GCM compareR GCM compareR is a web application developed to assist ecologists, conservationists and policy makers at understanding climate change scenarios and differences between Global Circulation Models (GCMs), and at assisting the triage of subsets of models in an objective and informed manner. GCM compareR is written in R and uses the web app development package shiny. The code of this app can be find in the project's github, https://github.com/marquetlab/GCM_compareR. The number of GCMs that are accessible to researchers and practitioners has grown large. Concretely, meteorological research centers worldwide have contributed more than 35 different GCMs for four distinct climate change scenarios as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5; (Taylor, Stouffer, and Meehl 2012)). All these models have shown good performance and skill in predicting historical climatic data, but present differences among them as a result of different sources of uncertainty (including model formulation, resolution and sensitivity to initial conditions, climate noise; (Flato et al. 2013)). GCMs could be ranked by their skill at specific geographic areas, but models that most accurately predict historic data are not necessarily the most useful for making future climate projections (Knutti 2008). In practice, best practices when conducting any evaluation advice for using multi-model approaches where differences in GCMs projections are adequantely understood and assessed as uncertainty (Pierce et al. 2009, Flato et al. (2013)). Also, and even though the ideal case would use all available GCMs, researchers are often forced to work with a few selected models for computational restrictions (Barsugli et al. 2013). However, the choice of some GCMs and not other has the potential to influence results (Synes and Osborne 2011), and thus it should be made following informed and replicable procedures (P. Mote et al. 2011, Snover et al. (2013), Vano et al. (2015)). GCM compareR has been design to serve the purpose of informing about differences and similarities between GCMs and climate change scenarios, and of assisting the triage of models that best suit every used needs.