An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Urban microclimate studies are gaining popularity due to rapid urbanization. Many studies documented that urban microclimate can affect building energy performance, human morbidity and mortality and thermal comfort. Historically, urban microclimate studies were conducted with observational methods such as field measurements. In the last decades, with the advances in computational resources, numerical simulation approaches have become increasingly popular. Nowadays, especially simulations with Computational Fluid Dynamics (CFD) is frequently used to assess urban microclimate. CFD can resolve the transfer of heat and mass and their interaction with individual obstacles such as buildings. Considering the rapid increase in CFD studies of urban microclimate, this paper provides a review of research reported in journal publications on this topic till the end of 2015. The studies are categorized based on the following characteristics: morphology of the urban area (generic versus real) and methodology (with or without validation study). In addition, the studies are categorized by specifying the considered urban settings/locations, simulation equations and models, target parameters and keywords. This review documents the increasing popularity of the research area over the years. Based on the data obtained concerning the urban location, target parameters and keywords, the historical development of the studies is discussed and future perspectives are provided. According to the results, early CFD microclimate studies were conducted for model development and later studies considered CFD approach as a predictive methodology. Later, with the established simulation setups, research efforts shifted to case studies. Recently, an increasing amount of studies focus on urban scale adaptation measures. The review hints a possible change in this trend as the results from CFD simulations can be linked up with different aspects (e.g. economy) and with different scales (e.g. buildings), and thus, CFD can play an important role in transferring urban climate knowledge into engineering and design practice.

/pdf/a-review-on-the-cfd-analysis-of-urban-microclimate-ssgoi0gku1.pdf

A review on the CFD analysis of urban microclimate

Contribution of trees and grasslands to the mitigation of human heat stress in a residential district of Freiburg, Southwest Germany

Analyzing the ENVI-met microclimate model’s performance and assessing cool materials and urban vegetation applications–A review

Shade plays an important role in designing pedestrian-friendly outdoor spaces in hot desert cities. This study investigates the impact of photovoltaic canopy shade and tree shade on thermal comfort through meteorological observations and field surveys at a pedestrian mall on Arizona State University's Tempe campus. During the course of 1 year, on selected clear calm days representative of each season, we conducted hourly meteorological transects from 7:00 a.m. to 6:00 p.m. and surveyed 1284 people about their thermal perception, comfort, and preferences. Shade lowered thermal sensation votes by approximately 1 point on a semantic differential 9-point scale, increasing thermal comfort in all seasons except winter. Shade type (tree or solar canopy) did not significantly impact perceived comfort, suggesting that artificial and natural shades are equally efficient in hot dry climates. Globe temperature explained 51 % of the variance in thermal sensation votes and was the only statistically significant meteorological predictor. Important non-meteorological factors included adaptation, thermal comfort vote, thermal preference, gender, season, and time of day. A regression of subjective thermal sensation on physiological equivalent temperature yielded a neutral temperature of 28.6 °C. The acceptable comfort range was 19.1 °C-38.1 °C with a preferred temperature of 20.8 °C. Respondents exposed to above neutral temperature felt more comfortable if they had been in air-conditioning 5 min prior to the survey, indicating a lagged response to outdoor conditions. Our study highlights the importance of active solar access management in hot urban areas to reduce thermal stress.

/pdf/impact-of-shade-on-outdoor-thermal-comfort-a-seasonal-field-19najjxl3n.pdf

Impact of shade on outdoor thermal comfort-a seasonal field study in Tempe, Arizona.

Impact of urban form and design on mid-afternoon microclimate in Phoenix Local Climate Zones

Some uncertainty in mobile microclimate observations stems from sensor lags. This is especially critical in mobile transect campaigns conducted in urban areas, where observations have to be related to the quickly varying complex surroundings of the sensor, which becomes difficult if the sensor has a high time constant relative to environmental scale and sensor velocity. We present an optimized method for sensor lag correction using a transfer function, based on the optimization of three correction parameters: moving average window size, transfer function setup, and linear time shift. We evaluate the method by comparing the corrected temperatures measured with “slow” Resistance Temperature Detectors (RTD) to a ground truth provided by synchronous measurements with thermocouples that have a time constant of less than one second. Theoretical assumptions about the correction procedure design are substantiated by the optimization procedure, which yields consistent results for mobile transect data sets recorded at different times of day and in different seasons.

Sensor lag correction for mobile urban microclimate measurements

In urban microclimate research, mobile transects are utilized to observe the relationship between atmospheric variables and the urban environment However, the data sets resulting from mobile measurements are complex: They are spatially dependent, multivariate, and often-times multitemporal At the same time, the spatial context of each observation - its field of view and area represented - is physically complex and dynamic These properties make analysis and visualization challenging We present a prototype visualization framework that assists researchers in the analysis of mobile transect measurements The system enables users to visualize and explore observations as walls that delineate the transect route on a map The observed attributes are stacked upon each other within these walls as ribbons to facilitate the qualitative analysis of spatial variability and multivariate correlations The relationship between observations and spatial context can interactively be explored by moving a slider along the transect route For each observation on the track, the spatially contextual source area is displayed and linked to a view of the fraction of land cover classes contained within the source area These qualitative analysis capabilities are complemented by an interactive clustering interface, which allows for the classification of transect segments according to a coherent pattern of multivariate relationships between a user-defined set of observations The framework was developed by a team comprising both visualization and urban microclimate researchers, and a case study shows its utility for this specialized application

https://www.computer.org/csdl/pds/api/csdl/proceedings/download-article/12OmNzxgHpT/pdf

TraVis - A visualization framework for mobile transect data sets in an urban microclimate context

In urban climatology, identifying areas of similar microclimatic conditions helps to relate fine-scale urban morphology variations to their impact on atmospheric surroundings. Mobile transect measurements yield high-resolution microclimate data that allow for the delineation of these areas at a fine scale. However, the resulting spatio-temporal multivariate data is complicated and requires careful analysis and visualization to identify the emergent climatic microenvironments. Our previous work used a glyph-based visualization to comprehensively visualize spatially aggregated multivariate data from mobile measurements over diverse routes. This aggregation was conducted over a regular grid, and the utilized glyphs encoded multivariate relationships, average wind direction during data collection, number of transects traversing a grid cell, and grid cell size. In this paper, we reduce the visual complexity of the resulting map by coloring the background of the grid cells based on a comparison of the glyphs. The result is a gridded map that visually emphasizes spatial zones of similar multivariate relationships and that takes the information encoded by the glyphs into account. A preliminary evaluation shows that the described approach yields zones that line up with the physical structure of the study site.

A data-driven approach to categorize climatic microenvironments

In urban microclimate research, ground-based thermography is used to gain insight into the spatial distribution of surface temperatures of various materials. Taking snapshots over a certain time span helps experts to observe the temporal thermo-radiative behavior of the monitored surface elements and therefore supports decisions on possible optimizations, e.g., improving the thermal comfort in a neighborhood. Appropriate visualization techniques facilitate decision-making and are thus crucial in the optimization process. In this study, we present a tool that eases the extraction of thermo-radiative features from multi-temporal thermographs taken from a monitored scene. Assisted by our tool, users can identify, choose, and register thermo-radiative features for each time step according to their individual research needs. The features’ temporal development is then visualized using a directed graph that encodes topological events as well as each feature’s size and summarizing statistics. To enhance this summary, a comprehensive animated sequence emphasizes the spatiotemporal behavior of the most significant thermo-radiative features. Salient developments are visually embedded and highlighted in the original infrared images, which are blended in an animation from time step to time step. Since we enable the user to interact with the data in a flexible way, noisy and low resolution image data sets can also be processed.

Kathrin Häb

Papers

Impact of urban form and design on mid-afternoon microclimate in Phoenix Local Climate Zones

Sensor lag correction for mobile urban microclimate measurements

TraVis - A visualization framework for mobile transect data sets in an urban microclimate context

A data-driven approach to categorize climatic microenvironments

Visualizing the temporal development of thermo-radiative features on ground-based thermographs