Climate change is affecting all sectors of human activities worldwide, including crop production. The aim of the paper was to evaluate the average daily air temperatures measured at one hundred meteorological stations across Slovakia in 1961–2010 and calculate the maximum length of the vegetation period for Solanum lycopersicum L., Brassica oleracea L. var. capitata and Daucus carota L. Future trends predictions of the temporal and spatial development across the duration of the vegetation period in Slovakia were elaborated for decades 2011–2020, 2041–2050, 2071–2080 and 2091–2100. Our results show that there was an earlier start to the vegetation period in spring and a later termination in autumn for past 30 years. There is a predicted trend of prolongation of the maximum duration of the vegetation period up to 20 days (Solanum lycopersicum L., Brassica oleracea L. var. capitata) and 15 days (Daucus carota L.) in comparison with the refence decade 2001–2010. The maximum vegetation period duration will extend from the south of Slovakia towards the north of the country. The predicted potential increase in crop vegetation periods will be limited by other constraints such as the availability of arable land and soil water availability.

The global mean near-surface temperature between 2012 and 2021 was 1.11 to 1.14 °C warmer than the pre-industrial level. This makes it the warmest period on record. The aim of this article was to investigate vegetation period changes (onset and termination of the temperature T ≥ 5 °C, T ≥ 10 °C, and T ≥ 15 °C) due to climate change from the average air temperature for the periods 1931–1961, 1961–1991, and 1991–2020 for 24 stations in Slovakia and forecast the length of vegetation periods for the periods 2021–2050, 2051–2080, and 2081–2110. The number of days with these characteristic temperatures was used as an input dataset, from which map outputs were generated in ArcGIS software. Spatial analysis of the vegetation periods in the past, present, and future showed an earlier start of the vegetation period in spring and a later ending in autumn during the last 30 years. The maximum duration of the vegetation period will expand from the south to the north of Slovakia. Future scenarios showed an extension of the vegetation period duration. On the other hand, this potential advantage for crop cultivation is limited by a lack of arable land in the north of Slovakia and by a lack of precipitation in the south of Slovakia.

This paper is focused on the temperature measurements which can detected the influence of temperature changes on the microclimate in animal production building after the installation of photovoltaic (PV) modules. The first series of experiments were performed on a specially designed model cowshed. For the data comparison and verification, the same measurements were realized in real conditions of the animal production object. The temperature balance was identified by measurements of the temperatures in the different parts of roof, PV modules, and the most important were measurements of the ambient temperature and temperatures in three levels of the cowshed interior. For the confirmation of results, measurements were done in two cowsheds, which had the same azimuth orientation and roof slope. The first cowshed was without installation of the PV modules on the roof and the second building had installed PV modules. By the data analyzed from experimentally obtained time-temperature dependencies, it was found that the installation of PV modules on the cowshed roof had a positive influence on the interior temperature balance. The installation of PV also had a positive effect on the cowshed microclimate, which was declared by calculation of the Temperature—Humidity—Index.

Global climate change is likely to influence evapotranspiration (ET); as a result, many ET calculation methods may not give accurate results under different climatic conditions. The main objective of this study is to verify the suitability of machine learning (ML) models as calculation methods for pan evaporation modeling on the macro-regional scale. The most significant PE changes in the different agroclimatic zones of the Slovak Republic were compared, and their considerable impacts were analyzed. On the basis of the agroclimatic zones, 35 meteorological stations distributed across Slovakia were classified into six macro-regions. For each of the meteorological stations, 11 variables were applied during the vegetation period in the years from 2010 to 2020 with a daily time step. The performance of eight different ML models—the neural network (NN) model, the autoneural network (AN) model, the decision tree (DT) model, the Dmine regression (DR) model, the DM neural network (DM NN) model, the gradient boosting (GB) model, the least angle regression (LARS) model, and the ensemble model (EM)—was employed to predict PE. It was found that the different models had diverse prediction accuracies in various geographical locations. In this study, the results of the values predicted by the individual models are compared.

The purpose of the paper was to show cognition from the theory of climate change. The map outputs of these changes offer the climate data from basic elements and characteristics of the energy balance in terms of the current state as well as the trends and assumptions of their future changes in...

An air humidity sensor based on the capacity principle and programmable digital air temperature sensors are designed in the work. The wind direction and wind speed sensor (anemometer) is based on the optoelectronic principle. Sensors register frequency impulses from the wind fan of the anemometer. Methods and materials conformable with modern electronics and informatics were used. The method of linear regression was used for calibration of sensors. The accuracy of an air temperature sensor was found better than 0,1 °C in the range from ‐55 to 125 °C, and an air humidity sensor was better than 1 % in the range from 0 to 98 %. The anemometer works in the range of wind velocity from 0 to 150 km.h⁻¹ with accuracy better than 1 % to 90 km.h⁻¹ and over 90 km/h better than 3 %. First of all these sensors were proposed for automatic weather stations widely used in the sector of agriculture (microclimatic weather stations), industry and for other technological operations where monitoring of temperature, wind speed, wind direction and humidity is required. The sensors will be used as models for educational purposes at the lessons of biometeorology and climatology too. Oro temperatūros ir drėgnio bei vėjo krypties ir greičio matavimo stebėsenos sistemos kūrimas Santrauka Straipsnyje aprašomi sukurtieji oro drėgnio, oro temperatūros bei vėjo krypties ir vėjo greičio (anemometras) jutikliai, pagrįsti optiniu-elektroniniu principu. Jutikliai registruoja anemometro menčių sukeliamus dažnio impulsus. Kuriant įrenginį taikyti nūdienos elektronikos ir informatikos metodai ir medžiagos. Jutikliai kalibruoti remiantis tiesinės regresijos metodu. Nustatytas oro temperatūros jutiklio, matuojant nuo –55 iki 125 ºC, tikslumas buvo didesnis nei 0,1 ºC, o oro drėgnio jutiklio, matuojant nuo 0 iki 98 % , – didesnis nei 1 %. Matavimo anemometru ribos yra nuo 0 iki 150 km/h, tikslumas – didesnis nei 1 %, kai vėjas siekia iki 90 km/h greičio, bei didesnis nei 3 %, kai vėjo greitis viršija 90 km/h. Jutiklius rekomenduota naudoti automatinėse mikroklimatinių sąlygų matavimo stotyse, plačiai taikomose žemės ūkyje, pramonėje bei kitiems tikslams, kai būtini temperatūros, vėjo greičio, vėjo krypties bei drėgnio matavimai. Jutikliai bus naudojami ir švietimo tikslams, dėstant biometeorologiją bei klimatologiją. Reikšminiai žodžiai: oro drėgnio jutiklis, oro temperatūros jutiklis, mikroklimatinių sąlygų nustatymo stotys, vėjo krypties jutiklis, optinis-elektroninis principas. Проектирование и реализация системы мониторинга для измерения температуры воздуха, атмосферной влажности, направления и скорости ветра Резюме Описаны сенсоры атмосферной влажности, температуры воздуха, а также скорости и направления ветра (анемометр), который работает по опто-электронному принципу. Сенсоры фиксируют частные импульсы, создаваемые лопатками анемометра. Для создания аппарата были применены новейшие методы и материалы современной электроники и информатики. Для калибрации сенсоров был использован метод линейной регрессии. Установленная точность сенсора температуры воздуха была больше, чем 0,1 ºC, в пределах от 55 до 125 ºC, а точность сенсора атмосферной влажности была больше, чем 1 %, в пределах от 0 до 98 %. Пределы измерения анемометра составили от 0 до 150 км/ч, точность – больше, чем 1 %, когда скорость не превышала 90 км/ч, и больше, чем 3 %, когда скорость превышала 90 км/ч. Созданные сенсоры рекомендуется использовать в качестве оборудования станций для измерения микроклиматических условий. Такие станции широко используются в сельском хозяйстве, промышленности и для других целей, требующих измерения температуры или влажности воздуха, скорости и направления ветра. Сенсоры будут также использоваться при изучении студентами курсов по биометеорологии и климатологии. Ключевые слова: сенсор атмосферной влажности, сенсор температуры воздуха, станции для измерения микроклиматических условий, сенсор направления ветра, опто-электронный принцип. Firstd Published Online: 14 Oct 2010 Keyword : air humidity sensor, air temperature sensor, weather stations, anemometer, wind direction sensor, optoelectronic principle