This page has only limited features, please log in for full access.
Urbanized hot spots incorporate a great diversity of microclimates dependent, among other factors, on local meteorological conditions. Until today, detailed analysis of the combination of climatic variables at local scale are very scarce in urban areas. Thus, there is an urgent need to produce a Local Weather Type (LWT) classification that allows to exhaustively distinguish different urban thermal patterns. In this study, hourly data from air temperature, wind speed and direction, accumulated precipitation, cloud cover and specific humidity (2009–2018) were integrated in a cluster analysis (K-means) in order to produce a LWT classification for Lisbon’s urban area. This dataset was divided by daytime and nighttime and thermal periods, which were generated considering the annual cycle of air temperatures. Therefore, eight LWT sets were generated. Results show that N and NW LWT are quite frequent throughout the year, with a moderate speed (daily average of 4–6 m/s). In contrast, the frequency of rainy LWT is considerably lower, especially in summer (below 10%). Moreover, during this season the moisture content of the air masses is higher, particularly at night. This methodology will allow deepening the knowledge about the multiple Urban Heat Island (UHI) patterns in Lisbon.
Cláudia Reis; António Lopes; Ezequiel Correia; Marcelo Fragoso. Local Weather Types by Thermal Periods: Deepening the Knowledge about Lisbon’s Urban Climate. Atmosphere 2020, 11, 840 .
AMA StyleCláudia Reis, António Lopes, Ezequiel Correia, Marcelo Fragoso. Local Weather Types by Thermal Periods: Deepening the Knowledge about Lisbon’s Urban Climate. Atmosphere. 2020; 11 (8):840.
Chicago/Turabian StyleCláudia Reis; António Lopes; Ezequiel Correia; Marcelo Fragoso. 2020. "Local Weather Types by Thermal Periods: Deepening the Knowledge about Lisbon’s Urban Climate." Atmosphere 11, no. 8: 840.
The increase and optimization of urban vegetation has been considered an effective mitigation measure of an urban heat island (UHI), with positive effects on human thermal comfort. In this study, the cooling potential of all green spaces in Lisbon was estimated. For that, several mobile measurements of air temperature data were made in a single park (Gulbenkian’s Garden). These measurements were used for the interpolation of air temperature. Furthermore, urban biomass was estimated using remote sensing products, namely Landsat satellite images. Ultimately, a linear regression model was built from the relation between vegetation density and air temperature. Results regarding the estimation of biomass (AGB) in the city of Lisbon were higher in winter than in summer. The urban green spaces cooling potential model showed that for every decrease of 1 °C in air temperature between a measuring point and a reference station we need to increase the area covered by vegetation by 50 m2 (planar measure). This methodology can be applied in other urban areas for the quantification of the cooling effect provided by vegetation in order to improve urban climate thermal conditions and human well-being and, consequently, to mitigate some consequences of future climate change.
Cláudia Reis; António Lopes. Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon. Sustainability 2019, 11, 2480 .
AMA StyleCláudia Reis, António Lopes. Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon. Sustainability. 2019; 11 (9):2480.
Chicago/Turabian StyleCláudia Reis; António Lopes. 2019. "Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon." Sustainability 11, no. 9: 2480.