DOI: 10.57707/fmi-b2share.bf9f2-6z158
title: Micro-climatic temperature measurements in the Finnish city of Tampere

description: Contains measurement data of air temperature for the manuscript "Real-time measurements of micro-climatic temperature and relative humidity in the Finnish cities of Tampere and Helsinki" by Kühn et al. (in preparation) of 23 measurement stations in Tampere. 

Technical Info: 

NB: Update on 21.5.2025: data file Tampere_202504.dat added.

The measurements were conducted at a height of 3 m in the locations listed in Table 1 during 07/2023-04/2025. Each measurement station consisted of three parts: a temperature and humidity sensor, a solar radiation shield, and an Internet of Things (IoT) device, which collected the measurement data and communicated them to a server via Long Range Wide Area Network (LoRaWAN). Temperature and relative humidity (RH) were measured by one integrated sensor, the Digital Matter I2C Temperature and Humidity Sensor [https://www.digitalmatter.com/wp-content/uploads/2020/09/I2C-Temperature-and-Humidity-Sensor-Datasheet.pdf]. Within the sensor, the temperature and RH were measured using the Silicon Labs Si7021-A20 I2C Humidity and Temperature Sensor chip. The chip is factory calibrated and has maximum operating ranges of 0% to 100% RH and -40°C to +125°C temperature. The measurement accuracy for temperature is maximum ±0.4°C if the ambient temperature is between -10°C and 85°C. The measurement accuracy of the chip is maximum ±3% RH if the ambient RH is between 0% and 80%.  

The Temperature and Humidity Sensor was protected by a radiation shield to minimize the influence of direct sunlight and thermal radiation on the measurements. The radiation shield (height 11.5 cm, radius 14 cm) was made of white plastic and consisted of 9 ventilated plates stacked in a cylindrical design allowing for adequate airflow while shielding the sensor from external radiation. 

Quality check 
The temperature data was quality checked using a multi-step procedure. First, values were screened based on long-term climatological daily minimum and maximum temperatures derived from 10 km × 10 km resolution gridded temperature data for the Tampere region (Aalto et al., 2016). Measurements falling clearly outside the climatological range were removed. Subsequently, remaining values were filtered based on statistical properties of the measurements, using median and median absolute deviation (MAD) over short time intervals to identify and remove outliers. A final threshold based on deviations from the local median was applied to exclude any remaining extreme values.

The Local Climate Zones (LCZs) in Table 1.  have been defined for each measurement station following the Global LCZ data (Demuzere 2022a, Demuzere, et al. 2022b) based on the Local Climate Zone (LCZ) Classification system by Stewart and Oke (2012).  

Table Of Contents:  

The descriptions of the measurement stations are in Table 1.  
Columns 
1. Station_code 
2. Station_id 
3. latitude 
4. longitude 
5. elevation above mean se alevel (m) 
6. LCZ_global_point (LCZ at the grid point nearest to the measurement station) 
7. LCZ_global_r200 (Mode of the LCZs within a 200-meter radius around the measurement station) 

The data (hourly Temperature) of each the measurements are in ASCII (tabulator as separator) files Tampere_YEAR.dat, with Celsius as Unit and missing value -999. 
Columns: 
1. Station_code 
2. Timestamp(YMDHH24) UTC 
3. Mean temperature of the previous hour 
4. Minimum temperature of the previous hour 
5. Maximum temperature of the previous hour 
6. Standard deviation of the temperature measurements during the previous hour  
7. Number of measurements during the previous hour (usually 12) 

References: 
Aalto, J., Pirinen, P., & Jylhä, K. (2016). New gridded daily climatology of Finland: Permutation-based uncertainty estimates and temporal trends in climate. Journal of Geophysical Research: Atmospheres, 121(8), 3807–3823. https://doi.org/10.1002/2015JD024651 
Stewart ID, Oke TR. Local Climate Zones for Urban Temperature Studies. Bull Am Meteorol Soc. 2012;93(12):1879-1900. doi:10.1175/BAMS-D-11-00019.1 
Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., van Vliet, J., and Bechtel, B. (2022a): A global map of local climate zones to support earth system modelling and urban-scale environmental science, Earth Syst. Sci. Data, 14, 3835-3873, https://doi.org/10.5194/essd-14-3835-2022. 
Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., van Vliet, J., and Bechtel, B. (2022b): Global map of Local Climate Zones. Zenodo. https://doi.org/10.5281/zenodo.6364593.