Monday, 2 August 2010: 2:00 PM
Crestone Peak I & II (Keystone Resort)
Urban heat stress during summer warm episodes received increased attention in the USA, but also in Europe. The European heat waves in 2003 and 2006 underlined that heat stress results in substantial thermal discomfort to citizens and adverse health effects for vulnerable groups, especially during long term heat exposure. Particularly in the early evening and night, urban areas remain warmer than the surrounding countryside, i.e. the urban heat island effect (UHI). In order to be able to adapt to or mitigate the UHI, it should be quantified and its physics should be understood. This study quantifies the UHI climatology for Dutch urban units ranging from villages to cities. Also, we aim to link the UHI intensity to the city topology, i.e. the relative available percentages of green vegetation, open water and building. Our focus on the Netherlands originates from the special features that belong to Dutch cities. First the ground water level in Dutch cities is relatively high, and many cities are characterized by a network of canals, so water availability is relatively high. Second, the Netherlands are located close the coast, thus sea breeze circulations may affect the UHI. Third, the western part of the Netherlands covers the most densely populated area in the world. Forth, the Dutch climate has been classified as mild Cfb climate in which heat stress is supposed to be rather rare. Unfortunately, routine meteorological observations in urban areas are scarce, and often limited to intensive field campaigns. Therefore, long term meteorological observations by hobby meteorologists are utilized to enable UHI quantification. The analysis shows that large Dutch cities experience a substantial UHI and threshold values for adverse human comfort are crossed 7 days per year on average, but more often for larger cities as Rotterdam (20 days per year). In addition, it was found that both the daily maximum UHI and maximum human discomfort expressed in the WBGT follow the General Extreme Value distribution rather well.
Supplementary URL: http://www.maq.wur.nl
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