The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

Webb, Mark J.; Andrews, Teresa; Bodas‐Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Hélène; Douville, H.; Good, Phillip I.; Kay, J. E.; Klein, S. A.; Marchand, Roger; Medeiros, Brian; Siebesma, A. P.; Skinner, Christopher B.; Stevens, Björn; Tselioudis, George; Tsushima, Yoko; Watanabe, Mayumi

doi:10.5194/gmd-2016-70

Cited by 68 publications

(84 citation statements)

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“…Klockmann et al, 2016;Brady et al, 2013;Pausata et al, 2011). We also expect analyses of the impacts of these LGM forcings to strongly benefit from diagnostics developed by the Modelling Intercomparison Projects (MIPs) dedicated to these components and processes, such as OMIP for the ocean (Griffies et al, 2016;Orr et al, 2017), SIMIP for sea-ice processes (Notz et al, 2016), LS3MIP for the land surface (van den Hurk et al, 2016), AerChemMIP for dust (Collins et al, 2017), CFMIP for clouds (Webb et al, 2017), and RFMIP for radiative forcing diagnostics (Pincus et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

The PMIP4 contribution to CMIP6 – Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments

et al. 2017

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Abstract. The Last Glacial Maximum (LGM, 21 000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and landsurface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. TheLGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with landsurface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM.

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Section: Introductionmentioning

confidence: 99%

The PMIP4 contribution to CMIP6 – Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments

et al. 2017

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“…Rapid adjustments are also important for many forcing agents including CO 2 . RFMIP requests joint histograms of cloud optical thickness and cloud top pressure from the "ISCCP simulator" (Klein and Jakob, 1999;Webb et al, 2001), part of the CFMIP Observation Simulator Package (Bodas-Salcedo et al, 2011) providing specialized diagnostics for the Cloud Feedback Model Intercomparison Project (CFMIP, see Webb et al, 2016). These will be used to estimate rapid adjustments by clouds using radiative kernels (Zelinka et al, 2012(Zelinka et al, , 2014) that map changes in cloud properties into top-of-atmosphere radiative flux perturbations.…”

Section: Planned Analyses: Effective Radiative Forcingmentioning

confidence: 99%

The Radiative Forcing Model Intercomparison Project (RFMIP): experimental protocol for CMIP6

2016

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Abstract. The phrasing of the first of three questions motivating CMIP6 -"How does the Earth system respond to forcing?" -suggests that forcing is always well-known, yet the radiative forcing to which this question refers has historically been uncertain in coordinated experiments even as understanding of how best to infer radiative forcing has evolved. The Radiative Forcing Model Intercomparison Project (RFMIP) endorsed by CMIP6 seeks to provide a foundation for answering the question through three related activities: (i) accurate characterization of the effective radiative forcing relative to a near-preindustrial baseline and careful diagnosis of the components of this forcing; (ii) assessment of the absolute accuracy of clear-sky radiative transfer parameterizations against reference models on the global scales relevant for climate modeling; and (iii) identification of robust model responses to tightly specified aerosol radiative forcing from 1850 to present.Complete characterization of effective radiative forcing can be accomplished with 180 years (Tier 1) of atmosphereonly simulation using a sea-surface temperature and sea ice concentration climatology derived from the host model's preindustrial control simulation. Assessment of parameterization error requires trivial amounts of computation but the development of small amounts of infrastructure: new, spectrally detailed diagnostic output requested as two snapshots at present-day and preindustrial conditions, and results from the model's radiation code applied to specified atmospheric conditions. The search for robust responses to aerosol changes relies on the CMIP6 specification of anthropogenic aerosol properties; models using this specification can contribute to RFMIP with no additional simulation, while those using a full aerosol model are requested to perform at least one and up to four 165-year coupled ocean-atmosphere simulations at Tier 1.

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“…The experimental designs are shown in Table 2. More details can be found in Chadwick et al [20] and Webb et al [21]. As piSST, with uniform +4K anomaly As piSST piSST4 × CO 2 As piSST The CO 2 is quadrupled compared with piSST, but only seen by the radiation scheme piSSTFuture As piSST, with patterned anomaly from abrupt4 × CO 2 -piControl As piSST piSSTTot As piSSTFuture The CO 2 is quadrupled compared with piSST, and is seen by both the radiation scheme and the plant physiological effect…”

Section: Methodsmentioning

confidence: 99%

Diagnosing Changes of Winter NAO in Response to Different Climate Forcings in a Set of Atmosphere-Only Timeslice Experiments

Ren

Chadwick

et al. 2018

Atmosphere

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Changes of the winter North Atlantic Oscillation (NAO) variability in response to different climate forcings, and their possible causes, are decomposed and investigated using a set of atmosphere-only timeslice experiments forced by sea surface temperature (SST) from coupled runs. The results indicate that the effects of uniform SST warming and direct CO 2 radiative forcing could enhance NAO variability, while SST pattern change could lead to large inter-model difference for model simulations. For the influences of uniform SST warming and the direct CO 2 radiative effect, the most significant air temperature increases occur at mid-low latitudes instead of northern polar regions, which produces a greater meridional temperature gradient at mid-high latitudes, thus leading to enhanced westerly winds according to the thermal wind theory. The effects of uniform SST warming and CO 2 direct radiative forcing could lead to intensification of winter NAO variability, although this result does not consider ocean-atmosphere coupling. The meridional temperature gradient decreases in most areas of the northern Atlantic under the forcing of SST pattern change, but with a larger inter-model uncertainty, which makes the change of winter NAO variability in response to SST pattern change an open issue.

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The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

Abstract: Please refer to the attached pdf for the authors' response. Please also note the supplement to this comment: http://www.geosci-model-dev-discuss.net/gmd-2016-70/gmd-2016-70-AC3-supplement.pdf Interactive comment on Geosci. Model Dev. Discuss.,

Cited by 68 publications

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The PMIP4 contribution to CMIP6 – Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments

The PMIP4 contribution to CMIP6 – Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments

The Radiative Forcing Model Intercomparison Project (RFMIP): experimental protocol for CMIP6

Diagnosing Changes of Winter NAO in Response to Different Climate Forcings in a Set of Atmosphere-Only Timeslice Experiments

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