Urban Heat Island (UHI) by Local Weather Types (LWT) maps for Lisbon Metropolitan Area (LMA)

Published: 1 April 2022| Version 1 | DOI: 10.17632/ypff9pyb6z.1
Contributor:
claudia reis

Description

Urban Heat Island (UHI) by local weather types (LWT) maps for the Lisbon Metropolitan Area (LMA) are made available. These maps were derived from the Copernicus Land Monitoring Service climate variables dataset that contains hourly air temperature raster data for 100 European cities (2008-2017), namely Lisbon and part of its metropolitan area. Fifteen raster GeoTIFF maps (Appendix 1) depicting UHI intensity by LWT in LMA are presented here. For each LWT, twenty-four hourly average UHI raster GeoTIFF maps are provided for each LWT (Appendix 2 to 16). Thermal summer: Raster GeoTIFF maps with the name “SUmild_cloudy” represent average UHI on mild, cloudy and humid days with light rain and moderate NW winds. Raster GeoTIFF maps with the name “SUmildNW” depict average UHI on mild, sunny and humid days with moderate NW and N winds. Raster GeoTIFF grids with the name “SUmildN” represent average UHI intensity on mild, sunny and humid days with strong N winds. Raster GeoTIFF maps with the name “SUhot” indicate average UHI on hot, sunny and humid summer days with moderate N winds. Raster GeoTIFF maps with the name “SUvhot” depict average UHI on very hot, sunny and humid days with moderate N winds. Thermal winter Raster GeoTIFF maps with the name “WcoldN” indicate average UHI on cold, cloudy and dry days with weak and variable winds, specially from N and NW. Raster GeoTIFF grids with the name “WcoldSW” depict average UHI on cold, cloudy, rainy and dry days with moderate SW and W winds. Raster GeoTIFF maps with the name “WvcoldN” represent average UHI on very cold, sunny and dry with moderate N winds. Raster GeoTIFF maps with the name “WvcoldNE” represent average UHI on Very cold, sunny and dry with weak NE, E and N winds. Thermal spring Raster GeoTIFF maps with the name “ScoldNW” represent average UHI on cold, cloudy and dry days with weak precipitation and moderate and variable winds, specially from NW, SW and W. Raster GeoTIFF maps with the name “ScoldN” depict average UHI on cold with moderate cloud coverage, dry and with moderate N winds. Raster GeoTIFF maps with the name “Smild” indicate average UHI on mild, sunny and humid spring days with moderate N winds. Thermal autumn Raster GeoTIFF grids with the name “Acold” indicate average UHI on cold, with moderate cloud cover and dry days with moderate N and NE winds. Raster GeoTIFF maps with the name “Acool” indicate average UHI on cool, cloudy, humid and rainy days with moderate SW and W winds . Raster GeoTIFF maps with the name “Amild” represent average UHI on mild, with moderate cloud cover, humid, with possibility of rain and weak N, NE and S winds. Raster GeoTIFF maps representing hourly average UHI intensity by LWT (Appendix 2 to 16) share the same name but end with with the respective hour (example: “SUmild_cloudy_1am” - hourly average UHI intensity at 1 am on mild, cloudy and humid summer days). An ArcGIS symbology layer (∗.lyr), named “UHI_symbology”, is also provided.

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Steps to reproduce

The average UHI intensity maps by LWT were produced using a climate variables dataset from the Copernicus Climate Change Service. This dataset contains hourly air temperature, specific humidity, relative humidity and wind speed data for 100 European cities (2008 to 2017), including Lisbon and part of its metropolitan area, with a reasonable spatial resolution (100 x100m). Only the air temperature files (2m above ground) were used to produce this data. Detailed information about thermal seasons and the LWT classification can be found on Reis et al., 2020. Hourly maps for Lisbon between 2008 to 2014 were extracted from the Copernicus dataset, which comprises 61368 NetCDF-4 air temperature files , 20190 (32,9%) for the thermal summer, 16814 (27,4%) for the thermal winter, 16447 (26,8%) for spring and 7917 (12,9%) for autumn. All files were divied by thermal seasons and LWT. In order to identify urban cells in the Copernicus window that covers a significant portion of LMA, an urban mask was create using LCZ 1 to 10 classes (1 – Compact high-rise; 2 – Compact midrise; 3 – Compact low-rise; 4 – Open high-rise; 5 – Open midrise; 6 – Open low-rise; 8 – Large low-rise; 9 – Sparsely built; 10 – Heavy industry). This standard typification of Land Cover/Land Use classes was recently updated for this study area by Oliveira et al., 2020. Additionally, a raster cell from the LCZ D class (Low plants) was chosen as a non-urban site. Hourly UHI intensity between 2008 and 2014 was calculated in R, according to the following equation: UHItCop = TUrb- TNUrb UHItCop indicates UHI intensity at each raster cell at time t, obtained from air temperature Copernicus dataset; TUrb represents air temperature of each urban cell in Copernicus grid at time t and; TNUrb represents the air temperature at a non-urban location (raster cell from LCZ low plants class). Ultimately, average UHI by LWT was calculated in ArcGIS using all hourly UHI generated files from days belonging to each particular set of meteorological conditions. Furthermore, hourly average UHI per LWT was also estimated in order to analyze the UHI daily cycle considering different meteorological conditions. References: Oliveira, A., Lopes, A., & Niza, S. (2020). Local climate zones in five southern European cities: An improved GIS-based classification method based on Copernicus data. Urban Climate, 33, 100631. DOI: 10.1016/j.uclim.2020.100631 Reis, C., Lopes, A., Correia, E., & Fragoso, M. (2020). Local Weather Types by Thermal Periods: Deepening the Knowledge about Lisbon’s Urban Climate. Atmosphere, 11(8), 840. DOI: https://doi.org/10.3390/atmos11080840 Reis, C., Lopes, A., & Nouri, A. (2022). Assessing Urban Heat Island effects through Local Weather Types in Lisbon’s Metropolitan Area using Big Data from the Copernicus Service. Urban Climate. In Press.

Institutions

Universidade de Lisboa Centro de Estudos Geograficos, Universidade de Lisboa

Categories

Climate Classification, Metropolitan Area Network, Environment and Health, Temperature, Urban Climate, Urban Heat Island Effect, Weather, Air Temperature

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