1. Environmental Prediction in Canadian Cities
Inferring turbulent exchange processes in an urban street canyon from high-frequency thermography
A. Christen(1), and J. A. Voogt(2) (1) Department of Geography, University of British Columbia, Vancouver, BC, Canada (5) Department of Geography, University of Western Ontario, London, ON, Canada
Environmental Prediction in Canadian Cities

2. Objectives
Previous work has demonstrated that we observe high-frequency temperature fluctuations of selected urban facets in IRT data and in time-sequential thermal imagery1.
Our hypothesis is that observed high-frequency temperature fluctuations are linked to turbulent sensible heat exchange of a selected facet (surface renewal).
Application - to quantify the scale and/or shape of the dominating eddies in exchange processes (spatial, duration) and their pahse velocities.
1 Christen et al. 2005, Christen and Voogt, 2009 (ICUC-9)

3. Elgin Street Experiment, Vancouver, Canada September 14/15, 2008
FLIR ThermoVision® A40M Thermal scanner
15 m mobile pump-up tower
PC stored data at 1 Hz
Reflective tape

4. To explore feasibility and limitations of this approach, a thermal scanner (Flir ThermoVision® A40M, operated at 1 Hz) was coupled with turbulence measurements (ultrasonic-anemometers, at 10 Hz) within a vegetated suburban street canyon of Vancouver, BC, Canada. The thermal scanner was mounted on a 15 m tower in the center of the canyon and monitored a representative cross-section of the street, lawns and buildings on each side. Two tripods in the field of view were equipped with ultrasonic-anemometers, infrared thermometers and fine-wire thermocouples and provide in-situ data from the atmosphere 30 cm above the surface and from the surface itself.

5. Tower base
Net radiometer
3-D Ultrasonic Anemometer-Thermometer
Pyranometer
Infrared thermometer
Fine-wire thermocouples
Surface wind / turbulence measurements on both sides of canyon (East, West) in FOV of scanner

6. Elgin Street - Experiment
24 hours of thermal image sequences of surface temperature T recoded at 1 Hz (320 x 240 pixels) in a fixed field of view.
10 Hz surface data from two 3D ultrasonic anemometers, thermocouples, and IRTs in the FOV.
Instead of absolute T, we use the deviation of surface temperature T‘ of each pixel from its temporal mean.
Fixed FOV along canyon sampled with 1 Hz at 320 x 240 pixels.
Continuous 10 Hz surface data from 3D ultrasonic anemometers, thermocouples, IRTs (synchronized with thermal scanner).

7. Visualizing wind in the thermal image sequence
Horizontal wind vector
Buildings
Circle: 1 m/s
Lawn
Cars
Street
Bushes

10. Why are lawns showing a high variability in T?
Turbulent energy exchange?
Geometric effects?
Sensible heat flux
Latent heat flux
Movement in wind
Low µ
Water availability
Grass is flexible + Anisotropy
Low µ
Dewfall (waves)

11. Can geometric effects explain T‘ patterns?
IRT
ground-based
Thermal Scanner
1 pixel of
10 minutes of
1 Hz measurements
CANYON WEST :20-15:30

12. Correlation between wind and T’
5 sec averages
Surface temperature
Wind

13. Correlation between wind and T’
:30 (10 sec time step)
Wind 30 cm above grass
heats up
cools down
wind slows down
wind speeds up

14. Sensible heat vs. correlation of du/dt and dTs/dt
QH transports
energy away from lawn
Sensible heat transfer
Efficiency of
QH transports
energy towards lawn

15. Extraction of two-point statistics
spatial separation (m)
temporal lag (sec)
along canyon
cross canyon
wind
169º
0.57 m s-1

16. Two-point correlations RTT vs. separation

17. Phase lag of two-point correlations of T’

18. Summary
Fluctuations in surface temperature can be measured over facets with low thermal admittance (lawns) and show coherent patterns over time.
Fluctuations in surface temperature are shown to be correlated to change in near-surface wind.
Exchange of sensible heat from urban lawn surfaces is driven by elongated turbulent structures moving along the canyon. The phase velocity of T’ fluctuations is faster than mean local subcanopy wind.

19. Funding agencies
Frederic Chagnon, Environment Canada
Ben Crawford, UBC
Sue Grimmond, King’s College, London
Adrian Jones, UBC
Rick Ketler, UBC
Ivan Liu, UBC
Fred Meier, TU Berlin
Kate Liss, UBC
Tim Oke, UBC
Dieter Scherer, TU Berlin
Chad Siemens, UBC
Derek van der Kamp, UBC
And residents of Elgin Street, Vancouver, Canada
Acknowledgements for technical assistance, program code, or instrumentation