual world of two three-dimensional climate simulations (ECHOGand HadCM3). This endeavor offers new possibilities to both constrain climate model into a reconstruction mode (through the assimilation approach) and to better assess documentary data in a quantitative way.
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| 4. |
- Philipp, Andreas, et al.
(författare)
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Long-Term Variability of Daily North Atlantic–European Pressure Patterns since 1850 Classified by Simulated Annealing Clustering
- 2007
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Ingår i: Journal of Climate. - 1520-0442. ; 20:16, s. 4065-4095
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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