English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Climate model emulators have a crucial role in assessingwarming levels of many emission scenarios from probabilistic climateprojections based on new insights into Earth system response to CO2and other forcing factors. This article describes one such tool, MCE, frommodel formulation to application examples associated with a recent modelintercomparison study. The MCE is based on impulse response functions andparameterized physics of effective radiative forcing and carbon uptake overocean and land. Perturbed model parameters for probabilistic projections aregenerated from statistical models and constrained with a Metropolis–Hastingsindependence sampler. Some of the model parameters associated withCO2-induced warming have a covariance structure, as diagnosed fromcomplex climate models of the Coupled Model Intercomparison Project (CMIP).Perturbed ensembles can cover the diversity of CMIP models effectively, andthey can be constrained to agree with several climate indicators such ashistorical warming. The model's simplicity and resulting successfulcalibration imply that a method with less complicated structures and fewercontrol parameters offers advantages when building reasonable perturbedensembles in a transparent way. Experimental results for future scenariosshow distinct differences between CMIP-consistent and observation-consistentensembles, suggesting that perturbed ensembles for scenario assessment needto be properly constrained with new insights into forced response overhistorical periods.

Minimal CMIP Emulator (MCE v1.2): a new simplified method for probabilistic climate projections