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<div class="co_mto_htmlabstract mt-3"> <div class="co_mto_htmlabstract-content mt-3"> <p>Climate adaptation and emergency management are major challenges in cities, that benefit from the incorporation of real-time weather, air quality, differential exposure and vulnerability data. We therefore need systems that allow us to map, for example, localised thermal heat stress, heavy precipitation events or air quality spatially resolved across cities at high temporal resolution. Key to the assessment of average conditions and weather extremes in cities are systems that are capable of resolving intra-urban variabilities and microclimates at the level of people, hence in the urban canopy layer at street-level. Placing sensors at street-level, however, is challenging: Sensors need to be small, rugged, safe, and they must measure a number of quantities within limited space. Such systems may ideally require little or no external power, provide remote accessibility, sensor interoperability and real-time data transfer and must be cost-effective for mass deployment. However, these characteristics as well as a wide spectrum of observed variables are not available in current commercial sensor network solutions, hence we designed and implemented a custom partly in-house developed two-tiered sensor system for mounting and installation at 3 m height on city-owned street lights in Freiburg, Germany.</p> <p>Our partly in-house developed two-tiered sensor network, consisting of fifteen fully self-developed, cost-effective “Tier-I stations” and 35 commercial “Tier-II stations” (LoRAIN, Pessl Instruments GmbH), aims to fill these gaps and to provide a modular, user-friendly WSN with a high spatial density and temporal resolution for research, practical applications and the general public. The Tier-I stations were designed and optimised from the ground up, including the printed circuit board (PCB), for temporally high-resolution WSNs that support wide ranges of sensors and that is expandable. The core of the system is a low-power embedded computer (Raspberry Pi Zero) running a custom multithreaded generic logging and remote control software that locally stores the data and transmits it to a custom <em>vapor</em>-based TCP server via GSM. The software also features system monitoring and error detection functions, as well as remote logging. The setup can easily be expanded on the fly by adding predefined sensors to a configuration file.<span class="Apple-converted-space"> </span>For better modularity, each station registers itself on the server and will be automatically integrated in all further processes and vice versa. Custom frontends as well as bidirectional communication and task distribution protocols enable remote access and across node interaction, resulting in a more easy-to-maintain system.<span class="Apple-converted-space"> </span></p> <p>In addition to air temperature, humidity and precipitation measured by the Tier II stations, the Tier-I station feature a ClimaVUE 50 all-in-one weather sensor and a BlackGlobe (Campbell Scientific, Inc.) that provides data on wind, radiation, pressure, lightning, solar radiation and black globe temperatures. That allows for calculation of thermal comfort indices in real-time. A webpage and the self-developed “uniWeather” (iOS-App, API) offers near-realtime data access and data interpretation for stakeholders and public outreach.</p> <!-- COMO-HTML-CONTENT-END --></div> </div>

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<p>Exposure and vulnerabilities to heat stress are concentrated in cities, yet exhibit large intra-urban variability. However, existing Weather Sensor Networks (WSNs) that monitor relevant meteorological conditions are typically installed at a much coarser resolution and generally do not cover canopy-layer conditions in cities. There are few examples of fine urban-scale massive sensor networks at street-level, however, they rarely provide any data beyond air temperature and humidity needed to assess, map and calculate thermal comfort, and many street-level networks often lack the real-time data transmission and quality control procedures necessary for real-time communication.</p> <p>Here, we present a customizable two-tiered WSN setup, coupled with a quality and data processing chain, to quantify, map and communicate heat exposure data and resolve intra-urban variabilities in real-time. The hierarchical urban canopy-layer network developed for long-term monitoring of thermal comfort conditions (and also heavy precipitation and wind storm impacts) in the city of Freiburg, Germany, consists of two different station systems that are integrated into public street lights at a uniform height of 3 m a.g.l. Thirteen “tier I stations“ are strategically placed in representative built-up and rural areas. They are equipped with a ClimaVUE 50 all-in-one weather sensor (precipitation, wind, radiation, temperature, humidity, pressure) and a Black Globe Sensor (both from Campbell Scientific, Inc.) which enables real-time thermal comfort calculations such as the Physiologically Equivalent Temperature (PET) or the Universal Thermal Climate Index (UTCI). Tier I stations feature a custom-built multi-purpose logger which is controlled by a Raspberry Pi Zero running a custom remote control software and GSM data transmission. This allows for a highly flexible setup that can easily be expanded to include additional sensors (e.g. air quality) in the future. In addition, 35 commercial “tier II stations“ (LoRAIN, Pessl Instruments GmbH) measure air temperature, humidity and precipitation and transmit data over NB-IoT.  These tier II stations significantly increase the spatial density of the WSN at a lower cost per site. In addition to urban street-light mounted locations, an additional eight sites in non-built-up locations capture areas with predominantly rural and natural land cover, with selected stations specifically measuring cold-air drainage channels into the city.</p> <p>With measuring and transmission intervals of one and five minutes, respectively, one major purpose of this WSN is to develop machine learning routines for data quality control and quality assessment in real-time and downscaling thermal comfort data from tier II to tier I stations and areas not covered by stations. Moreover, the WSN will provide input and validation data for numerical high-resolution modelling of urban heat exposure. Real-time visualizations inform researchers, city officials and the general public with instantaneous and historical data at neighborhood-scale. </p>