Inhaltszusammenfassung

Particularly in the light of current global warming, we trust in meteorological station data to quantify recent changes in the climate system. This data also forms the foundation of paleoclimatic reconstructions as well as climate models, confirming the importance of its reliability and representativeness to allow glimpses in past and future climate variability. Unfortunately, non-climatic impacts are sometimes incorporated in temperature records, hence biasing them. This thesis addresses the...Particularly in the light of current global warming, we trust in meteorological station data to quantify recent changes in the climate system. This data also forms the foundation of paleoclimatic reconstructions as well as climate models, confirming the importance of its reliability and representativeness to allow glimpses in past and future climate variability. Unfortunately, non-climatic impacts are sometimes incorporated in temperature records, hence biasing them. This thesis addresses the effect of urban heat islands (UHIs) on temperature readings, tackling the question of how to detect and remove this influence in long temperature series. Furthermore, it sheds a light on whether it is legitimate to characterise small settlements and associated weather stations as rural, thus regarding the urban bias negligible. In order to approach these questions, temperature readings with a high spatio-temporal resolution from sensor networks in several European villages and one city have been analysed. A first investigation showed the formation of significant urban heat islands in the villages Haparanda (Sweden), Geisenheim (Germany), and Cazorla (Spain). Minimum temperatures are most affected and display a decreasing UHI maximum intensity from North (1.4 °C) to South (0.9 °C). Land cover analysis revealed warming to be strongly correlated with nearby built-up area in all villages. In a second study, this relationship was also confirmed for the city of Brno (Czech Republic). The additional warming was quantified for all past measurement sites of the more than 200-year-old local meteorological station. A unique approach enabled the assessment of an urban heat island related bias at different times in the corresponding temperature record, allowing for a removal of this inadvertent influence. A correction led to a steeper warming trend particularly in minimum temperatures, with the strongest implications for spring (+0.3 °C / century). Similar results are found in Haparanda if correcting for site-related anthropogenic influence. For this study, measurements were conducted at each historical measurement location to exactly quantify site-specific warming features. Since Haparanda has a more than 150 year long temperature record and is situated remotely, relative homogenization based on reference data is not applicable here, hence boosting the importance of this data enhancement approach. Applying the same technique in the Spanish village Tivissa led to a substantial trend increase in minimum temperatures of up to 1 °C / century, while maximum temperatures were less, though inversely, affected. As the time series has been partly homogenized, results could be compared to the aforementioned method. While the new method’s strength is the exact consideration of break points in the time series due to relocations as well as the allowance for site-specific climatology, its weaknesses are to disregard other non-climatic factors as well as to display limitations if relocations are not well documented.» weiterlesen» einklappen

Autoren

Klassifikation

DDC Sachgruppe:
Geowissenschaften