2020
DOI: 10.1016/j.uclim.2020.100629
|View full text |Cite
|
Sign up to set email alerts
|

Nocturnal cooling in Local Climate Zone: Statistical approach using mobile measurements

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
10
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 24 publications
(12 citation statements)
references
References 24 publications
0
10
0
Order By: Relevance
“…Urban surface calculations that apply a combination of surface data and GIS-based or remote sensing-based concepts appear in a number of studies. In the LCZ mapping of the Nancy (France) urban area, the surface metadata gathered from field work and remote sensing sources were worked up by means of GIS tools (SAGA GIS), models (DSM) and manual calculations to obtain SVF, terrain roughness (Davenport calculations), building heights (from the national database of building footprints), ISF/PSF, and more [146][147][148]. A combination of models, such as SURY v1.0 (semi-empirical urban canopy parameterization), implemented in COSMO(-CLM) [149] or using topographic/aerial images [150] with the WUDAPT urban database platform, may produce high-resolution LCZ mapping.…”
Section: Combined Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Urban surface calculations that apply a combination of surface data and GIS-based or remote sensing-based concepts appear in a number of studies. In the LCZ mapping of the Nancy (France) urban area, the surface metadata gathered from field work and remote sensing sources were worked up by means of GIS tools (SAGA GIS), models (DSM) and manual calculations to obtain SVF, terrain roughness (Davenport calculations), building heights (from the national database of building footprints), ISF/PSF, and more [146][147][148]. A combination of models, such as SURY v1.0 (semi-empirical urban canopy parameterization), implemented in COSMO(-CLM) [149] or using topographic/aerial images [150] with the WUDAPT urban database platform, may produce high-resolution LCZ mapping.…”
Section: Combined Methodsmentioning
confidence: 99%
“…Deriving their conclusions from mobile measurements, Stewart et al [50] presented differences in the magnitudes of air temperature within the framework of LCZs. Several studies have used mobile measurements to detect T a patterns among built-up and land-cover LCZs, additionally coordinating their measurement campaigns with daytime and night-time periods of the day [97,142,[146][147][148], or with particular seasonal/extreme weather periods (e.g., summer season or heat-wave period) [75,96]. The results indicated distinct temperature differences between LCZs, with a tendency towards decreases towards the outskirts.…”
Section: Thermal Analysis Based On Mobile Measurementsmentioning
confidence: 99%
“…Some of these studies have also pointed out the need for assessing the performance of the LCZs, rather than just confirming that they display different trends. More specifically, they have focused on evaluating whether the differences between LCZs are statistically significant (Beck et al, 2018;Fenner et al, 2017;Leconte et al, 2020;Richard et al, 2018), if they concentrate at certain times of the year or under specific meteorological conditions (Arnds et al, 2017;Thomas et al, 2014;Yang et al, 2018), or if other parameters might affect the LCZs inter-and intra-variability (Kotharkar et al, 2019;Kwok et al, 2019;Leconte et al, 2017). However, research on the topic is still scarce and limited to a specific climatic context (mostly Cf, humid and warm temperate climates), and in some cases is based on short datasets.…”
Section: Using Local Climate Zones For Contextualising and Characteri...mentioning
confidence: 99%
“…The rate of change (RC) was considered to investigate the thermal behavior of the parking lots over time, because this approach has been adopted in previous urban climate studies [41][42][43][44]. The analysis was based on the sixty-minute average temperature to calculate the hourly RC ( • C h −1 ) (Equations (2) and ( 3)):…”
Section: Key Performance Indicators Of Parking Lot Dynamicsmentioning
confidence: 99%