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ARCPAC: Aerosol, Radiation,
and Cloud Processes
affecting Arctic Climate
Science and Implementation Plan
A Project of NOAA’s Climate Forcing and Air Quality
Programs for the International Polar Year 2008
ARCPAC: Aerosol, Radiation and Cloud Processes affecting Arctic Climate
A NOAA Climate Forcing Program Project for the International Polar Year 2008
Global temperature records show a statistically significant warming in the last
century, with most of the change attributed to anthropogenically emitted greenhouse
gases and associated climate feedbacks (Fig. 1). Temperature increases in the Arctic
exceed the global annual average (Fig. 2), with maximum warming occurring in winter
Closely linked to the observed and modeled warming is an observed decrease in
seasonal Arctic sea ice coverage and thickness. The minimum summertime extent of sea
ice is decreasing significantly (Fig. 3; Comiso, 2006), and this reduction now clearly
exceeds that expected from natural oceanographic and meteorological oscillations
(Johannessen et al., 2004; Francis and Hunter, 2006). Some models predict a fully icefree summertime Arctic Ocean (Winton, 2006), with attendant disruptions to Arctic
ecosystems, ocean circulation, and global climate. However, modeling of the Arctic
climate system is difficult due to complex and sensitive feedbacks (Serreze and Francis,
2006a,b) and many climate simulations struggle to replicate historical precipitation,
cloudiness, and sea ice properties (Walsh et al., 2002). Simulations of future climates
result in substantial model-to-model variability in Arctic climate parameters such as sea
ice extent and thickness, indicating that some important processes are not being
adequately described or simply are not included in the simulations (Winton, 2006).
Analyses of observations and recent climate simulations suggest that, in addition
to greenhouse gas-induced warming and feedbacks, Arctic warming may also be caused
by shorter-lived climate forcing agents. In particular, four processes have been
postulated to contribute significantly to observed atmospheric warming in the Arctic and
reductions in sea ice there. These processes include:
1) direct warming of the lower troposphere by the absorption of solar radiation and
IR emission by aerosol particles from anthropogenic and biomass burning sources
(e.g., Treffeisen, 2005; Ritter et al., 2005), 3
2) changes in snow melt due to deposition of soot (light-absorbing carbon) to the
surface in springtime (Hansen and Nazarenko, 2004; Flanner et al., 2007),
3) increases in IR emissivity of wintertime and springtime clouds in the Arctic due
to the effects of anthropogenic aerosol particles on cloud properties (Lubin and
Vogelmann, 2006; Garrett and Zhao, 2006), and
4) direct radiative effects of tropospheric ozone in the Arctic (Mickley et al., 1999;
Hansen et al., 2005).
During the International Polar Year of 2008, NOAA will engage in an airborne
field measurement campaign targeted at improving understanding of these four climaterelevant processes. This effort will be focused on direct measurements of properties and
processes that can be used to reduce uncertainty in radiation and climate models. The
measurements will be made in the Alaskan Arctic to closely coordinate with remotesensing and in situ observations planned for aircraft and ground sites in the vicinity of
Figure 1. Global-average radiative forcing (RF) estimates and ranges in 2005 for
anthropogenic forcing agents, the typical geographical extent of these forcings, and the
level of scientific understanding, LOSU (Intergovernmental Panel on Climate Change,
Figure 2. Seasonally separated measured rate of change of 2-m atmospheric temperatures
N and the global mean change (horizontal line). From Shindell et al., 2006.
Figure 3. Monthly anomalies of the area of minimum extent of Arctic sea ice from 1978
to 2005. Thick line is 12-month running mean; thin straight line is least-squares linear
fit. From Serreze and Francis, 2006a, courtesy of National Snow and Ice Data Center,
Boulder, CO. 5
Climate processes in the Arctic
The Arctic undergoes significant annual changes in its energy budget which are
driven largely by the seasonal cycle in solar radiation, surface sensible energy fluxes, and
albedo. Surface energy fluxes are controlled in part by the presence and extent of a layer
of sea ice and surface snow that partially insulate the Arctic Ocean from the overlying
atmosphere in winter and spring. During summer the snow melts, and the sea ice retreats
in extent, thickness, and areal density, allowing significant sensible and latent energy
fluxes between the ocean and atmosphere. Snow on top of sea ice is prevalent throughout
the late fall, winter and spring, but is especially important radiatively during the
springtime months when it increases surface albedo and prevents the relatively dark,
underlying sea-ice from absorbing solar radiation as the sun begins to rise. Also driving
tropospheric energetics, and coupled with the sea ice annual cycle, are variations in lower
tropospheric clouds. These clouds warm the surface in the dark winter months by IR
absorption and re-emission, and cool the surface in the summertime by reflection of solar
When coupled with ocean circulations, atmospheric dynamics and meteorology,
sea ice physics and wind forcings on sea-ice movement, the climate system in the Arctic
is seen to be a dynamic and complex system with many potential nonlinear feedbacks
both within the Arctic and with the global climate system. These feedbacks will modify
the climate effects of the well-documented phenomenon of large-scale air pollution
within the northern polar regions, known as Arctic haze.
Pilots and surface sites in the Arctic have long reported the annual occurrence of
visibility-reducing aerosol hazes in the Arctic in springtime. An extensive literature has
documented the chemical and optical characteristics of these hazes, and a climatology of
some key parameters extending more than 20 years has been developed for a few Arctic
sites (e.g., Quinn et al., 2007). The aerosol is composed predominantly of sulfate and sea
salt, with lesser contributions from nitrate, soot, soil and trace elements, and organic
compounds (e.g., Quinn et al., 2002). There is a pronounced seasonal cycle to both
intensive (e.g., type, size, composition) and extensive (e.g., mass loading, number 6
Figure 4. Time series of monthly averaged particulate nitrate and non-sea-salt sulfate
concentrations in μg S m
and μg N m
, respectively, for a) Barrow, Alaska and b) Alert,
Canada (from Quinn et al., 2007, data courtesy of the Canadian National Atmospheric
Chemistry (NAtChem) Database and Analysis System and NOAA PMEL
Figure 5. Monthly averaged a) light scattering and b) absorption at 550 nm by sub-10
micron aerosol at Barrow, Alaska (Mm
) and c) black carbon mass concentration (ng
) at Alert, Canada (from Quinn et al., 2007, data courtesy of NOAA GMD and the
Canadian National Atmospheric Chemistry (NAtChem) Database and Analysis System). 7
concentration) aerosol properties at surface sites throughout the Arctic (Figs. 4, 5).
During the time of maximum mass concentration—the late winter and early spring—
much of the aerosol is anthropogenic. There is some more limited evidence for a slightly
different seasonal cycle to Arctic haze properties aloft, with higher concentrations
occurring aloft later in the spring than at the surface (Scheuer et al., 2003). In addition,
aerosol layers associated with biomass burning sources have been observed in the Arctic
middle and upper troposphere in summer (Brock et al., 1989; Stohl, 2006).
By argument of isentropic transport, as well as more sophisticated analyses, the
dominant sources of the springtime surface aerosol maximum are seen to lie poleward of
the Arctic front (Fig. 6). On average, the largest contributions are believed to come from
northern Europe and the Russian Arctic, where large industrial complexes have long
operated (Sharma et al., 2006; Stohl, 2006). With declines in former Soviet Union
emissions, soot concentrations have fallen in the Arctic in springtime (e.g., Fig. 5, Quinn
et al., 2007). Because most industrial sources in North America lie southward of the
mean position of the Arctic front, and since advection from these sources to the Arctic
involves transport through the meteorologically active North Atlantic region,
Figure 6. Map showing mean positions of Arctic front in winter and summer, and main
transport pathways for pollution from the midlatitudes to the Arctic (Arctic Monitoring
and Assessment Programme, 2006). 8
North American sources are not believed to contribute more than occasionally to Arctic
haze (Stohl, 2006). Koch and Hansen (2005) suggest a significant contribution to
springtime Arctic soot loadings from industrialized regions of northeastern China, but
Stohl (2006) found this source region to be only a small contributor to the Arctic soot
II. Major uncertainties regarding atmospheric climate forcing in the Arctic
Model sensitivity studies indicate that, in addition to long-lived greenhouse gases
(LLGG), short-lived pollutants may play an important role in climate forcing in the
Arctic. However, despite more than 30 years of study of the sources and chemical
characteristics of Arctic haze, the climate-relevant properties of the aerosol are
inadequately characterized. As a consequence, climate models are not well constrained,
and major uncertainties remain in the magnitude of direct and indirect forcing by aerosols
in the Arctic and which anthropogenic sources contribute most to those forcings. As
noted previously, there are four primary processes not associated with LLGG that have
been identified as being possibly significant to Arctic climate.
Direct radiative forcing by aerosol particles
Direct radiative forcing refers to perturbations to the climate caused by the
interaction of aerosol particles with visible radiation. The direct radiative effects of
Arctic aerosols depend strongly on the single scatter albedo of the particles. Arctic haze
aerosol particles contain significant concentrations of carbon soot (Fig. 4), which is the
principal absorber of visible solar radiation, and which leads to a particle single scatter
ing albedo (ratio of scattered light to scattered and absorbed light) of ~0.94 (Delene and
Ogren, 2002). Quinn et al. (2007) calculated a net radiative heating of 1.6 W m
Arctic haze layer, with a surface cooling of 0.9 W m
due to the presence of the
scattering and absorbing haze above the high-albedo surface. The haze layer was
calculated to warm by 0.25 K day
, which is consistent with other recently determined
heating rates of 0.1-0.5 K day
(Treffeissen et al., 2005). Heating of the surface by 9
infrared emission from the warmer atmosphere was not considered by Quinn et al., but
may compensate for some of the surface cooling (Ritter et al., 2005).
The infrared and dynamical consequences of atmospheric heating by an absorbing
aerosol will depend in part on the vertical distribution of the aerosol, which is poorly
characterized in the Arctic. Repeated vertical profiles during the NSF-sponsored TOPSE
project (Scheuer et al., 2002), and SAGE-II and -III satellite-based extinction
observations in the middle and upper Arctic troposphere (Treffeisen et al., 2006) suggest
that hazes aloft may be more prevalent later in the Arctic spring, while surface hazes may
dominate during winter and early spring. This shift in vertical structure may reflect a
shift in source region, with more southern sources at higher potential temperatures
contributing to the higher layers (Stohl, 2006). A seasonal change in removal processes
may also be a factor, as near-surface clouds and precipitation become more prevalent as
springtime progresses. As a consequence, the optical properties of the hazes may differ
both seasonally and with altitude.
The single scattering albedo of the Arctic haze aerosol has been reported from the
NOAA ESRL/GMD site at Barrow, Alaska since 1988 (Delene and Ogren, 2002; Quinn
et al., 2007). During the January-April peak haze season, monthly median single scatter
ing albedos ranged from 0.93 to 0.96, indicating a significant absorbing component to the
particles. However, these measurements were obtained at relative humidities <40%, and
do not reflect possible ambient enhancements in both scattering and absorption due to the
hygroscopic growth of particles under ambient conditions. Measurements of the
dependence of aerosol light scattering on relative humidity began at the NOAA Barrow
ground site in 2006 and will continue during and after the IPY. Aerosol measurements at
the NOAA Barrow observatory will be further enhanced in 2007 with the addition of
instruments for measuring the number concentration of cloud condensation nuclei as a
function of water supersaturation, and of the size distribution of particles in the range of
15-800 nm diameter.
The geographical source of the carbon soot that causes the observed optical
absorption is in question. Koch and Hansen (2005) used a general circulation model to
determine that industrial emissions and biofuel combustion in southern Asia are a major
source of soot to the Arctic. This finding has been disputed by Stohl (2006), who used a 10
particle dispersion and emission inventory model to identify Europe and northern Asia as
the main source of Arctic soot in springtime, both at the surface and aloft. There are only
a few Arctic sites at which regular measurements of aerosol absorption are made, with
those at the Barrow observatory (Quinn et al., 2007) and the Canadian Arctic site of Alert
(Sharma et al., 2004; 2005) having the longest records. To our knowledge there is no
information in the Arctic on the soot mass absorption cross-section (MAC, absorption per
unit mass of soot), which is necessary to relate modeled soot mass concentrations to
optical absorption. The state of understanding of the MAC is poor (Bond et al., 2006),
and new measurement techniques need to be applied to determine its mean value and
variability in the atmosphere.
Soot deposition to snow
Small reductions in the albedo of Arctic snow to solar radiation are calculated to
have globally significant climate effects (Fig. 1). Analysis of light absorbing material in
remote Arctic snow samples indicates that soot (light absorbing carbon) particles are
sufficient to reduce snow albedo by several percent (Warren and Wiscombe, 1980). A
recent global climate simulation of the atmospheric transport and deposition of soot to
Arctic snow was coupled with a detailed snow physics and radiation model (Flanner et
al., 2007). The perturbations to Arctic climate included shifting the peak in the snowmelt
season to almost a month earlier in springtime, limited primarily by available sunlight.
As a result of earlier snowmelt, the Arctic sea-ice underneath absorbed more solar
radiation and melted earlier, with resulting Arctic-wide temperature increases of >2 K.
As already noted for the case of direct radiative forcing by aerosols, the soot
budget in global chemical transport and climate models is poorly constrained (Bond et
al., 2004). The extreme stability of the Arctic lower troposphere further complicates the
linkage between soot mass concentrations in air and those in snow. Cloud nucleation/
precipitation scavenging is the primary mechanism that removes soot from the
atmosphere to the snow surface under the stable meteorological conditions prevalent
under the Arctic (Noone and Clarke, 1988). If soot is present in particles that are
effective ice nuclei (IN), it may be preferentially present in cloud ice particles. However,
measured concentrations of IN are a few to a few tens per liter of air, indicating that 11
incorporation of additional soot into snowfall by cloud droplet riming or aerosol
scavenging is necessary to achieve observed concentrations of soot in snow of tens to
hundreds of ppbm. These processes are dependent upon the phase of the cloud particles
(liquid water, ice, or a mixture of the two), details of the soot size distribution, and the
inclusion of the soot in cloud droplets or ice crystals during formation.
Indirect aerosol forcing
The aerosol indirect effect on clouds typically causes a cooling of the Earth’s
surface by increasing the reflection of visible solar radiation. The potential indirect effect
in the Arctic is especially large because of the significant cloud radiative couplings with
energetics and dynamics (e.g., Vavrus, 2004). Strong surface temperature inversions in
the Arctic persist throughout the diurnal cycle, producing a unique situation for cloud
radiative effects. When low clouds are warmer than the surface, then infrared radiation
from the clouds warms the surface. Measurements in the Arctic can therefore provide
significant tests of the infrared portion of the indirect effect.
Low-level boundary layer clouds are typical in the Arctic for all seasons [Curry et
al., 1996]. Despite the cold temperatures in the Arctic these clouds are typically mixedphase, even in winter and spring [Pinto, 1998; Intrieri et al., 2002]. The phase
distribution of condensed water is a fundamental microphysical property that affects the
radiative properties of Arctic clouds; detailed cloud-resolving model studies have shown
that by increasing IN number density by 2-3 times, a largely liquid stratus deck can be
transformed into a broken, optically-thin ice cloud system [Harrington et al., 1999; Jiang
et al., 2000; Harrington and Olsson, 2001]. The resulting ice cloud has a much lower
number density of particles; these sparse, relatively large ice crystals reduce the cloud
emissivity, which decreases the cloud’s warming potential, and settle relatively rapidly,
thereby initiating precipitation and reducing the lifetime of the cloud. Lynch et al. 
found that including an IN parameterization increased precipitation by as much as 50%
and cooled the surface air temperature by up to 5
C over the baseline simulation without
ice microphysics. 12
Figure 7. Spectral emissivity from a radiative transfer calculation for an Arctic cloud
with constant liquid water content and variable effective radius (Lubin and Vogelmann,
Clouds in the springtime lower Arctic troposphere are often optically thin and
have low droplet number concentrations (<30 cm
, Garrett and Zhao, 2006). Arctic haze
has been shown to increase the number density of these supercooled liquid cloud droplets
and decrease the droplet effective radii, thereby increasing the cloud longwave emissivity
(Fig. 7, Lubin and Vogelmann, 2006). However, the Arctic haze may also contribute
more (or less) IN, increasing (decreasing) the rate of cloud glaciation, which reduces
(increases) cloud longwave emissivity. To unravel this complexity we must be able to
describe the relative fractions of CCN and IN in the aerosol population for a given water
vapor supersaturation; this ratio may vary significantly as it is sensitive to the distribution
and mixing state of the particle chemical composition, which is constantly evolving as the
aerosol population ages and interacts with fresh emissions, both in and out of cloud.
Processes governing ozone abundance
Depletion of ozone in the arctic boundary layer occurs when bromine compounds
are activated by sunlight in the spring. The duration and extent of these events may
change with a changing climate and provide a feedback to ozone radiative forcing (Fig.
8). A full study of ozone production and loss rates is beyond the scope of this study. 13
Instead, the focus will be to improve the understanding of halogen initiated
photochemistry that destroys ozone. Although these events have been regularly observed
(e.g. Ridley et al., 2003), uncertainties remain regarding the source of the halogen
radicals and their transport (Simpson et al., 2007). Furthermore, vertically resolved
measurements have not been achieved for most of the halogen species involved in spring
time arctic boundary layer catalytic ozone destruction. Fast response measurements of
halogen species will be used to determine their vertical distribution. These measurements
can then be compared with model results (e.g. Lehrer et al, 2004) to test the
understanding of ozone depletion events and their possible relationship to radiative
The combination of sea salt (Quinn et al, 2002) and conditions favorable to N2O5
formation (Tie et al, 2003) in the spring time arctic may make ClNO2, which can be
formed from reactions of N2O5 on chloride-containing aerosol particles, important to
polar boundary layer ozone. The specific halogen chemistry that we will examine
follows from the conversion of N2O5 to ClNO2. ClNO2 is photolyzed relatively rapidly
(0.5 to 1 hr lifetime), even under Arctic springtime conditions, to form NO2 and gasphase Cl atoms. This Cl is highly reactive towards VOCs and O3, forming either HCl or
ClO. The ClO radical reacts with HO2 producing HOCl, which is soluble and will be
taken up on aerosol particles and in droplets. Aqueous HOCl can further react with Cl
to produce the volatile compounds Cl2 and BrCl. BrCl can be photolyzed in the
gas phase, generating Cl and Br atoms, which cycle through the above chemistry again,
catalytically destroying ozone. The HOBr produced in the reaction of BrO with HO2 is
also soluble and will produce Br2 upon reaction with Br
. The species ClNO2, Cl2, BrCl,
Br2, and BrO, along with the extensive aerosol and O3 measurements that will be made
on the WP-3D, will give us the ability to assess the role of ClNO2 in initiating this ozone
destruction chemistry over a wide geographic area.
III. A NOAA-sponsored airborne campaign to investigate climate-relevant
atmospheric processes in the Arctic 14
Scientific questions to be addressed
NOAA will undertake a airborne field experiment, the Aerosol, Radiation, and
Cloud Processes affecting Arctic Climate (ARCPAC) in Alaska in late March and April
of 2008 to address the four major areas of non-greenhouse-gas atmospheric climate
Figure 8. Model predictions of annual mean net radiative forcing by tropospheric ozone
(Kiehl et al., 1999).
processes in the Arctic. A NOAA WP-3D aircraft will be used for this experiment and
will be based at Fairbanks, Alaska (Fig. 9). This experiment will be coordinated with the
POLARCAT activity of the IPY, with the NOAA baseline climate research station at
Barrow, Alaska, and with the intensive operations period executed at the DOE-sponsored
Atmospheric Radiation Measurement site adjacent to NOAA’s Barrow site. Specific
scientific questions to be addressed are listed below.
Q1: What are the chemical, optical, and microphysical characteristics of aerosols in
the Arctic in springtime?
• What is the solar extinction and absorption of the aerosol, and how do these
properties vary with relative humidity?
• What is the mass concentration and size distribution of soot?
• To what extent are soot particles coated with other materials, and do such coatings
influence the radiative and cloud-nucleating properties of the soot particles?
Figure 9. Map showing the area of operaton for ARCPAC. The WP-3D aircraft will be
based in Fairbanks, Alaska. The typical out-and-return range of the aircraft is shown by
the red circle.
• What is the contribution of organic material to the optical and chemical properties to
• How do aerosol concentrations, composition, optical properties, and cloud nucleating
properties above the surface relate to values measured at the surface?
• What is the radiative forcing and resulting atmospheric heating rates due to the
aerosol, and how do these values compare with those derived from spaceborne lidar,
surface lidar, and surface aerosol measurements?
• How do the composition and hygroscopic properties of aerosols relate to chemical
processing estimated from trace gases?
Q2: What are the source types (industrial, urban, biomass/biofuel, dust, sea-salt) of
the aerosol components, and the absorbing components in particular?
• What are the correlations between aerosol components and trace gases?
• How does the composition of the aerosol and trace gases compare to that expected
from transport and emission models such as FLEXPART?
• Does the vertical distribution of aerosol properties reflect differences in source
region, transport, and removal?
• What are the major sources that contribute to atmospheric and surface soot during the
critical springtime warming period?
Q3: What are the microphysical and optical characteristics of optically thin clouds
in the lower Arctic troposphere in springtime, and do pollution particles affect these
• What is the number density of CCN present in aerosol layers and in clean air, and is
there closure between the predicted CCN, from the observed aerosol composition and
• How does the number concentration of CCN, as a function of water supersaturation,
vary as a function of altitude?
• Is the cloud droplet number concentration in liquid clouds consistent with that
predicted from the observed CCN and cloud cooling rate?
• What is the relationship between measured IN concentrations and cloud ice number
concentrations and size?
• What are the measured solar reflectance and transmission, the IR radiance, and the
effective radius of Arctic clouds, and how do these values vary with CCN and IN
• How do directly measured and derived cloud properties compare with remotely
measured and derived parameters at the DOE ARM site?
Q4: What are the concentration of particles that serve as ice nuclei (IN) in
background and polluted air?
• What is the number density of IN present in aerosol layers and in clean air?
• What are the geographic sources of the IN in the Arctic?
Q5: Is soot present in particles that serve as IN and CCN?
• Is soot efficiently scavenged by cloud droplet nucleation, ice crystals, and snowfall?
• What role do coatings on soot particles play in nucleation scavenging and removal of
Q6: What halogen chemistry is occurring during Arctic spring?
• What is the distribution of gas phase chlorine and bromine compounds, especially
• What is the vertical distribution of sea-salt aerosol and what chemical processing has
• What is the relative importance of the sources of O3 in the Arctic and subArctic lower
troposphere in springtime (production vs. stratospheric vs. long-range transport)?
The six science questions lead to specific measurement requirements: 17
R1) The stratified nature of the Arctic lower stratosphere requires airborne and
remote-sensing measurements so that the properties and processes occurring in and
near radiatively important haze layers and stratiform clouds can be investigated.
R2) Because of the vertically stratified and spatially non-uniform distribution of
Arctic haze, fast-response in situ gas- and aerosol-phase instruments are required.
R3) The climatic importance of aerosol optical properties and soot number and
mass require accurate and fast-response measurements of these parameters, along
with measurements of the variation in optical properties with relative humidity.
R4) Because of the strong potential climate interaction between aerosols and cloud
microphysical and radiative properties, detailed cloud microphysical and visible
and infrared radiation measurements are needed. Modeling is essential to interpret
the aerosol, cloud and radiation observations and extrapolate them to climaterelevant scales.
R5) Improving understanding of halogen photochemistry in the Arctic requires
accurate measurement of gas phase halogen species and their vertical distribution,
as well as measurements of ozone and photolytic fluxes.
R6) Transport, chemistry, and climate models are needed to relate the observed
aerosol and gas-phase characteristics to sources and transport mechanisms and to
evaluate their importance.
R7) Because ground sites are essential for developing climatologies and for
understanding the temporal changes in atmospheric processes in the Arctic, short
term airborne studies should be made at locations and times that can be linked to
the surface sites.
Based on scientific questions Q1-Q6 and the measurement requirements R1-R7
that logically follow, NOAA will operate a WP-3D aircraft in the Alaskan Arctic in
spring of 2008 as part of the International Polar Year (IPY). NOAA’s Earth System
Research Laboratory (ESRL) and extramural colleagues have developed a powerful set of
precise and accurate gas- and particle-phase instruments for airborne investigations of air
quality and climate-relevant chemical and microphysical processes ranging in scale from
tens of meters to intercontinental distances. In particular, NOAA has developed new,
sensitive instruments for determining aerosol optical properties, including a cavity
ringdown method for directly measuring aerosol extinction at multiple wavelengths and
its variation with relative humidity. 18
ESRL scientists have also substantially modified, evaluated, tested, and operated
on aircraft a recently developed commercial instrument that measures the number and
mass of individual soot particles and that can determine the amount of condensed coating
on them. NOAA has also developed an unique instrument for measuring the composition
of single aerosol particles and the residue from evaporated cloud particles, and has
optimized a commercial aerosol mass spectrometer for airborne non-refractory aerosol
composition measurements. In addition, the NOAA Aircraft Operations Center has
recently purchased a set of state-of-the-art cloud probes for measuring the number, size,
and shape of cloud and precipitation particles. With the addition of well-tested gas-phase
and radiometric measurements, this payload is ideal for addressing the climate-relevant
scientific questions outlined above (Table 1).
The diverse objectives of the ARCPAC project cannot be met without the
experimental and scientific talents of non-NOAAcolleagues. In particular, measurements
of IN, CCN, bulk aerosol composition, solar spectral irradiance and infrared irradiance,
VOCs, and transport and chemical-transport modeling require equipment and expertise
from researchers from universities, other governmental laboratories, and international
Coordination with other IPY activities
The atmospheric measurement portion of the IPY is coordinated under the Polar
Study Using Aircraft, Remote Sensing, Surface Measurements and Models of Climate,
Chemistry, Aerosols, and Transport (POLARCAT) program (http://zardoz.nilu.no/
~andreas/POLARCAT/). This program links a large number of atmospheric
measurements ranging across the Eurasian, Canadian, and Alaskan Arctic together with
transport, chemistry, and climate models. A partner in POLARCAT is the Indirect and
Semi-Direct Aerosol Campaign (ISDAC) sponsored by the U. S. Department of Energy.
ISDAC is an intensive cloud and aerosol observing program that will be based at the
Atmospheric Radiation Measurement (ARM) site near Barrow, Alaska during April
2008, and which will involve detailed surface remote sensing and airborne measurements
of aerosol and cloud properties. Adjacent to the Barrow ARM site is the NOAA
ESRL/GMD baseline monitoring station. This site will operate a variety of instruments 19
Table 1. Priority instruments for the WP-3D aircraft during ARCPAC.
Size-resolved non-refractory aerosol
Compact time-of-flight aerosol mass
Single particle black carbon Single particle soot photometer
Single particle composition Laser mass spectroscopy
Bulk particle composition Particle-in-liquid sampler, IC
Aerosol size distribution Multiple CPCs, OPCs
(532, 1064 nm), f(RH)
Filter-based aerosol absorption
(467, 530, 660 nm)
Particle soot absorption photometer
Cloud condensation nuclei concentration CCN counter
Liquid water content/Total water content Hot wire probes
Cloud particle size distribution (0.5-50 μm) Forward/back scattering-cloud and aerosol
Cloud particle size distribution (2-50 μm) Forward scattering-cloud droplet probe
Cloud particle size distribution (25-1550 μm),
Photodiode imaging-cloud imaging probe
Ice nuclei concentration IN chamber with detector
Soot incorporation into IN SP2 behind IN chamber in fuselage
Actinic fluxes (near 280-690 nm, ↑ and ↓) Spectral actinic flux radiometer
Spectral irradiance (300-1700 nm, ↑ and ↓) Solar spectral flux radiometer
IR irradiance (4.5-42 µm, ↑ and ↓) Pyrgeometers
Ozone (O3) NO chemiluminescence
NO, NO2, NOy O3 chemiluminescence
Carbon dioxide (CO2) Nondispersive IR
Carbon monoxide (CO) UV fluorescence
VOCs Whole-air sampler
SO2 UV fluorescence and chemical ionization
mass spectrometry (CIMS)
Peroxyacyl nitric anhydrides (PANs)
Halogens (ClNO2, Br2, Cl2, BrCl, BrO)
Direct effect instruments
Indirect effect instruments
Tracer and halogen chemistry instruments 20
for measuring aerosol scattering, absorption, size distribution, CCN concentration, and
composition. The intensive measurement campaigns planned for Barrow in April 2008
make this location a logical ground site with which to coordinate the WP-3D flights.
During the study period, the research vessel Knorr will be sponsored by the
NOAA Marine Operations Center as the primary platform for the International Chemistry
Experiment in the Arctic Lower Troposphere (ICEALOT) experiment
http://saga.pmel.noaa.gov/Field/icealot/. Measurements of aerosol optical, microphysical, cloud-activation and chemical properties, along with gas-phase, remote sensing,
and meteorological variables, will be made in the North Greenland and Barents Seas.
This region is one of the primary transport pathways from Europe to
the Arctic (Stohl et al., 2006), and measurements in this area will provide information on
the properties of relatively fresh anthropogenic pollution as it enters the Arctic. This
information can be contrasted with the airborne measurements of more aged Arctic
aerosols to improve understanding of transformation processes occurring during the
aerosol’s long lifetime in the Arctic.
During April of 2008 period, the NASA/University of North Dakota DC-8
aircraft, as well as remote-sensing airborne platforms, will operate as part of the Arctic
Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS)
program. This airborne and satellite remote sensing mission will focus on aerosol
properties and ozone chemistry, and will be based at Kiruna, Sweden and Fairbanks,
Alaska during this springtime period. The NOAA WP-3D measurements of reactive
halogenated gas species will complement the more extensive DC-8 payload of HOx and
other species related to ozone production and loss rates.
Understanding of the context and representativeness of the WP-3D airborne
measurements will be improved by connecting the measurements with those made by
DOE and NOAA at their respective surface sites at Barrow, Alaska during the key
springtime transition season of April (Fig. 9). Fairbanks, Alaska is the best location near
Barrow for operating a large aircraft such as NOAA’s WP-3D. The WP-3D has the
appropriate range, endurance, altitude capability and payload for the investigations 21
outlined here. This aircraft is capable of operating safely in the demanding Arctic
environment while performing multiple vertical profiles, long-ranging horizontal
transects, and low-altitude sampling. With >8-hour endurance, a WP-3D can fly from
Fairbanks to Barrow and conduct more than 4 hours of research in the vicinity before
returning to Fairbanks (Fig. 9). The horizontal legs from Fairbanks to Barrow can
provide additional information regarding the latitudinal gradient in aerosol properties
across the mean position of the Arctic front.
Meteorology and modeling
The FLEXPART model will be used to identify specific regions of anthropogenic
pollutants, and, with newly developed polar-orbiting satellite capabilities, guide the
aircraft to regions likely to have aerosol-cloud interactions. The FLEXPART model
couples transport simulations using forecast or analyzed meteorological fields and
convective parameterizations with emission inventories to predict the locations and
concentrations of specific trace species (Stohl, 2006). Post-flight verification and
quantification of anthropogenic influence will utilize tracer species carbon monoxide
(CO), CO2, sulfur dioxide (SO2), and soot.
The FLEXPART model will also be used to diagnose specific source regions of
observed haze layers at different altitudes, and to estimate the length of time that air
parcels have been within the Arctic region. These “polar age” estimates can be compared
with hydrocarbon ratio measurements to improve understanding of transport and aging
processes within the Arctic.
In addition to transport modeling, diagnostic cloud models are being developed to
compare with the in situ and remote sensing observations of aerosol and cloud properties.
The specific model-measurement comparisons (Table 2) should permit a thorough
evaluation of the level of understanding of cloud droplet nucleation and growth, ice
formation, aerosol scavenging, and IR emission within the mixed-phase clouds expected
in the Arctic. The improvement in understanding of these key processes should lead to
better parameterizations for the global climate models that are required to diagnose
climate forcings and feedbacks between the atmosphere, sea ice, and ocean. 22
Table 2. Measurement and modeling comparisons.
In situ particle composition/size distribution,
cloud condensation- and ice- nuclei spectra,
cloud particle concentration, phase, size
Parcel model of cloud formation, ice
nucleation and growth
In situ cloud dimension and up/downdraft
velocity, cloud particle concentration, phase,
size, solar and IR transmission/emission
Large eddy simulation (LES) with
coupled cloud dynamics, microphysics,
radiation in 3D Eulerian framework
Surface-based remote sensing measurements
of cloud dynamics, phase, precipitation,
radiative characteristics, particle size, phase
LES with coupled cloud dynamics,
microphysics, radiation in 3D Eulerian
In-situ particle composition/size distribution
near and below cloud.
LES with in- and below-cloud aerosol
Surface measurements of soot concentration
in newly fallen snow
LES with in- and below-cloud aerosol
Gas phase chlorine compounds, sea salt
aerosol chemistry, actinic fluxes
Parcel model with heterogeneous
Arctic Monitoring and Assessment Programme (2006), Arctic Pollution 2006:
Acidification and Arctic Haze, Arctic Monitoring and Assessment Programme, Oslo,
Norway, available at http://www.amap.no.
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., J.-H. Woo, and Klimont, Z.
(2004), A technology-based global inventory of black and organic carbon emissions
from combustion, J. Geophys. Res., 109, D14203, doi:10.1029/2003JD003697.
Bond, T. C. and R. W. Bergstrom (2006), Light absorption by carbonaceous particles:
An investigative review, Aerosol. Sci. Technol., 40, 27-67, doi:10.1080/
Brock, C. A., L. F. Radke, J. H. Lyons and P. V. Hobbs (1989), Arctic hazes in summer
over Greenland and the North American Arctic. I. Incidence and origins, J. Atmos.
Chem., 9, 129-148.
Comiso, J. C. (2006), Arctic warming signals from satellite observations, Weather, 61,
70-76 doi:10.1256/ wea.22205.
Curry, J. A., W. B. Rossow, D. Randall, and J. L. Schramm (1996), Overview of Arctic
cloud and radiation characteristics. J. Clim., 9, 1731-1764. 23
Delene, D.J., and Ogren, J.A. (2002). Variability of aerosol optical properties at four
North American surface monitoring sites, J. Atmos. Sci., 59, 1135-1150.
Flanner, M. G., C. S. Zender, J. T. Randerson, and P. J. Rasch (2007), Present day
climate forcing and response from black carbon in snow, J. Geophys. Res., in press.
Francis , J. A. and E. Hunter (2006), New insight into the disappearing Arctic sea ice
(2006), EOS Trans. Am. Geophys. Union., 87, 46, 509-524.
Garrett, T. J. and C. Zhao (2006), Increased Arctic cloud longwave emissivity associated
with pollution from mid-latitudes, Nature, 440, doi:10.1038/nature04636.
Hansen, J., and L. Nazarenko (2004), Soot climate forcing via snow and ice albedos,
Proc. Natl. Acad. Sci., 101, 423– 428.
Hansen, J. et al. (2005), Efficacy of climate forcings, J. Geophys. Res., D18104,
Harrington, J.Y., T. Reisin, W.R. Cotton, and S.M. Kreidenweis (1999), Cloud resolving
simulations of Arctic stratus – Part II: Transition-season clouds, Atmos. Res., 51, 45-
Harrington, J.Y. and P.Q. Olsson (2001), A method for the parameterization of cloud
optical properties in bulk and bin microphysical models. Implications for arctic
cloudy boundary layers, Atmos. Res., 57, 51-80.
Intergovernmental Panel on Climate Change (2007), “Climate Change 2007: The
Physical Science Basis, Summary for Policymakers”, IPCC Secretariat, Geneva,
Switzerland, available at http://www.ipcc.ch.
Intrieri, J. M., M. D. Shupe, T. Uttal, and B. J. McCarty (2002), An annual cycle of
Arctic cloud characteristics observed by radar and lidar at SHEBA. J. Geophys. Res.,
Jiang, H.L., W.R. Cotton, J.O. Pinto, J.A. Curry and M.J. Weissbluth (2000), Cloud
resolving simulations of mixed-phase Arctic stratus observed during BASE:
Sensitivity to concentration of ice crystals and large-scale heat and moisture
advection, J. Atmos. Sci., 57, 2105-2117.
Johannessen, O. M., L. Bengtsson, M. W/ Miles, S. I. Kuzmina, V. A. Semenov, G. V.
Aledseev, A. P. Nagumyi, V. F. Zakharov, L. P. Bobylev, L. H. Pettersson, K.
Hasselmann, and H. P. Cattle (2004), Arctic climate change: observed and modeled
temperature and sea-ice variability, Tellus, 56A, 328–341.
Kiehl, J. T., T. L. Schneider, R. W. Portmann, and S. Solomon (1999), Climate forcing
due to tropospheric and stratospheric ozone, J. Geophys. Res., 104, 31,239-31,254. 24
Koch, D., and J. Hansen (2005), Distant origins of Arctic black carbon: A Goddard
Institute for Space Studies ModelE experiment. J. Geophys. Res., 110, D04204,
Lehrer, E., G. Honninger., and U. Platt (2004), A one dimensional model study of the
mechanism of halogen liberation and vertical transport in the polar troposphere,
Atmos. Chem. Phys., 4, 2427-2440.
Lynch, A.H., W.L. Chapman, J.E. Walsh and G Weller (1995), Development of a
regional climate model of the western Arctic. J. Climate, 8, 1555-1570, 1995.
Lubin, D. and A.M. Vogelmann (2006), A climatologically significant aerosol longwave
indirect effect in the Arctic, Nature Letters, 439 (26).
Mickley, L. J., P. P. Murti, D. J. Jacob, J. A. Logan, D. Rind, D. Koch (1999), Radiative
forcing form tropospheric ozone calculated with a unified chemistry-climate model, J.
Geophys. Res., 104, 30,153-30,172.
National Snow and Ice Data Center (2005), Press release, available at http://nsidc.org/
Noone, K. J., and A. D. Clarke (1988), Soot scavenging measurements in Arctic
snowfall, Atmos. Environ., 22, 2773-2778.
Pinto, J. O. (1998), Autumnal mixed-phase cloudy boundary layers in the Arctic. J.
Atmos. Sci., 55, 2016-2038.
Quinn, P.K., T.L. Miller, T.S. Bates, J.A. Ogren, E. Andrews, and G.E. Shaw (2002), A
three-year record of simultaneously measured aerosol chemical and optical properties
at Barrow, Alaska, J. Geophys. Res., 107, 10.1029/2001JD001248.
Quinn, P.K., G. Shaw, E. Andrews, E.G. Dutton, T. Ruoho-Airola and S. Gong (2007),
Arctic Haze: Current Trends and Knowledge Gaps, Tellus, 59, 99-114. doi:10.1111/
Ridley, B. A. et al., Ozone depletion events observed in the high latitude surface layer
during the TOPSE aircraft program (2003), J. Geophys. Res., 108 (D4), 8356,
Ritter, C., J. Notholt, J. Fischer, and C. Rathke (2005), Direct thermal radiative forcing of
tropospheric aerosol in the Arctic measured by ground based infrared spectrometry,
Geophys. Res. Lett., 32, L23816, doi:10.1029/2005GL024331. 25
Scheuer, E., R. W. Talbot, J. E. Dibb, G. K. Seid, L. DeBell, and B. Lefer (2003),
Seasonal distributions of fine aerosol sulfate in the North American Arctic basin
during TOPSE, J. Geophys. Res., 108, 8370, doi:10.1029/2001JD001364.
Serreze, M. C. and J. A. Francis (2006a), The Arctic on the fast track of change, Weather,
Serreze, M. and J. A. Francis (2006b), The Arctic amplification debate. Climatic Change,
76, 241-264, 2006.
Sharma, S., D. Lavoué, H. Cachier, L. A. Barrie, and S. L. Gong (2004), Long-term
trends of the black carbon concentrations in the Canadian Arctic, J. Geophys. Res.,
109, D15203, doi:10.1029/2003JD004331.
Sharma, S., E. Andrews, L. A. Barrie, J. A. Ogren, and D. Lavoué (2006), Variations and
sources of the equivalent black carbon in the high Arctic revealed by long-term
observations at Alert and Barrow: 1989–2003, J. Geophys. Res., 111, D14208,
Shindell, D., G. Faluvegi, A. Lacis, J. Hansen, R. Reudy and E. Aguilar (2006), The
influence of tropospheric ozone on Arctic climate, AMS congressional briefing, May
31, 2006, available at http://www.ametsoc.org/atmospolicy/documents/
Simpson et al. (2007), Halogens and their role in polar boundary-layer ozone depletion,
Atmos. Chem. Phys. Discuss., 7, 4285-4403.
Stohl, A. (2006), Characteristics of atmospheric transport into the Arctic troposphere, J.
Geophys. Res., 111, D11306, doi:10.1029/2005JD006888.
Stohl, A., T. Berg, J. F. Burkhart, A. M. Fjǽraa, C. Forster, A. Herber, Ø. Hov, C.
Lunder, W. W. McMillan, S. Oltmans, M. Shiobara, D. Simpson, S. Solberg, K.
Stebel, J. Ström, K. Tørseth, R. Treffeisen, K. Virkkunen, and K. E. Yttri (2006),
Arctic smoke – record high air pollution levels in the European Arctic due to
agricultural fires in Eastern Europe in spring 2006, Atmos. Chem. Phys., 511-534,
Tie, X., et al. (2003), Effect of sulfate aerosol on tropospheric NOx and ozone budgets:
Model simulations and TOPSE evidence, J. Geophys. Res., 108, D4, article number
Treffeisen, R. E., L. W. Thomason, J. Ström, A. B. Herber, S. P. Burton, and T.
Yamanouchi (2006), Stratospheric Aerosol and Gas Experiment (SAGE) II and III
aerosol extinction measurements in the arctic middle and upper troposphere, J.
Geophys. Res., D17203, doi:10.1029/2005JD006271. 26
Treffeisen, R., A. Herber, J. Ström, M. Shiobara, T. Yamanouchi, S. Yamagata, K.
Holmén, M. Kriews, and O. Schrems (2004), Interpretation of Arctic aerosol
properties using cluster analysis applied to observations in the Svalbard area, Tellus
Vavrus, S. (2004), The impact of cloud feedbacks on Arctic climate under greenhouse
forcing, J. Clim., 17, 603-615.
Walsh, J. E., V. M. Kattsov, W. L. Chapman, V. Govorkova, and T. Pavlova (2002),
Comparison of Arctic climate simulations by uncoupled and coupled global models.
J. Clim., 15, 1429-1446.
Warren, S. G. and W. J. Wiscombe (1980), A model for the spectral albedo of snow. II:
Snow containing atmospheric aerosols, J. Atmos. Sci., 37, 2734-2745.
Winton, M. (2006), Amplified Arctic climate change: What does surface albedo feedback
have to do with it? Geophys. Res. Lett., 33, L03701, doi:10.1029/2005GL025244.
The U.S. government routinely conducts experiments on weather modification
by Chris Handy
Global Research, October 21, 2007
Daily Texan, University of Texas via U Wire – 2007-07-30
The U.S. government routinely conducts experiments on weather modification, and has been doing so for at least half a century. Previously classified under such names as “Project Cirrus” (1947) and “Project Popeye” (1966), weather modification is no longer a secret practice. In fact, a bill (S517) was sponsored in 2005 by Texas Sen. Kay Bailey Hutchinson, a Republican, “to establish the Weather Modification Operations and Research Board, and for other purposes.” This bill did not become law. Yet, there is reason to believe that various government institutions are carrying out numerous legal and illegal weather experiments without informing the public.
This isn’t just a suspicion of the United States. The Chinese government announced in April the creation of the first-ever artificial snowfall over the city of Nagqu in Tibet. The event was only one in a series of Chinese weather modification experiments that have been going on for years. China, in fact, now conducts more cloud seeding projects than any other nation.
Cloud seeding through the use of silver iodide was discovered as a viable way to make rain clouds in 1946. In 1947, the U.S. military attempted to use this method to seed a hurricane, which later hit the Georgia coast near Savannah. In the mid-1960s, similar techniques were used in hopes of muddying the Ho Chi Minh Trail in Vietnam. The idea was to slow enemy troop movements through the introduction of inclement weather, and conversely to prevent foul weather over allies.
But cloud seeding with silver iodide is an archaic technique compared with newer advances in nanotechnology and other methods for weather monitoring and control. Microelectric Mechanical Sensors (MEMS) and the newer Global Environmental MEMS Sensors (GEMS), are extremely tiny machines used to monitor weather patterns.
No larger than dust particles, the sensors are designed to be sent up inside hurricanes and other weather systems in large numbers, reporting back data as they literally become a part of those systems. This data can later be used to improve weather forecasting and potentially control the weather through a better understanding of the complex mathematics involved in such systems. One goal is to “steer” these systems, sending them to specific targets and increasing or decreasing their size.
Another extremely controversial participant in the weather modification game is the infamous HAARP antenna grid in Gakona, Alaska. HAARP, the High Frequency Active Auroral Research Program, is an enormous array of antennas inspired by the free energy experiments of 19th-century electrical playboy Nikola Tesla. Commencing sometime around 1990, HAARP was only recently declassified, and much of the current research there is said to take place in secret.
HAARP fires massive amounts of energy into the ionosphere, heating and distorting a section up to 30 miles in diameter. There are various strange and frightening claims made about the project. It may be capable of shifting the position of the jetstream, which could impact global weather in ways that we still do not understand well. Other claims about HAARP, such as that it is part of a massive government mind-control operation or that it forms the main component of a giant death ray, are difficult to verify. But these theories are not as implausible as one might think.
Even in the face of mountains of evidence, many people still believe that weather modification of any kind is only a fantasy. People must be aware that these technologies have been around for a long time, are indeed being used and have great potential for dangerous and unethical uses. Our planet’s weather is part of a single interconnected system and any change to it, whether natural or not, affects every other element of that system. The organizations most interested in modifying this system appear to be applying their theories in incredibly irresponsible ways.
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