On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Webb, Mark J.; Senior, C. A.; Sexton, David M. H.; Ingram, William; Williams, Keith D.; Ringer, Mark A.; McAvaney, B. J.; Colman, Robert; Soden, Brian J.; Gudgel, R.; Knutson, Thomas R.; Emori, Seita; Ogura, Tomoo; Tsushima, Yoko; Andronova, Natalia; Li, B.; Musat, Ionela; Bony, Sandrine; Taylor, Karl E.

doi:10.1007/s00382-006-0111-2

Cited by 357 publications

(325 citation statements)

References 48 publications

Supporting

Mentioning

306

Contrasting

Unclassified

Order By: Relevance

“…We computed the contributions of each component to the total feedback variance by applying the following method (Boer and Yu 2003b;Webb et al 2006;Williams and Webb 2009;Yokohata et al 2010;Yoshimori et al 2011): Fig. 6 The red squares represent a scatter plot of radiative forcing (W/m 2 ; horizontal axis) and feedback parameters (W/m 2 /K; vertical axis); the red line represents their total least-squares regression.…”

Section: Sw Cloud Feedbackmentioning

confidence: 99%

“…9a). Here we broke down the global mean feedback to the local feedback by regressing the local radiation (and other Webb et al 2006). We compared the spatial pattern of the SWcld feedback with the patterns of the cloud albedo changes (Fig.…”

Section: Sw Cloud Feedbackmentioning

confidence: 99%

“…The present climate biases and future climate changes in a single model may be sensitive to changes in parameter values in the model physical schemes (Murphy et al 2004). The Met Office Hadley Centre's project ''Quantifying Uncertainty of Model Predictions'' (QUMP) and http://climateprediction.net are the first and most comprehensive projects to investigate the parametric uncertainties of climate responses to external forcing (Murphy et al 2004(Murphy et al , 2007Stainforth et al 2005;Webb et al 2006;Collins et al 2006Collins et al , 2007Collins et al , 2011Brierley et al 2010;Jackson et al 2011). These investigators constructed several perturbed physics ensembles (PPEs) in which they swept uncertain parameters within the HadCM3 model (Gordon et al 2000).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Perturbed physics ensemble using the MIROC5 coupled atmosphere–ocean GCM without flux corrections: experimental design and results

et al. 2012

View full text Add to dashboard Cite

In this study, we constructed a perturbed physics ensemble (PPE) for the MIROC5 coupled atmosphere-ocean general circulation model (CGCM) to investigate the parametric uncertainty of climate sensitivity (CS). Previous studies of PPEs have mainly used the atmosphere-slab ocean models. A few PPE studies using a CGCM applied flux corrections, because perturbations in parameters can lead to large radiation imbalances at the top of the atmosphere and climate drifts. We developed a method to prevent climate drifts in PPE experiments using the MIROC5 CGCM without flux corrections. We simultaneously swept 10 parameters in atmosphere and surface schemes. The range of CS (estimated from our 35 ensemble members) was not wide (2.2-3.2°C). The shortwave cloud feedback related to changes in middle-level cloud albedo dominated the variations in the total feedback. We found three performance metrics for the present climate simulations of middle-level cloud albedo, precipitation, and ENSO amplitude that systematically relate to the variations in shortwave cloud feedback in this PPE.

show abstract

Section: Sw Cloud Feedbackmentioning

confidence: 99%

Section: Sw Cloud Feedbackmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Perturbed physics ensemble using the MIROC5 coupled atmosphere–ocean GCM without flux corrections: experimental design and results

et al. 2012

View full text Add to dashboard Cite

show abstract

“…These are highly uncertain and are key to producing the range of global temperature sensitivities to forcing seen in GCMs [Webb et al, 2006]. However, most solar radiation is either absorbed by the surface or refl ected back to space.…”

Section: Understanding Precipitation Change and Its Link To Temperaturementioning

confidence: 99%

Eos, Transactions, American Geophysical Union Volume 89, Number 21, 20 May 2008

2008

EoS Transactions

View full text Add to dashboard Cite

Mass., Constraints on melt-water fl ux through the West Greenland ice-sheet: Modeling of hydro-fracture drainage of supraglacial lakes.Sasha Peter Carter, University of Texas at Austin, Ice fl ow history, basal melt, and hydraulic connections in the Dome C Lake District headwaters over the last glacial cycle inferred from hydropotential, internal layers, and basal refl ectivity in airborne radar sounding data. Mineral and Rock Physics (MRP)Ludmila

show abstract

“…The uncertainty in cloud feedbacks in turn is believed to be primarily due to low-level clouds [Vial et al, 2013;Webb et al, 2006;Medeiros et al, 2008].…”

Section: Introductionmentioning

confidence: 99%

Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations

Nam

Quaas

2013

Geophysical Research Letters

View full text Add to dashboard Cite

Regimes of tropical low-level clouds are commonly identified according to large-scale subsidence and lower tropospheric stability (LTS). This definition alone is insufficient for the distinction between regimes and limits the comparison of low-level clouds from CloudSat radar observations and the ECHAM5 GCM run with the COSP radar simulator. Comparisons of CloudSat radar cloud altitude-reflectivity histograms for stratocumulus and shallow cumulus regimes, as defined above, show nearly identical reflectivity profiles, because the distinction between the two regimes is dependent upon atmospheric stability below 700 hPa and observations above 1.5 km. Regional subsets, near California and Hawaii, for example, have large differences in reflectivity profiles than the dynamically defined domain; indicating different reflectivity profiles exist under a given large-scale environment. Regional subsets are better for the evaluation of low-level clouds in CloudSat and ECHAM5 as there is less contamination between 2.5 km and 7.5 km from precipitating hydrometeors which obscured cloud reflectivities. Key Points: Identification of low clouds by large-scale dynamics insufficient for radar Stratocumulus and shallow cumulus regimes have nearly identical reflectivities Geographical regions are better for evaluating low-level clouds with a radar. © 2013. American Geophysical Union. All Rights Reserved

show abstract

On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Cited by 357 publications

References 48 publications

Perturbed physics ensemble using the MIROC5 coupled atmosphere–ocean GCM without flux corrections: experimental design and results

Perturbed physics ensemble using the MIROC5 coupled atmosphere–ocean GCM without flux corrections: experimental design and results

Eos, Transactions, American Geophysical Union Volume 89, Number 21, 20 May 2008

Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations

Contact Info

Product

Resources

About