Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6)  experimental design and organization

Eyring, Veronika; Bony, Sandrine; Meehl, Gerald A.; Senior, C. A.; Stevens, Björn; Stouffer, Ronald J.; Taylor, Karl E.

doi:10.5194/gmd-9-1937-2016

Cited by 7,628 publications

(6,768 citation statements)

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“…The CMIP6 solar forcing dataset described in this paper and the metadata description have been published at http://solarisheppa.geomar.de/cmip6 and linked to the Earth System Grid Federation (ESGF), https://esgf-node.llnl.gov/projects/ input4mips/, with version control and digital objective identifiers (DOIs) assigned. An overview of the CMIP6 Special Issue can be found in Eyring et al (2016).…”

Section: Solar Ozone Forcingmentioning

confidence: 99%

“…An atmospheric ionization dataset has been calculated based on the Ap-based precipitation model, using a computationally fast ionization parameterization (Fang et al, 2010) and atmospheric composition from the NRLMSISE-00 model (Picone et al, 2002). This calculation considered MEE (30-1000 keV) with maximum energy deposition at altitudes between about 60 and 90 km (van de Kamp et al, 2016).…”

Section: Mid-energy Electrons (Mees) From the Radiation Beltsmentioning

confidence: 99%

“…Auroral electrons originate from the Earth's magnetosphere, and are accelerated to energies of 1-30 keV during auroral substorms (Fang et al, 2008). Sudden enhancements of their flux occur during geomagnetic active periods, which are more frequent 1-2 years after the peak of the 11-year solar cycle.…”

Section: Introductionmentioning

confidence: 99%

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Solar forcing for CMIP6 (v3.2)

et al. 2017

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Abstract. This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with respect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7 index as well as particle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, electrons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850CMIP6 preindustrial control, historical ( -2014, and future (2015-2300) simulations. For the preindustrial control simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunderminimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.For the historical simulations, the TSI and SSI time series are defined as the average of two solar irradiance models that are adapted to CMIP6 needs: an empirical onePublished by Copernicus Publications on behalf of the European Geosciences Union. A new and lower TSI value is recommended: the contemporary solar-cycle average is now 1361.0 W m −2 . The slight negative trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only a small global radiative forcing of −0.04 W m −2 . In the 200-400 nm wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 % compared to 35 %).We compare the climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using timeslice experiments of two chemistry-climate models and a reference radiative transfer model. The differences in the long-term mean SSI in the CMIP6 dataset, compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates of −0.35 K day −1 at the stratopause), cooler stratospheric temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (−3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K day −1 at the stratopause), temperatures (∼ 1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar-cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset.CMIP6 models wi...

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Section: Solar Ozone Forcingmentioning

confidence: 99%

Section: Mid-energy Electrons (Mees) From the Radiation Beltsmentioning

confidence: 99%

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Solar forcing for CMIP6 (v3.2)

et al. 2017

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“…A new version of the EC-Earth model is currently under development that will use the aerosol number and mass concentrations from TM5 to calculate cloud activation in IFS. This representation will be used for the Aerosol Chemistry Model Intercomparison Project (AerChemMIP; Collins et al, 2017) as part of the WCRP Coupled Model Intercomparison Project phase 6 (CMIP6; Eyring et al, 2016). Although computationally demanding, the inclusion of spectral (bin) microphysics might be necessary to achieve a level of detail necessary to determine the impact of clouds on the characteristics of aerosol size distributions.…”

Section: Resultsmentioning

confidence: 99%

The impact of precipitation evaporation on the atmospheric aerosol distribution in EC-Earth v3.2.0

et al. 2018

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Abstract. The representation of aerosol-cloud interaction in global climate models (GCMs) remains a large source of uncertainty in climate projections. Due to its complexity, precipitation evaporation is either ignored or taken into account in a simplified manner in GCMs. This research explores various ways to treat aerosol resuspension and determines the possible impact of precipitation evaporation and subsequent aerosol resuspension on global aerosol burdens and distribution. The representation of aerosol wet deposition by large-scale precipitation in the EC-Earth model has been improved by utilising additional precipitation-related 3-D fields from the dynamical core, the Integrated Forecasting System (IFS) general circulation model, in the chemistry and aerosol module Tracer Model, version 5 (TM5). A simple approach of scaling aerosol release with evaporated precipitation fraction leads to an increase in the global aerosol burden (+7.8 to +15 % for different aerosol species). However, when taking into account the different sizes and evaporation rate of raindrops following , the release of aerosols is strongly reduced, and the total aerosol burden decreases by −3.0 to −8.5 %. Moreover, inclusion of cloud processing based on observations by Mitra et al. (1992) transforms scavenged small aerosol to coarse particles, which enhances removal by sedimentation and hence leads to a −10 to −11 % lower aerosol burden. Finally, when these two effects are combined, the global aerosol burden decreases by −11 to −19 %. Compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, aerosol optical depth (AOD) is generally underestimated in most parts of the world in all configurations of the TM5 model and although the representation is now physically more realistic, global AOD shows no large improvements in spatial patterns. Similarly, the agreement of the vertical profile with CloudAerosol Lidar with Orthogonal Polarization (CALIOP) satellite measurements does not improve significantly. We show, however, that aerosol resuspension has a considerable impact on the modelled aerosol distribution and needs to be taken into account.

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“…An accurate representation of stratospheric ozone in climate models is therefore essential if they are to be used to project realistic future climate behavior (e.g., Nowack et al, 2015). While many climate models calculate stratospheric ozone distributions with a fully coupled stratospheric chemistry scheme, Eyring et al (2016) reported that not all models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) will have that ability and therefore need to prescribe atmospheric ozone concentrations. This requires a long-term, latitudinally and vertically resolved ozone database.…”

Section: Introductionmentioning

confidence: 99%

An updated version of a gap-free monthly mean zonal mean ozone database

Haßler

Kremser

Bodeker

et al. 2018

Earth Syst. Sci. Data

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Abstract. An updated and improved version of a global, vertically resolved, monthly mean zonal mean ozone database has been calculated -hereafter referred to as the BSVertOzone (Bodeker Scientific Vertical Ozone) database. Like its predecessor, it combines measurements from several satellite-based instruments and ozone profile measurements from the global ozonesonde network. Monthly mean zonal mean ozone concentrations in mixing ratio and number density are provided in 5 • latitude bins, spanning 70 altitude levels (1 to 70 km), or 70 pressure levels that are approximately 1 km apart (878.4 to 0.046 hPa). Different data sets or "tiers" are provided: Tier 0 is based only on the available measurements and therefore does not completely cover the whole globe or the full vertical range uniformly; the Tier 0.5 monthly mean zonal means are calculated as a filled version of the Tier 0 database where missing monthly mean zonal mean values are estimated from correlations against a total column ozone (TCO) database. The Tier 0.5 data set includes the full range of measurement variability and is created as an intermediate step for the calculation of the Tier 1 data where a least squares regression model is used to attribute variability to various known forcing factors for ozone. Regression model fit coefficients are expanded in Fourier series and Legendre polynomials (to account for seasonality and latitudinal structure, respectively). Four different combinations of contributions from selected regression model basis functions result in four different Tier 1 data sets that can be used for comparisons with chemistry-climate model (CCM) simulations that do not exhibit the same unforced variability as reality (unless they are nudged towards reanalyses). Compared to previous versions of the database, this update includes additional satellite data sources and ozonesonde measurements to extend the database period to 2016. Additional improvements over the previous version of the database include the following: (i) adjustments of measurements to account for biases and drifts between different data sources (using a chemistry-transport model, CTM, simulation as a transfer standard), (ii) a more objective way to determine the optimum number of Fourier and Legendre expansions for the basis function fit coefficients, and (iii) the derivation of methodological and measurement uncertainties on each database value are traced through all data modification steps. Comparisons with the ozone database from SWOOSH (Stratospheric Water and OzOne Satellite Homogenized data set) show good agreement in many regions of the globe. Minor differences are caused by different bias adjustment procedures for the two databases. However, compared to SWOOSH, BSVertOzone additionally covers the troposphere. Version 1.0 of BSVertOzone is publicly available at https://doi.org/http://doi.org/10

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Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization

Cited by 7,628 publications

References 40 publications

Solar forcing for CMIP6 (v3.2)

Solar forcing for CMIP6 (v3.2)

The impact of precipitation evaporation on the atmospheric aerosol distribution in EC-Earth v3.2.0

An updated version of a gap-free monthly mean zonal mean ozone database

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