Abstract
In the agricultural domain, decision-making is greatly guided by agricultural meteorology, which is the science that applies knowledge of weather and climate to qualitative and quantitative improvement in agricultural efficiency. The study area is challenged with increasing multifaceted agricultural production risks and complex agricultural ecosystems, which require analysis and understanding of local rainfall and temperature patterns. Digital technologies, such as the automatic weather station, play a pivotal role to monitor the physical environment, successively. This study engaged on a thorough analysis and interpretation of long-term rainfall and temperature data. The results would enable farmers and other users to comprehend valuable knowledge for improved productivity. The objectives of this paper were to analyse long-term climate data for Glen automatic weather station. To determine decadal climate patterns and trends, determine seasonal shifts, climate variability and climate change and quantify the frequency of the occurrence of weather extremes and develop suitable adaptation strategies relating to agronomic, phenological and physiological data necessary for crop modelling, operational evaluation and statistical analysis. The applied methods entailed Microsoft Excel and INSTAT Plus statistical software, which used to detect the interactions of environmental factors and suitable agricultural productivity. Understanding of rainfall and temperature patterns is required for agricultural management decisions, on planting date selection, crop suitability, livestock adaptation, ecosystem conservation. Agro meteorological knowledge derived from meteorological parameters, temperature, rainfall, wind and weather extremes, and may enhance agricultural productivity. Analysis of long-term and decadal trends in the time series indorse a sequence of alternately increasing and decreasing in mean annual rainfall and air temperature in Glen Farm.
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More From: Asian Journal of Advances in Agricultural Research
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