Micro-climatic temperature measurements in the Finnish city of Rovaniemi

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, Helsinki and Rovaniemi" by Kühn et al. (in preparation) of 12 measurement stations in Rovaniemi.

Technical Info:
NB: update on 4.12.2025, file Rovaniemi_202511.dat added.

The measurements were conducted at a height of 3 m in the locations listed in Rovaniemi_Table1.txt during 3.6.2025-30.11.2025. 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 Rovaniemi_Table1_New. 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 Rovaniemi_Table1.txt.
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 Rovaniemi_YearMonth.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.

本数据集包含库恩（Kühn）等（撰写中）的论文《芬兰坦佩雷、赫尔辛基和罗瓦涅米市微气候温度与相对湿度实时测量》中，罗瓦涅米地区12个气象站的气温测量数据。

技术说明：
备注：2025年12月4日更新，新增文件Rovaniemi_202511.dat。
测量于2025年6月3日至2025年11月30日期间，在Rovaniemi_Table1.txt中列出的点位开展，测量高度为3米。每个测量站由三部分组成：温湿度传感器、太阳辐射屏蔽罩，以及物联网（Internet of Things, IoT）设备，后者负责采集测量数据并通过长距离广域网（Long Range Wide Area Network, LoRaWAN）将数据传输至服务器。

温湿度由集成传感器Digital Matter I2C温湿度传感器[https://www.digitalmatter.com/wp-content/uploads/2020/09/I2C-Temperature-and-Humidity-Sensor-Datasheet.pdf]完成，该传感器内置Silicon Labs Si7021-A20 I2C温湿度传感器芯片。该芯片已完成工厂校准，工作量程为相对湿度0%~100%、温度-40℃~+125℃。当环境温度处于-10℃~85℃区间时，温度测量精度最高可达±0.4℃；当环境相对湿度处于0%~80%区间时，相对湿度测量精度最高可达±3%。

温湿度传感器配备辐射屏蔽罩以降低直射阳光与热辐射对测量的干扰。该屏蔽罩高11.5cm，半径14cm，采用白色塑料制成，由9片通风板以圆柱结构堆叠而成，既可保证空气流通，又能为传感器屏蔽外部辐射。

质量校验
气温数据通过多步骤流程开展质量控制：首先基于坦佩雷地区10km×10km分辨率格点气温数据（Aalto等，2016）得到长期气候学逐日最高、最低气温阈值，筛除明显超出该气候学范围的测量值；随后基于测量统计特性进行过滤，通过短时区间内的中位数与中位数绝对偏差（median absolute deviation, MAD）识别并剔除异常值；最后基于与局部中位数的偏差设置最终阈值，排除剩余极端值。

本数据集已根据Stewart与Oke（2012）提出的本地气候区（Local Climate Zone, LCZ）分类体系，结合全球LCZ数据（Demuzere, 2022a; Demuzere等, 2022b），为Rovaniemi_Table1_New.txt中每个测量站定义了对应的本地气候区。

数据说明
测量站的详细信息存储于Rovaniemi_Table1.txt，各列含义如下：
1. 站点代码（Station_code）
2. 站点ID（Station_id）
3. 纬度（latitude）
4. 经度（longitude）
5. 海拔高度（米，elevation above mean sea level (m)）
6. 格点最近点本地气候区（LCZ_global_point，即测量站最近格点对应的LCZ）
7. 200米半径范围内本地气候区众数（LCZ_global_r200，即测量站周边200米半径内LCZ的众数）

各测量站的逐小时气温数据存储于以Rovaniemi_YearMonth.dat命名的ASCII分隔文件中，制表符为分隔符，单位为摄氏度，缺失值标记为-999。各列含义如下：
1. 站点代码（Station_code）
2. 时间戳（UTC格式，格式为YMDHH24，Timestamp(YMDHH24) UTC）
3. 前一小时平均气温（Mean temperature of the previous hour）
4. 前一小时最低气温（Minimum temperature of the previous hour）
5. 前一小时最高气温（Maximum temperature of the previous hour）
6. 前一小时气温测量值的标准差（Standard deviation of the temperature measurements during the previous hour）
7. 前一小时的有效测量次数（通常为12次，Number of measurements during the previous hour (usually 12)）

参考文献
1. 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
2. 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
3. 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.
4. 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.