scholarly journals A global satellite view of aerosol cloud interactions

2004 ◽  
Vol 4 (5) ◽  
pp. 6823-6836 ◽  
Author(s):  
C. Luo

Abstract. Long-term and large-scale correlations between Advanced Very High-Resolution Radiometer (AVHRR) aerosol optical depth and International Satellite Cloud Climatology Project (ISCCP) monthly cloud amount data show significant regional scale relationships between cloud amount and aerosols, consistent with aerosol-cloud interactions. Positive correlations between aerosols and cloud amount are associated with North American and Asian aerosols in the North Atlantic and Pacific storm tracks, and mineral aerosols in the tropical North Atlantic. Negative correlations are seen near biomass burning regions of North Africa and Indonesia, as well as south of the main mineral aerosol source of North Africa. These results suggest that there are relationships between aerosols and clouds in the observations that can be used by general circulation models to verify the correct forcing mechanisms for both direct and indirect radiative forcing by clouds.

2020 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Toshihiko Takemura

Abstract. Complex aerosol–cloud–precipitation interactions lead to large differences in estimates of aerosol impacts on climate among general circulation models (GCMs) and satellite retrievals. Typically, precipitating hydrometeors are treated diagnostically in most GCMs, and their radiative effects are ignored. Here, we quantify how the treatment of precipitation influences the simulated effective radiative forcing due to aerosol–cloud interactions (ERFaci) using a state-of-the-art GCM with a two-moment prognostic precipitation scheme that incorporates the radiative effect of precipitating particles, and investigate how microphysical process representations are related to macroscopic climate effects. Prognostic precipitation substantially weakens the magnitude of ERFaci (by approximately 75 %) compared with the traditional diagnostic scheme, and this is the result of the increased longwave (warming) and weakened shortwave (cooling) components of ERFaci. The former is attributed to additional adjustment processes induced by falling snow, and the latter stems largely from riming of snow by collection of cloud droplets. The significant reduction in ERFaci does not occur without prognostic snow, which contributes mainly by buffering the cloud response to aerosol perturbations through depleting cloud water via collection. Prognostic precipitation also alters the regional pattern of ERFaci, particularly over northern mid-latitudes where snow is abundant. The treatment of precipitation is thus a highly influential controlling factor of ERFaci, contributing more than other uncertain tunable processes related to aerosol–cloud–precipitation interactions. This change in ERFaci caused by the treatment of precipitation is large enough to explain the existing difference in ERFaci between GCMs and observations.


2016 ◽  
Vol 113 (21) ◽  
pp. 5812-5819 ◽  
Author(s):  
Graham Feingold ◽  
Allison McComiskey ◽  
Takanobu Yamaguchi ◽  
Jill S. Johnson ◽  
Kenneth S. Carslaw ◽  
...  

The topic of cloud radiative forcing associated with the atmospheric aerosol has been the focus of intense scrutiny for decades. The enormity of the problem is reflected in the need to understand aspects such as aerosol composition, optical properties, cloud condensation, and ice nucleation potential, along with the global distribution of these properties, controlled by emissions, transport, transformation, and sinks. Equally daunting is that clouds themselves are complex, turbulent, microphysical entities and, by their very nature, ephemeral and hard to predict. Atmospheric general circulation models represent aerosol−cloud interactions at ever-increasing levels of detail, but these models lack the resolution to represent clouds and aerosol−cloud interactions adequately. There is a dearth of observational constraints on aerosol−cloud interactions. We develop a conceptual approach to systematically constrain the aerosol−cloud radiative effect in shallow clouds through a combination of routine process modeling and satellite and surface-based shortwave radiation measurements. We heed the call to merge Darwinian and Newtonian strategies by balancing microphysical detail with scaling and emergent properties of the aerosol−cloud radiation system.


2016 ◽  
Vol 113 (21) ◽  
pp. 5781-5790 ◽  
Author(s):  
John H. Seinfeld ◽  
Christopher Bretherton ◽  
Kenneth S. Carslaw ◽  
Hugh Coe ◽  
Paul J. DeMott ◽  
...  

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.


2020 ◽  
Vol 20 (22) ◽  
pp. 13771-13780
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Toshihiko Takemura

Abstract. Complex aerosol–cloud–precipitation interactions lead to large differences in estimates of aerosol impacts on climate among general circulation models (GCMs) and satellite retrievals. Typically, precipitating hydrometeors are treated diagnostically in most GCMs, and their radiative effects are ignored. Here, we quantify how the treatment of precipitation influences the simulated effective radiative forcing due to aerosol–cloud interactions (ERFaci) using a state-of-the-art GCM with a two-moment prognostic precipitation scheme that incorporates the radiative effect of precipitating particles, and we investigate how microphysical process representations are related to macroscopic climate effects. Prognostic precipitation substantially weakens the magnitude of ERFaci (by approximately 54 %) compared with the traditional diagnostic scheme, and this is the result of the increased longwave (warming) and weakened shortwave (cooling) components of ERFaci. The former is attributed to additional adjustment processes induced by falling snow, and the latter stems largely from riming of snow by collection of cloud droplets. The significant reduction in ERFaci does not occur without prognostic snow, which contributes mainly by buffering the cloud response to aerosol perturbations through depleting cloud water via collection. Prognostic precipitation also alters the regional pattern of ERFaci, particularly over northern midlatitudes where snow is abundant. The treatment of precipitation is thus a highly influential controlling factor of ERFaci, contributing more than other uncertain “tunable” processes related to aerosol–cloud–precipitation interactions. This change in ERFaci caused by the treatment of precipitation is large enough to explain the existing difference in ERFaci between GCMs and observations.


2007 ◽  
Vol 20 (11) ◽  
pp. 2602-2622 ◽  
Author(s):  
Ping Zhu ◽  
James J. Hack ◽  
Jeffrey T. Kiehl

Abstract In this study, it is shown that the NCAR and GFDL GCMs exhibit a marked difference in climate sensitivity of clouds and radiative fluxes in response to doubled CO2 and ±2-K SST perturbations. The GFDL model predicted a substantial decrease in cloud amount and an increase in cloud condensate in the warmer climate, but produced a much weaker change in net cloud radiative forcing (CRF) than the NCAR model. Using a multiple linear regression (MLR) method, the full-sky radiative flux change at the top of the atmosphere was successfully decomposed into individual components associated with the clear sky and different types of clouds. The authors specifically examined the cloud feedbacks due to the cloud amount and cloud condensate changes involving low, mid-, and high clouds between 60°S and 60°N. It was found that the NCAR and GFDL models predicted the same sign of individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate for all three types of clouds (low, mid, and high) despite the different cloud and radiation schemes used in the models. However, since the individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate generally have the opposite signs, the net cloud feedback is a subtle residual of all. Strong cancellations between individual cloud feedbacks may result in a weak net cloud feedback. This result is consistent with the findings of the previous studies, which used different approaches to diagnose cloud feedbacks. This study indicates that the proposed MLR approach provides an easy way to efficiently expose the similarity and discrepancy of individual cloud feedback processes between GCMs, which are hidden in the total cloud feedback measured by CRF. Most importantly, this method has the potential to be applied to satellite measurements. Thus, it may serve as a reliable and efficient method to investigate cloud feedback mechanisms on short-term scales by comparing simulations with available observations, which may provide a useful way to identify the cause for the wide spread of cloud feedbacks in GCMs.


2014 ◽  
Vol 71 (7) ◽  
pp. 2516-2533 ◽  
Author(s):  
Alexander Ruzmaikin ◽  
Hartmut H. Aumann ◽  
Evan M. Manning

Abstract New global satellite data from the Atmospheric Infrared Sounder (AIRS) are applied to study the tropospheric relative humidity (RH) distribution and its influence on outgoing longwave radiation (OLR) for January and July in 2003, 2007, and 2011. RH has the largest maxima over 90% in the equatorial tropopause layer in January. Maxima in July do not arise above 60%. Seasonal variations of about 20% in zonally averaged RH are observed in the equatorial region of the low troposphere, in the equatorial tropopause layer, and in the polar regions. The seasonal variability in the recent decade has increased by about 5% relative to that in 1973–88, indicating a positive trend. The observed RH profiles indicate a moist bias in the tropical and subtropical regions typically produced by the general circulation models. The new data and method of evaluating the statistical significance of bimodality confirm bimodal probability distributions of RH at large tropospheric scales, notably in the ascending branch of the Hadley circulation. Bimodality is also seen at 500–300 hPa in mid- and high latitudes. Since the drying time of the air is short compared with the mixing time of moist and dry air, the bimodality reflects the large-scale distribution of sources of moisture and the atmospheric circulation. Analysis of OLR dependence on surface temperature shows a 0.2 W m−2 K−1 difference in sensitivities between clear-sky and all-sky OLR, indicating a positive longwave cloud radiative forcing. Diagrams of the clear-sky OLR as functions of percentiles of surface temperature and relative humidity in the tropics are designed to provide a new measure of the supergreenhouse effect.


2015 ◽  
Vol 15 (5) ◽  
pp. 6851-6886 ◽  
Author(s):  
E. Gryspeerdt ◽  
P. Stier ◽  
B. A. White ◽  
Z. Kipling

Abstract. Satellite studies of aerosol–cloud interactions usually make use of retrievals of both aerosol and cloud properties, but these retrievals are rarely spatially co-located. While it is possible to retrieve aerosol properties above clouds under certain circumstances, aerosol properties are usually only retrieved in cloud free scenes. Generally, the smaller spatial variability of aerosols compared to clouds reduces the importance of this sampling difference. However, as precipitation generates an increase in spatial variability, the imperfect co-location of aerosol and cloud property retrievals may lead to changes in observed aerosol–cloud–precipitation relationships in precipitating environments. In this work, we use a regional-scale model, satellite observations and reanalysis data to investigate how the non-coincidence of aerosol, cloud and precipitation retrievals affects correlations between them. We show that the difference in the aerosol optical depth (AOD)-precipitation relationship between general circulation models (GCMs) and satellite observations can be explained by the wet scavenging of aerosol. Using observations of the development of precipitation from cloud regimes, we show how the influence of wet scavenging can obscure possible aerosol influences on precipitation from convective clouds. This obscuring of aerosol–cloud–precipitation interactions by wet scavenging suggests that even if GCMs contained a perfect representation of aerosol influences on convective clouds, the difficulty of separating the "clear-sky" aerosol from the "all-sky" aerosol in GCMs may prevent them from reproducing the correlations seen in satellite data.


2008 ◽  
Vol 65 (7) ◽  
pp. 2107-2129 ◽  
Author(s):  
Xiaoqing Wu ◽  
Sunwook Park ◽  
Qilong Min

Abstract Increased observational analyses provide a unique opportunity to perform years-long cloud-resolving model (CRM) simulations and generate long-term cloud properties that are very much in demand for improving the representation of clouds in general circulation models (GCMs). A year 2000 CRM simulation is presented here using the variationally constrained mesoscale analysis and surface measurements. The year-long (3 January–31 December 2000) CRM surface precipitation is highly correlated with the Atmospheric Radiation Measurement (ARM) observations with a correlation coefficient of 0.97. The large-scale forcing is the dominant factor responsible for producing the precipitation in summer, spring, and fall, but the surface heat fluxes play a more important role during winter when the forcing is weak. The CRM-simulated year-long cloud liquid water path and cloud (liquid and ice) optical depth are also in good agreement (correlation coefficients of 0.73 and 0.64, respectively) with the ARM retrievals over the Southern Great Plains (SGP). The simulated cloud systems have 50% more ice water than liquid water in the annual mean. The vertical distributions of ice and liquid water have a single peak during spring (March–May) and summer (June–August), but a second peak occurs near the surface during winter (December–February) and fall (September–November). The impacts of seasonally varied cloud water are very much reflected in the cloud radiative forcing at the top-of-atmosphere (TOA) and the surface, as well as in the vertical profiles of radiative heating rates. The cloudy-sky total (shortwave and longwave) radiative heating profile shows a dipole pattern (cooling above and warming below) during spring and summer, while a second peak of cloud radiative cooling appears near the surface during winter and fall.


2013 ◽  
Vol 13 (7) ◽  
pp. 18809-18853
Author(s):  
M. R. Vuolo ◽  
M. Schulz ◽  
Y. Balkanski ◽  
T. Takemura

Abstract. The quantification and understanding of direct aerosol forcing is essential in the study of climate. One of the main issues that makes its quantification difficult is the lack of a complete comprehension of the role of the aerosol and clouds vertical distribution. This work aims at reducing the incertitude of aerosol forcing due to the vertical superposition of several short-lived atmospheric components, in particular different aerosols species and clouds. We propose a method to quantify the contribution of different parts of the atmospheric column to the forcing, and to evaluate model differences by isolating the effect of radiative interactions only. Any microphysical or thermo-dynamical interactions between aerosols and clouds are deactivated in the model, to isolate the effects of radiative flux coupling. We investigate the contribution of aerosol above, below and in clouds, by using added diagnostics in the aerosol-climate model LMDz. We also compute the difference between the forcing of the ensemble of the aerosols and the sum of the forcings from individual species, in clear-sky. This difference is found to be moderate on global average (14%) but can reach high values regionally (up to 100%). The non-additivity of forcing already for clear-sky conditions shows, that in addition to represent well the amount of individual aerosol species, it is critical to capture the vertical distribution of all aerosols. Nonlinear effects are even more important when superposing aerosols and clouds. Four forcing computations are performed, one where the full aerosol 3-D distribution is used, and then three where aerosols are confined to regions above, inside and below clouds respectively. We find that the forcing of aerosols depends crucially on the presence of clouds and on their position relative to that of the aerosol, in particular for black carbon (BC). We observe a strong enhancement of the forcing of BC above clouds, attenuation for BC below clouds, and a moderate enhancement when BC is found within clouds. BC forcing efficiency amounts to 44, 171, 333 and 178 W m-2 per unit optical depth for BC below, within, above clouds and for the 3-D BC distribution, respectively. The different behaviour of forcing nonlinearities for these three components of the atmospheric column suggests that, an important reason for differences between cloudy-sky aerosol forcings from different models may come from different aerosol and clouds vertical distributions. Our method allows to evaluate the contribution to model differences due to aerosol and clouds radiative interactions only, by reading 3-D aerosol and cloud fields from different GCMs, into the same model. This method avoids differences in calculating optical aerosol properties and forcing to enter into the discussion of inter-model differences. It appears that the above and in-cloud amount of BC is larger for SPRINTARS (190 compared to 179), increasing its cloudy-sky forcing efficiency with respect to LMDz, being thus potentially an important factor for inter-model differences.


2015 ◽  
Vol 15 (1) ◽  
pp. 153-172 ◽  
Author(s):  
M. C. Wyant ◽  
C. S. Bretherton ◽  
R. Wood ◽  
G. R. Carmichael ◽  
A. Clarke ◽  
...  

Abstract. A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar to observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.


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