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GCM compare R: A web application to assess differences and assist in the selection of general circulation models for climate change research
Author(s) -
Fajardo Javier,
Corcoran Derek,
Roehrdanz Patrick R.,
Hannah Lee,
Marquet Pablo A.
Publication year - 2020
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.13360
Subject(s) - gcm transcription factors , computer science , climate change , downscaling , general circulation model , climate model , selection (genetic algorithm) , range (aeronautics) , relevance (law) , session (web analytics) , climatology , environmental science , data science , machine learning , ecology , political science , law , geology , materials science , world wide web , composite material , biology
Climate change research often relies on downscaled general circulation models (GCM), projections of future scenarios that are used to build ecological and evolutionary models. With more than 35 different GCMs widely available at a resolution of 10 km and finer, standardized methods to understand the differences among GCM projections in a region of interest and to choose which GCM to use for analysis are essential to maximize relevance to policy and to assure a proper treatment of uncertainty. To help researchers and policymakers understand and select form the range of available GCM scenarios, we have developed GCM compare R, an open‐source web application written in r using shiny . GCM compare R is freely accessible with an easy interactive user interface, has preloaded climate scenario data to increase the speed of analysis and is fully documented to ensure reproducibility. Users of the application need no prior experience in coding. GCM compare R is designed to compare GCMs and different climate change scenarios to provide full, documented exploration of the possible alternative futures from within the range of projections in CMIP5 climate models. Designed with a wide group of users in mind, including ecologists, conservationists and policymakers, the application is designed to adapt analyses to any geographic area of interest. Results are provided as figures, tables and maps that clearly communicate the differences among model projections for the region. Additionally, the tool allows for the export of a report that records the parameter choices and results of a session, along with contextual information, to make the analysis fully transparent and replicable.