Towards a simplified calculation of perceived temperature within the urban canopy layer

Transcription

1 Meteorol. Inst. - MeMi Group Towards a simplified calculation of perceived temperature within the urban canopy layer Jana Fischereit Meteorological Inst., CEN, University of Hamburg, Germany, correspondence: jana.fischereit@uni-hamburg.de ASI 2 Urban Comfort, Hong Kong, 10 Dec 2015

2 Objectives Simple calculation of a perceived temperature include only dominant parameters Aim: How accurate are different input parameters need to be known? Sensitivity analysis with a simple urban canyon model and heat balance model 1

3 Methodology: Modelling environment Munich Energy-Balance Model for Individuals with Physiological Equivalent Temperature (PET) 2

4 Methodology: Modelling environment Simple urban canyon model Radiation-Module (T mrt ) T, RH, FF from weather station in Hamburg Munich Energy-Balance Model for Individuals with Physiological Equivalent Temperature (PET) 2

5 Methodology: Simulations dim. Fct: PET (T, RH, FF, T mrt, age, gender, ) T mrt (T, RH, φ, hour, H, W, o, ) Treating 3 parameter groups as independent 1. Meteorological parameters 2. Human parameters 3. Street design parameters 3

6 Methodology: Simulations dim. Fct: PET (T, RH, FF, T mrt, age, gender, ) Extending cuboid-method (Früh et al. 2011) Separately: summer, winter male, female Linear regression T mrt (T, RH, φ, hour, H, W, o, ) Treating 3 parameter groups as independent 1. Meteorological parameters 2. Human parameters 3. Street design parameters 3

7 Results: Maximum impact on PET PET = c 1 + a 1 T + a 2 RH + a 3 FF + a 4 T mrt 4

8 Results: Maximum impact on PET PET = c 1 + a 1 T + a 2 RH + a 3 FF + a 4 T mrt ΔPET = a 1 ΔT and same for other param. 4

9 Results: Maximum impact on PET PET = c 1 + a 1 T + a 2 RH + a 3 FF + a 4 T mrt ΔPET = a 1 ΔT and same for other param. 4

10 Outlook Investigate other parameters: street design + age, clothing, Applying non-linear regression 5

11 Outlook Investigate other parameters: street design + age, clothing, Applying non-linear regression Thank you for your Attention! 5

12 References Bruse, M. (1999): Die Auswirkungen kleinskaliger Umweltgestaltung auf das Mikroklima Entwicklung des prognostischen numerischen Modells ENVI-met zur Simulation der Wind-, Temperatur- und Feuchteverteilung in städtischen Strukturen Ph.D. thesis, Geowissenschaften, Ruhr-University Bochum, Bochum, Germany. Bruse, M. (2015): PET-Calculation in ENVI-met, personal communication Fischereit (2015): Mean Radiant Temperature: Overview, implementation and results, Dokumentation Gierisch, A. (2011): Mikroskalige Modellierung meteorologischer und anthropogener Einflüsse auf die Wärmeabgabe eines Gebäudes Master's thesis, Geowissenschaften, University of Hamburg, Hamburg, Germany. Höppe (1984): Die Energiebilanz des Menschen. PhD thesis, Geowissenschaften, wissenschaftliche Mitteilungen, Meteorologisches Institut, Universität München, 49 Höppe (1999): The physiological equivalent temperature a universal index for the biometeorological assessment of the thermal environment. International Journal of Biometeorology 43(2):71-75, DOI /s Huttner, S. (2012): Further development and application of the 3D microclimate simulation ENVImet Ph.D. thesis, Geography, Johannes Gutenberg-University Mainz, Germany Schlünzen, K. H., D. D. Flagg, B. H. Fock, A. Gierisch, C. Lüpkes, V. Reinhardt, C. Spensberger, 2012: Scientific Documentation of the Multiscale Model System M-SYS Meteorological Institute, University of Hamburg MEMI Technical Report 4. VDI (2008) Methods for the human biometeorological evaluation of climate and air quality for urban and regional planning at regional level, Part I: Climate. VDI 3787, part 2, Beuth, Berlin 6