Air Temperature and Relative Humidity Datasets from an Urban Meteorological Network in the City Area of Novi Sad (Serbia).

This data article describes two groups of datasets which capture, firstly - 10-minutes air temperature (Ta) and relative humidity (RH) data from 27 urban and non-urban sites over a period of 3.5 years covering 2014-2018; and secondly - hourly Ta data from 12 urban sites over a period of 2 years covering 2016 and 2017. Both datasets are from urban meteorological network located in the Novi Sad city (Serbia). These datasets have 2 different types of information in the collection: one type provides details about the monitoring sites at which the Ta and RH sensors are placed, while the second type contains Ta and RH data at all sensor locations. In all, the 10-minutes dataset contains about 185,000 instances of Ta and RH data, and the hourly datasets contain 17,544 instances of Ta data. The 10-minutes datasets were not quality controlled, but the hourly Ta data has been cleaned and gap-filled so there are 24 measures at each site for each day. There are multiple potential uses, where this data can be applied. It can provide insights in understanding intra-urban and inter-urban research, urban climate modeling on local or micro scales, heat-related public health investigations and urban environment inquiries. It can also be used in machine learning experiments, for example, to test the accuracy of classification algorithms or to build and validate spatio-temporal machine learning functions, either for classification purposes or for gap filling. These datasets are directly citable through its DOIs and available for download from the Zenodo platform or from the Fair Micromet Portal.

Hospital admission tendencies caused by day-to-day temperature changes during summer: a case study for the city of Novi Sad (Serbia).

Increased temperature risk in cities threatens the health and well-being of urban population and is fueled by climate change and intensive urbanization. Consequently, further steps must be taken for assessing temperature conditions in cities and their association with public health, in order to improve public health prevention at local or regional level. This study contributes to solving the problems by analyzing the connection between extreme temperatures and the tendencies of all-cause hospital admissions. The analyses used (a) 1-h air temperature data, and (b) daily data of all-cause hospital admissions. The datasets include the summer period (June, July, August) for the years 2016 and 2017. We tested the effects of two temperature indices, day-to-day change in maximum temperature - Tmax,c and daily temperature range - Tr, with all-cause hospital admission subgroups, such as all-cause cases - Ha, hospital admissions in the population below 65 - Ha<65, and hospital admissions in the population aged 65 and over - Ha≥65. The results show the highest values of Ha when Tmax,c is between 6 and 10 °C. Therefore, more intensive hospital admissions can be expected when Tmax increases from day-to-day (positive values of Tmax,c), and it is more visible for Ha and Ha<65 (1 °C = 1% increase in hospital admissions). Also, Tr values between 10 °C and 14 °C cause an increase in the number of hospital admissions, and it is more noticeable for Ha≥65.

Analysis of air temperature dynamics in the "local climate zones" of Novi Sad (Serbia) based on long-term database from an urban meteorological network.

A comprehensive analysis of air temperature (Ta) dynamics in "local climate zones" (LCZs) of Novi Sad (Serbia) was based on measurements from 17 stations during 3 years. Hourly changes of Ta, cooling rates (CR), heating rates (HR), and urban heat island (UHI) intensity were assessed on seasonal and annual level and during heat wave (HW) and cold wave (CW) periods. Substantial differences are observed for minimum (Tmin) and mean temperatures (Tmean) between LCZs. Two-phase nocturnal cooling was recognized with the first cooling phase characterized by intensive LCZ dependent cooling starting at 1-3 h before sunset and lasting until 3-4 h after sunset. The second cooling phase lasts until sunrise and is characterized by less intensive and LCZ nondependent cooling. The most intensive cooling (CRpeak) was observed in first cooling phase of HW and ranged from - 1.6 °C h-1 in street canyon (LCZ 2) to - 3.9 °C h-1 in forest (LCZ A). Furthermore, a new cooling indicator (CRtotal) was introduced. Due to cooling differences, the most intensive UHI of 5.5 °C was noticed between LCZs 2 and A at sunset + 1 h during HW. Two-phase diurnal heating was also recognized in LCZs with the first heating phase characterized by intensive LCZ dependent heating starting at sunrise and lasting until 4-7 h afterwards. The most intensive heating (HRpeak) ranged from 2.0 °C h-1 in street canyon to 3.0 °C h-1 in industrial area (LCZ 8) during HW. The second heating phase lasts until sunset and is characterized by less intensive heating and smaller HR differences between LCZs.

Progressing urban climate research using a high-density monitoring network system.

An increasing number of urban meteorological networks (UMNs) and automated data acquisition are irreplaceable tools in modern urban climate monitoring, evaluation, and analysis. The most serious issue in such systems is data loss, caused primarily by communication problems between stations and servers. The Novi Sad Urban Network (NSUNET) consists of 28 remote stations and 2 servers built solely on open-source technologies. It is used for monitoring climate peculiarities and acquiring long-term meteorological data from the urban area of Novi Sad, as well as for the early warning notification to the city emergency services of the current urban weather conditions. Since its deployment, the system has managed to overcome most of the problems related to today's UMNs, to operate at a low Internet service fee, and ensure high reliability and performance on low-budget hardware. This study includes details on how to develop such a system and it presents a statistical analysis of the NSUNET system's performances and the measurement data. Furthermore, this kind of monitoring system provides good results in the analysis of air/surface temperature and outdoor human thermal comfort in the local climate zones (LCZs) of urban and surrounding areas and can help identify hot spots/districts in the urban area.