scholarly journals Dispersion Aerosol Indirect Effect in Turbulent Clouds: Laboratory Measurements of Effective Radius

2018 ◽  
Vol 45 (19) ◽  
pp. 10,738-10,745 ◽  
Author(s):  
K. K. Chandrakar ◽  
W. Cantrell ◽  
A. B. Kostinski ◽  
R. A. Shaw
2017 ◽  
Vol 30 (17) ◽  
pp. 6959-6976 ◽  
Author(s):  
Yolanda L. Shea ◽  
Bruce A. Wielicki ◽  
Sunny Sun-Mack ◽  
Patrick Minnis

Cloud response to Earth’s changing climate is one of the largest sources of uncertainty among global climate model (GCM) projections. Two of the largest sources of uncertainty are the spread in equilibrium climate sensitivity (ECS) and uncertainty in radiative forcing due to uncertainty in the aerosol indirect effect. Satellite instruments with sufficient accuracy and on-orbit stability to detect climate change–scale trends in cloud properties will improve confidence in the understanding of the relationship between observed climate change and cloud property trends, thus providing information to better constrain ECS and radiative forcing. This study applies a climate change uncertainty framework to quantify the impact of measurement uncertainty on trend detection times for cloud fraction, effective temperature, optical thickness, and water cloud effective radius. Although GCMs generally agree that the total cloud feedback is positive, disagreement remains on its magnitude. With the climate uncertainty framework, it is demonstrated how stringent measurement uncertainty requirements for reflected solar and infrared satellite measurements enable improved constraint of SW and LW cloud feedbacks and the ECS by significantly reducing trend uncertainties for cloud fraction, optical thickness, and effective temperature. The authors also demonstrate improved constraint on uncertainty in the aerosol indirect effect by reducing water cloud effective radius trend uncertainty.


2018 ◽  
Author(s):  
Alexa D. Ross ◽  
Robert E. Holz ◽  
Gregory Quinn ◽  
Jeffrey S. Reid ◽  
Peng Xian ◽  
...  

Abstract. Satellite observations and model simulations cannot, by themselves, give full insight into the complex relationships between aerosols and clouds. This is especially the case over the greater Southeast Asia, an area that is particularly sensitive to changes in precipitation yet possesses some of the world’s largest observability and predictability challenges. We present a new collocated dataset that combines satellite observations from Aqua's Moderate-resolution Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) with the Navy Aerosol Analysis and Prediction System (NAAPS). The dataset is designed with the capability to investigate aerosol-cloud relationships and provides coincident and vertically resolved cloud and aerosol observations for a ten-year period. Using model reanalysis aerosol fields from the NAAPS and coincident cloud liquid effective radius retrievals from MODIS (removing cirrus contamination using CALIOP), we investigate the first aerosol indirect effect. We find overall that as expected, aerosol loading anti-correlates with cloud effective radius, with maximum sensitivity in cumulous mediocris clouds with heights in the 3–4.5 km level. The highest susceptibility in droplet effective radius to modeled perturbations in particle concentrations were found in the more remote regions of the western Pacific Ocean and Indian Ocean. Conversely, there was much less variability in cloud droplet size near emission sources over both land and water. We hypothesize this is suggestive of a high background aerosol population already saturating the cloud condensation nuclei budget.


2006 ◽  
Vol 6 (3) ◽  
pp. 3757-3799 ◽  
Author(s):  
T. Storelvmo ◽  
J. E. Kristjansson ◽  
G. Myhre ◽  
M. Johnsrud ◽  
F. Stordal

Abstract. The indirect effect of aerosols via liquid clouds is investigated by comparing aerosol and cloud characteristics from the Global Climate Model CAM-Oslo to those observed by the MODIS instrument onboard the TERRA and AQUA satellites (http://modis.gsfc.nasa.gov). The comparison is carried out for 15 selected regions ranging from remote and clean to densely populated and polluted. For each region, the regression coefficient and correlation coefficient for the following parameters are calculated: Aerosol Optical Depth vs. Liquid Cloud Optical Thickness, Aerosol Optical Depth vs. Liquid Cloud Droplet Effective Radius and Aerosol Optical Depth vs. Cloud Liquid Water Path. Modeled and observed correlation coefficients and regression coefficients are then compared for a 3-year period starting in January 2001. Additionally, global maps for a number of aerosol and cloud parameters crucial for the understanding of the aerosol indirect effect are compared for the same period of time. Significant differences are found between MODIS and CAM-Oslo both in the regional and global comparison. However, both the model and the observations show a positive correlation between Aerosol Optical Depth and Cloud Optical Depth in practically all regions and for all seasons, in agreement with the current understanding of aerosol-cloud interactions. The correlation between Aerosol Optical Depth and Liquid Cloud Droplet Effective Radius is variable both in the model and the observations. However, the model reports the expected negative correlation more often than the MODIS data. Aerosol Optical Depth is overall positively correlated to Cloud Liquid Water Path both in the model and the observations, with a few regional exceptions.


2006 ◽  
Vol 6 (11) ◽  
pp. 3583-3601 ◽  
Author(s):  
T. Storelvmo ◽  
J. E. Kristjánsson ◽  
G. Myhre ◽  
M. Johnsrud ◽  
F. Stordal

Abstract. The indirect effect of aerosols via liquid clouds is investigated by comparing aerosol and cloud characteristics from the Global Climate Model CAM-Oslo to those observed by the MODIS instrument onboard the TERRA and AQUA satellites http://modis.gsfc.nasa.gov). The comparison is carried out for 15 selected regions ranging from remote and clean to densely populated and polluted. For each region, the regression coefficient and correlation coefficient for the following parameters are calculated: Aerosol Optical Depth vs. Liquid Cloud Optical Thickness, Aerosol Optical Depth vs. Liquid Cloud Droplet Effective Radius and Aerosol Optical Depth vs. Cloud Liquid Water Path. Modeled and observed correlation coefficients and regression coefficients are then compared for a 3-year period starting in January 2001. Additionally, global maps for a number of aerosol and cloud parameters crucial for the understanding of the aerosol indirect effect are compared for the same period of time. Significant differences are found between MODIS and CAM-Oslo both in the regional and global comparison. However, both the model and the observations show a positive correlation between Aerosol Optical Depth and Cloud Optical Depth in practically all regions and for all seasons, in agreement with the current understanding of aerosol-cloud interactions. The correlation between Aerosol Optical Depth and Liquid Cloud Droplet Effective Radius is variable both in the model and the observations. However, the model reports the expected negative correlation more often than the MODIS data. Aerosol Optical Depth is overall positively correlated to Cloud Liquid Water Path both in the model and the observations, with a few regional exceptions.


2018 ◽  
Vol 18 (17) ◽  
pp. 12747-12764 ◽  
Author(s):  
Alexa D. Ross ◽  
Robert E. Holz ◽  
Gregory Quinn ◽  
Jeffrey S. Reid ◽  
Peng Xian ◽  
...  

Abstract. Satellite observations and model simulations cannot, by themselves, give full insight into the complex relationships between aerosols and clouds. This is especially true over Southeast Asia, an area that is particularly sensitive to changes in precipitation yet poses some of the world's largest observability and predictability challenges. We present a new collocated dataset, the Curtain Cloud-Aerosol Regional A-Train dataset, or CCARA. CCARA includes collocated satellite observations from Aqua's Moderate-resolution Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) with the Navy Aerosol Analysis and Prediction System (NAAPS). The CCARA dataset is designed with the capability to investigate aerosol–cloud relationships in regions with limited aerosol retrievals due to high cloud amounts by leveraging the NAAPS model reanalysis of aerosol concentration in these regions. This combined aerosol and cloud dataset provides coincident and vertically resolved cloud and aerosol observations for 2006–2016. Using the model reanalysis aerosol fields from the NAAPS and coincident cloud liquid effective radius retrievals from MODIS (cirrus contamination using CALIOP), we investigate the first aerosol indirect effect in Southeast Asia. We find that, as expected, aerosol loading anti-correlates with cloud effective radius, with maximum sensitivity in cumulous mediocris clouds with heights in the 3–4.5 km level. The highest susceptibilities in droplet effective radius to modeled perturbations in particle concentrations were found in the more remote and pristine regions of the western Pacific Ocean and Indian Ocean. Conversely, there was much less variability in cloud droplet size near emission sources over both land and water. We hypothesize this is suggestive of a high aerosol background already saturated with cloud condensation nuclei even during the relatively clean periods, in contrast to the remote ocean regions, which have periods where the aerosol concentrations are low enough to allow for larger droplet growth.


Author(s):  
Graham Feingold ◽  
Reinhard Furrer ◽  
Peter Pilewskie ◽  
Lorraine A. Remer ◽  
Qilong Min ◽  
...  

2012 ◽  
Vol 60 ◽  
pp. 153-163 ◽  
Author(s):  
M.G. Manoj ◽  
P.C.S. Devara ◽  
Susmitha Joseph ◽  
A.K. Sahai

2013 ◽  
Author(s):  
Kai Zhang ◽  
Xiaohong Liu ◽  
Jin-Ho Yoon ◽  
Minghuai Wang ◽  
Jennifer M. Comstock ◽  
...  

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