scholarly journals The Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

2019 ◽  
Author(s):  
Grégory Cesana ◽  
Anthony D. Del Genio ◽  
Hélène Chepfer
Keyword(s):  
Climate Models ◽  
Global Scale ◽  
Original Method ◽  
Cloud Feedback ◽  
Satellite Observations ◽  
Geometrical Shape ◽  
Spatial Distributions ◽  
Shallow Convection ◽  
Cloud Feedbacks ◽  
Cloud Height

Abstract. Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both space-borne and large eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosols Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CAlipso Dataset (CASCCAD). To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent and vertical variability, which is applied to both CALIPSO and combined CloudSat-CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and and Sc-Cu transition case studies. Then, the global statistics are compared against those from existing passive and active-sensor satellite observations. Our results indicate that the cloud optical thickness –as used in passive-sensor observations– is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. On the contrary, classifying Cu and Sc clouds based on their geometrical shape leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, shipbased and field campaigns. Furthermore, we show that our method improves existing Sc-Cu classification by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection (Cu) and boundary layer (Sc) clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, DOI:https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ and on zenodo website at https://zenodo.org/record/2667637 .

scholarly journals The Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

2019 ◽  
Vol 11 (4) ◽  
pp. 1745-1764 ◽  
Author(s):  
Grégory Cesana ◽  
Anthony D. Del Genio ◽  
Hélène Chepfer
Keyword(s):  
Climate Models ◽  
Global Scale ◽  
Original Method ◽  
Cloud Feedback ◽  
Satellite Observations ◽  
Geometrical Shape ◽  
Spatial Distributions ◽  
Shallow Convection ◽  
Cloud Feedbacks ◽  
Cloud Height

Abstract. Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSat–CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and Sc–Cu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness – as used in passive-sensor observations – is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing Sc–Cu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019).

scholarly journals The impact of parametrized convection on cloud feedback

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140414 ◽  
Author(s):  
Mark J. Webb ◽  
Adrian P. Lock ◽  
Christopher S. Bretherton ◽  
Sandrine Bony ◽  
Jason N. S. Cole ◽  
...  
Keyword(s):  
Climate Models ◽  
Correction Method ◽  
Cloud Feedback ◽  
Temperature Perturbation ◽  
Cloud Feedbacks ◽  
Stratocumulus Clouds ◽  
Shallow Clouds ◽  
Convection Schemes ◽  
The Individual ◽  
The Impact

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.

scholarly journals Does Antarctic glaciation cool the world?

2012 ◽  
Vol 8 (4) ◽  
pp. 2645-2693 ◽  
Author(s):  
A. Goldner ◽  
M. Huber ◽  
R. Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Ice Sheet ◽  
Cloud Feedback ◽  
Modern World ◽  
Antarctic Ice Sheet ◽  
Cloud Feedbacks ◽  
Wide Range ◽  
The Antarctic

Abstract. In this study we compare the simulated climatic impact of adding the Antarctic Ice Sheet to the "Greenhouse World" of the Eocene and removing the Antarctic Ice Sheet from the Modern world. The Modern surface temperature anomaly (ΔT) induced by Antarctic Glaciation ranges from −1.22 to −0.18 K when CO2 is dropped from 2240 to 560 ppm, whereas the Eocene ΔT is nearly constant at −0.3 K. We calculate the climate sensitivity parameter S[Antarctica] which is defined as the change in surface temperature (ΔT) divided by the change in radiative forcing (ΔQAntarctica) imposed by prescribing the glacial properties of Antarctica. While the ΔT associated with the imposed Antarctic properties is relatively consistent across the Eocene cases, the radiative forcing is not. This leads to a wide range of S[Antarctica], with Eocene values systematically smaller than Modern. This differing temperature response in Eocene and Modern is partially due to the smaller surface area of the imposed forcing over Antarctica in the Eocene and partially due to the presence of strong positive sea-ice feedbacks in the Modern. The system's response is further mediated by differing shortwave cloud feedbacks which are large and of opposite sign operating in Modern and Eocene configurations. A negative cloud feedback warms much of the Earth's surface as a large ice sheet is introduced in Antarctica in the Eocene, whereas in the Modern this cloud feedback is positive and acts to enhance cooling introduced by adding an ice sheet. Because of the importance of cloud feedbacks in determining the final temperature sensitivity of the Antarctic Ice Sheet our results are likely to be model dependent. Nevertheless, these model results show that the radiative forcing and feedbacks induced by the Antarctic Ice Sheet did not significantly decrease global mean surface temperature across the Eocene-Oligocene transition (EOT) and that other factors like declining atmospheric CO2 are more important for cooling across the EOT. The results indicate that climate transitions associated with glaciation depend on the climate background state. This means that using paleoclimate proxy data by itself, from the EOT to estimate Earth System Sensitivity, into the future, is made difficult without relying on climate models and consequently these modelling estimates will have large uncertainty, largely due to low clouds.

scholarly journals The Vertical Structure of Radiative Heating Rates: A Multimodel Evaluation Using A-Train Satellite Observations

2019 ◽  
Vol 32 (5) ◽  
pp. 1573-1590 ◽  
Author(s):  
G. Cesana ◽  
D. E. Waliser ◽  
D. Henderson ◽  
T. S. L’Ecuyer ◽  
X. Jiang ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Climate Models ◽  
Lower Troposphere ◽  
Cloud Amount ◽  
Global Scale ◽  
Satellite Observations ◽  
Radiative Heating ◽  
Infrared Heating ◽  
Heating Rates ◽  
Uncertainty Estimates

Abstract We assess the vertical distribution of radiative heating rates (RHRs) in climate models using a multimodel experiment and A-Train satellite observations, for the first time. As RHRs rely on the representation of cloud amount and properties, we first compare the modeled vertical distribution of clouds directly against lidar–radar combined cloud observations (i.e., without simulators). On a near-global scale (50°S–50°N), two systematic differences arise: an excess of high-level clouds around 200 hPa in the tropics, and a general lack of mid- and low-level clouds compared to the observations. Then, using RHR profiles calculated with constraints from A-Train and reanalysis data, along with their associated maximum uncertainty estimates, we show that the excess clouds and ice water content in the upper troposphere result in excess infrared heating in the vicinity of and below the clouds as well as a lack of solar heating below the clouds. In the lower troposphere, the smaller cloud amount and the underestimation of cloud-top height is coincident with a shift of the infrared cooling to lower levels, substantially reducing the greenhouse effect, which is slightly compensated by an erroneous excess absorption of solar radiation. Clear-sky RHR differences between the observations and the models mitigate cloudy RHR biases in the low levels while they enhance them in the high levels. Finally, our results indicate that a better agreement between observed and modeled cloud profiles could substantially improve the RHR profiles. However, more work is needed to precisely quantify modeled cloud errors and their subsequent effect on RHRs.

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

2012 ◽  
Vol 25 (11) ◽  
pp. 3715-3735 ◽  
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.

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

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140415 ◽  
Author(s):  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Limited Area ◽  
Slight Reduction ◽  
Low Latitude ◽  
Cloud Feedbacks ◽  
Cloud Regimes

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.

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

2012 ◽  
Vol 25 (11) ◽  
pp. 3736-3754 ◽  
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.

scholarly journals On the Usage of Spectral and Broadband Satellite Instrument Measurements to Differentiate Climate Models with Different Cloud Feedback Strengths

2013 ◽  
Vol 26 (17) ◽  
pp. 6561-6574 ◽  
Author(s):  
Daniel R. Feldman ◽  
Daniel M. Coleman ◽  
William D. Collins
Keyword(s):  
Near Infrared ◽  
Climate Models ◽  
Longwave Radiation ◽  
Cloud Feedback ◽  
Climate System ◽  
Spectral Radiance ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Cloud Feedbacks ◽  
The Difference

Abstract Top-of-atmosphere radiometric signals associated with different high- and low-cloud–radiative feedbacks have been examined through the use of an observing system simulation experiment (OSSE). The OSSE simulates variations in the spectrally resolved and spectrally integrated signals that are due to a range of plausible feedbacks of the climate system when forced with CO2 concentrations that increase at 1% yr−1. This initial version of the OSSE is based on the Community Climate System Model, version 3 (CCSM3), and exploits the fact that CCSM3 exhibits different cloud feedback strengths for different model horizontal resolutions. In addition to the conventional broadband shortwave albedos and outgoing longwave fluxes, a dataset of shortwave spectral reflectance and longwave spectral radiance has been created. These data have been analyzed to determine simulated satellite instrument signals of poorly constrained cloud feedbacks for three plausible realizations of Earth's climate system produced by CCSM3. These data have been analyzed to estimate the observational record length of albedo, outgoing longwave radiation, shortwave reflectance, or longwave radiance required to differentiate these dissimilar Earth system realizations. Shortwave spectral measurements in visible and near-infrared water vapor overtone lines are best suited to differentiate model results, and a 33% difference in shortwave–cloud feedbacks can be detected with 20 years of continuous measurements. Nevertheless, at most latitudes and with most wavelengths, the difference detection time is more than 30 years. This suggests that observing systems of sufficiently stable calibration would be useful in addressing the contribution of low clouds to the spread of climate sensitivities currently exhibited by the models that report to the Intergovernmental Panel on Climate Change (IPCC).

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

2018 ◽  
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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