Lower-Tropospheric Mixing as a Constraint on Cloud Feedback in a Multiparameter Multiphysics Ensemble

Kamae, Youichi; Shiogama, Hideo; Ogura, Tomoo; Yokohata, Tokuta; Kimoto, Masahide

doi:10.1175/jcli-d-16-0042.1

Cited by 25 publications

(38 citation statements)

References 65 publications

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“…Previous studies indicate that simulated strength of convective mixing between the lower and middle tropical troposphere is related to cloud feedback and climate sensitivity in multi-model ensembles (Sherwood et al, 2014;Kamae et al, 2016). The results suggest that shallow convective mixing contributes to inter-model spread in climate sensitivity, which causes difficulty in assessing the impact of climate change.…”

Section: Discussionmentioning

confidence: 87%

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

et al. 2017

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Abstract. This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere-ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitudelongitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

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Section: Discussionmentioning

confidence: 87%

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

et al. 2017

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“…They developed PPEs based on the eight MPE models and examined the uncertainty in cloud feedback and ECS. Figure 3 shows the shortwave cloud feedback in the MPMPE (Kamae et al 2016b) evaluated using the International Satellite Cloud Climatology Project (ISCCP) simulator (Klein and Jakob 1999;Webb et al 2001) implemented in the models and ISCCP cloud radiative kernel (Zelinka et al 2012a). Estimated feedbacks were generally consistent with estimates (difference in all-sky and clear-sky TOA radiation) of Shiogama et al (2014).…”

Section: Structural and Parametric Uncertainty In Low Cloud Feedbackmentioning

confidence: 71%

“…Compared with MIROC5A with a large negative shortwave cloud feedback and a low ECS, models with swapped physics schemes (cloud, convection, and turbulence) to older ones generally show larger cloud feedback and higher ECS (Table 2; Fig. 3; Watanabe et al 2012b;Shiogama et al 2014;Kamae et al 2016b). The difference in the shortwave cloud feedback among the eight MPE models can largely be attributed to spreads in low cloud and middle cloud feedback over the tropical ocean (Watanabe et al 2012b).…”

Section: Structural and Parametric Uncertainty In Low Cloud Feedbackmentioning

confidence: 97%

“…It is needed to examine the physical processes determining total cloud feedback and its components (fractional coverage, clout top height, and optical depth) including low cloud feedback in the multiple PPEs. However, it has not been clarified why different PPEs show different parameter sensitivity of low and middle cloud feedback (Shiogama et al 2014;Kamae et al 2016b). Swapping physics schemes like cumulus convection may result in a different behavior of cloud in a control climate and its change in a perturbed climate (Watanabe et al 2012b).…”

Section: Structural and Parametric Uncertainty In Low Cloud Feedbackmentioning

confidence: 99%

“…Swapping physics schemes like cumulus convection may result in a different behavior of cloud in a control climate and its change in a perturbed climate (Watanabe et al 2012b). Kamae et al (2016b) applied the observational constraint of low cloud feedback (LTM) to the MPMPE and concluded that LTM is effective to constrain the uncertainty in low cloud feedback, but is not applicable to total cloud feedback and ECS, at least for a part of PPEs. The physical reasons for the differences in the LTM-ECS relationship among different ensembles are still unclear.…”

Section: Structural and Parametric Uncertainty In Low Cloud Feedbackmentioning

confidence: 99%

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Recent progress toward reducing the uncertainty in tropical low cloud feedback and climate sensitivity: a review

2016

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Equilibrium climate sensitivity (ECS) to doubling of atmospheric CO 2 concentration is a key index for understanding the Earth's climate history and prediction of future climate changes. Tropical low cloud feedback, the predominant factor for uncertainty in modeled ECS, diverges both in sign and magnitude among climate models. Despite its importance, the uncertainty in ECS and low cloud feedback remains a challenge. Recently, researches based on observations and climate models have demonstrated a possibility that the tropical low cloud feedback in a perturbed climate can be constrained by the observed relationship between cloud, sea surface temperature and atmospheric dynamic and thermodynamic structures. The observational constraint on the tropical low cloud feedback suggests a higher ECS range than raw range obtained from climate model simulations. In addition, newly devised modeling frameworks that address both spreads among different model structures and parameter settings have contributed to evaluate possible ranges of the uncertainty in ECS and low cloud feedback. Further observational and modeling approaches and their combinations may help to advance toward dispelling the clouds of uncertainty.

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Coupling between lower‐tropospheric convective mixing and low‐level clouds: Physical mechanisms and dependence on convection scheme

Vial

Bony

Dufresne

et al. 2016

J Adv Model Earth Syst

134

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Several studies have pointed out the dependence of low‐cloud feedbacks on the strength of the lower‐tropospheric convective mixing. By analyzing a series of single‐column model experiments run by a climate model using two different convective parametrizations, this study elucidates the physical mechanisms through which marine boundary‐layer clouds depend on this mixing in the present‐day climate and under surface warming. An increased lower‐tropospheric convective mixing leads to a reduction of low‐cloud fraction. However, the rate of decrease strongly depends on how the surface latent heat flux couples to the convective mixing and to boundary‐layer cloud radiative effects: (i) on the one hand, the latent heat flux is enhanced by the lower‐tropospheric drying induced by the convective mixing, which damps the reduction of the low‐cloud fraction, (ii) on the other hand, the latent heat flux is reduced as the lower troposphere stabilizes under the effect of reduced low‐cloud radiative cooling, which enhances the reduction of the low‐cloud fraction. The relative importance of these two different processes depends on the closure of the convective parameterization. The convective scheme that favors the coupling between latent heat flux and low‐cloud radiative cooling exhibits a stronger sensitivity of low‐clouds to convective mixing in the present‐day climate, and a stronger low‐cloud feedback in response to surface warming. In this model, the low‐cloud feedback is stronger when the present‐day convective mixing is weaker and when present‐day clouds are shallower and more radiatively active. The implications of these insights for constraining the strength of low‐cloud feedbacks observationally is discussed.

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Lower-Tropospheric Mixing as a Constraint on Cloud Feedback in a Multiparameter Multiphysics Ensemble

Cited by 25 publications

References 65 publications

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

Recent progress toward reducing the uncertainty in tropical low cloud feedback and climate sensitivity: a review

Coupling between lower‐tropospheric convective mixing and low‐level clouds: Physical mechanisms and dependence on convection scheme

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