Scientific publications

Identifying Crop and Orchard Growing Stages Using Conventional Temperature and Humidity Reports

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


Stevan Savic, Ivan Šecerov, Branislava Lalic, Dongyun Nie,
Mark Roantree

Vegetation is a climate modifier: It is a primary modifier, such as the Amazon rain forest, or secondary modifier, such as the agricultural fields of Pannonian lowlands in Central Europe. At periods of winter crop spring renewal and the start of the orchard growing season, enhanced evapotranspiration shifts energy balance partitions from sensible toward latent heat flux. This surface flux alteration converges into the boundary layer, and it can be detected in the daily variations of air temperature and humidity as well as daily temperature range records. The time series of micrometeorological measurements and phenological observations in dominant plant canopies conducted by Forecasting and Reporting Service for Plant Protection of the Republic of Serbia (PIS) are explored to select indices that best record the signatures of plant growth stages in temperature and humidity daily variations. From the timing of extreme values and inflection points of relative humidity (R1 and R2) and normalized daily temperature range (DTR/Td), we identified the following stages: (a) start of flowering (orchard)/spring start of the growing season (crop), (b) full bloom (orchard)/development (crop), (c) maximum LAI reached/yield formation (orchard and crop), and (d) start of dormancy (orchard)/leaf drying (crop). The average day of year (DOY) for dominant plants corresponds to the timing obtained from climatological time series recorded on a representative climate station.

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 T
a 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 T
a 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 intraurban 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 

Atmosphere 202213, 700

Data in Brief 49 (2023) 109425