How to visualize the Urban Heat Island in Gridded Datasets?
<p>The Urban Heat Island (UHI) describes the increase of near surface temperatures within an urban area compared to its rural surrounding. While the concept of the UHI is in itself quite simple, it is more complex to apply it to gridded datasets. The main complication lies in the rural baselin...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2021-04-01
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| Series: | Advances in Science and Research |
| Online Access: | https://asr.copernicus.org/articles/18/41/2021/asr-18-41-2021.pdf |
| Summary: | <p>The Urban Heat Island (UHI) describes the increase of near surface temperatures within an urban area compared to its rural surrounding. While the concept of the UHI is in itself quite simple, it is more complex to apply it to gridded datasets.
The main complication lies in the rural baseline definition.
Therefore, we propose three approaches to calculate the spatial UHI representation for gridded datasets from (i) a single point baseline, (ii) an area averaged baseline, and (iii) a nearest neighbor-based baseline field.
Based on these approaches, seven methods are tested as an example for a case study utilizing model simulations for three metropolitan areas in Central and Western Europe (Berlin, Paris and Rhine-Ruhr Metropolitan Area).
The results show that all methods perform reasonable in absence of complex terrain, biases and large scale temperature gradients.
However, with at least one of these features present, the UHI visualization is less prominent or nonexistent, except for the nearest-neighbor approach which consistently shows reasonable spatial characteristics of the UHI across all scenarios.</p> |
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| ISSN: | 1992-0628 1992-0636 |