J. Attema

Urban fine-scale forecasting reveals weather conditions with unprecedented detail

CapsuleFeasibility of Numerical Weather Prediction at urban neighborhood and street scales demonstrated for summer conditions in the Amsterdam metropolitan region (Netherlands). As the number of urban dwellers increases from an estimated 4 billion in 2014 to an expected 6.5 billion by 2050 (UN 2014), urbanization is putting an increasing strain on human comfort, productivity and health in cities worldwide.

Smartphone App brings human thermal comfort forecast in your hands

DECEMBER 2017 AMERICAN METEOROLOGICAL SOCIETY | W hat activity would you consider doing tomorrow if the weather forecast predicts a temperature of 27°C? Taking your kids or grandparents for a walk, or maybe a good opportunity to visit that new art museum? That walk may become stressful if it is sunny and the path offers little shade along the way. However, on a windy day, or on a route shaded from direct sunlight, such as a narrow street canyon, thermal conditions may be just fine. By utilizing expert knowledge of the combined effects of temperature, humidity, wind speed, and radiation on the human thermal energy balance, it is possible to refine the general forecast to be more site specific about human comfort while outdoors. Climate change (McCarthy et al. 2010, Coumou and Rahmstorf 2012, Coumou and Robinson 2013), urbanization-related heating [the urban heat island effect (UHI)], and recorded excess mortality during recent European heat waves generated an acute awareness for heat-related health risks. The elderly, people with cardiovascular diseases, and outdoor workers are particularly vulnerable (Zander et al. 2015). Accordingly, the need for easily accessible and local forecasting of human thermal comfort is growing. This paper presents a new smartphone app that communicates a location-specific human thermal comfort forecast based on the latest innovations in urban climate and biometeorology, computer science, communication technology, and land-use mapping. The forecasts were evaluated against four years of observations in the Netherlands. Humans are relatively limited in physiological thermoregulation strategies to cope with heat or cold and must rely on choice of clothing, shelter, or behavioral thermoregulation. Such strategies may also affect the choice of outdoor activities. A person’s interpretation of a standard weather forecast is subjective, and various empirical thermal indices to enhance weather forecasts have been introduced. These include the wind chill factor (Osczevski and Bluestein 2005) to quantify wind speed effects on the severity of cold weather conditions and the heat index (Steadman 1979) for hot conditions coupled with the effect of humidity on a perceived temperature scale. Unfortunately, none of these empirical indices build upon a physically sound human thermal energy balance model, and site-specific information, as introduced by urban morphology, has been neglected. Human thermal energy balance modeling has resulted in an “apparent” temperature that combines weather conditions, such as temperature, humidity, wind speed, and radiation. The latest insights are represented in the universal thermal climate index (UTCI) (Blzejczyk et al. 2012, Bröde et al. 2012). The UTCI is favored because it marries a dynamic clothing model and a state-of-the-art thermophysiological model of human heat transfer and temperature regulation (Fiala et al. 2012). The dynamic clothing model is based on what a person would wear according to the outdoor temperature (Havenith et al. 2012). The total human radiation load as part of the human thermal energy balance is expressed by a single temperature known as the mean radiant temperature Tmrt [Fanger 1970; see also sidebar “UTCI and mean radiant temperature Tmrt”]. The UTCI covers the full thermal exposure range Smartphone App Brings Human Thermal Comfort Forecast in Your Hands

Summer in the City: Forecasting and Mapping Human Thermal Comfort in Urban Areas

Urbanization affects human thermal comfort and health, especially for vulnerable groups such as the elderly and people with established health issues. To mitigate adverse thermal comfort and accompanying excess mortality there is an urgent need of tools for forecasting urban thermal comfort on short to medium-ranged time scales. In this use-case, we present the setup of a prototype of a high-resolution forecasting system at a neighborhood scale spatial resolution. The system builds on both traditional data sources, such as height-and terrain maps, and aerial photographs, as innovative datasources like the Dutch cadastre and the Dutch Statistics office. Additionally, crowd sourced temperature observations, special measuring campaigns, and a dense network of meteo stations will be used for validation.