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Cited by 239

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Simulated Urban Climate Response to Modifications in Surface Albedo and Vegetative Cover

Sailor, David J.·1995·Journal of Applied Meteorology

Abstract

Three-dimensional meteorological simulations have been conducted to investigate the potential impact of urban surface characteristic modifications on local climate. Results for a base case simulation for the Los Angeles basin are compared to results from cases in which urban albedo or vegetative cover are increased. The methodology for determining the distribution and magnitude of these simulated surface modifications is presented. Increasing albedo over downtown Los Angeles by 0.14 and over the entire basin by an average of 0.08 decreased peak summertime temperatures by as much as 1.5°C. This level of albedo augmentation also lowered boundary layer heights by more than 50 m and reduced the magnitude and penetration of the sea breeze. A second simulation, in which vegetative cover was increased, showed qualitatively similar impacts. The results from these simulations indicate a potential to reduce urban energy demand and atmospheric pollution by 5%–10% through application of reasonable surface modification strategies.

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Metadata

Authors
Sailor, D. J.
Venue
Journal of Applied Meteorology
Published
1995-07-01
Volume
34
Issue
7
Pages
1694-1704
ISSN
  • 0021-8952 (ISSN-L)
  • 1520-0450
  • 0894-8763
OpenAlex
W1996931125
Cited by
239
References
0
FWCI
6.16
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Simulated Urban Climate Response to Modifications in Surface Albedo and Vegetative Cover. https://app.cochat.ai/papers/10.1175/1520-0450-34.7.1694
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Sailor, D. J. (1995). Simulated Urban Climate Response to Modifications in Surface Albedo and Vegetative Cover. Journal of Applied Meteorology. https://doi.org/10.1175/1520-0450-34.7.1694

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.