Insights into low-latitude cloud feedbacks from high-resolution models

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: ‘thermodynamic’ cloudiness reduction from warming of the atmosphere–ocean column, ‘radiative’ cloudiness reduction from CO 2 - and H 2 O-induced increase in atmospheric emissivity aloft, ‘stability-induced’ cloud increase from increased lower tropospheric stratification, and ‘dynamical’ cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

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A cloud feedback emulator (CFE, version 1.0) for an intermediate complexity model

Geoscientific Model Development ◽

10.5194/gmd-10-945-2017 ◽

2017 ◽

Vol 10 (2) ◽

pp. 945-958 ◽

Cited By ~ 2

Author(s):

David J. Ullman ◽

Andreas Schmittner

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Cloud Feedback ◽

Global Climate Models ◽

Cloud Feedbacks ◽

Intermediate Complexity ◽

Model Cloud ◽

Radiative Feedbacks ◽

The University

Abstract. The dominant source of inter-model differences in comprehensive global climate models (GCMs) are cloud radiative effects on Earth's energy budget. Intermediate complexity models, while able to run more efficiently, often lack cloud feedbacks. Here, we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4 × CO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.

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The University of Victoria Cloud Feedback Emulator (UVic-CFE): cloud radiative feedbacks in an intermediate complexity model

10.5194/gmd-2016-220 ◽

2016 ◽

Author(s):

David Ullman ◽

Andreas Schmittner

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Cloud Feedback ◽

Global Climate Models ◽

Cloud Feedbacks ◽

Intermediate Complexity ◽

Model Cloud ◽

Radiative Feedbacks ◽

The University

Abstract. The dominant source of inter-model differences in comprehensive global climate models (GCMs) are cloud radiative effects on Earth's energy budget. Intermediate complexity models, while able to run more efficiently, often lack cloud feedbacks. Here, we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4xCO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.

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A General Filter for Stretched-Grid Models: Application in Cartesian Geometry

Monthly Weather Review ◽

10.1175/2010mwr3531.1 ◽

2011 ◽

Vol 139 (5) ◽

pp. 1637-1653 ◽

Cited By ~ 1

Author(s):

Dorina Surcel ◽

René Laprise

Keyword(s):

Computational Efficiency ◽

Climate Models ◽

Dynamical Downscaling ◽

Global Climate ◽

Effective Means ◽

Computational Cost ◽

Global Climate Models ◽

Limited Area ◽

Area Of Interest ◽

Cartesian Geometry

Global climate models with variable resolution are effective means to represent regional scales over an area of interest while avoiding the nesting issues of limited-area models. The stretched-grid approach provides a dynamical downscaling approach that naturally allows two-way interactions between the regional and global scales of motion. Concentrating the resolution over a subset of the earth’s surface increases computational efficiency and reduces the computational costs compared to global uniform high-resolution models; however, it does not come free of some problems related to the variation of resolution. To address the issues associated with the stretching and anisotropy of the computational grid, a general convolution filter with a flexible response function is developed. The main feature of this filter is to locally remove scales shorter than a user-prescribed spatially varying length scale. The filtering effectiveness and computational efficiency of the filter can be custom tailored by an appropriate compromise between the filtering response and the width of the convolution stencil. This approach has been tested in one- and two-dimensional Cartesian geometry. It is shown that an effective filter can be obtained using a limited spatial stencil for the convolution to reduce computational cost, and that an adjustable spatially variable and nearly isotropic response can be obtained for application on variable grids.

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Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

Journal of Climate ◽

10.1175/jcli-d-11-00248.1 ◽

2012 ◽

Vol 25 (11) ◽

pp. 3715-3735 ◽

Cited By ~ 120

Author(s):

Mark D. Zelinka ◽

Stephen A. Klein ◽

Dennis L. Hartmann

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Grid Point ◽

Cloud Fraction ◽

Cloud Feedback ◽

Global Climate Models ◽

Radiative Transfer Model ◽

Transfer Model ◽

Cloud Feedbacks ◽

Low Clouds

This study proposes a novel technique for computing cloud feedbacks using histograms of cloud fraction as a joint function of cloud-top pressure (CTP) and optical depth (τ). These histograms were generated by the International Satellite Cloud Climatology Project (ISCCP) simulator that was incorporated into doubled-CO2 simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project. The authors use a radiative transfer model to compute top of atmosphere flux sensitivities to cloud fraction perturbations in each bin of the histogram for each month and latitude. Multiplying these cloud radiative kernels with histograms of modeled cloud fraction changes at each grid point per unit of global warming produces an estimate of cloud feedback. Spatial structures and globally integrated cloud feedbacks computed in this manner agree remarkably well with the adjusted change in cloud radiative forcing. The global and annual mean model-simulated cloud feedback is dominated by contributions from medium thickness (3.6 < τ ≤ 23) cloud changes, but thick (τ > 23) cloud changes cause the rapid transition of cloud feedback values from positive in midlatitudes to negative poleward of 50°S and 70°N. High (CTP ≤ 440 hPa) cloud changes are the dominant contributor to longwave (LW) cloud feedback, but because their LW and shortwave (SW) impacts are in opposition, they contribute less to the net cloud feedback than do the positive contributions from low (CTP > 680 hPa) cloud changes. Midlevel (440 < CTP ≤ 680 hPa) cloud changes cause positive SW cloud feedbacks that are 80% as large as those due to low clouds. Finally, high cloud changes induce wider ranges of LW and SW cloud feedbacks across models than do low clouds.

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How Well Do Large‐Eddy Simulations and Global Climate Models Represent Observed Boundary Layer Structures and Low Clouds Over the Summertime Southern Ocean?

Journal of Advances in Modeling Earth Systems ◽

10.1029/2020ms002205 ◽

2020 ◽

Vol 12 (11) ◽

Author(s):

R. L. Atlas ◽

C. S. Bretherton ◽

P. N. Blossey ◽

A. Gettelman ◽

C. Bardeen ◽

...

Keyword(s):

Boundary Layer ◽

Southern Ocean ◽

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Large Eddy Simulations ◽

Low Clouds ◽

Layer Structures ◽

Large Eddy

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The Climatology of the Atmospheric Boundary Layer in Contemporary Global Climate Models

Journal of Climate ◽

10.1175/jcli-d-17-0498.1 ◽

2018 ◽

Vol 31 (22) ◽

pp. 9151-9173 ◽

Cited By ~ 6

Author(s):

Richard Davy

Keyword(s):

Boundary Layer ◽

General Circulation ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

General Circulation Models ◽

Global Climate Models ◽

Cmip5 Models ◽

Seasonal Cycles ◽

Layer Depth

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.

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Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part II: Attribution to Changes in Cloud Amount, Altitude, and Optical Depth

Journal of Climate ◽

10.1175/jcli-d-11-00249.1 ◽

2012 ◽

Vol 25 (11) ◽

pp. 3736-3754 ◽

Cited By ~ 137

Author(s):

Mark D. Zelinka ◽

Stephen A. Klein ◽

Dennis L. Hartmann

Keyword(s):

Optical Depth ◽

Climate Models ◽

Negative Impact ◽

Positive Impact ◽

Cloud Amount ◽

Cloud Feedback ◽

Global Climate Models ◽

Positive Contribution ◽

Total Cloud Amount ◽

Cloud Feedbacks

Cloud radiative kernels and histograms of cloud fraction, both as functions of cloud-top pressure and optical depth, are used to quantify cloud amount, altitude, and optical depth feedbacks. The analysis is applied to doubled-CO2 simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project. Global, annual, and ensemble mean longwave (LW) and shortwave (SW) cloud feedbacks are positive, with the latter nearly twice as large as the former. The robust increase in cloud-top altitude in both the tropics and extratropics is the dominant contributor to the positive LW cloud feedback. The negative impact of reductions in cloud amount offsets more than half of the positive impact of rising clouds on LW cloud feedback, but the magnitude of compensation varies considerably across the models. In contrast, robust reductions in cloud amount make a large and virtually unopposed positive contribution to SW cloud feedback, though the intermodel spread is greater than for any other individual feedback component. Overall reductions in cloud amount have twice as large an impact on SW fluxes as on LW fluxes, such that the net cloud amount feedback is moderately positive, with no models exhibiting a negative value. As a consequence of large but partially offsetting effects of cloud amount reductions on LW and SW feedbacks, both the mean and intermodel spread in net cloud amount feedback are smaller than those of the net cloud altitude feedback. Finally, the study finds that the large negative cloud feedback at high latitudes results from robust increases in cloud optical depth, not from increases in total cloud amount as is commonly assumed.

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Stratocumulus Clouds in Southeastern Pacific Simulated by Eight CMIP5–CFMIP Global Climate Models

Journal of Climate ◽

10.1175/jcli-d-13-00376.1 ◽

2014 ◽

Vol 27 (8) ◽

pp. 3000-3022 ◽

Cited By ~ 25

Author(s):

Jia-Lin Lin ◽

Taotao Qian ◽

Toshiaki Shinoda

Keyword(s):

Cloud Cover ◽

Large Scale ◽

Climate Models ◽

Global Climate ◽

Cloud Feedback ◽

Global Climate Models ◽

Temperature Structure ◽

Model Intercomparison ◽

Stratocumulus Clouds ◽

Intercomparison Project

Abstract This study examines the stratocumulus clouds and associated cloud feedback in the southeast Pacific (SEP) simulated by eight global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and Cloud Feedback Model Intercomparison Project (CFMIP) using long-term observations of clouds, radiative fluxes, cloud radiative forcing (CRF), sea surface temperature (SST), and large-scale atmosphere environment. The results show that the state-of-the-art global climate models still have significant difficulty in simulating the SEP stratocumulus clouds and associated cloud feedback. Comparing with observations, the models tend to simulate significantly less cloud cover, higher cloud top, and a variety of unrealistic cloud albedo. The insufficient cloud cover leads to overly weak shortwave CRF and net CRF. Only two of the eight models capture the observed positive cloud feedback at subannual to decadal time scales. The cloud and radiation biases in the models are associated with 1) model biases in large-scale temperature structure including the lack of temperature inversion, insufficient lower troposphere stability (LTS), and insufficient reduction of LTS with local SST warming, and 2) improper model physics, especially insufficient increase of low cloud cover associated with larger LTS. The two models that arguably do best at simulating the stratocumulus clouds and associated cloud feedback are the only ones using cloud-top radiative cooling to drive boundary layer turbulence.

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Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations

10.5194/acp-2018-785 ◽

2018 ◽

Cited By ~ 1

Author(s):

Daniel T. McCoy ◽

Paul R. Field ◽

Gregory S. Elsaesser ◽

Alejandro Bodas-Salcedo ◽

Brian H. Kahn ◽

...

Keyword(s):

Water Vapor ◽

Liquid Water ◽

Climate Models ◽

Moisture Flux ◽

Cloud Feedback ◽

Global Climate Models ◽

Extratropical Cyclones ◽

Liquid Water Path ◽

Cloud Feedbacks ◽

Water Path

Abstract. Extratropical cyclones provide a unique set of challenges and opportunities in understanding variability in cloudiness over the extratropics (poleward of 30°). We can gain insight into the shortwave cloud feedback from examining cyclone variability. Here we contrast global climate models (GCMs) with horizontal resolutions from 7 km up to hundreds of kilometers with Multi-Sensor Advanced Climatology Liquid Water Path (MAC-LWP) microwave observations of cyclone properties from the period 1992–2015. We find that inter-cyclone variability in both observations and models is strongly driven by moisture flux along the cyclone's warm conveyor belt (WCB). Stronger WCB moisture flux enhances liquid water path (LWP) within cyclones. This relationship is replicated in GCMs, although its strength varies substantially across models. In the southern hemisphere (SH) oceans 28–42 % of the observed interannual variability in cyclone LWP may be explained by WCB moisture flux variability. This relationship is used to propose two cloud feedbacks acting within extratropical cyclones: a negative feedback driven by Clausius-Clapeyron increasing water vapor path (WVP), which enhances the amount of water vapor available to be fluxed into the cyclone; and a feedback moderated by changes in the life cycle and vorticity of cyclones under warming, which changes the rate at which existing moisture is imported into the cyclone. We show that changes in moisture flux drive can explain the observed trend in Southern Ocean cyclone LWP over the last two decades. Transient warming simulations show that the majority of the change in cyclone LWP can be explained by changes in WCB moisture flux, as opposed to changes in cloud phase. The variability within cyclone composites is examined to understand what cyclonic regimes the mixed phase cloud feedback is relevant to. At a fixed WCB moisture flux cyclone LWP increases with increasing SST in the half of the composite poleward of the low and decreases in the half equatorward of the low in both GCMs and observations. Cloud-top phase partitioning observed by the Atmospheric Infrared Sounder (AIRS) indicates that phase transitions may be driving increases in LWP in the poleward half of cyclones.

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