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Urban Extreme

The new UHE-Daily dataset contains geolocated extreme heat events and urban population exposure estimates for more than 13,000 urban settlements worldwide from 1983 to 2016. Urban extreme heat events and urban population exposure are identified for each settlement in the data record at five combined temperature-humidity thresholds:

Urban Extreme

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According to Cascade Tuholske, a Postdoctoral Research Scientist hosted by CIESIN, the release of this dataset is significant because it may help decision-makers from a variety of disciplines become more attuned to the dangers at the intersection of extreme heat and population.

Users can download the UHE-Daily dataset from the SEDAC and Earthdata Search websites. The data are available as a .zip file containing both .json and .csv file formats, as well as a .zip file with .shp files. Each .zip file also contains a README.txt file that explains the data variables. In addition, all UHE-Daily records can be mapped with the latitude and longitude of the urban settlement. For more advanced users, the code used to perform the analyses of the UHE-Daily dataset is available on Github.

As the data reveal, urban population growth accounted for two-thirds of the increases in exposure, while actual warming contributed a third. The cities most affected by population increases tend to be in the low latitudes, closer to the equator. This does not mean that these locations did not experience warming, only that population growth was even more significant. Conversely, the exposure in other cities had more to do with warming than population growth. For example, since the populations of European cities have generally stayed the same, their increases in exposure were driven almost exclusively by increased warmth. In the United States, about 40 sizable cities have seen rapidly growing exposure, mainly clustered in Texas and the Gulf Coast. In many, the causes of the rises have been varying combinations of both increasing population and increasing heat.

Although the study by Tuholske et al is not the first to document the dangers of excessive urban heat, it makes an important contribution to the literature on the subject by quantifying, on a granular level, the number of people affected in locations around the world, and the degree to which exposure is being driven by population versus climate.

Given that heat waves around the globe have become more frequent, long lasting, and intense, and that the number of days people are experiencing extreme heat is on the rise around the globe, it seems this new SEDAC dataset and the insights it offers have arrived right on time.

Zhao's team has developed a model that closes two major gaps in urban climate modeling. First, most traditional climate models effectively ignore cities entirely. Urban areas make up only 2-3 percent of the earth's land, so their effect on global models is negligible, but more than half of the world's population lives in urban areas, so their impact is significant. The team's new modeling approach addresses that by providing urban-specific climate signals.

Second, because of this lack of urban representation in state-of-the-art climate models, there were no global-scale, multi-model projections for urban climates. The multi-model projections are critical to characterize the robustness and uncertainty of the projections, which is very important for estimating the climate-driven risks, for example, the likelihood of climate extremes. The new model provides global multi-model projections of local urban climates.

"This work highlights the critical importance of having multi-model projections to accurately estimate the likelihood of extreme events that will occur in the future under climate change," Zhao said. More information:Zhonghua Zheng et al, Large model structural uncertainty in global projections of urban heat waves, Nature Communications (2021). DOI: 10.1038/s41467-021-24113-9Journal information:Nature Communications

Extreme temperatures, especially long-lasting heat and cold waves in urban areas, lead to thermal stress of the population and increase the number of weather-related health risks and deaths. The observed climate trend and the associated increase of extreme weather events are expected to continue in the future. Thus, the evaluation of urban thermal stress and the associated health effects becomes an important issue for urban planning and risk management. For Austrian cities, an information system for temperature warnings already exists (Weather warnings, ZAMG), which is based on the information of regional weather forecast models. However, this information does not have the required spatial resolution needed to resolve urban structure and thus to account for the urban heat island effect or cold stress situations in winter.

The aim of this project is to provide the basis for the improvement of extreme weather/thermal (dis)comfort warning systems in Austrian major cities by using high-resolution weather predictions (100 m). Therefore, the soil model SURFEX (developed by Météo France) coupled with the AROME numerical weather forecast model is applied to selected cities in Austria and used to determine the best model configuration to compute short-term forecasts (+60 hours). This method provides not a full dynamical model, but a way of pyhsical downscaling with height corrections and a high-resolution surface model.

In this project, land use parameterization will be updated and improved based on Pan-European High Resolution Layers (e.g. Urban Atlas) of the Copernicus Land Monitoring service in ECOCLIMAP (predefined land use classes for SURFEX). The model output will be verified with in-situ operational and crowd-sourced observations. Furthermore, the results will be compared to the micro-scale urban climate model MUKLIMO_3 from the German Weather Service (100 m) and various thermal infrared (TIR with 150 to 250 m) datasets. The novel modeling approach for simulating thermal stress in urban areas serves as the basis for improving the operational prediction system of extreme temperatures, for optimizing the future extreme weather warning system at the ZAMG, and for decision-making for the involved cities and their stakeholders.

Abstract: Human health and social development are significantly affected by urban extreme heat. It is a new proposition for human-land relationship in the field of geography to measure the characteristics and social consequences of urban extreme heat. Applying the tool of social vulnerability to studies of urban extreme heat, this paper takes 296 cities in China as research objects and establishes quantitative indicators of urban extreme heat such as high temperature days, high temperature intensity, heat wave frequency, heat wave duration and heat wave intensity. By using daily maximum temperature data, urban statistics and census data, we systematically analyze the characteristics of urban extreme heat. Meanwhile, we construct a framework for urban social vulnerability to extreme heat and based on this framework, we developed a common evaluation index system of social vulnerability according to the three dimensions of exposure, sensitivity and adaptive capacity. Finally, we conduct social vulnerability assessments for the 296 cities, classify social vulnerability levels, and analyze the causes of urban social vulnerability. The results are shown as follows. (1) The extreme heat events are mainly concentrated in southern cities, especially in the eastern and central parts of the country. Although there are fewer extreme heat events in northern cities, the intensity of high temperature is more prominent. (2) The urban exposure index to extreme heat in China has obvious spatial agglomeration characteristics, while the sensitivity index and adaptability index are scattered. (3) Cities with high social vulnerability index are mainly concentrated in most areas of East and Central China, and in a few areas of Southwest and North China. The proportion of cities with high, middle and low social vulnerability index was 25.3%, 46.3% and 28.4%, respectively. (4) The number of social sensitive cities is the largest, followed by high temperature exposure cities, and the number of insufficient adaptability cities is the smallest. In addition, exposure index contributes the most in cities with high social vulnerability index, and sensitivity index contributes the most in cities with middle and low social vulnerability indexes. This study can provide reference and enlightenment for relationship research between disaster and society, quantitative expression of characteristics of urban extreme heat and assessment of social vulnerability to extreme heat.

Green Roofs are one of the measures to mitigate the Urban Heat Island (UHI) effects. The cooling effects of green roofs are well studied in the literature. Green roofs can change temperatures and modify humidity. Here we postulate that the change in microenvironment due to green roofing may also have a potential to modify mesoscale convection and hence the intensity, distribution and related aspects of heavy (extreme) precipitation. We first develop and present a conceptual thought experiment as to possible pathways of mesoscale convection changes amidst green infrastructure changes. We then evaluate the postulation using the detailed urban WRF modeling system by taking the example of an extreme rainfall case that affected Mumbai city on 29 August 2017. The event while labelled 'extreme' is typical of the heavy rain events the city has been experiencing in recent years. The event was simulated for different green roof scenarios, viz. 10%, 25%, 50%, as well as 75%, and 100% green roof over the urban area. The green roof simulations are compared with respect to 'no green roof' simulation (control run). After this a prior green roof specification experiment, a multi-criteria Monte Carlo experiment was undertaken to assess the possible location and magnitude of green roofing that will be required to have 1, 2, and 3 deg C changes for the city. Using the resulting green roof distribution WRF results were regenerated to see whether the temperature effects are similarly obtained when using coupled analysis. Initial results suggest green roofing may further increase the intensity of heavy rainfall and this leads to an interesting question regarding what mitigation pathway should a city consider- when green infrastructure for temperature regulation may cause possibly higher flood potential. 041b061a72


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