Several UHI and urban humidity studies were conducted in India during the 1970s and subsequent decades. Locations include the tropical wet/dry cities of Mumbai (Mukherjee and Daniel, 1976; Kumar et al.,) Calcutta (Padmanabhamurtty, 1986), Madras (Sundersingh, 1990/1991) and Visakhapatnam (Padamnabhamurty, 1986), and the subtropical dry cities Delhi (Padmanabhamurty and Bahl, 1982) and Pune (Padmanabhamurty, 1979; Deosthali, 2000). Sarkar H. (2004) investigated the UHI phenomenon by using remote sensing land-cover data and a GIS database management system for population density. The study revealed that urban heat islands have a direct relation with land cover and population growth in tropical cities.Rose et al. (2005) compared changing land use patterns of Chennai city with average climate conditions to identify the nature of UHI influences. They found that major factors contributing to UHI are changes in land use, street canyon geometry and thermal properties of urban and rural materials.

Badarinath et al. (2005) studied the urban heat island formation using satellite data and concluded that the temperature variations during day and night correlated well with density patterns of urban areas. Mohan et al. (2009) used surface meteorological observations, i.e., data extractions from mini weather stations and meteorological towers in Delhi during summer. It was observed that a much higher UHI effect occurred due to anthropogenic heat emissions. UHI pockets were found primarily in commercial areas, busy traffic intersections, and densely populated residential areas.

Ramachandra and Kumar (2010) reviewed the pattern of growth in Greater Bangalore and its impact on local climate using satellite-derived land surface temperature (LST) measurements. Mohan et al. (2011) studied annual and seasonal temperature trends for maximum, minimum and mean temperatures of the four meteorological stations in the National Capital Region (NCR) of India, namely Safdarjung, Palam, Gurgaon and Rohtak. It was observed that there was a trend in minimum temperatures while no specific trend in the maximum and mean temperatures existed. Increasing warming trends in the night-time temperatures reflect the contribution of changing land-use patterns and additional anthropogenic heat that may enhance UHI intensities in the city.

Most of the UHI studies in India focus on measurements of UHI intensity and the influence of land cover on urban thermal conditions. Though the role of urban morphology in modifying the urban heat island is an established fact, there have been very few studies exploring the relationship between urban morphology and urban climate in an Indian context.

Stewart and Oke (2012) suggested that Standardization of representation and classification of urban areas and their measurement sites was extremely critical for better applicability of urban heat island study. They developed Local Climatic Zone (LCZ) classification system for standardizing the method of study. LCZs are defined on the basis of surface structure, surface cover, type of material and human activity.

This paper investigates the relation between urban morphology and the heat island effect in the context of Indian cities using Local Climate Zone (LCZ) classification system as a spatial and analytical framework. Local Climatic Zones are mapped for Nagpur city using Google Earth and on site documentation. The UHI study is conducted using transverse surveys through specific LCZ types. Finally, air temperature observations are analysed in the context of LCZ types.

Mobile transects are frequently used to collect high-resolution microclimate data along a predefined route. In an urban context, this technique advances the understanding of how urban structure and design affect the atmospheric environment. The relationship between land use/land cover and microclimate at the “human scale” corresponding to human body height and urban structure is dependent on a complex signal corresponding to the surface energy and water balance in the sensor’s source area, with intra-canopy atmospheric dynamics integrating heterogeneous patterns.

Currently, source areas are frequently computed to facilitate the interpretation of flux tower measurements. For urban climate studies, utilized sensors in such campaigns are usually installed above the roof level, so that the urban area under investigation can be treated as a 2-dimensional surface with known turbulence and roughness characteristics. For microclimate measurements carried out within the urban canopy layer, however, source area estimation becomes theoretically challenging. Simple statistical techniques relating microclimate observations to surrounding land cover have not performed well, owing to issues of scale, observational accuracy, lack of diverse representative intra-canopy observations, and poorly characterized source areas.

This study utilizes high-resolution mobile intra-canopy transect observations in a residential area in Gilbert, Arizona. Observed mobile data are corrected for sensor lag. Various methods of source area estimation are evaluated in an attempt to establish the empirical limits of the explanatory power of this approach relating land use and microclimate. The performance of the approaches is assessed for multiple canopy structures, seasons, wind conditions, and times of day, with differing domains identified. Based on the findings, a statistical model can be constructed to extrapolate the data over a larger spatial domain.

Urban planners are strongly encouraged to include climatic information in the urban planning process. In order to tackle this issue, qualitative recommendations are already available. In the meantime, most of the existing numerical models require skills and knowledge in urban climatology in order to use them and to analyse their output. Therefore, decision-makers are looking forward to new accessible approaches that can evaluate quantitatively the climatic impact of different urban planning proposals [1].

The combination of a climatic zoning and mobile measurements offers numerous perspectives regarding the production of quantitative climatic data that can be managed by institutional stakeholders. This paper presents a methodology to create an Urban Heat Island (UHI) map for an entire conurbation based on mobile measurements performed in several neighborhoods [2]. This methodology has been applied on a middle size European city (Nancy, France). The Local Climate Zone (LCZ) [3] scheme has been used to organize the field campaigns and to build areas that are homogeneous in terms of thermal behavior and urban features. The LCZ thermal patterns have already been investigated through the study of the air temperature amplitude and microscale recurrent hotspots and coldspots [4].

The chosen methodology is divided into four steps. First, urban indicators regarding urban morphology and land use have been calculated, and LCZ have been built over the studied conurbation. Second, mobile measurements have been performed to survey the LCZ at high spatial resolution (three meters distance step). Two campaigns have been completed during summer 2012 and 2013. The screen-height temperature has been recorded during daytime and nighttime for a range of cloud cover and wind conditions. Third, the air temperature differences between the investigated LCZ has been presented as thermal maps. Average air temperature difference is about 4.4°C between LCZ type Compact Midrise and LCZ type Low Plants. Fourth, these temperature differences between LCZ types have been extended to many other LCZ of the conurbation. These maps give an overview of the spatial air temperature distribution at sub-mesoclimatic scale. They also allow to investigate the influence of the relative position of the LCZ within the conurbation on their thermal behavior.

[1] Grimmond, C.S.B., Roth, M., Oke, T.R., Au, Y.C., Best, M., Betts, R., Carmichael, G., Cleugh, H., Dabberdt, W., Emmanuel, R., Freitas, E., Fortuniak, K., Hanna, S., Klein, P., Kalkstein, L.S., Liu, C.H., Nickson, A., Pearlmutter, D., Sailor, D. and Voogt, J. (2010). Climate and more sustainable cities : climate information for improved planning and management of cities (producers/capabilities perspective). Procedia Environmental Sciences, 1:247-274.

[2] Leconte, F, Bouyer, J., Claverie, R. and Pétrissans, M. Methodology for semi-empirical climatic modeling using on-board measurements. 8th International Conference on Urban Climate. Dublin (Ireland), 6th-10th August 2012.

[3] Stewart, I. (2011). Redefining the Urban Heat Island. Ph.D Thesis, The University of British Columbia, Vancouver.

[4] Leconte, F, Bouyer, J., Claverie, R. and Pétrissans, M. (2014). Using Local Climate Zone scheme for UHI assessment: evaluation of the method using mobile measurements. Building and Environment, (DOI : 10.1016/j.buildenv.2014.05.005).

The development of Local Climate Zones (LCZs) allows a quantitative classification of local surface characteristics with regard to their effect on local climate. The size of LCZs generally ranges from hundreds of metres to kilometres according to the homogeneity of surface characteristics. However, in high-density cities like Hong Kong, the surface environment varies considerably within short distances. In order to determine the optimal size of LCZs for spatial mapping in Hong Kong, a sensitivity test was conducted to compare the effect of the size on night-time air temperature (Ta) and relatively humidity (RH) in 14 study areas. Four grid sizes (500m, 400m, 300m, and 200m) were compared for their effect on the spatial average and standard deviation of Ta and RH. Ta and RH values are simulated for individual ground pixels using ENVI-met. Analysis of Variance (ANOVA) test is conducted to examine the effect of LCZ sizes and post-hoc Tukey’s test is used to find significant different pairs. According to the ANOVA test, there are no significant differences (α=0.05) in the average of Ta and RH between the LCZ sizes. However, the effect of LCZ sizes is found to be significant in the standard deviation of Ta and RH, suggesting that there are differences in the homogeneity of surface characteristics. The post-hoc Tukey’s test also shows that the 200m grid size is significantly different from the other three grid sizes. It was also found that the standard deviation of both Ta and RH decreases with the size of LCZs, suggesting an increasing homogeneity of the surface environment regarding its effect on local climate. Spatial maps of LCZs also show that the variations of surface characteristics within high- and medium-density areas are better captured at 200m resolution. The grid size determined in the present study will subsequently be used in spatial mapping of LCZs in Hong Kong. It also provides a basis for the development of potentially new LCZ classes which are specific to high-density urban environment.

Manipulating the urban fabric is fundamental to managing the warming trend in the growing high-density tropical settings to both mitigate the negative consequences as well as adapt cities to live with these changes. However, the current planning regime is yet to address the challenges posed by local, regional and global warming.

An in-depth understanding of the interaction between the physical form and the climatic context is crucial for the generation of climate sensitive urban planning approaches. However, data needs and methods of analysis remain problematic at present to achieve this.

In this paper, we showcase a simpler method of contextual analysis using the Local Climate Zone (LCZ) system in warm humid Colombo, Sri Lanka. Mean Radiant Temperature (MRT) – key variable in outdoor thermal comfort at street level – is linked to urban indicators encompassing geometric and surface cover characteristics in the LCZ classification, together with climate variables generated by the use of the microclimate simulation model ENVI-met. The simulations include a series of LCZ-based morphology options to reduce MRT in the urban outdoors at present and in a future warm scenario. Statistical analyses of the results test the applicability and sensitivity of urban morphological variables to help mitigate / adapt to local and global warming.

The work contributes towards a deeper understanding of the effect of building morphology on local level warming, with minimal data input. This could help develop climate-sensitive planning and policy in warm humid climates.

How urban areas influence on microclimate is a primary concern to adapt city planning and to mitigate the impacts of the combination of the global warming and urban heat island. In this paper, we present a new urban climate model at district scale, GéoClim Tool, which takes into account energy transfers (radiation, conduction, storage, convection, and latent heat), envelope material behaviors and uses (anthropogenic loads). GéoClim Tool processing chain is implemented in the OrbisGIS geographic information system (Bocher et al. 2008) using SQL requests and the Groovy interface.

GéoClim Tool is developed using the geographical database BDTopo® produced by the French IGN. A pre-processing partitions urban territory in relevant elementary areas: the « city blocks » (Lesbegueries et al. 2009) which are defined from the road network to respect the spatial organization of the city and the building configurations. Although the present geo-databases can give some indications on façade materials properties, it is difficult to know the envelope composition or the building occupancy levels. To address these uncertainties different scenarios are proposed based on urban typology, year of construction and thermal regulation evolutions. After a morphological analysis at city block scale (Bernabé et al. 2014), a kmeans clustering technique (Forgy 1965) is used to identify seven types of urban blocks that can be found in most European cities.

GéoClim Tool is constituted of different computation sub-models. A simplified method based on morphological parameters has been developed to evaluate the solar trapping effect and to predict radiative balance of urban structure (Bernabé et al. 2014). A wall thermal model is developed for each surface classes (grounds, walls and roof). GéoClim Tool evaluates the heat budget of a building based on the assumption that it is a single box for each city block. It gives an average room-air temperature or the building energy demand. Energy balance is written at city block scale taking into account the interactions of each city block with its neighbors to obtain the air temperature, at middle height of buildings.

GéoClim Tool outputs are the different energy fluxes, surface and air temperatures and the energy consumption of buildings at city blocks scale. Those data can be observed hour by hour or integrated. Climatic indicators can be computed from model outputs to generate climate maps and help stakeholder to identify the city blocks that are the most vulnerable to urban heat island. To evaluate mitigating actions at city block scale of three cooling strategies are compared: surface albedo improvement, vegetation and water inputs.