A Representative Democracy to Reduce Interdependency in a Multimodel Ensemble

By B. Sanderson, Reto Knutti, Peter M. Caldwell. 2015

348 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/30c679c9c037cad0716b0bac023d1c7136a38591

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Citations in the corpus

Vegetation demographics in Earth System Models: A review of progress and priorities (2018, background): “Rather, until relevant data and knowledge gaps are filled through concerted empirical and model-based research, we expect that an ensemble of techniques will allow for more robust predictions of likely trajectories of vegetation structural changes, their impacts on biogeochemistry and climate feedba”
Reduced global warming from CMIP6 projections when weighting models by performance and independence (2020, methodology): “In the past, combinations of horizontally-resolved regional temperature, precipitation, and sea level pressure fields, have typically been used (e.g., Knutti et al., 2013; Sanderson et al., 2017; Boé, 2018; Lorenz et al., 2018; Brunner et al., 2019).”
Causes of Higher Climate Sensitivity in CMIP6 Models (2020, background): “Despite the fact that models from different centers may also be related (Knutti et al., 2013; Sanderson et al., 2015), we use this approach because accurately defining model independence is still an area of ongoing research and the required machinery would distract from the focus of this work.”
Skill and independence weighting for multi-model assessments (2016, methodology): “110 Our methodology is based on the concepts outlined by Sanderson et al (2015) 111 [7], a comparatively simple method for sub-sampling models the original archive, 112 keeping models which were maximally independent and skillful in reproducing 113 past climate.”
Evaluating Emergent Constraints on Equilibrium Climate Sensitivity (2018, background): “Both of these approaches typically assume that each model is an independent sample, but Sanderson et al. (2015) note that a quarter to a half of the CMIP5 models they analyzed were functionally redundant.”
Emergent constraints on equilibrium climate sensitivity in CMIP5: do they hold for CMIP6? (2020, methodology): “Duplicated code in multiple models is expected to lead to an overestimation of the sample size of a model ensemble and may result in spurious correlations (Sanderson et al., 2015). Possible approaches could be to stop treating all models 140 equally by either applying a model weighting based on a mo”
Protected areas network is not adequate to protect a critically endangered East Africa Chelonian: Modelling distribution of pancake tortoise, Malacochersus tornieri under current and future climates (2020, methodology): “Future scenarios’ uncertainty were also accessed through ten Global Circulation Models (GCMs) available in CHELSA; we avoided those with high co-dependency [61], resulting in the selection of MIROC5, CESM1-CAM5, IPSL-CM5A-MR, FIO-ESM, GISS-E2-H, CSIRO-Mk3-6-0, GISS-E2-R, GFDL-ESM2G, MIROC-ESM-CHEM a”