BioCAS: Biometeorological Climate impact Assessment System for building-scale impact assessment of heat-stress related mortality

An urban climate analysis system for Seoul was combined with biometeorological models for the spatially distributed assessment of heat stress risks. The Biometeorological Climate impact Assessment System (BioCAS) is based on the Climate Analysis Seoul (CAS) workbench which provides urban planners with gridded data relevant for local climate assessment at 25 m and 5 m spatial resolutions. The influence of building morphology and vegetation on mean radiant temperature Tmrt was simulated by the SOLWEIG model. Gridded hourly perceived temperature PT was computed using the Klima-Michel Model for a hot day in 2012. Daily maximum perceived temperature PTmax was then derived from these data and applied to an empirical-statistical model that explains the relationship between PTmax and excess mortality rate rEM in Seoul. The resultant rEM map quantifies the detrimental impact of hot weather at the building scale. Mean (maximum) values of rEM in old and new town areas in an urban re-development site in Seoul were estimated at 2.3 % (50.7 %) and 0 % (8.6 %), respectively, indicating that urban re-development in the new town area has generally resulted in a strong reduction of heat-stress related mortality. The study illustrates that BioCAS can generally be applied for the quantification of the impacts of hot weather on human health for different urban development scenarios. Further improvements are required, particularly to consider indoor climate conditions causing heat stress, as well as socio-economic status and population structure of local residents

Räumliche Variabilität human-biometeorologischer Größen bezogen auf Hitzestress in Berlin, Deutschland – mit Fokus auf Lufttemperatur und Strahlung

Heat stress endangers the health and lives of people especially in cities, since air temperature is often higher there than in the surrounding countryside. Human-biometeorological conditions related to heat stress are spatially variable, also within a city. Processes from the meso- to the micro-scale, i.e., large-scale weather situations and individual streets, have to be considered to capture this spatial variability. Analyses of human-biometeorological conditions on different scales are essential to examine the spatial variability and to understand underlying processes. They also enable the identification of hotspots in the city, which is valuable for implementing adaptation measures. So far, however, high-resolution and city-wide analyses, which consider micro- and meso-scale processes, have been rare. The aim of this work is to investigate spatial variability of human-biometeorological conditions related to heat stress in Berlin at different scales and to contribute to future multi-scale analyses. Models on meso- and micro-scales were tested in terms of deviations from observations of near-surface air temperature (T2) and mean radiant temperature (Tmrt). These models were then applied together with measurements to assess spatial variability of human-biometeorological conditions in Berlin. Furthermore, the propagation of spatial patterns from one scale to the other was examined. To study the meso-scale, the Central Europe Refined Analysis (CER) was developed and T2 was evaluated against weather stations. The CER is a new dataset based on dynamical downscaling of a global reanalysis using the Weather Research and Forecasting model (WRF). On the micro-scale, three widely-used models – ENVI-met, RayMan and SOLWEIG – were evaluated, with respect to Tmrt. SOLWEIG was selected for further use due to the smallest deviations from observations and fast computation. A new sub-version of SOLWEIG for automated workflows was developed, which allows city-wide simulations. Thus, the weather situation from a meso-scale model as well as the influence of micro-scale urban structures on Tmrt was considered. The spatial variability of human-biometeorological conditions in Berlin was examined with the meso-scale analysis CER and the coupled SOLWEIG model. An indoor/outdoor observation network was also used for assessing the spatial variability on the building-scale. The results reveal a high degree of spatial variability at the meso-, micro-, city , and building-scale for T2, Tmrt, and the Universal Thermal Climate Index (UTCI). At the meso-scale, a nocturnal urban heat island, and intra-urban differences between built-up and green areas were established, reaching 1.3 K and 0.4 K as a monthly average, respectively. At the city-scale and with regard to Tmrt, the degree of spatial variability was higher. Around noon, Tmrt values varied between 30°C and 60°C; the highest Tmrt values were reached in open, unshaded areas. The effect of façade greening on spatial variability of Tmrt and UTCI on the micro-scale, however, was low. The spatial variability at building-scale was high, with differences in the UTCI between buildings of 3 K on average over the summer. Thus, in some buildings, on more than 50% of the summer days, moderate heat stress occurred (UTCI ≥ 26°C). Spatial patterns, however, were not directly propagated from one scale to the other. Different processes were relevant for different scales. The pattern of Tmrt at the city-scale was influenced by the meso-scale T2 pattern in the daytime, but the spatial variability was mainly a result of the shadows cast by buildings and trees. At the building-scale, the spatial patterns of the indoor UTCI were hardly affected by the spatial patterns of the outdoor UTCI in the immediate neighbourhood of the building. Other factors, such as ventilation and building characteristics, seem more important. Knowledge about propagation through the scales is particularly valuable for future multi-scale model development.Hitzestress gefährdet die Gesundheit und das Leben von Menschen insbesondere in Städten, weil dort die Lufttemperatur häufig höher ist als im Umland. Zudem sind die für Hitzestress relevanten human-biometeorologischen Bedingungen innerhalb einer Stadt räumlich variabel. Um diese räumliche Variabilität zu erfassen, müssen Prozesse von der Meso- bis zur Mikroskala, also die großskalige Wettersituationen genauso wie einzelne Straßenzüge, berücksichtigt werden. Analysen human-biometeorologischer Bedingungen auf verschiedenen Skalen sind essenziell, um die räumliche Variabilität in Städten zu erfassen und zugrundeliegende Prozesse zu verstehen. Sie ermöglichen auch, Hotspots in der Stadt zu identifizieren, um dort Anpassungsmaßnahmen umzusetzen. Bisher sind hochaufgelöste und stadtweite Analysen, die mikro- und mesoskalige Prozesse berücksichtigen, jedoch kaum vorhanden. Ziel dieser Arbeit ist es daher, die räumliche Variabilität von human-biometeorologischen Bedingungen in Berlin auf verschiedenen Skalen zu untersuchen und einen Beitrag für künftige multiskalige Analysen zu leisten. Dazu werden verschiedene Modelle auf der Meso- und Mikroskala bezogen auf Abweichung zu Messungen der mittleren Strahlungstemperatur (Tmrt) und oberflächennaher Lufttemperatur (T2) getestet. Die Modelle wurden dann zusammen mit Messungen verwendet, um die räumliche Variabilität human-biometeorologischer Bedingungen in Berlin zu erfassen. Außerdem wurde die Übertragung der räumlichen Muster von der einen zur anderen Skala untersucht. Zur Untersuchung der Mesoskala wurde die Central Europe Refined Analysis (CER) entwickelt und anhand von Messdaten bezogen auf T2 evaluiert. Die CER ist einen neuer Datensatz basierend auf dynamischem Downscaling einer globalen Reanalyse mit dem Weather Research and Forecasting model (WRF). Auf der Mikroskala wurden drei häufig verwendete Modelle, ENVI-met, RayMan und SOLWEIG, hinsichtlich der Tmrt evaluiert. Aufgrund der geringsten Abweichungen zu Messdaten und der kurzen Rechenzeit wurde SOLWEIG für die weitere Verwendung ausgewählt. Eine neuentwickelte Sub-Version von SOLWEIG mit einem automatisierten Arbeitsablauf ermöglicht es, stadtweite Simulationen durchzuführen. Dadurch werden sowohl die Wettersituation aus einem mesoskaligen Modell als auch der mikroskaligen Einfluss von Stadtstrukturen auf die Tmrt berücksichtigt. Anhand der mesoskaligen Analyse CER und des gekoppelten SOLWEIG Modells wurde die räumliche Variabilität human-biometeorologischer Größen in Berlin untersucht. Ein Innen-/Außenraum-Klimamessnetz wurde verwendet, um die räumliche Variabilität auf der Gebäudeskala zu betrachten. Die Ergebnisse zeigen eine hohe räumliche Variabilität der T2, Tmrt und des Universal Thermal Climate Index (UTCI) auf der Meso-, Stadt- und Gebäudeskala. T2 wies auf der Mesoskala eine nächtliche städtische Wärmeinsel (1.3 K im Monatsmittel) und intra-urbane Differenzen zwischen bebauten Flächen und Grünflächen (0.7 K im Monatsmittel) auf. Auf der Stadtskala und in Bezug auf Tmrt war die räumliche Variabilität ausgeprägter. Zur Mittagszeit traten Tmrt-Werte zwischen 30°C und 60°C auf, wobei die höchsten Werte an offenen, nicht-beschatteten Flächen vorkamen. Die Wirkung von Fassadenbegrünung auf die räumliche Variabilität von Tmrt und UTCI in der Mikroskala war hingegen gering. Auf der Gebäudeskala war die Variabilität bezogen auf den UTCI mit bis zu 3 K im Sommermittel deutlich ausgeprägt, so dass in manchen Gebäuden an 50% der Sommertage moderater Hitzestress (UTCI ≥ 26°C) auftrat. Die räumlichen Muster übertrugen sich aber nicht direkt von der einen zur anderen Skala. Auf den jeweiligen Skalen waren unterschiedliche Prozesse relevant. Das Muster der Tmrt tagsüber auf der Stadtskala war zwar auch von der mesoskaligen Lufttemperaturverteilung beeinflusst, die räumliche Variabilität wurde allerdings hauptsächlich durch Schattenwürfe von Gebäuden und Bäumen verursacht. Auch auf der Gebäudeskala war das räumliche Muster von UTCI im Innenraum kaum von dem räumlichen Muster im Außenraum im direkten Umfeld der Gebäude beeinflusst. Dort scheinen andere Faktoren wie Belüftung und Gebäudeeigenschaften mehr Einfluss zu haben. Solche Kenntnisse über die Übertragung der Muster zwischen den Skalen sind besonders für künftige multiskalige Modellentwicklungen wichtig

Review of User-Friendly Models to Improve the Urban Micro-Climate

Various micro-scale models for comparing alternative design concepts have been developed in recent decades. The objective of this study is to provide an overview of current user-friendly micro-climate models. In the results, a vast majority of models identified were excluded from the review because the models were not micro-scale, lacking a user-interface, or were not available. In total, eight models met the seven-point inclusion criteria. These models were ADMS Temperature and Humidity model, advanced SkyHelios model, ANSYS FLUENT, ENVI-met, RayMan, SOLWEIG, TownScope, and UMEP. These models differ in their complexity and their widespread use in the scientific community, ranging from very few to thousands of citations. Most of these models simulate air temperature, global radiation, and mean radiant temperature, which helps to evaluate outdoor thermal comfort in cities. All of these models offer a linkage to CAD or GIS software and user support systems at various levels, which facilitates a smooth integration to planning and design. We detected that all models have been evaluated against observations. A wider model comparison, however, has only been performed for fewer models. With this review, we aim to support the finding of a reliable tool, which is fit for the specific purpose

Evaluating the Effects of Façade Greening on Human Bioclimate in a Complex Urban Environment

The evaluation of the effectiveness of countermeasures for a reduction of urban heat stress, such as façade greening, is challenging due to lacking transferability of results from one location to another. Furthermore, complex variables such as the mean radiant temperature (Tmrt) are necessary to assess outdoor human bioclimate. We observed Tmrt in front of a building façade in Berlin, Germany, which is half-greened while the other part is bare. Tmrt was reduced (mean 2 K) in front of the greened compared to the bare façade. To overcome observational shortcomings, we applied the microscale models ENVI-met, RayMan, and SOLWEIG. We evaluated these models based on observations. Our results show that Tmrt (MD = −1.93 K) and downward short-wave radiation (MD = 14.39 W/m2) were sufficiently simulated in contrast to upward short-wave and long-wave radiation. Finally, we compare the simulated reduction of Tmrt with the observed one in front of the façade greening, showing that the models were not able to simulate the effects of façade greening with the applied settings. Our results reveal that façade greening contributes only slightly to a reduction of heat stress in front of building façades

Technological opportunities for sensing of the health effects of weather and climate change: a state-of-the-art-review

Sensing and measuring meteorological and physiological parameters of humans, animals, and plants are necessary to understand the complex interactions that occur between atmospheric processes and the health of the living organisms. Advanced sensing technologies have provided both meteorological and biological data across increasingly vast spatial, spectral, temporal, and thematic scales. Information and communication technologies have reduced barriers to data dissemination, enabling the circulation of information across different jurisdictions and disciplines. Due to the advancement and rapid dissemination of these technologies, a review of the opportunities for sensing the health effects of weather and climate change is necessary. This paper provides such an overview by focusing on existing and emerging technologies and their opportunities and challenges for studying the health effects of weather and climate change on humans, animals, and plants