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

A news update from the students and new professionals group of the International Society of Biometeorology

An update from the new Chair and Executive Committee of the Students and New Professionals Group of the International Society of Biometeorology.

The effects of extreme heat on human health in tropical Africa

This review examines high-quality research evidence that synthesises the effects of extreme heat on human health in tropical Africa. Web of Science (WoS) was used to identify research articles on the effects extreme heat, humidity, Wet-bulb Globe Temperature (WBGT), apparent temperature, wind, Heat Index, Humidex, Universal Thermal Climate Index (UTCI), heatwave, high temperature and hot climate on human health, human comfort, heat stress, heat rashes, and heat-related morbidity and mortality. A total of 5, 735 articles were initially identified, which were reduced to 100 based on a set of inclusion and exclusion criteria. The review discovered that temperatures up to 60°C have been recorded in the region and that extreme heat has many adverse effects on human health, such as worsening mental health in low-income adults, increasing the likelihood of miscarriage, and adverse effects on well-being and safety, psychological behaviour, efficiency, and social comfort of outdoor workers who spend long hours performing manual labour. Extreme heat raises the risk of death from heat-related disease, necessitating preventative measures such as adaptation methods to mitigate the adverse effects on vulnerable populations during hot weather. This study highlights the social inequalities in heat exposure and adverse health outcomes.

Analysis of long- and short-term biometeorological conditions in the Republic of Serbia

Long- and short-term biometeorological conditions in the Republic of Serbia were analyzed using official meteorological data from numerous weather stations located across the country. Selected biometeorological indices HUMIDEX, Physiologically Equivalent Temperature (PET), and Universal Thermal Climate Index (UTCI) are calculated based on air temperature, relative humidity, wind speed, and cloudiness data from the meteorological stations on annual and summer level as well as during selected heat wave periods during 2000-2020. Application of different biometeorological indices provides similar but somewhat different results. For example, average annual HUMIDEX and UTCI values indicate no thermal stress and no discomfort at all stations, while PET indicates the occurrence of slight to moderate cold stress at all stations. Average summer PET and UTCI indicate the occurrence of slight to moderate heat stress throughout the country, while HUMIDEX indicates no discomfort. Trends of biometeorological indices on annual and summer level show a general increase throughout the country. Furthermore, heat wave analysis indicated that the most populated cities of Serbia are under dangerous and extreme heat stress during these extreme temperature events, which can influence human health and well-being. The obtained biometeorological information can be used for the preparation of climate adaptation strategies that consider the human biometeorological conditions, with a special focus on developing climate-sensitive and comfortable cities.

An urban energy balance-guided machine learning approach for synthetic nocturnal surface Urban Heat Island prediction: A heatwave event in Naples

Southern European functional urban areas (FUAs) are increasingly subject to heatwave (HW) events, calling for anticipated climate adaptation measures. In the urban context, such adaptation strategies require a thorough understanding of the built-up response to the incoming solar radiation, i.e., the urban energy balance cycle and its implications for the Urban Heat Island (UHI) effect. Despite readily available, diurnal Land Surface Temperature (LST) data does not provide a meaningful picture of the UHI, in these midlatitudes FUAs. On the contrary, the mid-morning satellite overpass is characterized by the absence of a significant surface UHI (SUHI) signal, corresponding to the period of the day when the urban-rural air temperature difference is typically negative. Conversely, nocturnal high-resolution LST data is rarely available. In this study, an energy balance-based machine learning approach is explored, considering the Local Climate Zones (LCZ), to describe the daily cycle of the heat flux components and predict the nocturnal SUHI, during an HW event. While the urban and rural spatial outlines are not visible in the diurnal thermal image, they become apparent in the latent and storage heat flux maps - built-up infrastructures uptake heat during the day which is released back into the atmosphere, during the night, whereas vegetation land surfaces loose diurnal heat through evapotranspiration. For the LST prediction model, a random forest (RF) approach is implemented. RF results show that the model accurately predicts the LST, ensuring mean square errors inferior to 0.1 K. Both the latent and storage heat flux components, together with LCZ classification, are the most important explanatory variables for the nocturnal LST prediction, supporting the adoption of the energy balance approach. In future research, other locations and time-series data shall be trained and tested, providing an efficient local urban climate monitoring tool, where in-situ air temperature observations are not available.

Analysing Historical and Modelling Future Soil Temperature at Kuujjuaq, Quebec (Canada): Implications on Aviation Infrastructure

The impact of climate change on soil temperatures at Kuujjuaq, Quebec in northern Canada is assessed. First, long-term historical soil temperature records (1967–1995) are statistically analyzed to provide a climatological baseline for soils at 5 to 150 cm depths. Next, the nature of the relationship between atmospheric variables and soil temperature are determined using a statistical downscaling model (SDSM) and National Centers for Environmental Prediction (NCEP), a climatological data set. SDSM was found to replicate historic soil temperatures well and used to project soil temperatures for the remainder of the century using climate model output Canadian Second Generation Earth System Model (CanESM2). Three Representative Concentration Pathway scenarios (RCP 2.6, 4.5 and 8.5) were used from the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). This study found that the soil temperature at this location may warm at 0.9 to 1.2 °C per decade at various depths. Annual soil temperatures at all depths are projected to rise to above 0 °C for the 1997–2026 period for all climate scenarios. The melting soil poses a hazard to the airport infrastructure and will require adaptation measures.

Air Humidity Characteristics in “Local Climate Zones” of Novi Sad (Serbia) Based on Long-Term Data

This study aims to investigate spatial and temporal dynamics and relationship between air temperature and five air humidity parameters (relative humidity, water vapor pressure, absolute humidity, specific humidity, and vapor pressure deficit) in Novi Sad, Serbia, based on two-year data (December 2015–December 2017). The analysis includes different urban areas of Novi Sad, which are delineated in five built (urban) types of local climate zones (LCZ) (LCZ 2, LCZ 5, LCZ 6, LCZ 8, and LCZ 9), and one land cover (natural) local climate zone (LCZ A) located outside the urban area. Temporal analysis included annual, seasonal, and monthly dynamics of air temperature and air humidity parameters, as well as their patterns during the extreme periods (heat and cold wave). The results showed that urban dry island (UDI) occurs in densely urbanized LCZ 2 from February to October, unlike other urban LCZs. The analysis of the air humidity dynamics during the heat wave shows that UDI intensity is most pronounced during the daytime, but also in the evening (approximately until midnight) in LCZ 2. However, lower UDI intensity is observed in the afternoon, in other urban LCZs (LCZ 6, LCZ 8, and LCZ 9) and occasionally in the later afternoon in LCZ 5. Regression analysis confirms the relationship between air temperature and each of the analyzed air humidity parameters.

An Application of the LCZ Approach in Surface Urban Heat Island Mapping in Sofia, Bulgaria

This article presents the results of the thermal survey of the capital of Bulgaria (Sofia) carried out in August 2019, with the application of an unmanned aerial system (UAS). The study is based on the concept of local climate zones (LCZs), taking into account the influence of the features of land use/land cover and urban morphology on the urban climate. The basic spatial units used in the study are presented in the form of a regular grid consisting of 3299 cells with sides of 250 × 250 m. A total of 13 types of LCZs were identified, of which LCZs 6, 5, 8, 4, D, and A form the largest share. In the thermal imaging of the surface, a stratified sampling scheme was applied, which allowed us to select 74 cells, which are interpreted as representative of all cells belonging to the corresponding LCZ in the urban space. The performed statistical analysis of the thermal data allowed us to identify both the most thermally loaded zones (LCZs 9, 4, and 5) and the cells forming Urban Cool Islands (mainly in LCZs D and C). The average surface temperature in Sofia during the study period (in the time interval between 8:00 p.m. and 10:00 p.m.) was estimated at 20.9 °C, and between the different zones it varied in the range 17.2–25.1 °C. The highest maximum values of LST (27.9–30.6 °C) were registered in LCZ 4 and LCZ 5. The relation between the spatial structure of the urban thermal patterns and urban surface characteristics was also analyzed. Regression analysis confirmed the hypothesis that as the proportion of green areas increases, surface temperatures decrease, and, vice versa, as the proportion of built-up and impermeable areas increases, surface temperatures increase. A heat load map (via applying a z-transformation to standardize the temperature values), a map of the average surface temperature, and a map of the average intensity of the heat island on the surface were generated in the GIS environment. The results of the study adequately reflect the complex spatial model of the studied phenomenon, which gives grounds to conclude that the research approach used is applicable to similar studies in other cities.

Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal

Lisbon is a European Mediterranean city, greatly exposed to heatwaves (HW), according to recent trends and climate change prospects. Considering the Atlantic influence, air temperature observations from Lisbon’s mesoscale network are used to investigate the interactions between background weather and the urban thermal signal (UTS) in summer. Days are classified according to the prevailing regional wind direction, and hourly UTS is compared between HW and non-HW conditions. Northern-wind days predominate, revealing greater maximum air temperatures (up to 40 °C) and greater thermal amplitudes (approximately 10 °C), and account for 37 out of 49 HW days; southern-wind days have milder temperatures, and no HWs occur. Results show that the wind direction groups are significantly different. While southern-wind days have minor UTS variations, northern-wind days have a consistent UTS daily cycle: a diurnal urban cooling island (UCI) (often lower than –1.0 °C), a late afternoon peak urban heat island (UHI) (occasionally surpassing 4.0 °C), and a stable nocturnal UHI (1.5 °C median intensity). UHI/UCI intensities are not significantly different between HW and non-HW conditions, although the synoptic influence is noted. Results indicate that, in Lisbon, the UHI intensity does not increase during HW events, although it is significantly affected by wind. As such, local climate change adaptation strategies must be based on scenarios that account for the synergies between potential changes in regional air temperature and wind.