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Xiao-Ming Hu, Petra M. Klein, Ming Xue, Julie K. Lundquist, Fuqing Zhang, and Youcun Qi

heat island (UHI) effect, in which near-surface temperatures in metropolitan areas are typically higher than in the surrounding rural areas ( Oke 1976 , 1982 ; Arnfield 2003 ). Biophysical hazards such as heat stress, air pollution, and associated public health problems have been linked to UHI development ( Zhang et al. 2009 ; Zhou and Shepherd 2010 ; Steeneveld et al. 2011 ; Chow et al. 2012 ; Fischer et al. 2012 ), which puts urban populations at even higher risks if the frequency of

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Peter Hoffmann and K. Heinke Schlünzen

that although no optimal method exists, the k -means-based methods usually perform well (e.g., Beck and Philipp 2010 ; Cahynová and Huth 2010 ; Huth 2010 ). As stated by Huth et al. (2008) , the circulation patterns should be regarded as purpose made. Therefore, each target parameter requires the construction of its own optimal classification. In this study, we construct a WPC computed with a k -means-based method for the target parameter urban heat island (UHI). Hamburg (Germany) is used as

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Fred M. Vukovich, William J. King, J. W. Dunn III, and J. J. B. Worth

form 27 January 1979) The observed surface and upper air temperature and wind field patterns on 8 June 1976 in St. Louis,Missouri, were analyzed aud compared with simulation results from a three-dimeusion~l hydrodynamicmodel. An urban heat island (1-2-C temperature difference between the urban and rural regions) persisted during the day. The daytime temperature differential was relatively' weak compared to that atnight Q-,5-C difference). In contrast, the urban heat island circulation was more

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Hiroshi Yoshikado

1. Introduction Increased air temperature in urban areas compared with surrounding rural areas is a well-known phenomenon called the urban heat island (UHI). This phenomenon is most clearly observed in large cities. In the case of Tokyo, the annual average temperature has increased at a rate of 3.2°C (100 yr) −1 for the period between 1931 and 2011 ( JMA 2012 ). For the same period, 17 observatories in remote small towns recorded an average temperature increase of 1.5°C (100 yr) −1 . This

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Ryosaku Ikeda and Hiroyuki Kusaka

1. Introduction Numerical studies on the urban heat island phenomenon have been actively performed to investigate its formation mechanisms. There are three main ways to describe the urban thermal environment: 1) slab model, 2) single-layer urban canopy model (e.g., Masson 2000 ; Kusaka et al. 2001 ; Harman et al. 2004 ; Best 2005 ; Kanda et al. 2005 ; Lee and Park 2008 ), and 3) multilayer urban canopy model (MUCM; e.g., Kondo and Liu 1998 ; Brown 2000 ; Hagishima et al. 2001 ; Vu et

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Jie Lu, S. Pal Arya, William H. Snyder, and Robert E. Lawson Jr.

Introduction A thermal plume is generated by an underlying heat island in the form of an area source. If the heating is confined to a finite area, a vertical thermal plume and associated circulation will develop due to the temperature (density) difference between the heat source and its environs. The plume stops rising as the temperature difference between the plume and its ambient vanishes due to the entrainment or mixing of fluid from a stable environment. Therefore, the height of a plume z

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Hiroyuki Kusaka and Fujio Kimura

Introduction The surface layer in cities is generally warmer than that of the surrounding areas. Near a city, the surface isotherms look like the topographic contours around an island. Thus, this phenomenon has become known as the urban heat island, which is clearly observed under atmospheric conditions of a clear sky and light wind. Many observational studies have provided us with essential ideas about the urban heat island phenomenon. These earlier studies have been summarized by Yoshino

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Douglas M. Leahey and James P. Friend

1162 JOURNAL OF APPLIED METEOROLOGY Voz. uxz 10A Model for Predicting the Depth of the Mixing Layer Over an Urban Heat Island with Applications to New York City~ DOUGLAS M. LEAHEY AND JAMES P. Paiv.~DDept. oJ Meteorology and Oceanography, N~v York Un~erslty(Manuscript received 24 June t97t, in revised form It August t971) ABSTRACT Over a city within a mixing layer

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Jerome D. Fast, Joel C. Torcolini, and Randy Redman

et al. 2000 ). Another application of temperature dataloggers is to determine the spatial characteristics of the urban heat island (UHI) effect by deploying a network of sensors across a city. Previous observations in Phoenix, as with many large cities, have indicated the presence of a UHI. Tarleton and Katz (1995) and Balling and Cerveny (1987) used data from the NWS Phoenix airport and a station in Wickenburg, Arizona, 87 km northwest of Phoenix, to show that daily minimum temperatures in

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C. J. G. Morris, I. Simmonds, and N. Plummer

urban–rural temperature difference known as the urban heat island (UHI) is a well-documented human-induced climate modification. Ackerman (1985) , Moreno-Garcia (1994) , Kidder and Essenwanger (1995) , and Figuerola and Mazzeo (1998) suggest that the wind speed and the amount of cloud cover are the most significant meteorological parameters that influence the intensity and development of the UHI. This is because the cloud amount and wind speed affect the insolation and ventilation, which serve

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