Abstract
The analysis of climate data is tedious and time-consuming, delaying the analysis of millions of meteorological data worldwide. Local level decision making about climate change requires converting data into information. The aim was to develop software to analyze thousands of meteorological data in seconds. We first designed the database, selected the statistical tests used in time series analyses, and chose agroclimatic indexes, before designing the algorithms. Finally, we developed the software having in mind its easiness of use, and its efficiency for processing data and interpreting results. The software was tested several times by potential users, which allowed improvements in the development and design of the software. Clic-MD includes a set of routines for calculating derived variables most used in land evaluation such as agroclimatic indices, probability of rainfall by month, and others. Clic-MD allows for identifying climate change trends (climate anomalies and extreme events).
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