scholarly journals Supplementary material to "Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data"

2017 ◽  
Author(s):  
Daniel T. McCoy ◽  
Frida A.-M. Bender ◽  
Daniel P. Grosvenor ◽  
Johannes K. Mohrmann ◽  
Dennis L. Hartmann ◽  
...  
Keyword(s):  
Satellite Data ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Droplet Number Concentration ◽  
Supplementary Material

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 Supplementary material to "On the Relationship Between Cloud Water Composition and Cloud Droplet Number Concentration"

2020 ◽  
Author(s):  
Alexander B. MacDonald ◽  
Ali Hossein Mardi ◽  
Hossein Dadashazar ◽  
Mojtaba Azadi Aghdam ◽  
Ewan Crosbie ◽  
...  
Keyword(s):  
Cloud Droplet ◽  
Cloud Water ◽  
Number Concentration ◽  
Water Composition ◽  
Cloud Droplet Number Concentration ◽  
Supplementary Material ◽  
The Relationship

scholarly journals New Particle Formation in the South Aegean Sea during the Etesians: importance for CCN production and cloud droplet number

2016 ◽  
Author(s):  
P. Kalkavouras ◽  
E. Bossioli ◽  
S. Bezantakos ◽  
A. Bougiatioti ◽  
N. Kalivitis ◽  
...  
Keyword(s):  
Water Vapor ◽  
Cloud Droplet ◽  
Aegean Sea ◽  
Particle Formation ◽  
Number Concentration ◽  
Cloud Formation ◽  
Particle Nucleation ◽  
New Particle Formation ◽  
Cloud Droplet Number Concentration ◽  
Measurement Period

Abstract. We examine the concentration levels and size distribution of submicron aerosol particles along with the concentration of trace gases and meteorological variables over the central (Santorini) and south Aegean Sea (Crete) from 15 to 28 July 2013, a period that includes Etesian events and moderate northern winds. Particle nucleation bursts were recorded during the Etesian flow at both stations, with those observed at Santorini reaching up to 1.5 × 104 particles cm−3. On Crete (at Finokalia station), the fraction of nucleation-mode particles was diminished, but a higher number of Aitken-mode was observed as a result of the downward mixing and photochemistry. Aerosol and photochemical pollutants covaried throughout the measurement period: lower concentrations were observed during the period of strong Etesian flow (e.g. 43–70 ppbv for ozone, 1.5–5.7 μg m−3 for sulfate), but were substantially enhanced during the period of moderate winds (i.e., increase of up to 32 % for ozone, and 140 % for sulfate). To understand how new particle formation (NPF) affects cloud formation, we quantify its impact on the CCN levels and cloud droplet number concentration. We find that NPF can double CCN number (at 0.1 % supersaturation) but the resulting strong competition for water vapor in cloudy updrafts decreases maximum supersaturation by 14 % and augments the potential droplet number only by 12 %. Therefore, although NPF events may strongly elevate CCN numbers, the relative impacts on cloud droplet number (compared to pre-event levels) is eventually limited by water vapor availability and depends on the prevailing cloud formation dynamics and the aerosol levels associated with the background in the region.

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 Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations

2017 ◽  
Vol 17 (16) ◽  
pp. 9815-9836 ◽  
Author(s):  
Ralf Bennartz ◽  
John Rausch
Keyword(s):  
Cloud Droplet ◽  
Number Concentration ◽  
Error Sources ◽  
Screening Criteria ◽  
Warm Cloud ◽  
Optimal Screening ◽  
Regional Estimates ◽  
Cloud Droplet Number Concentration ◽  
Observation Geometry ◽  
Made In

Abstract. We present and evaluate a climatology of cloud droplet number concentration (CDNC) based on 13 years of Aqua-MODIS observations. The climatology provides monthly mean 1 × 1° CDNC values plus associated uncertainties over the global ice-free oceans. All values are in-cloud values, i.e. the reported CDNC value will be valid for the cloudy part of the grid box. Here, we provide an overview of how the climatology was generated and assess and quantify potential systematic error sources including effects of broken clouds, and remaining artefacts caused by the retrieval process or related to observation geometry. Retrievals and evaluations were performed at the scale of initial MODIS observations (in contrast to some earlier climatologies, which were created based on already gridded data). This allowed us to implement additional screening criteria, so that observations inconsistent with key assumptions made in the CDNC retrieval could be rejected. Application of these additional screening criteria led to significant changes in the annual cycle of CDNC in terms of both its phase and magnitude. After an optimal screening was established a final CDNC climatology was generated. Resulting CDNC uncertainties are reported as monthly-mean standard deviations of CDNC over each 1 × 1° grid box. These uncertainties are of the order of 30 % in the stratocumulus regions and 60 to 80 % elsewhere.

scholarly journals Modelling the relationship between liquid water content and cloud droplet number concentration observed in low clouds in the summer Arctic and its radiative effects

2020 ◽  
Vol 20 (1) ◽  
pp. 29-43
Author(s):  
Joelle Dionne ◽  
Knut von Salzen ◽  
Jason Cole ◽  
Rashed Mahmood ◽  
W. Richard Leaitch ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Water Content ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Number Concentration ◽  
Radiative Effect ◽  
Low Clouds ◽  
Cloud Radiative Effect ◽  
Cloud Droplet Number Concentration

Abstract. Low clouds persist in the summer Arctic with important consequences for the radiation budget. In this study, we simulate the linear relationship between liquid water content (LWC) and cloud droplet number concentration (CDNC) observed during an aircraft campaign based out of Resolute Bay, Canada, conducted as part of the Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments study in July 2014. Using a single-column model, we find that autoconversion can explain the observed linear relationship between LWC and CDNC. Of the three autoconversion schemes we examined, the scheme using continuous drizzle (Khairoutdinov and Kogan, 2000) appears to best reproduce the observed linearity in the tenuous cloud regime (Mauritsen et al., 2011), while a scheme with a threshold for rain (Liu and Daum, 2004) best reproduces the linearity at higher CDNC. An offline version of the radiative transfer model used in the Canadian Atmospheric Model version 4.3 is used to compare the radiative effects of the modelled and observed clouds. We find that there is no significant difference in the upward longwave cloud radiative effect at the top of the atmosphere from the three autoconversion schemes (p=0.05) but that all three schemes differ at p=0.05 from the calculations based on observations. In contrast, the downward longwave and shortwave cloud radiative effect at the surface for the Wood (2005b) and Khairoutdinov and Kogan (2000) schemes do not differ significantly (p=0.05) from the observation-based radiative calculations, while the Liu and Daum (2004) scheme differs significantly from the observation-based calculation for the downward shortwave but not the downward longwave fluxes.

scholarly journals Improvement of airborne retrievals of cloud droplet number concentration of trade wind cumulus using a synergetic approach

2019 ◽  
Vol 12 (3) ◽  
pp. 1635-1658 ◽  
Author(s):  
Kevin Wolf ◽  
André Ehrlich ◽  
Marek Jacob ◽  
Susanne Crewell ◽  
Martin Wirth ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Base ◽  
Trade Wind ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Research Aircraft ◽  
Cloud Droplet Number Concentration

Abstract. In situ measurements of cloud droplet number concentration N are limited by the sampled cloud volume. Satellite retrievals of N suffer from inherent uncertainties, spatial averaging, and retrieval problems arising from the commonly assumed strictly adiabatic vertical profiles of cloud properties. To improve retrievals of N it is suggested in this paper to use a synergetic combination of passive and active airborne remote sensing measurement, to reduce the uncertainty of N retrievals, and to bridge the gap between in situ cloud sampling and global averaging. For this purpose, spectral solar radiation measurements above shallow trade wind cumulus were combined with passive microwave and active radar and lidar observations carried out during the second Next Generation Remote Sensing for Validation Studies (NARVAL-II) campaign with the High Altitude and Long Range Research Aircraft (HALO) in August 2016. The common technique to retrieve N is refined by including combined measurements and retrievals of cloud optical thickness τ, liquid water path (LWP), cloud droplet effective radius reff, and cloud base and top altitude. Three approaches are tested and applied to synthetic measurements and two cloud scenarios observed during NARVAL-II. Using the new combined retrieval technique, errors in N due to the adiabatic assumption have been reduced significantly.

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.

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