webXTREME: a simple web tool for calculating agroclimatic indicators of extreme events

Tommy Klein, Argyrios Samourkasidis, I.N. Athanasiadis, Gianni Bellocchi, Pierluigi Calanca

Research output: Chapter in Book/Report/Conference proceedingAbstract


Extreme events such as frost, drought or excessive heat occurring during a critical plant stage can cause extensive and sometimes irreversible damages to agricultural production. Tools for gauging the occurrence of extreme events can thus play an important role in the context of agricultural decision problems. Agroclimatic indicators offer simple means to discriminate between favourable and unfavourable conditions. Their evaluation can be supported by dedicated software tools, even though this typically requires local installation of the proposed solution. Here we present webXTREME, a new web-based tool to characterize the occurrence and intensity of extreme events in agriculture (available through www.modextreme.org/webxtreme, accessed on 6 April, 2016). Objectives, which motivated its development, were: ease of access (available from any internet-connected device), simple setup, universal compatibility (no installation required), extensibility and the possibility to offer regular updating services. webXTREME was designed to help scientists and practitioners with various backgrounds to configure the solving algorithms by taking into account plant-specific thresholds and relevant time windows during the growing seasons of arable crops, grasslands and woody species. Graphical display of the results enables comparative assessments, either in space or in time. webXTREME was implemented using Shiny, an open-source web application framework for R. This allows combining the computational power of dedicated R functions with modern web technologies. webXTREME can easily be integrated into other modelling platforms (e.g. BioMA, http://bioma.jrc.ec.europa.eu).
Original languageEnglish
Title of host publication8th International Congress on Environmental Modelling and Software
EditorsSabine Sauvage, José-Miguel Sánchez-Pérez, Andrea Emilio Rizzoli
ISBN (Print)9788890357459
Publication statusPublished - 2016


  • extreme events
  • agroclimatic indicators
  • R statistical language
  • Shiny web application framework for R


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