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Johannes P. Werner, Juerg Luterbacher, and Jason E. Smerdon

Abstract

A pseudoproxy comparison is presented for two statistical methods used to derive annual climate field reconstructions (CFRs) for Europe. The employed methods use the canonical correlation analysis (CCA) procedure presented by Smerdon et al. and the Bayesian hierarchical model (BHM) method adopted from Tingley and Huybers. Pseudoproxy experiments (PPEs) are constructed from modeled temperature data sampled from the 1250-yr paleo-run of the NCAR Community Climate System Model (CCSM) version 1.4 model by Ammann et al. Pseudoproxies approximate the distribution of the multiproxy network used by Mann et al. over the European region of interest. Gaussian white noise is added to the temperature data to mimic the combined signal and noise properties of real-world proxies. Results indicate that, while both methods perform well in areas with good proxy coverage, the BHM method outperforms the CCA method across the entire field and additionally returns objective error estimates.

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Naiming Yuan, Minghu Ding, Yan Huang, Zuntao Fu, Elena Xoplaki, and Juerg Luterbacher

Abstract

In this study, observed temperature records of 12 stations from Antarctica island, coastline, and continental areas are analyzed by means of detrended fluctuation analysis (DFA). After Monte Carlo significance tests, different long-term climate memory (LTM) behaviors are found: temperatures from coastal and island stations are characterized by significant long-term climate memory whereas temperatures over the Antarctic continent behave more like white noise, except for the Byrd station, which is located in the West Antarctica. It is argued that the emergence of LTM may be dominated by the interactions between local weather system and external slow-varying systems (ocean), and therefore the different LTM behaviors between temperatures over the Byrd station and that over other continental stations can be considered as a reflection of the different climatic environments between West and East Antarctica. By calculating the trend significance with the effect of LTM taken into account, and further comparing the results with those obtained from assumptions of autoregressive (AR) process and white noise, it is found that 1) most of the Antarctic stations do not show any significant trends over the past several decades, and 2) more rigorous trend evaluation can be obtained if the effect of LTM is considered. Therefore, it is emphasized that for air temperatures over Antarctica, especially for the Antarctica coastline, island, and the west continental areas, LTM is nonnegligible for trend evaluation.

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Rob Allan, Philip Brohan, Gilbert P. Compo, Roger Stone, Juerg Luterbacher, and Stefan Brönnimann

No abstract available.

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Stella Dafka, Andrea Toreti, Juerg Luterbacher, Prodromos Zanis, Evangelos Tyrlis, and Elena Xoplaki

Abstract

Episodes of extremely strong northerly winds (known as etesians) during boreal summer can cause hazardous conditions over the Aegean Archipelago (Greece) and represent a threat for the safe design, construction, and operation of wind energy turbines. Here, these extremes are characterized by employing a peak-over-threshold approach in the extended summer season (May–September) from 1989 to 2008. Twelve meteorological stations in the Aegean are used, and results are compared with 6-hourly wind speed data from five ERA-Interim–driven regional climate model (RCM) simulations from the European domain of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX). The main findings show that, in the range of wind speeds for the maximum power output of the turbine, the most etesian-exposed stations could operate 90% at a hub height of 80 m. The central and northern Aegean are identified as areas prone to wind hazards, where medium- to high-wind (class II or I according to the International Electrotechnical Committee standards) wind turbines could be more suitable. In the central Aegean, turbines with a cutout wind speed > 25 m s−1 are recommended. Overall, RCMs can be considered a valuable tool for investigating wind resources at regional scale. Therefore, this study encourages a broader use of climate models for the assessment of future wind energy potential over the Aegean.

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