scholarly journals An Estimate of Low-Cloud Feedbacks from Variations of Cloud Radiative and Physical Properties with Sea Surface Temperature on Interannual Time Scales

2011 ◽  
Vol 24 (4) ◽  
pp. 1106-1121 ◽  
Author(s):  
Zachary A. Eitzen ◽  
Kuan-Man Xu ◽  
Takmeng Wong
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Radiative Properties ◽  
Radiative Effect ◽  
Cloud Optical Depth ◽  
Cloud Radiative Effect ◽  
Low Cloud ◽  
Sst Anomaly

Abstract Simulations of climate change have yet to reach a consensus on the sign and magnitude of the changes in physical properties of marine boundary layer clouds. In this study, the authors analyze how cloud and radiative properties vary with SST anomaly in low-cloud regions, based on five years (March 2000–February 2005) of Clouds and the Earth’s Radiant Energy System (CERES)–Terra monthly gridded data and matched European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological reanalaysis data. In particular, this study focuses on the changes in cloud radiative effect, cloud fraction, and cloud optical depth with SST anomaly. The major findings are as follows. First, the low-cloud amount (−1.9% to −3.4% K−1) and the logarithm of low-cloud optical depth (−0.085 to −0.100 K−1) tend to decrease while the net cloud radiative effect (3.86 W m−2 K−1) becomes less negative as SST anomalies increase. These results are broadly consistent with previous observational studies. Second, after the changes in cloud and radiative properties with SST anomaly are separated into dynamic, thermodynamic, and residual components, changes in the dynamic component (taken as the vertical velocity at 700 hPa) have relatively little effect on cloud and radiative properties. However, the estimated inversion strength decreases with increasing SST, accounting for a large portion of the measured decreases in cloud fraction and cloud optical depth. The residual positive change in net cloud radiative effect (1.48 W m−2 K−1) and small changes in low-cloud amount (−0.81% to 0.22% K−1) and decrease in the logarithm of optical depth (–0.035 to –0.046 K−1) with SST are interpreted as a positive cloud feedback, with cloud optical depth feedback being the dominant contributor. Last, the magnitudes of the residual changes differ greatly among the six low-cloud regions examined in this study, with the largest positive feedbacks (∼4 W m−2 K−1) in the southeast and northeast Atlantic regions and a slightly negative feedback (−0.2 W m−2 K−1) in the south-central Pacific region. Because the retrievals of cloud optical depth and/or cloud fraction are difficult in the presence of aerosols, the transport of heavy African continental aerosols may contribute to the large magnitudes of estimated cloud feedback in the two Atlantic regions.

scholarly journals An emulator approach to stratocumulus susceptibility

2019 ◽  
Vol 19 (15) ◽  
pp. 10191-10203 ◽  
Author(s):  
Franziska Glassmeier ◽  
Fabian Hoffmann ◽  
Jill S. Johnson ◽  
Takanobu Yamaguchi ◽  
Ken S. Carslaw ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Surface Fluxes ◽  
Complex Data ◽  
Radiative Effect ◽  
Liquid Water Path ◽  
Cloud Albedo ◽  
Cloud Radiative Effect ◽  
Wide Range

Abstract. The climatic relevance of aerosol–cloud interactions depends on the sensitivity of the radiative effect of clouds to cloud droplet number N, and liquid water path LWP. We derive the dependence of cloud fraction CF, cloud albedo AC, and the relative cloud radiative effect rCRE=CF⋅AC on N and LWP from 159 large-eddy simulations of nocturnal stratocumulus. These simulations vary in their initial conditions for temperature, moisture, boundary-layer height, and aerosol concentration but share boundary conditions for surface fluxes and subsidence. Our approach is based on Gaussian-process emulation, a statistical technique related to machine learning. We succeed in building emulators that accurately predict simulated values of CF, AC, and rCRE for given values of N and LWP. Emulator-derived susceptibilities ∂ln⁡rCRE/∂ln⁡N and ∂ln⁡rCRE/∂ln⁡LWP cover the nondrizzling, fully overcast regime as well as the drizzling regime with broken cloud cover. Theoretical results, which are limited to the nondrizzling regime, are reproduced. The susceptibility ∂ln⁡rCRE/∂ln⁡N captures the strong sensitivity of the cloud radiative effect to cloud fraction, while the susceptibility ∂ln⁡rCRE/∂ln⁡LWP describes the influence of cloud amount on cloud albedo irrespective of cloud fraction. Our emulation-based approach provides a powerful tool for summarizing complex data in a simple framework that captures the sensitivities of cloud-field properties over a wide range of states.

Low-Cloud, Boundary Layer, and Sea Ice Interactions over the Southern Ocean during Winter

2017 ◽  
Vol 30 (13) ◽  
pp. 4857-4871 ◽  
Author(s):  
Casey J. Wall ◽  
Tsubasa Kohyama ◽  
Dennis L. Hartmann
Keyword(s):  
Boundary Layer ◽  
Sea Ice ◽  
Open Water ◽  
Cloud Fraction ◽  
Global Climate Models ◽  
Radiative Effect ◽  
Cloud Radiative Effect ◽  
Low Cloud ◽  
Ice Edge ◽  
Sea Ice Edge

During austral winter, a sharp contrast in low-cloud fraction and boundary layer structure across the Antarctic sea ice edge is seen in ship-based measurements and in active satellite retrievals from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO), which provide an unprecedented view of polar clouds during winter. Sea ice inhibits heat and moisture transport from the ocean to the atmosphere, and, as a result, the boundary layer is cold, stable, and clear over sea ice and warm, moist, well mixed, and cloudy over open water. The mean low-cloud fraction observed by CALIPSO is roughly 0.7 over open water and 0.4–0.5 over sea ice, and the low-cloud layer is deeper over open water. Low-level winds in excess of 10 m s−1 are common over sea ice. Cold advection off of the sea ice pack causes enhanced low-cloud fraction over open water, and thus an enhanced longwave cloud radiative effect at the surface. Quantitative estimates of the surface longwave cloud radiative effect contributed by low clouds are presented. Finally, 10 state-of-the-art global climate models with satellite simulators are compared to observations. Near the sea ice edge, 7 out of 10 models simulate cloudier conditions over open water than over sea ice. Most models also underestimate low-cloud fraction both over sea ice and over open water.

scholarly journals Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA) against CERES Tropical Deep Convective Cloud Object Observations

2009 ◽  
Vol 137 (1) ◽  
pp. 207-223 ◽  
Author(s):  
Kuan-Man Xu
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Large Scale ◽  
Grid Cell ◽  
Convective Cloud ◽  
Radiative Properties ◽  
Detection Rates ◽  
Cloud Optical Depth ◽  
Object A ◽  
Deep Convective Cloud

Abstract This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis (EOA) and 40-yr ECMWF Re-Analysis (ERA-40) are validated against those obtained from Earth Observing System satellite cloud object data for the January–August 1998 and March 2000 periods. These properties include the ice water path (IWP), cloud-top height and temperature, cloud optical depth, and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud object type for the January–August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud-top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The less sophisticated data assimilation technique and the lack of snow water content information in ERA-40, not the larger horizontal grid spacing, are also responsible for the disagreements with observed pdfs of cloud physical properties, although the detection rates of cloud object occurrence are improved for small-size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights on grid-cell dynamics.

scholarly journals An emulator approach to stratocumulus susceptibility

2019 ◽  
Author(s):  
Franziska Glassmeier ◽  
Fabian Hoffmann ◽  
Jill S. Johnson ◽  
Takanobu Yamaguchi ◽  
Ken S. Carslaw ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Surface Fluxes ◽  
Complex Data ◽  
Radiative Effect ◽  
Liquid Water Path ◽  
Cloud Albedo ◽  
Cloud Radiative Effect ◽  
Wide Range

Abstract. The climatic relevance of aerosol-cloud interactions depends on the sensitivity of the radiative effect of clouds to cloud droplet number N and liquid water path LWP. We derive the dependence of cloud fraction CF, cloud albedo AC and the relative cloud radiative effect rCRE = CF · AC on N and LWP from 159 large-eddy simulations of nocturnal stratocumulus. These simulations vary in their initial conditions for temperature, moisture, boundary-layer height and aerosol concentration but share boundary conditions for surface fluxes and subsidence. Our approach is based on Gaussian process emulation, a statistical technique related to machine learning. We succeed in building emulators that accurately predict simulated values of CF, AC and rCRE for given values of N and LWP. Emulator-derived susceptibilities ∂ ln rCRE/∂ ln N and ∂ ln rCRE/∂ ln LWP cover the non-drizzling, fully-overcast regime as well as the drizzling regime with broken cloud cover. Theoretical results, which are limited to the non-drizzling regime, are reproduced. The susceptibility ∂ ln rCRE/∂ ln N captures the strong sensitivity of the cloud radiative effect to cloud fraction, while the susceptibility ∂ ln rCRE/∂ ln LWP describes the influence of cloud amount on cloud albedo irrespective of cloud fraction. Our emulation-based approach provides a powerful tool for summarizing complex data in a simple framework that captures the sensitivities of cloud field properties over a wide range of states.

scholarly journals Climatology of stratocumulus cloud morphologies: microphysical properties and radiative effects

2014 ◽  
Vol 14 (13) ◽  
pp. 6695-6716 ◽  
Author(s):  
A. Muhlbauer ◽  
I. L. McCoy ◽  
R. Wood
Keyword(s):  
Physical Properties ◽  
Global Scale ◽  
Cloud Fraction ◽  
Cloud Base ◽  
Trade Wind ◽  
Radiative Effects ◽  
Regional Variability ◽  
Microphysical Properties ◽  
Low Clouds ◽  
Low Cloud

Abstract. An artificial neural network cloud classification scheme is combined with A-train observations to characterize the physical properties and radiative effects of marine low clouds based on their morphology and type of mesoscale cellular convection (MCC) on a global scale. The cloud morphological categories are (i) organized closed MCC, (ii) organized open MCC and (iii) cellular but disorganized MCC. Global distributions of the frequency of occurrence of MCC types show clear regional signatures. Organized closed and open MCCs are most frequently found in subtropical regions and in midlatitude storm tracks of both hemispheres. Cellular but disorganized MCC are the predominant type of marine low clouds in regions with warmer sea surface temperature such as in the tropics and trade wind zones. All MCC types exhibit a pronounced seasonal cycle. The physical properties of MCCs such as cloud fraction, radar reflectivity, drizzle rates and cloud top heights as well as the radiative effects of MCCs are found highly variable and a function of the type of MCC. On a global scale, the cloud fraction is largest for closed MCC with mean cloud fractions of about 90%, whereas cloud fractions of open and cellular but disorganized MCC are only about 51% and 40%, respectively. Probability density functions (PDFs) of cloud fractions are heavily skewed and exhibit modest regional variability. PDFs of column maximum radar reflectivities and inferred cloud base drizzle rates indicate fundamental differences in the cloud and precipitation characteristics of different MCC types. Similarly, the radiative effects of MCCs differ substantially from each other in terms of shortwave reflectance and transmissivity. These differences highlight the importance of low-cloud morphologies and their associated cloudiness on the shortwave cloud forcing.

On the Relationships between Subtropical Clouds and Meteorology in Observations and CMIP3 and CMIP5 Models*

2015 ◽  
Vol 28 (8) ◽  
pp. 2945-2967 ◽  
Author(s):  
Timothy A. Myers ◽  
Joel R. Norris
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Cloud Fraction ◽  
Sea Surface ◽  
Radiative Effect ◽  
Low Level ◽  
Temperature Advection ◽  
Cloud Radiative Effect ◽  
High Level ◽  
The Relationship

Abstract Climate models’ simulation of clouds over the eastern subtropical oceans contributes to large uncertainties in projected cloud feedback to global warming. Here, interannual relationships of cloud radiative effect and cloud fraction to meteorological variables are examined in observations and in models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively). In observations, cooler sea surface temperature, a stronger estimated temperature inversion, and colder horizontal surface temperature advection are each associated with larger low-level cloud fraction and increased reflected shortwave radiation. A moister free troposphere and weaker subsidence are each associated with larger mid- and high-level cloud fraction and offsetting components of shortwave and longwave cloud radiative effect. It is found that a larger percentage of CMIP5 than CMIP3 models simulate the wrong sign or magnitude of the relationship of shortwave cloud radiative effect to sea surface temperature and estimated inversion strength. Furthermore, most models fail to produce the sign of the relationship between shortwave cloud radiative effect and temperature advection. These deficiencies are mostly, but not exclusively, attributable to errors in the relationship between low-level cloud fraction and meteorology. Poor model performance also arises due to errors in the response of mid- and high-level cloud fraction to variations in meteorology. Models exhibiting relationships closest to observations tend to project less solar reflection by clouds in the late twenty-first century and have higher climate sensitivities than poorer-performing models. Nevertheless, the intermodel spread of climate sensitivity is large even among these realistic models.

scholarly journals Subseasonal variability of low cloud radiative properties over the southeast Pacific Ocean

2010 ◽  
Vol 10 (8) ◽  
pp. 4047-4063 ◽  
Author(s):  
R. C. George ◽  
R. Wood
Keyword(s):  
Large Scale ◽  
Cloud Fraction ◽  
Radiative Properties ◽  
Pressure System ◽  
Cloud Albedo ◽  
Cloud Properties ◽  
Droplet Concentration ◽  
Subseasonal Variability ◽  
Low Cloud ◽  
Macrophysical Properties

Abstract. Subseasonal variability of cloud radiative properties in the persistent southeast Pacific stratocumulus deck is investigated using MODIS satellite observations and NCEP reanalysis data. A once-daily albedo proxy is derived based on the fractional coverage of low cloud (a macrophysical field) and the cloud albedo, with the latter broken down into contributions from microphysics (cloud droplet concentration) and macrophysics (liquid water path). Subseasonal albedo variability is dominated by the contribution of low cloud fraction variability, except within 10–15° of the South American coast, where cloud albedo variability contributes significantly. Covariance between cloud fraction and cloud albedo also contributes significantly and positively to the variance in albedo, which highlights how complex and inseparable the factors controlling albedo are. Droplet concentration variability contributes only weakly to the subseasonal variability of albedo, which emphasizes that attributing albedo variability to the indirect effects of aerosols against the backdrop of natural meteorological variability is extremely challenging. The dominant large scale meteorological variability is associated with the subtropical high pressure system. Two indices representing changes in the subtropical high strength and extent explain 80–90% of this variability, and significantly modulate the cloud microphysical, macrophysical, and radiative cloud properties. Variations in droplet concentration of up to 50% of the mean are associated with the meteorological driving. We hypothesize that these fluctuations in droplet concentration are a result of the large scale meteorology and their correlation with cloud macrophysical properties should not be used as evidence of aerosol effects. Mechanisms by which large scale meteorology affects cloud properties are explored. Our results support existing hypotheses linking cloud cover variability to changes in cold advection, subsidence, and lower tropospheric stability. Within 10° of the coast interactions between variability in the surface high pressure system and the orography appear to modulate both cloud macrophysical properties and aerosol transport through suppression of the marine boundary layer depth near the coast. This suggests one possible way in which cloud macrophysical properties and droplet concentration may be correlated independently of the second aerosol indirect effect. The results provide variability constraints for models that strive to represent both meteorological and aerosol impacts on stratocumulus clouds.

scholarly journals Statistical Analyses of Satellite Cloud Object Data from CERES. Part III: Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds

2007 ◽  
Vol 64 (3) ◽  
pp. 762-785 ◽  
Author(s):  
Yali Luo ◽  
Kuan-Man Xu ◽  
Bruce A. Wielicki ◽  
Takmeng Wong ◽  
Zachary A. Eitzen
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Weather Prediction ◽  
Cloud Microphysics ◽  
Retrieval Algorithm ◽  
Medium Size ◽  
Size Category ◽  
Cloud Optical Depth ◽  
Large Size ◽  
Cloud Resolving Model

Abstract The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth’s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium-, and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Niño) and March 2000 (weak La Niña). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud-top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud-top height while it overestimates the differences in the observed outgoing longwave radiation and cloud-top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.

scholarly journals A novel method for estimating shortwave direct radiative effect of above-cloud aerosols using CALIOP and MODIS data

2014 ◽  
Vol 7 (6) ◽  
pp. 1777-1789 ◽  
Author(s):  
Z. Zhang ◽  
K. Meyer ◽  
S. Platnick ◽  
L. Oreopoulos ◽  
D. Lee ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Optical Depth ◽  
Radiative Forcing ◽  
Orthogonal Polarization ◽  
Radiative Effect ◽  
Cloud Optical Depth ◽  
Modis Data ◽  
Joint Histogram ◽  
The Impact ◽  
Southeastern Atlantic

Abstract. This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and MODIS (Moderate Resolution Imaging Spectroradiometer) data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a precomputed look-up table based on radiative transfer calculations. We verify that for smoke and polluted dust over the southeastern Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 13:30 local time) shortwave DRE of above-cloud aerosol (ACA) that generally agrees with a more rigorous pixel-level computation within 4%. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeastern Atlantic Ocean would increase, from the original value of 6.4 W m−2 based on operational CALIOP AOD to 9.6 W m−2 if CALIOP AOD retrievals are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m−2 if CALIOP AOD retrievals are biased low by a factor of 5 as suggested in Jethva et al. (2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m−2 AOD−1, suggesting a near-linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that given an above-cloud aerosol type the optical depth of the underlying clouds plays a larger role than above-cloud AOD in the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets.

Sign in / Sign up

Export Citation Format

Share Document