Towards city-wide, building-resolving analysis of mean radiant temperature

Abstract This study presents a method to simulate Tmrt building-resolving while considering both micro-scale urban structures and meso-scale atmospheric conditions. We extended the model SOLWEIG, one of the few methods to derive mean radiant temperature (Tmrt) building-resolved and city-wide, to include spatial patterns of meteorological input. Based on a day within an extreme heat event (2003) in Berlin, Germany, we examined the effect of the new method on Tmrt, which uses gridded meteorological input data from a mesoscale weather model, compared to a standard set-up using ungridded data. Results indicted a considerable effect of spatially resolved air temperature (up to 3.2 K) during midnight. Furthermore, we detected high sensitivity of Tmrt to the partitioning of direct and diffuse short-wave radiation. The spatial pattern of Tmrt revealed that at midday the city centre exhibited low values compared to open areas. We conclude that considering meso-scale atmospheric conditions and urban structure for simulating Tmrt city-wide can lead to a more appropriate description of heat-stress hazards and might also be valuable for climate-sensitive urban planning.

[1]  Annie M. Hunter,et al.  Planning for cooler cities: A framework to prioritise green infrastructure to mitigate high temperatures in urban landscapes , 2015 .

[2]  E. Fischer,et al.  A Review of the European Summer Heat Wave of 2003 , 2010 .

[3]  János Unger,et al.  The most problematic variable in the course of human-biometeorological comfort assessment — the mean radiant temperature , 2011 .

[4]  W. Endlicher,et al.  Spatial analysis of hospital admissions for respiratory diseases during summer months in Berlin taking bioclimatic and socio-economic aspects into account , 2014 .

[5]  G. Kamali,et al.  Evaluation of 12 models to estimate hourly diffuse irradiation on inclined surfaces , 2008 .

[6]  S. Hajat,et al.  Heat-related mortality: a review and exploration of heterogeneity , 2009, Journal of Epidemiology & Community Health.

[7]  Fredrik Lindberg,et al.  Sunlit fractions on urban facets – Impact of spatial resolution and approach , 2015 .

[8]  D. Lettenmaier,et al.  Changes in observed climate extremes in global urban areas , 2015 .

[9]  Dieter Scherer,et al.  Spatial and temporal air temperature variability in Berlin, Germany, during the years 2001–2010 , 2014 .

[10]  George Havenith,et al.  UTCI—Why another thermal index? , 2011, International Journal of Biometeorology.

[11]  A. Matzarakis,et al.  The effect of air temperature and human thermal indices on mortality in Athens, Greece , 2012, Theoretical and Applied Climatology.

[12]  Timothy R. Oke,et al.  Evaluation of the ‘local climate zone’ scheme using temperature observations and model simulations , 2014 .

[13]  Alberto Martilli,et al.  Current research and future challenges in urban mesoscale modelling , 2007 .

[14]  A. Clappier,et al.  An Urban Surface Exchange Parameterisation for Mesoscale Models , 2002 .

[15]  H. Suehrcke,et al.  Diffuse fraction correlations , 1991 .

[16]  Hermann Kaufmann,et al.  Potential of Hyperspectral Remote Sensing for Analyzing the Urban Environment , 2011 .

[17]  Dieter Scherer,et al.  Evaluating the Effects of Façade Greening on Human Bioclimate in a Complex Urban Environment , 2015 .

[18]  Jason Ching,et al.  A perspective on urban canopy layer modeling for weather, climate and air quality applications , 2013 .

[19]  H. Mayer,et al.  Modelling radiation fluxes in simple and complex environments—application of the RayMan model , 2007, International journal of biometeorology.

[20]  F. Lindberg,et al.  SOLWEIG 1.0 – Modelling spatial variations of 3D radiant fluxes and mean radiant temperature in complex urban settings , 2008, International journal of biometeorology.

[21]  Alberto Martilli,et al.  A Double-Canyon Radiation Scheme for Multi-Layer Urban Canopy Models , 2012, Boundary-Layer Meteorology.

[22]  Andreas Matzarakis,et al.  Comparison of mean radiant temperature from field experiment and modelling: a case study in Freiburg, Germany , 2014, Theoretical and Applied Climatology.

[23]  David Rayner,et al.  Characteristics of the mean radiant temperature in high latitude cities—implications for sensitive climate planning applications , 2014, International Journal of Biometeorology.

[24]  Fredrik Lindberg,et al.  Meteorological forcing data for urban outdoor thermal comfort models from a coupled convective boundary layer and surface energy balance scheme , 2015 .

[25]  G. Kamali,et al.  Estimating solar radiation on tilted surfaces with various orientations: a study case in Karaj (Iran) , 2006 .

[26]  Christian Schuster,et al.  Land use patterns, temperature distribution, and potential heat stress risk - The case study Berlin, Germany , 2014, Comput. Environ. Urban Syst..

[27]  S. Seneviratne,et al.  Role of land surface processes and diffuse/direct radiation partitioning in simulating the European climate , 2011 .

[28]  A. Pullin,et al.  Urban greening to cool towns and cities: a systematic review of the empirical evidence. , 2010 .

[29]  B. Ritter,et al.  A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations , 1992 .

[30]  S. Schubert,et al.  The Influence of green areas and roof albedos on air temperatures during Extreme Heat Events in Berlin, Germany , 2013 .

[31]  M. Bruse,et al.  Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model , 1998 .

[32]  M. Deserti,et al.  Overview of tools and methods for meteorological and air pollution mesoscale model evaluation and user training. , 2008 .

[33]  David Rayner,et al.  Mean radiant temperature - A predictor of heat related mortality , 2014 .

[34]  F. Lindberg,et al.  Potential changes in outdoor thermal comfort conditions in Gothenburg, Sweden due to climate change: the influence of urban geometry , 2011 .

[35]  V. D. Assimakopoulos,et al.  Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation , 2006 .

[36]  Edward Ng,et al.  Climate Information for Improved Planning and Management of Mega Cities (Needs Perspective) , 2010 .

[37]  Kyu Rang Kim,et al.  Estimating spatial patterns of air temperature at building‐resolving spatial resolution in Seoul, Korea , 2016 .

[38]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[39]  W. Beckman,et al.  Diffuse fraction correlations , 1990 .

[40]  A. Hense,et al.  The Regional Climate Model COSMO-CLM (CCLM) , 2008 .

[41]  F. Lindberg,et al.  Different methods for estimating the mean radiant temperature in an outdoor urban setting , 2007 .

[42]  Wilhelm Kuttler,et al.  Measures against heat stress in the city of Gelsenkirchen, Germany , 2013 .

[43]  R. Sokhi,et al.  Response of London’s Urban Heat Island to a Marine Air Intrusion in an Easterly Wind Regime , 2010, Boundary-Layer Meteorology.

[44]  Christian Schuster,et al.  Quantification of heat-stress related mortality hazard, vulnerability and risk in Berlin, Germany , 2013 .

[45]  Katharina M. A. Gabriel,et al.  Urban and rural mortality rates during heat waves in Berlin and Brandenburg, Germany. , 2011, Environmental pollution.

[46]  Gerhard Smiatek,et al.  Time invariant data preprocessor for the climate version of the COSMO model (COSMO-CLM) , 2008 .

[47]  F. Lindberg,et al.  The effect of urban geometry on mean radiant temperature under future climate change: a study of three European cities , 2015, International Journal of Biometeorology.

[48]  F. Lindberg,et al.  Nature of vegetation and building morphology characteristics across a city: Influence on shadow patterns and mean radiant temperatures in London , 2011, Urban Ecosystems.

[49]  Andreas Matzarakis,et al.  Human-biometeorological assessment of heat stress reduction by replanning measures in Stuttgart, Germany , 2014 .

[50]  Fredrik Lindberg,et al.  The influence of vegetation and building morphology on shadow patterns and mean radiant temperatures in urban areas: model development and evaluation , 2011 .

[51]  Christian Schuster,et al.  Heat mortality in Berlin – Spatial variability at the neighborhood scale , 2014 .

[52]  Maria Tombrou,et al.  The International Urban Energy Balance Models Comparison Project: First Results from Phase 1 , 2010 .

[53]  S. Schubert,et al.  Evaluation of the coupled COSMO‐CLM/DCEP model with observations from BUBBLE , 2014 .