In dieser Arbeit wird die Entwicklung eines Gebäudeenergiemodells (BEM) und eines Schemas für die mittlere Strahlungstemperatur ($T_mrt$) vorgestellt, das in das Doppel-Canyon basierte städtische Bestandsschichtsschema (DCEP) integriert ist. Das erweiterte DCEP-BEM Modell zielt darauf ab, eine Verbindung zwischen anthropogener Wärme und dem Stadtklima herzustellen, indem Gebäude in Straßenschluchten einbezogen werden, um die Energieflüsse auf städtischen Oberflächen, die Auswirkungen der anthropogenen Wärme auf die Atmosphäre, die Innenraumlufttemperatur und die Abwärme von Klimaanlagen zu untersuchen. Das DCEP-BEM wird mit dem mesoskaligen Klimamodell COSMO-CLM (COnsortium for Small-scale MOdelling in CLimate Mode, im Folgenden CCLM) gekoppelt und zur Simulation des Winters und Sommers 2018 in Berlin. Die Auswertung der Wintersimulationen zeigt, dass CCLM/DCEP-BEM den mittleren Tagesverlauf der gemessenen turbulenten Wärmeströme gut reproduziert und die simulierte 2-m-Lufttemperatur und den städtischen Wärmeinseleffekt (UHI) verbessert. Im Sommer bildet das CCLM/DCEP-BEM die Innenraumlufttemperatur richtig ab und verbessert die Ergebnisse für die 2-m-Lufttemperatur und die UHI leicht. Außerdem wird das CCLM/DCEP-BEM angewendet, um die Abwärmeemissionen von Klimaanlagen im Sommer zu untersuchen. Die Abwärmeemissionen der Klimaanlagen erhöhen die Lufttemperatur in Oberflächennähe erheblich. Der Anstieg ist in der Nacht und in hochurbanisierten Gebieten stärker ausgeprägt. Es werden zwei Standorte für die AC-Außengeräte betrachtet: entweder an der Wand eines Gebäudes (VerAC) oder auf dem Dach eines Gebäudes (HorAC). Die Auswirkung von HorAC ist im Vergleich zu VerAC insgesamt geringer, was darauf hindeutet, dass HorAC einen kleineren Einfluss auf die oberflächennahe Lufttemperatur und den UHI hat. Ein Schema für $T_mrt$ wird für das CCLM/DCEP-BEM entwickelt und umfassend validiert. Es wird gezeigt, dass dieses Schema eine zuverlässige Darstellung von $T_mrt$ bietet. / This work presents the development of a building energy model (BEM) and a mean radiant temperature ($T_mrt$) scheme integrated in the urban canopy scheme Double Canyon Effect Parametrization (DCEP). The extended DCEP-BEM model aims to establish a link between anthropogenic heat emissions and urban climate by including the interior of buildings in urban street canyons to investigate the energy fluxes on urban surfaces, the effects of anthropogenic heat on the atmosphere, the evolution of indoor air temperature, and waste heat from air conditioning (AC) systems. DCEP-BEM is coupled with the mesoscale climate model COSMO-CLM (COnsortium for Small-scale MOdelling in CLimate Mode, hereafter CCLM) and applied to simulate the winter and summer 2018 of Berlin. The evaluation for winter simulations indicates that CCLM/DCEP-BEM reproduces well the average diurnal characteristics of the measured turbulent heat fluxes and considerably improves the simulated 2-m air temperature and urban heat island (UHI). In summer, CCLM/DCEP-BEM accurately reproduces the indoor air temperature, and slightly improves the performance of the 2-m air temperature and the UHI effect. Furthermore, CCLM/DCEP-BEM is applied to explore the waste heat emissions from AC systems in summer. AC waste heat emissions considerably increase the near-surface sensible heat flux and air temperature. The increase is more pronounced during the night and in highly urbanised areas. Two locations for the AC outdoor units are considered: either on the wall of a building (VerAC) or on the rooftop of a building (HorAC). The effect of HorAC is overall smaller compared to VerAC, indicating that HorAC has a smaller impact on the near-surface air temperature and the UHI effect. A $T_mrt$ scheme is developed for CCLM/DCEP-BEM and extensively evaluated. It is shown that this scheme provides a reliable representation of $T_mrt$.

Indiana University-Purdue University Indianapolis (IUPUI) / In the United States extreme heat events have grown in size and stature over the past 20 years. Urban Heat Islands exacerbate these extreme heat events leaving a sizable portion of people at risk for heat related fatalities. The evidence of this is seen in the Chicago heat wave of 1995 which killed 500 people over the course of a week and the European heat wave of 2003 which killed 7,000 people in the course of a month. The main guiding questions then become how government and the media can most effectively warn people about the occurrence of extreme heat events? Should extreme heat warnings be issued by T.V., newspaper or by radio? Even if warnings are issued will the population at large still change their behavior? Another possible question is whether people most vulnerable to extreme heat will change their behavior? A survey in 2010 by NASA will be the main basis for this analysis. This survey set out to see how well people in Phoenix, Philadelphia, and Dayton responded to extreme heat alerts by changing their behavior.

Indiana University-Purdue University Indianapolis (IUPUI) / Urban forestry is a very important element of urban structures that can improve the environment and life quality within the urban areas. Having an accurate classification of urban forests and grass areas would help improve focused urban tree planting and urban heat wave mitigation efforts. This research project will compare the use of high – resolution aerial imagery and LiDAR data when used to classify canopy and grass areas. The high – resolution image, with 1 – meter resolution, was captured by The National Agriculture Imagery Program (NAIP) on 6/6/2012. Its coordinate system is the North American Datum of 1983 (NAD83). The LiDAR data, with 1.0 – meter average post spacing, was captured by Indiana Statewide Imagery and LiDAR Program from 03/13/2011 to 04/30/2012.The study area is called the Near East Side Community Organization (NESCO) neighborhood. It is located on the east side of downtown Indianapolis, Indiana. Its boundaries are: 65 interstate, East Massachusetts Avenue, East 21st Street, North Emerson Avenue, and the rail road tracks on the south of the East Washington Street. This research will also perform the accuracy assessment based on the results of classifications using high – resolution aerial imagery and LiDAR data in order to determine and explain which method is more accurate to classify urban canopy and grass areas.

Indiana University-Purdue University Indianapolis (IUPUI) / The purpose of this study was to identify urban heat island locations within Center Township, Indiana and to develop a model to determine areas of high social vulnerability. In addition, an urban heat island mitigation strategy was developed for socially vulnerable and highest temperature locations. Land surface temperature was estimated using Landsat ETM+ satellite imagery. Social vulnerability was estimated using principal components analysis and spatial analysis methods such as kernel density functions. These methods incorporate various socioeconomic variables, land surface temperature, and tree canopy cover. Tree canopy cover was extracted using Quickbird imagery among other techniques. Areas with high social vulnerability, high temperature and low tree canopy cover were analyzed and plantable spaces were assessed. The findings of this study will be shared with Keep Indianapolis Beautiful, Inc. so that they can inform their tree planting campaigns that seek to reduce the effects of urban heat islands on socially vulnerable populations.

Indiana University-Purdue University Indianapolis (IUPUI) / The purpose of this study was to locate the most suitable blocks to plant trees within Indianapolis, Indiana’s Near Eastside Community (NESCO). LiDAR data were utilized, with 1.0 meter average post spacing, captured by the Indiana Statewide Imagery and LiDAR Program from March 13, 2011 to April 30, 2012, to conduct a covertype classification and identify blocks that have low canopies, high impervious surfaces and high surface temperatures. Tree plantings in these blocks can help mitigate the effects of the urban heat island effect. Using 2010 U.S. Census demographic data and the principal component analysis, block groups with high social vulnerability were determined, and tree plantings in these locations could help reduce mortality from extreme heat events. This study also determined high and low priority plantable space in order to emphasize plantable spaces with the potential to shade buildings; this can reduce cooling costs and the urban heat island, and it can maximize the potential of each planted tree.