Collaborative Distributed Evaluation System for Earth System Models

Institute

AS-RCEC

Research Center for Environmental Changes, Taiwan, China

AWI

Alfred Wegener Institute, Germany

BCC

Beijing Climate Center, China

CAMS

Chinese Academy of Meteorological Sciences, China

CAS

Chinese Academy of Science, China

CCCma

Canadian Centre for Climate Modelling and Analysis, Canada

CMCC

Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici,Italy

CNRM-CERFACS

Centre National de Recherches Meteorologiques,France

CSIRO

Commonwealth Scientific and Industrial Research Organisation, Australia

CSIRO-ARCCSS

CSIRO-Australian Research Council Centre of Excellence for Climate System Science

E3SM-Project

Lawrence Livermore National Laboratory, USA. (and other institutions)

EC-Earth-Consortium

30 research institutes from 12 European countries

FIO-QLNM

First Institute of Oceanography, Qingdao National Laboratory for Marine Science and Technology, China

INM

Institute for Numerical Mathematics, Russia

IPSL

Institut Pierre Simon Laplace, France

KIOST

Korea Institute of Ocean Science and Technology, Republic of Korea

MIROC

Japan Agency for Marine-Earth Science and Technology (and other 3 institutes), Japan

MOHC

Met Office Hadley Centre, UK

MPI-M

Max Planck Institute for Meteorology, Germany

MRI

Meteorological Research Institute, Japan

NASA-GISS

Goddard Institute for Space Studies, USA

NCAR

National Center for Atmospheric Research, USA

NCC

NorESM Climate modeling Consortium consisting of CICERO (and other 6 institutes), Norway

NIMS-KMA

National Institute of Meteorological Sciences/Korea Meteorological Administration, Republic of Korea

NOAA-GFDL

National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, USA

NUIST

Nanjing University of Information Science and Technology, China

SNU

Seoul National University, Republic of Korea

THU

Department of Earth System Science, Tsinghua University, China

UA

Department of Geosciences, University of Arizona, USA

Experiment

Historical (1850-2014)

It aims to simulate the Earth system from the mid-19th century to the present day using observed historical changes in greenhouse gas concentrations, aerosols, solar radiation, and volcanic activity as external forcing.

amip (1979-2014)

It represents the Atmospheric Model Intercomparison Project (AMIP), used to evaluate the performance of atmospheric models in simulating the climate system without feedbacks from the rest of the Earth system.

1pctCO₂ (150 years)

A 1% per year increase in atmospheric CO₂ concentration starting from preindustrial levels (year 0) until CO₂ concentrations reach double the preindustrial level (~ year 70). After that, CO₂ concentrations are held constant at the doubled level until year 150.

piControl (500 years)

It represents the “preindustrial control” experiment, with greenhouse gas concentrations and other forcings held constant at preindustrial levels. It is used as a baseline for comparing the effects of different forcings in other experiments, and for studying the natural variability of the Earth's climate system.

abrupt-4xCO₂ (150 years)

This experiment involves an instantaneous quadrupling of atmospheric CO₂ concentrations from preindustrial levels, followed by a 150-year simulation period to study the climate response to a large, rapid increase in greenhouse gas concentrations.

ssp126 (2015-2100)

This Shared Socioeconomic Pathways (SSP) experiment represents a future scenario with low greenhouse gas emissions (the forcing levels of 2.6 W/m²), consistent with a future world with a high level of sustainability and focus on reducing greenhouse gas emissions.

ssp245 (2015-2100)

This SSP experiment represents a future scenario with medium greenhouse gas emissions (the forcing levels of 4.5 W/m²), consistent with a future world with intermediate levels of sustainability and moderate reductions in greenhouse gas emissions.

ssp370 (2015-2100)

This SSP experiment represents a future scenario with high greenhouse gas emissions (the forcing levels of 7.0 W/m²), consistent with a future world with low levels of sustainability and no or little reduction in greenhouse gas emissions.

ssp585 (2015-2100)

This SSP experiment represents a future scenario with very high greenhouse gas emissions (the forcing levels of 8.5 W/m²), consistent with a future world with low levels of sustainability and no or little reduction in greenhouse gas emissions.

Variable Group

Variable groups are used to organize the many variables that are simulated by the models participating in CMIP6. The variable groups are named according to a standardized naming convention that includes a prefix and a suffix. The prefix indicates the variable type, while the suffix indicates the frequency of the data (e.g., monthly, daily, etc.).

AERmon

Monthly mean atmospheric aerosol variables.

AERmonZ

Monthly mean atmospheric aerosol variables as in AERmon, but with vertical resolution included.

Amon

Monthly mean atmospheric variables.

Emon

Monthly mean variables related to the Earth's energy budget.

ImonAnt

Monthly mean variables related to the Antarctic sea ice.

ImonGre

Monthly mean variables related to the Greenland ice sheet.

LImon

Monthly mean variables related to the land surface with vertical resolution included.

Lmon

Monthly mean variables related to the land surface.

SImon

Seasonal mean variables related to the sea ice.

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