estimation of urban bioclimate by micro scale models for the … › en › sites › uas ›...
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Estimation of urban bioclimate by micro scale
models for the development
of adaptation possibilities in cities
Prof. Dr. Andreas Matzarakis
Research Center Human Biometeorology
Deutscher Wetterdienst, Freiburg
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Quantification of climate for cities
Air temperature? – Equivalent temperature (thermal indices)
Measurements and simulations
Micro scale models
Quantification of urban spaces
Long term analysis
Hot spot analysis
Climate change data/simulations
Data visualization and transfer
Outlook/Questions
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Target: Human / Method
Models
Application and examples
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Assessment of effects of climate
Not only air temperature
Air humidity
Wind
Radiation
Thermo-physiology (activity and clothing)
Energy balance of humans
Physiologically Equivalent Temperature
Thermal index
(Matzarakis, 2007)
Effect of the thermal atmosphere
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Under stationary conditions due to priciples of thermodynamics:
total of input energies = total of output energies
H + Q* + QH +QL + QSw + Qre = 0
H: internal heat production (metabolic heat production - heat loss due to
physical (mechanical) work)
Q*: net radiation (radiative heat flux)
QH: turbulent flux of sensible heat (convection heat flux), interchange of
sensible heat between the surface of the body and the ambient air
QL: turbulent flux of latent heat due to water vapour diffusion through the
skin into the ambient air
QSw: turbulent flux of latent heat due to sweat evaporation
Qre: heat flux due to respiration (heating and humidification of respired air)
Human energy balance
(VDI, 1998, Matzarakis, 2001)
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Physiologically Equivalent Temperature (PET):
Modern Thermal Indices (derived thermal indices: PMV, PET, SET*, PT, UTCI)
Tcore
TSkin
1.1
m
Ta
v
VP
TmrtTmrt = Ta
v =0.1m/s
VP = 12 hPa
Tcore
TSkin
1.1
m
Definition: Mwork = 80 W
Icl = 0.9 clo
PET of 20 °C means thermal comfort
Thermal indices
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Thermal indices (PMV, PET),
Thermal perception,
Physiological stresss
Threshold values of thermal indices PMV
and PET for different grades of thermal
sensitivity of human beings and physiological
stress on human beings
(according to Matzarakis and Mayer, 1996)
Adjustment of scale (new):
Taiwan, Israel, (Nigeria), Greece,
Hungary, …
Thermal indices – Assessment scale
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Target: Human / Method
Models
Application and examples
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Micro scale models (free available)
SkyHelios
RayMan
ENVI-met
Solweig
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RayMan Pro - A Tool for Applied Climatology
(urban climatology, human-biometeorology, tourism
climatology, …) Sunshine duration
Sun paths
Shadow
Global radiation
Mean radiant temperature
Predicted Mean Vote (PMV)
Phys. Equiv. Temp. (PET)
Stand. Effec. Temp. (SET*)
Universal Thermal Climate Index (UTCI)
Perceived Temperature (pT)
new: mPET
Simple environments
Complex environments
Topography
Fish-Eye
Hemisph. input/SVF
Meteo data
Climate data
....
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Vector and grid data
Google Earth implementation
Interfaces and outputs for
RayMan
Interface/Output for Climate
Mapping Tool
Sun paths
Sun duration/diagram
Shade
Sky view factor(s)
Roughness
Local climate zones (partially)
Global radiation
Mean radiant temperature
Wind speed and direction
PET and UTCI
SkyHelios
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Target: Human / Method
Models
Application and examples
• Events (popular examples)
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Events – Sports
Images: the guardian
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Exposition: Air condition
• HVAC
• Transfer/Transportation
• Adaptation humans
Images: the guardian
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Climate data – Climate diagram
FIFA 2022
(Matzarakis and Fröhlich, 2015)
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FIFA 2022
Los Angeles Time,
23. August 2014
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Doha, Ta, PET
Period: March 1999 to Jan 2014 (Matzarakis and Fröhlich, 2015)
FIFA 2022
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Controverse
• Suggestion: Winter
• Contra: we can cool everything
• FIFA: now in Winter
• Diverse reactions and perceptions
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Target: Human / Method
Models
Application and examples
• Political pressure (Freiburg)
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Environmental pressure (pop, politics)
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Fröhlich and Matzarakis, 2012
ENVI-met
Results: ENVI-met
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05/24/11
Day 3 (13:00)
Fröhlich and Matzarakis, 2013
ENVI-met
Results: ENVI-met
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After reconstruction
Fröhlich and Matzarakis, 2013
ENVI-met
Results: ENVI-met
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SVF before MP1
Green area
MP2
KG I - North
MP3
KG II - North
MP4
UB - Northeast
MP5
Theatre
MP6
KG II - Middle
MP7
Bus stop
Fröhlich and Matzarakis, 2013 Results: SkyHelios
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SVF after - Place of Old Synagogue MP1
Green area
MP2
KG I - North
MP3
KG II - North
MP4
UB - Northeast
MP5
Theatre
MP6
KG II - Middle
MP7
Bus stop
MP PET35 PET35a Δ (h)
1 348.1 338.1 -10 2 196.2 207.2 11 3 322.4 329.1 6.7 4 302.6 273.5 -29.1 5 313.9 313.3 -0.6 6 275.9 218.1 -57.8 7 204.4 330.2 125.8
Fröhlich and Matzarakis, 2013
Effect: wind and Tmrt
Results: RayMan Pro/SkyHelios
SVF
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Target: Human / Method
Models
Application and examples
• Fundamental studies (aspect ratio, orientation)
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Urban canyon – basic analysis
Typical urban canyons in Freiburg
Rotation of canyons
Input Co-ordinates
Buildings/solid surfaces
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15 m
5 m 10 m 15 m 20 m 25 m 30 m 35 m 40 m
Building: 15 m, variable street width
Matzarakis and Herrmann, 2011
Urban canyon – street variability
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15 m
Street width 15 m, variable building height
40 m 35 m 30 m 25 m 20 m 15 m 10 m 5 m
Matzarakis and Herrmann, 2011
Urban canyon – building height variability
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Street width 15 m, Building height 15 m, Rotation
0 °
15 °
30 °
45 °
60 °
75 °
90 °
105 °
120 °
135 °
150 °
165 °
180 °
N
W E
S Matzarakis and Herrmann, 2011
Urban canyon – orientation
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Adaptation measures – Street canyon
Ketterer & Matzarakis, 2014 object: middle of a street canyon model:
RayMan
data: 2000 -2010
cold stress PET < 13 °C
heat stress PET > 29 °C
thermal comfort 13.1 °C < PET < 29 °C
thermal comfort/
street orientation 0 ° 15 ° 30 ° 45 ° 60 ° 75 ° 90 ° 105 ° 120 ° 135 ° 150 ° 165 °
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Target: Human / Method
Models
Application and examples
• Trees
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Positive/Negative
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Outside Inside
Data: Landesanstalt für Wald und Forst, München,
Question: Forests and bioclimate during heat waves ? Matzarakis, 2010
Heat wave 2003 - Ta
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Heat wave August 2003 - PET Outside Inside
Matzarakis, 2010
Data: Landesanstalt für Wald und Forst, München,
Question: Forests and bioclimate during heat waves ?
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0
50
100
150
200
250
300
350
400
450
500
-22-17-12 -7 -2 3 8 13 18 23 28 33 38 43 48 53 58
Fre
qu
en
cy
PET (°C)
PET frequency distribution for Freiburg, 2071-2100
1961-1990PETTmrt = Tav-1v+1
(Matzarakis and Endler, 2010)
Climate change and adaptation
(shade/wind) < 1973
1973 - 2000
2002
Post 2002
2006-2009
2009
2010-2013
Future
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Target: Human / Method
Models
Application and examples
• Communication aspects
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First level of information: qualitative
Second level of information: quantitative
Third level: way of transferring information
Most important level: communication of information
Data and information
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Cold air production
Ventilation
Public transportation
Shade
(Sheet: Köhler, 2008)
Vision from an urban planner
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Not only air temperature – Human Biometeorology
Appropriate data and information
Measurements and simulations
Urban areas - modelling
Combination of methods/data
No clickable solutions
Less case studies – more long term (H/W)
Models provide additional data: SD, Sun paths, …
Focus Radiation and wind
Recommendations to users of models
Validation
Consider possibilities and limitation – aim of development
PLEASE: read/consider manual
Statements/Summary