Postfrontal nanoparticles at Cape Grim: observations

2009 ◽  
Vol 6 (6) ◽  
pp. 508 ◽  
Author(s):  
John L. Gras ◽  
Salah I. Jimi ◽  
Steven T. Siems ◽  
Paul B. Krummel
Keyword(s):  
Global Climate ◽  
Cloud Droplet ◽  
Condensation Nucleus ◽  
Cold Fronts ◽  
Peak Separation ◽  
Cloud Properties ◽  
Mesoscale Structures ◽  
Counter Efficiency ◽  
Essential Components ◽  
Cape Grim

Environmental context. Clouds and the factors controlling cloud properties are essential components in understanding and accurately predicting global climate change. This work examines nanometre-sized atmospheric particles, particularly bursts of enhanced particle concentrations following cold fronts over the Southern Ocean. The properties of these events have been established to enable modelling of their significance as a source of cloud-droplet-forming nuclei. Abstract. Nanoparticles (diameter <10 nm) were studied in clean maritime air at Cape Grim over a 2-year period. Concentrations were determined using a condensation nucleus counter (CNC) and an ultra-CNC (UCNC), requiring careful treatment of drifts in counter efficiency. This is the first extended examination of nanoparticles following cold fronts and shows that nanoparticle enhancements were present following 94% of 121 cold fronts studied. Typical enhancements were ~100 cm–3 with maxima ~300–500 cm–3, occur 9–11 h after the front and contain multiple peaks with peak-to-peak separation of 8–11 h. Most enhancements were associated with drier conditions, indicative of increased entrainment of free-tropospheric air after the front. The quasi-periodicity of the enhancements may be related to mesoscale structures in cloud fields following fronts but this requires testing. This quantification of event properties allows evaluation of the significance of these events for the cloud nucleating particle (CCN) population.

A short climatology of nanoparticles at the Cape Grim Baseline Air Pollution Station, Tasmania

2007 ◽  
Vol 4 (5) ◽  
pp. 301 ◽  
Author(s):  
S. I. Jimi ◽  
J.L. Gras ◽  
S. T. Siems ◽  
P. B. Krummel
Keyword(s):  
Air Pollution ◽  
Particle Production ◽  
Global Climate ◽  
Number Concentration ◽  
Radiation Balance ◽  
Air Mass ◽  
Air Masses ◽  
Cloud Properties ◽  
Aerosol Sources ◽  
Cape Grim

Environmental context. Atmospheric particles play an important role in the global climate system; they contribute to the radiation balance directly, but they also have an indirect effect by modifying cloud properties and influencing precipitation. Over the Southern Ocean, nanometre-sized particle production is believed to be largely natural, although the processes that lead to these particles are not well understood. This work provides new observations of atmospheric nanoparticles, and shows that they arise from diverse sources of production. Abstract. This paper presents analyses of a two-year record of aerosol measurements made at the Cape Grim Baseline Air Pollution Station (CGBAPS) in Tasmania covering the period 1999 and 2000. The focus of the study is nanoparticles, defined here as particles with diameter Dp, in the range 3 ≤ Dp ≤ 12 nm; with the number concentration determined using two condensation particle counters, a TSI 3025 UCPC (Dp ≥ 3 nm) and a TSI CN3760 (Dp ≥ 12 nm). Total aerosol (Dp ≥ 3 nm) and nanoparticle concentrations were examined for three broad air mass origins, namely ‘Baseline’ or background maritime, continental Australia and Tasmanian air masses. Total median aerosol concentrations in the Baseline, continental and Tasmanian sectors typically ranged from 100 to 900, 1300 to 1900 and 500 to 1200 cm–3, respectively. The median ranges for the nanoparticle concentrations were 50–350 cm–3 in Baseline air, 150–450 cm–3 in continental air and 100–300 cm–3 in Tasmanian air. While the total aerosol concentrations in the three sectors were quite different, the nanoparticle concentrations were less so. Nanoparticle diurnal concentrations showed substantial differences between the three sectors, indicative of different aerosol sources or precursor sources in the regions designated by these wind sectors.

Postfrontal nanoparticles at Cape Grim: impact on cloud nuclei concentrations

2009 ◽  
Vol 6 (6) ◽  
pp. 515 ◽  
Author(s):  
John L. Gras
Keyword(s):  
Growth Rates ◽  
Concentration Ratio ◽  
Marine Boundary Layer ◽  
Cloud Droplet ◽  
Particle Growth ◽  
Particle Removal ◽  
Cloud Properties ◽  
Droplet Nuclei ◽  
Background Particle ◽  
Cape Grim

Environmental context. Accurate prediction of climate change requires good knowledge of all the contributing processes; those processes controlling clouds and cloud properties are of particular importance. In this study the growth of bursts of nanometre-sized particles observed following cold fronts over the Southern Ocean was modelled to assess their importance as a source of cloud droplet nuclei. This showed that these post-frontal events were responsible for ~8% of the cloud nucleus population in winter but much less in summer. Abstract. Aerosol removal and growth rates were determined for the Cape Grim marine boundary layer (MBL) using local observations. Background particle growth rates, estimated using replacement of condensable sulfur species lost to particle removal are 0.04 nm h–1 (winter) and 0.17 nm h–1 (summer) and for post-frontal nucleation-events growth rates determined using evolution of the concentration ratio of particles with diameter >3 nm and 11 nm are ~0.3–0.4 nm h–1, consistent with reported high-latitude events. A box model using region-specific loss and growth rates predicts free-troposphere/MBL N3 ratios of 1.3–2.1 and 2.4–2.5 for background and event growth rates, compared with observations in the range of 0.7–1.5. Post-frontal nucleation events were found to contribute from <1 to ~8% of the CCN population depending on season and growth rate. However, these events help maintain the MBL Aitken population, contributing up to ~30%.

scholarly journals A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck

2010 ◽  
Vol 10 (14) ◽  
pp. 6527-6536 ◽  
Author(s):  
M. A. Brunke ◽  
S. P. de Szoeke ◽  
P. Zuidema ◽  
X. Zeng
Keyword(s):  
Diurnal Cycle ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Cloud Fraction ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Southeast Pacific ◽  
Cloud Thickness

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003–2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP~h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP~h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h~LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85° W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20° S, 75° W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.

scholarly journals Cloud droplet activation of secondary organic aerosol is mainly controlled by molecular weight, not water solubility

2018 ◽  
Author(s):  
Jian Wang ◽  
John E. Shilling ◽  
Jiumeng Liu ◽  
Alla Zelenyuk ◽  
David M. Bell ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Water Solubility ◽  
Global Climate ◽  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Average Molecular Weight ◽  
Cloud Droplet ◽  
Oxidation Level ◽  
Organic Species ◽  
Droplet Activation

Abstract. Aerosol particles strongly influence global climate by modifying the properties of clouds. An accurate assessment of the aerosol impact on climate requires knowledge of the concentration of cloud condensation nuclei (CCN), a subset of aerosol particles that can activate and form cloud droplets in the atmosphere. Atmospheric particles typically consist of a myriad of organic species, which frequently dominate the particle composition. As a result, CCN concentration is often a strong function of the hygroscopicity of organics in the particles. Earlier studies showed organic hygroscopicity increases nearly linearly with oxidation level. Such increase of hygroscopicity is conventionally attributed to higher water solubility for more oxidized organics. By systematically varying the water content of activating droplets, we show that for the majority of secondary organic aerosols (SOA), essentially all organics are dissolved at the point of droplet activation. Therefore, the organic hygroscopicity is not limited by solubility, but is dictated mainly by the molecular weight of organic species. Instead of increased water solubility as previously thought, the increase of the organic hygroscopicity with oxidation level is largely because (1) SOA formed from smaller precursor molecules tend to be more oxidized and have lower average molecular weight and (2) during oxidation, fragmentation reactions reduce average organic molecule weight, leading to increased hygroscopicity. A simple model of organic hygroscopicity based on molecular weight, oxidation level, and volatility is developed, and it successfully reproduces the variation of SOA hygroscopicity with oxidation level observed in the laboratory and field studies.

scholarly journals CLOUD DROPLET FORMATION UTILIZING ATMOSPHERIC POLLUTANT (NH4) 2SO4 AS CONDENSATION NUCLEUS

1998 ◽  
Vol 6 ◽  
pp. 91-96
Author(s):  
Sadataka SHIBA ◽  
Taku KATO ◽  
Yushi HIRATA ◽  
Shunsaku YAGI
Keyword(s):  
Cloud Droplet ◽  
Condensation Nucleus ◽  
Droplet Formation ◽  
Atmospheric Pollutant

scholarly journals A Bootstrap Technique for Testing the Relationship between Local-Scale Radar Observations of Cloud Occurrence and Large-Scale Atmospheric Fields

2006 ◽  
Vol 63 (11) ◽  
pp. 2813-2830 ◽  
Author(s):  
Roger Marchand ◽  
Nathaniel Beagley ◽  
Sandra E. Thompson ◽  
Thomas P. Ackerman ◽  
David M. Schultz
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Initial Conditions ◽  
Global Climate ◽  
Stable State ◽  
Local Scale ◽  
Global Climate Models ◽  
Scale Model ◽  
Synoptic Scale ◽  
Cloud Properties

Abstract A classification scheme is created to map the synoptic-scale (large scale) atmospheric state to distributions of local-scale cloud properties. This mapping is accomplished by a neural network that classifies 17 months of synoptic-scale initial conditions from the rapid update cycle forecast model into 25 different states. The corresponding data from a vertically pointing millimeter-wavelength cloud radar (from the Atmospheric Radiation Measurement Program Southern Great Plains site at Lamont, Oklahoma) are sorted into these 25 states, producing vertical profiles of cloud occurrence. The temporal stability and distinctiveness of these 25 profiles are analyzed using a bootstrap resampling technique. A stable-state-based mapping from synoptic-scale model fields to local-scale cloud properties could be useful in three ways. First, such a mapping may improve the understanding of differences in cloud properties between output from global climate models and observations by providing a physical context. Second, this mapping could be used to identify the cause of errors in the modeled distribution of clouds—whether the cause is a difference in state occurrence (the type of synoptic activity) or the misrepresentation of clouds for a particular state. Third, robust mappings could form the basis of a new statistical cloud parameterization.

scholarly journals A critical look at spatial scale choices in satellite-based aerosol indirect effect studies

2010 ◽  
Vol 10 (23) ◽  
pp. 11459-11470 ◽  
Author(s):  
B. S. Grandey ◽  
P. Stier
Keyword(s):  
Radiative Forcing ◽  
Spatial Scales ◽  
Cloud Droplet ◽  
Spatial Variations ◽  
Opposite Pattern ◽  
Cloud Properties ◽  
Methodological Errors ◽  
Albedo Effect ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Analysing satellite datasets over large regions may introduce spurious relationships between aerosol and cloud properties due to spatial variations in aerosol type, cloud regime and synoptic regime climatologies. Using MODerate resolution Imaging Spectroradiometer data, we calculate relationships between aerosol optical depth τa derived liquid cloud droplet effective number concentration Ne and liquid cloud droplet effective radius re at different spatial scales. Generally, positive values of dlnNedlnτa are found for ocean regions, whilst negative values occur for many land regions. The spatial distribution of dlnredlnτa shows approximately the opposite pattern, with generally postive values for land regions and negative values for ocean regions. We find that for region sizes larger than 4° × 4°, spurious spatial variations in retrieved cloud and aerosol properties can introduce widespread significant errors to calculations of dlnNedlnτa and dlnredlnτa. For regions on the scale of 60° × 60°, these methodological errors may lead to an overestimate in global cloud albedo effect radiative forcing of order 80% relative to that calculated for regions on the scale of 1° × 1°.

scholarly journals Composite Analysis of Winter Cyclones in a GCM: Influence on Climatological Humidity

2006 ◽  
Vol 19 (9) ◽  
pp. 1652-1672 ◽  
Author(s):  
Mike Bauer ◽  
Anthony D. Del Genio
Keyword(s):  
Water Vapor ◽  
General Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Circulation Model ◽  
Cloud Properties ◽  
Frontal Zones ◽  
Goddard Institute ◽  
Ageostrophic Circulation

Abstract The role of midlatitude baroclinic cyclones in maintaining the extratropical winter distribution of water vapor in an operational global climate model is investigated. A cyclone identification and tracking algorithm is used to compare the frequency of occurrence, propagation characteristics, and composite structure of 10 winters of storms in the Goddard Institute for Space Studies general circulation model (GCM) and in two reanalysis products. Cyclones are the major dynamical source of water vapor over the extratropical oceans in the reanalyses. The GCM produces fewer, generally weaker, and slower-moving cyclones than the reanalyses and is especially deficient in storms associated with secondary cyclogenesis. Composite fields show that GCM cyclones are shallower and drier aloft than those in the reanalyses and that their vertical structure is less tilted in the frontal region because of the GCM’s weaker ageostrophic circulation. This is consistent with the GCM’s underprediction of midlatitude cirrus. The GCM deficiencies do not appear to be primarily due to parameterization errors; the model is too dry despite producing less storm precipitation than is present in the reanalyses and in an experimental satellite precipitation dataset, and the weakness and shallow structure of GCM cyclones is already present at storm onset. These shortcomings may be common to most climate GCMs that do not resolve the mesoscale structure of frontal zones, and this may account for some universal problems in climate GCM midlatitude cloud properties.

scholarly journals Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions

2020 ◽  
Vol 20 (11) ◽  
pp. 6291-6303
Author(s):  
Guy Dagan ◽  
Philip Stier
Keyword(s):  
Initial Conditions ◽  
Cloud Droplet ◽  
Large Data ◽  
Data Set ◽  
Cloud Properties ◽  
Large Spread ◽  
The Difference ◽  
Ice Content ◽  
Aerosol Effects ◽  
Longwave Flux

Abstract. Aerosol effects on cloud properties and the atmospheric energy and radiation budgets are studied through ensemble simulations over two month-long periods during the NARVAL campaigns (Next-generation Aircraft Remote-Sensing for Validation Studies, December 2013 and August 2016). For each day, two simulations are conducted with low and high cloud droplet number concentrations (CDNCs), representing low and high aerosol concentrations, respectively. This large data set, which is based on a large spread of co-varying realistic initial conditions, enables robust identification of the effect of CDNC changes on cloud properties. We show that increases in CDNC drive a reduction in the top-of-atmosphere (TOA) net shortwave flux (more reflection) and a decrease in the lower-tropospheric stability for all cases examined, while the TOA longwave flux and the liquid and ice water path changes are generally positive. However, changes in cloud fraction or precipitation, that could appear significant for a given day, are not as robustly affected, and, at least for the summer month, are not statistically distinguishable from zero. These results highlight the need for using a large sample of initial conditions for cloud–aerosol studies for identifying the significance of the response. In addition, we demonstrate the dependence of the aerosol effects on the season, as it is shown that the TOA net radiative effect is doubled during the winter month as compared to the summer month. By separating the simulations into different dominant cloud regimes, we show that the difference between the different months emerges due to the compensation of the longwave effect induced by an increase in ice content as compared to the shortwave effect of the liquid clouds. The CDNC effect on the longwave flux is stronger in the summer as the clouds are deeper and the atmosphere is more unstable.

scholarly journals Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

2017 ◽  
Vol 10 (12) ◽  
pp. 4747-4759 ◽  
Author(s):  
Rintaro Okamura ◽  
Hironobu Iwabuchi ◽  
K. Sebastian Schmidt
Keyword(s):  
Deep Learning ◽  
Radiative Transfer ◽  
Optical Thickness ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Optical Remote Sensing ◽  
Transfer Effects ◽  
Cloud Properties

Abstract. Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.

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