Meteorological automated weather station data application for plant water requirements estimation

In order to adequately control water requirements for plants, it is necessary to perform continuous standardized meteorological conditions measurements from the largest possible number of points. This is possible by automated measurements which lead to an increase in the number of records and their immediate accessibility. Automatic stations provide a large amount of data; however, in comparison to standard stations, they do not obey the existing standard procedures. This particularly applies to the comparability of instruments and, to some extent, the time of measurements. Similarly, other differences include data processing procedures; hence a risk of results others than the standard ones. The observations of plant water requirements are based on the results of agrometeorological indices, mostly on the precipitation measurements. The aim of this research was a comparison of the selected agrometeorological indices essential in agriculture (precipitation, reference evapotranspiration, climatic water balance and standardized precipitation index), measured or calculated in the growing season (from April to September) at standard and automatic weather stations and a verification whether the automated station data can be applied without any modifications whatsoever. The investigation was drawing on the data collected between 2000 and 2004 in the Kuyavia region, central Poland. The focus of the research was the interaction between the data series compared. Searching for the ways to adjust the automated to standard 10-day growing season data was an important aspect of the investigation. Despite the different measurement results between both stations compared, great correlation coefficients of the results facilitated the development of mathematical formulas to allow for the use of the automated data series instead of standard records.

• The use of automatic data instead of standard could affect the climate data recorded.
• We compared indices records calculated at standard and automatic stations.
• We verified whether the automated station data can be applied without any modifications.