Abstract

Abstract. We describe the development, tuning and climate of Planet Simulator (PLASIM)–Grid-ENabled Integrated Earth system model (GENIE), a new intermediate complexity Atmosphere–Ocean General Circulation Model (AOGCM), built by coupling the Planet Simulator to the ocean, sea-ice and land-surface components of the GENIE Earth system model. PLASIM–GENIE supersedes GENIE-2, a coupling of GENIE to the Reading Intermediate General Circulation Model (IGCM). The primitive-equation atmosphere includes chaotic, three-dimensional (3-D) motion and interactive radiation and clouds, and dominates the computational load compared to the relatively simpler frictional-geostrophic ocean, which neglects momentum advection. The model is most appropriate for long-timescale or large ensemble studies where numerical efficiency is prioritised, but lack of data necessitates an internally consistent, coupled calculation of both oceanic and atmospheric fields. A 1000-year simulation with PLASIM–GENIE requires approximately 2 weeks on a single node of a 2.1 GHz AMD 6172 CPU. We demonstrate the tractability of PLASIM–GENIE ensembles by deriving a subjective tuning of the model with a 50-member ensemble of 1000-year simulations. The simulated climate is presented considering (i) global fields of seasonal surface air temperature, precipitation, wind, solar and thermal radiation, with comparisons to reanalysis data; (ii) vegetation carbon, soil moisture and aridity index; and (iii) sea surface temperature, salinity and ocean circulation. Considering its resolution, PLASIM–GENIE reproduces the main features of the climate system well and demonstrates usefulness for a wide range of applications.

Highlights

  • The Grid-ENabled Integrated Earth system model (GENIE; Lenton et al, 2007) has been developed as a modular framework that allows for a spectrum of intermediate complexity Earth system models to be created by selecting different options for the various climate and carbon cycle components

  • We describe the development, tuning and climate of Planet Simulator (PLASIM)–Grid-ENabled Integrated Earth system model (GENIE), a new intermediate complexity Atmosphere–Ocean General Circulation Model (AOGCM), built by coupling the Planet Simulator to the ocean, sea-ice and land-surface components of the GENIE Earth system model

  • We have presented a new intermediate complexity AOGCM PLASIM–GENIE, which reproduces the main features of the climate system well and represents a substantial upgrade to GENIE-1 through the representation of important atmospheric dynamical feedbacks that are absent in an energy–moisture-balance model (EMBM)

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Summary

Introduction

The Grid-ENabled Integrated Earth system model (GENIE; Lenton et al, 2007) has been developed as a modular framework that allows for a spectrum of intermediate complexity Earth system models to be created by selecting different options for the various climate and carbon cycle components. Complementary to GENIE-1, PLASIM has been applied in a range of atmospheric studies, for instance investigating the global entropy budget (Fraedrich and Lunkeit, 2008), double Inter-Tropical Convergence Zone dynamics in an aquaplanet (Dahms et al, 2011), the Permian climate (Roscher et al, 2011) and a snowball Earth (Micheels and Montenari, 2008). PLASIM simulates vastly better climatology than the EMBM of GENIE-1, it lacks dynamic representations of ocean and sea ice (and does not model the carbon cycle), so it too neglects important Earth system feedbacks. The coupled model PLASIM–GENIE has been developed to join the limited number of models that bridge the gap between EMICs with simplified atmospheric dynamics and state of the art Atmosphere–Ocean General Climate Models (AOGCMs). We here demonstrate the tractability of PLASIM– GENIE ensembles by tuning the model with a 50-member ensemble of 1000-year simulations

PLASIM–ENTS
GOLDSTEIN
GOLDSTEINSEAICE
Coupling methodology
Tuning methodology
Ensemble design
Ensemble outputs
SCF and ADRAG
Selection of a subjectively tuned parameter set
Simulated climate of the subjective tuning
Summary and conclusions
Code availability
Full Text
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