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Previous research has shown that we believe more in the reality of climate change when we experience warmer-than-usual temperatures. This reflects a psychological process in which easily accessible information from personal weather experiences is used as a heuristic to form climate opinions. This paper replicates and extends upon a research design and results of Egan and Mullin to provide the first systematic European study of the Local Warming Effect. Based on data from 12 European countries, the analysis shows that when objective temperatures increase by two standard deviations (5 °C) relative to normal temperatures, climate opinions are strengthened by around 0.5–1.0 percentage points – comparable to the effect of a full step to the left on a 0–10 political ideology scale. [ABSTRACT FROM AUTHOR]

Long and homogeneous series are a necessary requirement for reliable climate analysis. Relocation of measuring equipment from one station to another, such as from the city center to a rural area or a nearby airport, is one of the causes of discontinuities in these long series that may affect trend estimates. In this paper, an updated procedure for the composition of long series, by combining data from nearby stations, is introduced. It couples an evolution of the blending procedure already implemented within the European Climate Assessment and Dataset (ECA&D, which combines data from stations no more than 12.5 km apart from each other) with a duplicate removal, alongside the quantile matching homogenization procedure. The ECA&D contains approximately 3000 homogenized series for each temperature variable prior to the blending procedure, and approximately 820 of these are longer than 60 years; the process of blending increases the number of long series to more than 900. Three case studies illustrate the effects of the homogenization on single blended series, showing the effectiveness of separate adjustments on extreme and mean values (Geneva, Switzerland), on cases in which blending is complex (Rheinstetten, Germany), and on series that are completed by adding relevant portions of Global Telecommunications System synoptic data (Siauliai, Lithuania). A trend assessment on the whole European continent reveals the removal of negative and very large trends, demonstrating a stronger spatial consistency. The new blended and homogenized dataset will allow a more reliable use of temperature series for indices calculation and for the calculation of gridded datasets and it will be available online for users (https://www.ecad.eu). [ABSTRACT FROM AUTHOR]

Atmospheric variables play a fundamental role in driving man-managed ecosystems and more specifically in agro-ecosystems, determining the quantity and quality of crop production. On the other hand, climate variability can be seen as the superimposition of gradual and abrupt changes. This paper is focused on European surface air temperature in the period 1951-2010. Analysis of this dataset identified breakpoints that define two homogeneous sub-periods: 1951-1987 and 1988-2010. Thermal resources for crops were analyzed adopting a 'normal heat hours' approach. Computation highlighted a general increase in thermal resources in the European continent for crop groups II and III (C3 and C4 plants adapted to high or moderate temperatures), while a decline of thermal resources for crop group I (cold adapted C3) was highlighted in the Mediterranean area. The climate variability justifies a change in the potential latitudinal limits of different groups of crops, representing a fundamental step for crop adaptation to climate change. [ABSTRACT FROM AUTHOR]

Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45–65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45–55°N, oat had its maximum at 55–65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops. [ABSTRACT FROM PUBLISHER]

Abstract: This paper aims to address some gaps in current knowledge by studying temporal and spatial variations in Artemisia pollen counts (2000–2009) at 13 sites located in different biogeographical areas of Central and Eastern Europe. Analysis showed that start dates of Artemisia pollen seasons are greatly dependent on temperature during June and July, with hot summer temperatures having a tendency to delay summer flowering. However, this relationship is not linear and the rate at which seasons become later increases when mean minimum June–July temperatures reach a threshold of about 13°C. No explanation for variations in pollen season intensity could be found. The geographical location or amount of urbanisation did not influence, either positively or negatively, the seasonal pollen index. Second peaks in Artemisia pollen seasons can be described as the pollen seasons of late flowering Artemisia species, and mainly occurred in the geographical area south of the Carpathian Mountains. These second peaks can significantly influence the seasonal pollen index, contributing over 50% to the season''s total Artemisia pollen recorded at one site. [Copyright &y& Elsevier]

Abstract: This invited review and opinion piece, assesses the impact of climate change on mycotoxins in food: only one paper and an abstract referred directly from a substantial literature search and then only in relation to Europe. Climate change is an accepted probability by most scientists. Favourable temperature and water activity are crucial for mycotoxigenic fungi and mycotoxin production. Fungal diseases of crops provide relevant information for pre-harvest mycotoxin contamination. However, the mycotoxin issue also involves post-harvest scenarios. There are no data on how mycotoxins affect competing organisms in crop ecosystems. In general, if the temperature increases in cool or temperate climates, the relevant countries may become more liable to aflatoxins. Tropical countries may become too inhospitable for conventional fungal growth and mycotoxin production. Could this lead to the extinction of thermotolerant Aspergillus flavus? Currently cold regions may become liable to temperate problems concerning ochratoxin A, patulin and Fusarium toxins (e.g. deoxynivalenol). Regions which can afford to control the environment of storage facilities may be able to avoid post-harvest problems but at high additional cost. There appears to be a lack of awareness of the issue in some non-European countries. The era will provide numerous challenges for mycotoxicologists. [Copyright &y& Elsevier]

The idea of using large-scale information to predict local climate variability is widely exploited in climate change impact studies as an alternative to computationally expensive high-resolution models. This approach implies the hypothesis that the statistical relationship between large-scale climate states and local variables defined for the present-day climate remains valid in the altered climate. In this paper, the concept of weather regimes is used to deduce a relationship between large-scale circulation and European winter temperature. The change in temperature with increased greenhouse gases is, however, not homogeneous among the individual regimes. As a result, the impact of the weather regimes on local temperature changes varies in the future, limiting its usefulness for refining temperature changes to the small scale. [ABSTRACT FROM AUTHOR]

Understanding the climate change processes requires application of special methodologies for revealing a ground surface temperature history (GSTH). It was proved by different authors that the GSTH may be determined on the basis of analysis of the temperature field observed in short boreholes. In this paper, the authors analyze four mathematical models describing the GSTH: (1) sudden change, (2) linear increase, (3) square root of time increase and (4) exponential increase. Fifteen borehole temperature profiles from Europe, Asia and North America were selected in three groups based on their geographical proximity. After careful analysis of temperature-depth profiles in these boreholes it was found out that two models (linear increase and square root of time increase) provide the best fit with field data. The calculated warming rates in the 20th century were compared with those obtained by a few parameters estimation (FPE) technique. [ABSTRACT FROM AUTHOR]