scholarly journals Aerosol indirect effects on continental low-level clouds over Sweden and Finland

2014 ◽  
Vol 14 (22) ◽  
pp. 12167-12179 ◽  
Author(s):  
M. K. Sporre ◽  
E. Swietlicki ◽  
P. Glantz ◽  
M. Kulmala
Keyword(s):  
Boundary Layer ◽  
Radiative Forcing ◽  
Remote Sensing Data ◽  
Cloud Droplet ◽  
Weather Radar ◽  
Number Concentration ◽  
Effective Radius ◽  
Distribution Data ◽  
Low Level ◽  
Radar Images

Abstract. Aerosol effects on low-level clouds over the Nordic Countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds is investigated using reanalysis data from the European Centre for Medium-Range Weather Forecasts. The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosol–cloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.

scholarly journals Aerosol indirect effects on continental low-level clouds over Sweden and Finland

2014 ◽  
Vol 14 (9) ◽  
pp. 12931-12966
Author(s):  
M. K. Sporre ◽  
E. Swietlicki ◽  
P. Glantz ◽  
M. Kulmala
Keyword(s):  
Boundary Layer ◽  
Radiative Forcing ◽  
Remote Sensing Data ◽  
Cloud Droplet ◽  
Weather Radar ◽  
Number Concentration ◽  
Effective Radius ◽  
Distribution Data ◽  
Low Level ◽  
Radar Images

Abstract. Aerosol effects on low-level clouds over the nordic countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds are investigated using reanalysis data from the European Centre for Medium-Range Forecasts. The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosol cloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.

scholarly journals Study of global cloud droplet number concentration with A-Train satellites

2014 ◽  
Vol 14 (14) ◽  
pp. 7125-7134 ◽  
Author(s):  
S. Zeng ◽  
J. Riedi ◽  
C. R. Trepte ◽  
D. M. Winker ◽  
Y.-X. Hu
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Global Climate Models ◽  
Orthogonal Polarization ◽  
Atmospheric Conditions ◽  
Cloud Droplet Number Concentration ◽  
Passive Sensors

Abstract. Cloud droplet number concentration (CDNC) is an important microphysical property of liquid clouds that impacts radiative forcing, precipitation and is pivotal for understanding cloud–aerosol interactions. Current studies of this parameter at global scales with satellite observations are still challenging, especially because retrieval algorithms developed for passive sensors (i.e., MODerate Resolution Imaging Spectroradiometer (MODIS)/Aqua) have to rely on the assumption of cloud adiabatic growth. The active sensor component of the A-Train constellation (i.e., Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)/CALIPSO) allows retrievals of CDNC from depolarization measurements at 532 nm. For such a case, the retrieval does not rely on the adiabatic assumption but instead must use a priori information on effective radius (re), which can be obtained from other passive sensors. In this paper, re values obtained from MODIS/Aqua and Polarization and Directionality of the Earth Reflectance (POLDER)/PARASOL (two passive sensors, components of the A-Train) are used to constrain CDNC retrievals from CALIOP. Intercomparison of CDNC products retrieved from MODIS and CALIOP sensors is performed, and the impacts of cloud entrainment, drizzling, horizontal heterogeneity and effective radius are discussed. By analyzing the strengths and weaknesses of different retrieval techniques, this study aims to better understand global CDNC distribution and eventually determine cloud structure and atmospheric conditions in which they develop. The improved understanding of CDNC can contribute to future studies of global cloud–aerosol–precipitation interaction and parameterization of clouds in global climate models (GCMs).

scholarly journals Study of cloud droplet number concentration using the A-Train satellites

2013 ◽  
Vol 13 (11) ◽  
pp. 29035-29058
Author(s):  
S. Zeng ◽  
J. Riedi ◽  
C. R. Trepte ◽  
D. M. Winker ◽  
Y.-X. Hu
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Global Climate Models ◽  
Atmospheric Conditions ◽  
Cloud Droplet Number Concentration ◽  
Passive Sensors

Abstract. Cloud droplet number concentration (CDNC) is an important microphysical property of liquid clouds that impacts radiative forcing, precipitation and it is pivotal for understanding of cloud-aerosols interactions. Current studies of this parameter at global scales with satellite observations are still challenging, especially because retrieval algorithms developed for passive sensors (i.e. MODIS/Aqua) have to rely on the assumption of cloud adiabatic growth. The active sensor component of the A-Train constellation (i.e., CALIOP/CALIPSO) allows retrievals of CDNC from depolarization measurements at 532 nm. For that case, the retrieval does not rely on the adiabatic assumption but instead must use a priori information on effective radius (re), which can be obtained from other passive sensors. In this paper, re values obtained from MODIS/Aqua and POLDER/PARASOL (two passive sensors, conponents of the A-Train) are used to constrain CDNC retrievals from CALIOP. Intercomparison of CDNC products retrieved from MODIS and CALIOP sensors is performed, and the impacts of cloud entrainment, drizzling, horizontal heterogeneity, and effective radius are discussed. By analyzing the strengths and weaknesses of different retrieval techniques, this study aims to better understand global CDNC distribution, and eventually determine cloud structure and atmospheric conditions in which they develop. The improved understanding of CDNC should help contribute to future studies of global cloud-aerosol-precipitation interaction and parameterization of clouds in global climate models (GCMs).

scholarly journals MBL drizzle properties and their impact on cloud property retrievals

2015 ◽  
Vol 8 (4) ◽  
pp. 4307-4323
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Property ◽  
Annual Means ◽  
Mean Differences ◽  
The Impact

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrievals from ground-based measurements at the ARM Azores site from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6% with a maximum of 55.8% in winter and a minimum of 35.6% in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 5.48 (1.29) g m−2, 68.7 (39.5) μm, and 0.14 (0.38) cm−3. The seasonal mean LWPd values are less than 4% of the MWR-retrieved LWP values. The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.12 and 0.38 μm, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle on cloud property retrievals is insignificant at the ARM Azores site.

scholarly journals Investigation of aerosol indirect effects on monsoon clouds using ground-based measurements over a high-altitude site in Western Ghats

2016 ◽  
Author(s):  
V. Anil Kumar ◽  
G. Pandithurai ◽  
P. P. Leena ◽  
K. K. Dani ◽  
P. Murugavel ◽  
...  
Keyword(s):  
High Altitude ◽  
Indirect Effects ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Number Concentration ◽  
Effective Radius ◽  
Aerosol Indirect Effects ◽  
Cloud Droplet Number Concentration ◽  
Aerosol Effects

Abstract. The effect of aerosols on cloud droplet number concentration and droplet effective radius are investigated from ground-based measurements over a high-altitude site where in clouds pass over the surface. First aerosol indirect effect AIE estimates were made using i) relative changes in cloud droplet number concentration (AIEn) and ii) relative changes in droplet effective radius (AIEs) with relative changes in aerosol for different LWC values. AIE estimates from two different methods reveal that there is systematic overestimation in AIEn as compared to that of AIEs. Aerosol indirect effects (AIEn and AIEs) and Dispersion effect (DE) at different liquid water content (LWC) regimes ranging from 0.05 to 0.50 gm-3 were estimated. The analysis demonstrates that there is overestimation of AIEn as compared to AIEs which is mainly due to DE. Aerosol effects on spectral dispersion in droplet size distribution plays an important role in altering Twomey’s cooling effect and thereby changes in climate. This study shows that the higher DE in the medium LWC regime which offsets the AIE by 30%.

scholarly journals Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data

2018 ◽  
Vol 18 (3) ◽  
pp. 2035-2047 ◽  
Author(s):  
Daniel T. McCoy ◽  
Frida A.-M. Bender ◽  
Daniel P. Grosvenor ◽  
Johannes K. Mohrmann ◽  
Dennis L. Hartmann ◽  
...  
Keyword(s):  
North America ◽  
Radiative Forcing ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Ozone Monitoring Instrument ◽  
Anthropogenic Aerosol ◽  
Near Surface ◽  
Cloud Properties ◽  
Cloud Droplet Number Concentration ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Cloud droplet number concentration (CDNC) is the key state variable that moderates the relationship between aerosol and the radiative forcing arising from aerosol–cloud interactions. Uncertainty related to the effect of anthropogenic aerosol on cloud properties represents the largest uncertainty in total anthropogenic radiative forcing. Here we show that regionally averaged time series of the Moderate-Resolution Imaging Spectroradiometer (MODIS) observed CDNC of low, liquid-topped clouds is well predicted by the MERRA2 reanalysis near-surface sulfate mass concentration over decadal timescales. A multiple linear regression between MERRA2 reanalyses masses of sulfate (SO4), black carbon (BC), organic carbon (OC), sea salt (SS), and dust (DU) shows that CDNC across many different regimes can be reproduced by a simple power-law fit to near-surface SO4, with smaller contributions from BC, OC, SS, and DU. This confirms previous work using a less sophisticated retrieval of CDNC on monthly timescales. The analysis is supported by an examination of remotely sensed sulfur dioxide (SO2) over maritime volcanoes and the east coasts of North America and Asia, revealing that maritime CDNC responds to changes in SO2 as observed by the ozone monitoring instrument (OMI). This investigation of aerosol reanalysis and top-down remote-sensing observations reveals that emission controls in Asia and North America have decreased CDNC in their maritime outflow on a decadal timescale.

scholarly journals Investigation of aerosol indirect effects on monsoon clouds using ground-based measurements over a high-altitude site in Western Ghats

2016 ◽  
Vol 16 (13) ◽  
pp. 8423-8430 ◽  
Author(s):  
Vasudevan Anil Kumar ◽  
Govindan Pandithurai ◽  
Parakkatt Parambil Leena ◽  
Kundan K. Dani ◽  
Palani Murugavel ◽  
...  
Keyword(s):  
High Altitude ◽  
Indirect Effects ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Number Concentration ◽  
Effective Radius ◽  
Aerosol Indirect Effects ◽  
Spectral Dispersion ◽  
Cloud Droplet Number Concentration ◽  
Aerosol Effects

Abstract. The effect of aerosols on cloud droplet number concentration and droplet effective radius is investigated from ground-based measurements over a high-altitude site where clouds pass over the surface. First aerosol indirect effect (AIE) estimates were made using (i) relative changes in cloud droplet number concentration (AIEn) and (ii) relative changes in droplet effective radius (AIEs) with relative changes in aerosol for different cloud liquid water contents (LWCs). AIE estimates from two different methods reveal that there is systematic overestimation in AIEn as compared to that of AIEs. Aerosol indirect effects (AIEn and AIEs) and dispersion effect (DE) at different LWC regimes ranging from 0.05 to 0.50 g m−3 were estimated. The analysis demonstrates that there is overestimation of AIEn as compared to AIEs, which is mainly due to DE. Aerosol effects on spectral dispersion in droplet size distribution play an important role in altering Twomey's cooling effect and thereby changes in climate. This study shows that the higher DE in the medium LWC regime offsets the AIE by 30 %.

scholarly journals The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data

2021 ◽  
Author(s):  
Edward Gryspeerdt ◽  
Daniel T. McCoy ◽  
Ewan Crosbie ◽  
Richard H. Moore ◽  
Graeme J. Nott ◽  
...  
Keyword(s):  
Satellite Data ◽  
Radiative Forcing ◽  
Sampling Strategy ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Properties ◽  
Systematic Biases ◽  
Cloud Droplet Number Concentration ◽  
Aerosol Cloud Interactions ◽  
The Impact

Abstract. Cloud droplet number concentration (Nd) is of central importance to observation-based estimates of aerosol indirect effects, being used to quantify both the cloud sensitivity to aerosol and the base state of the cloud. However, the derivation of Nd from satellite data depends on a number of assumptions about the cloud and the accuracy of the retrievals of the cloud properties from which it is derived, making it prone to systematic biases. A number of sampling strategies have been proposed to address these biases by selecting the most accurate Nd retrievals in the satellite data. This work compares the impact of these strategies on the accuracy of the satellite retrieved Nd, using a selection of insitu measurements. In stratocumulus regions, the MODIS Nd retrieval is able to achieve a high precision (r2 of 0.5–0.8). This is lower in other cloud regimes, but can be increased by appropriate sampling choices. Although the Nd sampling can have significant effects on the Nd climatology, it produces only a 20 % variation in the implied radiative forcing from aerosol-cloud interactions, with the choice of aerosol proxy driving the overall uncertainty. The results are summarised into recommendations for using MODIS Nd products and appropriate sampling.

scholarly journals The challenge of simulating the sensitivity of the Amazonian clouds microstructure to cloud condensation nuclei number concentrations

2019 ◽  
Author(s):  
Pascal Polonik ◽  
Christoph Knote ◽  
Tobias Zinner ◽  
Florian Ewald ◽  
Tobias Kölling ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Cloud Base ◽  
Condensation Nuclei ◽  
Aerosol Cloud ◽  
Microphysical Properties

Abstract. The realistic representation of cloud-aerosol interactions is of primary importance for accurate climate model projections. The investigation of these interactions in strongly contrasting clean and polluted atmospheric conditions in the Amazon area has been one of the motivations for several field observations, including the airborne Aerosol, Cloud, Precipitation, and Radiation Interactions and DynamIcs of CONvective cloud systems – Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON-CHUVA) campaign based in Manaus, Brazil in September 2014. In this work we combine in situ and remotely sensed aerosol, cloud, and atmospheric radiation data collected during ACRIDICON-CHUVA with regional, online-coupled chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysical properties (droplet number concentration and effective radius). We found agreement between modeled and observed median cloud droplet number concentrations (CDNC) for low values of CDNC, i.e., low levels of pollution. In general, a linear relationship between modeled and observed CDNC with a slope of two was found, which means a systematic underestimation of modeled CDNC as compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations and cloud droplet effective radii (reff) was also underestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN per cm3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Regional background aerosol concentrations were sufficiently high such that the additional CCN emitted from local fires did not cause a notable change in modelled cloud microphysical properties. In addition, we evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, aimed at in situ observations and satellite retrievals. Our study casts doubt on the validity of regional scale modeling studies of the cloud albedo effect in convective situations for polluted situations where the number concentration of CCN is greater than 500 cm−3.

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