Intercomparison and combination of low-cost urban air temperature measurement approaches [Dataset]

Abstract

Measurements of urban air temperatures (Tair) are vital to successful adaptation and mitigation policies to increasing urban heat stress. However, in-situ measurements in cities are often scarce and costly, and therefore low-cost approaches are increasingly used to study urban Tair. This allows for inexpensive, yet still highly spatially and temporally resolved observations of urban Tair. Despite their merits, a common issue of such low-cost approaches is lacking data quality and potential measurement errors. Here, we compare three low-cost measurement approaches regarding their ability to capture intra-urban variability of Tair over a period of 24 hours in Bern, Switzerland: a) A network of 79 low-cost measurement devices (LCD), b) bicycle mounted mobile measurements (BCY), and c) 581 Netatmo citizen weather stations (CWS). As the BCY sensor is actively ventilated, it is used as the reference for intercomparisons with LCD and CWS. Compared to the BCY, the median difference of Tair for LCD is found to be slightly negative over the entire study period (-0.07 K) as well as during night-time (-0.09 K), and positive during daytime (0.07 K). The CWS show a positive median difference of 0.66 K over the entire study period, 0.98 K during night-time, and a negative difference of -0.18 K during daytime. BCY and LCD both show a distinct pattern of nocturnal intra-urban Tair variability, which is less pronounced in the CWS measurements. Furthermore, the intercomparison of the three approaches across local climate zones reveals that CWS do not well represent forested areas. Whilst the bias sources of the individual approaches require in-depth investigation in future studies (e.g., external heat sources and measurement height for BCY, daytime short-wave radiation errors for LCD, and nocturnal thermal heating by nearby buildings for CWS), we conclude that the combination of the three measurement approaches provides a high observation density in urban environments at low costs.