Download 1 Changes in Hurricane Climatology in Recent Decades Anais Orsi

Changes in Hurricane Climatology in Recent Decades
Anais Orsi
Dian Putrasahan
Ha Joon Song
James Means
Scripps Institution of Oceanography
Abstract
Hurricanes can inflict catastrophic property damage and human life loss. Thus, it is
important to determine how the character of these powerful storms could change with
global warming. In this paper we examine different ways of measuring hurricanes, and
look at how time series of various hurricane metrics have been analyzed in recent
scientific literature. We conclude that the expected connections between hurricane
activity and global warming are still equivocal.
Introduction and Background
A hurricane is an intense tropical cyclone that has sustained winds of greater than
33 meters sec-1. Hurricanes form in the world’s tropical oceans at latitudes from about 8°
from the equator to about 20° from the equator—their structure is dependent on the
balance between the Coriolis and pressure gradient forces and hence cannot occur too
near to the equator, where the Coriolis force vanishes. They are known to occur in the
North Atlantic, western North Pacific, eastern North Pacific, Southwest Pacific, and
Indian oceans, as well as their associated marginal seas.
Hurricanes are classified according to the Saffir-Simpson intensity scale, which grades
hurricanes according to their maximum sustained surface wind speed. The SaffirSimpson Scale is outlined in the table below. An important thing to understand about
hurricane intensity and the corresponding Saffir-Simpson classification is that there is
often no direct measurement of storm intensity. If information is available from
“Hurricane Hunter” flights it is the preferred method of assigning intensity, although
1
even in this case the wind speed at the surface is inferred from the flight level winds so it
is also an indirect measurement.
Saffir-Simpson Category
Sustained Wind Speed (ms-1)
1
33–42
2
43–49
3
50–58
4
59–69
5
≥ 70
If flight information is unavailable then hurricane intensity is usually assigned by the
Dvorak classification. In this scheme, the presentation of the hurricane in satellite
imagery is compared to standard images of tropical cyclones and maximum wind speed is
inferred from comparison with the standards. Allowance is made for storm “spin-up” and
“spin-down” so that the intensity classification is not allowed to change too quickly. The
original classification flowchart as described by Dvorak [1] is shown in Figure 1, and
although the procedure has been updated [2], the present technique remains very similar.
Before the Dvorak classification surface winds were estimated from central pressure and
sea state estimated from visual observation from aircraft.
Figure 1.Template and chart taken from Dvorak's paper showing how to classify
hurricanes by their banding and central features in order to arrive at T number.
2
Hurricanes are heat engines, and derive their intense energy from the latent heat of
vaporization of water. To sustain a hurricane requires an environment with a high latent
heat content and low friction. It has been empirically determined that these requirements
are only filled over ocean basins with water temperature exceeding 26°C. Hurricanes
quickly diminish in intensity when they move over cooler waters; when they make
landfall; when they encounter dry or stable air; or when they move into an environment
of vertical wind shear. It is the dependence on sea surface temperature that has led to
speculation that global warming—specifically warming of the tropical ocean basins—
could lead to changes in the frequency, distribution and intensity of hurricanes.
Figure 2. Adopted from Webster et al [3], this plot shows trends in sea surface
temperature for different ocean basins.
However, it should be noted the other factors mentioned above may be just as important
to hurricane climatology, but those factors are not as simply connected with global
warming.
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Evidence for Changes in Hurricane Climatology
Both the 2004 and 2005 hurricane seasons have been exceptional in the number of
hurricanes affecting the United States and the damage caused by them, which as led to
much speculation in both the print and broadcast media that there has been an increase in
hurricane occurrence due to global warming. However, it is debatable whether such a
trend exists. For example, Figure 3 is a plot of National Hurricane Center data of US
hurricane strike by decade, with the data split into all hurricanes (categories 1 through 5)
and major hurricanes (categories 3, 4, and 5). It is not at all clear from examining this
plot that there is any trend whatsoever, either for all hurricanes or major hurricanes. This
is a very limited data set, however, and it is advisable to examine more detailed studies of
hurricane frequency and intensity, and especially studies that look at tropical basins other
than the Atlantic/Caribbean/Gulf of Mexico.
U.S. Hurricane Strikes by Decade
30
Number of Hurricanes
25
20
Total
15
Major
10
5
0
18511860
18611870
18711880
18811890
18911900
19011910
19111920
19211930
19311940
19411950
19511960
19611970
19711980
19811990
19912000
20012004
Decade
Figure 3. U.S. Hurricane strikes by decade, for all hurricanes and just major hurricanes.
Figure 4 shows another measure of hurricane climatology, the Accumulated Cyclone
Energy (ACE) index. The ACE is a statistic that the National Oceanic and Atmospheric
Administration (NOAA) uses to measure the total seasonal tropical cyclone activity. It is
4
calculated by summing the squared values of a storm’s maximum wind speed (taken
every six hours) for all Atlantic storms for a season.
300
250
200
150
100
50
19
50
19
52
19
54
19
56
19
58
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
0
Figure 4. ACE index for the North Atlantic since 1950, showing values above average
for most of the last decade.
Webster et al [3] look at trends in tropical cyclone number, duration, and intensity for
various tropical basins over the period 1970–2004. They find no global trend for a
change in either the frequency or duration of tropical cyclones worldwide. They do find
a statistically significant increase in the number and duration of North Atlantic hurricanes
over the same period, but do not attribute this to ocean warming because the same trends
are not seen in other oceans. This is shown in Figure 5. Although we can see the decadal
oscillations in both the number of hurricanes and the number of hurricane days, the 35
year span doesn’t shown an overall increasing trend except over the North Atlantic. The
North Atlantic shows an increasing trend both in the number of hurricanes and the
number of hurricane days. This follows the trend of increasing summer sea surface
temperature, but considering that all the other basins also have had increasing sea surface
temperature without a concomitant increase in the number of hurricanes, it is hard to
conclude that the global warming leads to an increase in the number of hurricanes.
5
Figure 5. Plot from Webster et al of the number of hurricanes and hurricane days by
tropical ocean basin.
They also look at hurricane intensity by breaking the frequency histogram into Category
1, Categories 2 and 3, and Categories 4 and 5. When examined this way they find a
statistically significant positive trend in the frequency of the Category 4 and 5 storms.
This is apparent in Figure 6, taken from Webster et al’s paper.
Gray [4] does not believe that firm evidence for an increase in intense tropical cyclones
exists. Rather, he believes that the data as used by Webster et al is biased because the
observational techniques used to classify storms by their Saffir-Simpson category are
inadequate to distinguish between Category 3 and the Category 4 and 5 storms examined
in the Webster et al paper. He shows evidence that if the Categories 3 to 5 storms are
combined, there has been essentially no change in their global frequency outside of the
Atlantic over the last ten years. There has been a substantial increase in their frequency
in the Atlantic, which he attributes to multi-decadal changes in the Atlantic thermohaline
circulation.
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Figure 6. Graphs from paper by Webster et al, showing an apparent increase in the
fraction of intense hurricanes over the past two decades.
In another recent paper [5], Kerry Emanuel looks at several measures of the energy
dissipated by a storm. The first one he examines is called the power dissipation, or PD:
τ r0
PD=2π ∫ ∫ CD ρ V rdrdt
3
0 0
However, it is difficult to calculate the PD for most storms. It requires a knowledge of
both the pressure and wind speed field as well as the surface drag coefficient. As a more
tractable storm metric he defines the power dissipation index, or PDI. The definition of
PDI is
τ
PDI ≡ ∫ V 3max dt
0
Here τ is the lifetime of the storm, and Vmax is the maximum sustained wind speed at any
point in time. The PDI is very similar to the ACE used by NOAA for evaluating
Atlantic hurricane seasons, but it puts a higher emphasis on the most destructive storms
by using the maximum wind speed cubed rather than squared. Emanuel uses the National
Hurricane Center and the U.S. Navy Joint Typhoon Warning Centers’ [6, 7] best tracks
databases to calculate the PDI for all tropical cyclones from about 1930 to the present.
These databases provide re-analyzed track and intensity data for all identified tropical
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cyclones. These databases provide maximum wind (rounded to nearest 5 knots) every six
hours during the cyclone’s life.
He plots the summed annual PDI for different ocean basins, both separate and combined,
on the same graph as basin sea surface temperature. Appropriate scaling is used so that
the plots are of the same order. The sea surface temperature and PDI show a marked
similarity on these plots and the results are very suggestive of a relationship between the
two.
Figure 7. Plot from Emanuel’s paper showing PDI and sea surface temperature for the
combined North Atlantic and West Pacific basins.
There are, however, criticisms to be made of Emanuel’s work. The plots show no error
bars for either the PDI or the sea surface temperature. A simple calculation shows that
the PDI should have a minimum relative uncertainty given by
ΔPDI min 3ΔVmax
∝
PDI
Vmax
8
where ΔPDI min represents the minimum uncertainty in the PDI and ΔVmax is the
uncertainty in Vmax . This represents the minimum uncertainty in the PDI because it only
takes into account the uncertainty due to uncertainties in the maximum wind speed, and
not due to other factors, such as an inaccurate specification of the storm lifetime.
This failure to account for the uncertainties in PDI due to the uncertainties in the
maximum wind speed is a major deficiency of the paper, as pointed out by Gray [8]
among others. Major changes have been made in the way that maximum wind speed was
estimated over the time span of the databases used by Emanuel. Emanuel has tried to
account for some of these changes by developing new algorithms to adjust older wind
speeds. Emanuel’s new algorithms lower some of the older values by as much as 10
meters per second. This adjustment is in addition to the rounding to the nearest 5 knots
of best track wind speeds, and other errors in wind speed estimation. Considering that a
typical hurricane may have maximum winds on the order of 50 meters per second, a
relative uncertainty of the maximum wind speed of up to 20% might be seen. This would
lead to an uncertainty of the PDI of 60%, which will totally swamp the correlation
implied by the graph. It is very difficult to compare historical wind speed data computed
by different techniques, and cubing those wind speeds has the effect of tripling any
uncertainties in those wind speeds.
Two other recent papers by Trenberth [9], and Pielke et al [10] also look at changes in
hurricane climatology due to global warming, and come to the conclusion that there is no
solid basis for implicating global warming in changes to hurricane climatology. This
does not mean that they do not believe that such changes may be occurring, but rather
that there are other factors (wind shear, temperature of the entire tropospheric column,
etc.) that must be examined when looking for causal changes to hurricane intensity.
Indeed, higher sea surface temperatures are associated with a higher water content of the
lower troposphere. Since 1998, the amount of total column water vapor over the ocean
has increased by 1.3% per decade [9]. Higher available latent heat would favor the
development of tropical storms. However, the convective available potential energy is
also affected by large scale subsiding air that increases the stability and dryness of the
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atmosphere, and is often associated with wind shear through the troposphere. Analysis of
the 250-850 hPa wind shear for the Atlantic shows a downward trend of 0.3 m/s per
decade over the period 1949-2003, which is too small to have much effect [5]. In
addition, Pielke et al believe that the destructiveness of future hurricanes will be much
more dependent on sociological factors, such as increased population and building in
hurricane prone areas, than on any increase in the severity of storms [10].
Conclusion
There are theoretical reasons to expect that there might be a connection between global
warming, higher sea surface temperatures, and increased intensity of tropical cyclones.
Recent research has looked into this possibility and the results are suggestive of increased
tropical cyclone intensity over the past several decades. However, the results at this time
are far from conclusive and further observational and theoretical study is needed to
elucidate any relationship between global warming and the climatology of tropical
storms.
References
1. Dvorak, V. F. Tropical cyclone intensity analysis and forecasting from satellite
imagery. Mon. Wea. Rev. 103, 420-430. (1975).
2. Dvorak, V.F., 1984: Tropical cyclone intensity analysis using satellite data.
NOAATechnical Report NESDIS 11, 45 pp.
3. Webster, P.J., et al., 2005: Changes in tropical cyclone number, duration, and
intensity in a warming environment. Science, 309, 1844-1846.
4. Gray, W.M., 2005: Comments on Webster, et al., Science, 309, 1844-1846.
Submitted to Science.
5. Emanuel, K., 2005: Increasing destructiveness of tropical cyclones over the past 30
years. Nature, 436, 686-688.
6. Joint Typhoon Warning Center Best Tracks for the Southern Hemisphere, Pacific and
Northern Indian Oceans. http://www.npmoc.navy.mil/jtwc/best_tracks/
7. National Hurricane Center Atlantic and Eastern North Pacific Best Tracks.
http://www.nhc.noaa.gov/pastall.shtml
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8. Gray, W.M., 2005: Comments on: “Increasing destructiveness of tropical cyclones
over the past 30 years” by Kerry Emanuel, Nature, 31 July 2005, Vol. 436, pp. 686688. Submitted to Nature
9. Trenberth, K., 2005: Uncertainty in Hurricanes and Global Warming. Science, 308,
1753-1754.
10. Pielke, Jr., R. A., C. Landsea, M. Mayfield, J. Laver and R. Pasch, in press, 2005.
December. Hurricanes and global warming, Bulletin of the American Meteorological
Society.
11
Reviews of Atmospheric Science Topics
November 2005
Progress in Understanding Chlorofluorocarbons in the Lower
Stratosphere
L. Elmegreen, L. Nahid, and D. Richter
Scripps Institution of Oceanography, UCSD
Abstract
Chlorofluorocarbons (CFCs) have been under scrutiny since the 1970’s due to their
ability to act both as greenhouse gases (GHGs) and as ozone depleting substances (ODSs).
Current efforts are being made to determine CFC concentrations in the stratosphere using gas
chromatography and infrared absorption and emission techniques. Satellites have been crucial
for determining concentrations over large areas. Recent studies show that CFC mixing ratios
decrease with latitude and altitude. Studies also show that fluorine concentrations in the
stratosphere can be used to determine CFC mixing ratios, and the change in the mixing ratio over
time. Although CFC production has decreased, CFC mixing ratios in the stratosphere are likely
to increase over time due to stockpiles (or banks) of CFCs.
Introduction
History of Use
Chlorofluorocarbons (CFCs) have
been in use since the 1950’s in applications
such as refrigeration, air conditioning, foams,
aerosols, fire protection and solvents. Global
concentrations of CFCs increased largely
from the 1970s to the 1990s [IPCC, 2005].
Today, most emissions originate from
manufacture, unintended byproduct releases,
intentionally emissive applications, and
evaporation.
However,
the
largest
contributions to the atmosphere come from
banks. Banks are the total amount of
substances contained in existing equipment,
chemical stockpiles, foams and other products
not yet released to the atmosphere [IPCC,
2005].
Ozone Depletion
Stratospheric ozone depletion has
been observed since 1970 and is caused
primarily by increases in concentrations of
reactive chlorine and bromine compounds in
the atmosphere. They are produced by
degradation
of
anthropogenic
Ozone
Depleting Substances (ODSs), including
halons, CFCs, hydrochlorofluorocarbons
(HCFCs), methyl chloroform, carbon
tetrachloride, and methyl bromide [IPCC,
2005].
CFCs were first implicated in ozone
destruction in 1974 by Molina and Rowland
[Schauffler et al., 2003]. To address the
growing hole in the ozone layer, the
production of CFCs, HCFCs, halons, methyl
chloroform, and carbon tetrachloride began to
be regulated in developed countries by the
Montreal
Protocol
and
subsequent
amendments [United Nations Environmental
Programe (UNEP), 1987, 1992, 1997]. The
protocol applies only to developed countries,
and does not regulate the emissions from
banks. Even so, it has been very successful in
curbing ODS contributions to the atmosphere,
as recent data indicate that stratospheric
chlorine levels have approximately stabilized
and may have already started to decline
[IPCC, 2005].
CFC
replacements,
such
as
hydrofluorocarbons
(HFCs)
and
perfluorocarbons (PFCs), have been identified
as potential long-term replacements for ODSs
because they contain neither bromine nor
chlorine, which are ultimately responsible for
Elmegreen et al., 2
ozone depletion. Ozone recovery is expected
to follow decreases in chlorine and bromine
loading in the stratosphere as ODS
concentrations decline. However, emissions
of other greenhouse gases such as CO2,
methane and nitrous oxide can affect both
tropospheric and stratospheric chemistry, and
will have some effect on ozone recovery
[IPCC, 2005].
Global warming
CFCs are also greenhouse gases, as
are many of their replacements. The relative
future warming and cooling effects from
emissions of CFCs, HCFCs, HFCs, PFCs and
halons vary with gas lifetimes, chemical
properties and time of emission. The
atmospheric lifetime for most CFCs is
decades to centuries [IPCC, 2005].
Figure 1. The atmospheric window, a region
characterized by low IR absorption from non-CFC
greenhouse gases [IPCC 2005].
Halocarbons, including CFCs, absorb
Earth’s outgoing infrared radiation in a
spectral range where energy is not removed
by CO2 or water vapor. This gap filled by
halocarbons is sometimes referred to as the
atmospheric window (Figure 1). As a result, a
halocarbon molecule may be many thousand
times more efficient at absorbing radiant
energy emitted from the Earth than a
molecule of CO2. While the primary radiative
effect of CO2 and water vapor is to warm the
surface climate but cool the stratosphere, the
direct radiative effect of halocarbons is to
warm both the troposphere and stratosphere
[IPCC, 2005].
The amount of direct radiative forcing
generated by a gas is given by the product of
its mixing ratio in ppb and its radiative
efficiency in W m-2 [IPCC, 2005]. Between
1970 and 2000, 23% of the increase in
greenhouse forcing from well-mixed GHGs
was due to increases in halocarbons. In
contrast, from 1750 to 2000, halocarbon
increases accounted for only 13% of the
increase in greenhouse forcing. However,
CFC replacements generally have lower
global warming potentials, and total
halocarbon emissions have decreased in
recent years, so the combined CO2-equivalent
emission of halocarbons has been reduced.
The CO2-eq per year of greenhouse forcing by
CFC emissions is projected to decrease from
1.7 gigatons in 2002 to 0.3 gigatons CO2-eq in
2015 [IPCC, 2005].
CFCs also have an indirect cooling
effect though their degradation of the ozone
layer. Ozone is a GHG, and its formation
releases latent heat to the atmosphere. CFCs
reduce the heating effect from both these
phenomena, resulting in indirect cooling. A
depleted ozone layer transmits more solar
radiation, causing warming, but this warming
effect is small compared to the cooling
effects. However, the indirect cooling effect
of CFCs is very likely less than their direct
warming effect [IPCC, 2005].
CFC Reactivity
Chlorofluorocarbons are ideal as
refrigerants and blowing agents because of
their extremely stable nature in the local
atmosphere. However, it is because of their
non-reactivity that they pose a threat as both
Elmegreen et al., 3
an ozone destroying species and as a
greenhouse gas. Our understanding of the
sources and sinks, as well as the lifetime of
CFCs, is essential for monitoring and
predicting their environmental impact.
The lifetime of a compound is defined
as the time it takes for the concentration of
that compound to decay to 1/e (Eq. 1). For
any given compound, the lifetime can be
written as:
"X =
# Burden
# Loss Rate
atm
(1)
The burden of CFCs can be calculated from
observations combined with emission data.
Calculating
the CFC loss rate is more
!
complex because there are several processes
that may contribute to the loss of CFCs from
the atmosphere. Some of those processes are
uptake into the oceans, wet and dry
deposition,
and
reactions
(including
photolysis). The lifetimes of many common
CFCs have been quantified using this
approach, as well as a mass balance
technique.
Mass
balance
involves
extrapolating the concentration of CFCs
measured in one region to a total atmospheric
mass. This mass must balance the emissions
into and losses of CFCs from the atmosphere.
From emissions data banks, the loss can be
calculated.
Research has shown that CFCs are
unable to photolyse with wavelengths above
290 nm. The ultraviolet radiation that is
filtered out in the upper stratosphere makes
!
CFCs stable enough to reach the lower
stratosphere. In addition, CFCs are not very
soluble in water, making wet deposition and
ocean uptake very small contributors to the
loss of CFCs. Because of these qualities,
CFCs have particularly long lifetimes. For
example, CFC-11 has a global lifetime of 4080 years, and CFC-12 lasts twice as long
[Finlayson-Pitts et al., 2000].
Reactions involving CFCs have been
widely studied over the past few decades. An
example of CFC photolysis is shown below:
CF2Cl2 + hv( λ < 240 nm) ⇒ CF2Cl. + Cl.
Cl. + O3 ⇒ ClO. + O2
ClO . + O ⇒ Cl. + O2
The major sink of CFCs is therefore
stratospheric photolysis. The chlorine radical
acts as a catalyst in ozone destruction.
Subsequent reactions of the chlorine produce
temporary reservoirs of chlorine such as HCl
and ClONO2.
These reservoirs release
chlorine radicals in high concentrations upon
the start of Antarctic spring. For this reason,
CFCs have been implicated in the appearance
of an ozone hole over the southern pole.
The ability of any given CFC to
destroy ozone depends directly on its formula
and structure. To rank CFCs in terms of their
ability to destroy ozone, scientists have
assigned Ozone Depleting Potentials (ODPs)
to each CFC. This is similar to the Global
Warming Potential (GWP) assigned to all
greenhouse gases. The ODP is defined as the
ratio of the global loss of ozone from that
compound at steady state per unit mass
emitted relative to the loss of ozone due to the
emission of a unit mass of a reference
compound (CFC-11, CFCl3). Eq. 2 gives the
full definition of ODP; see Finlayson-Pitts et
al., [2000] for more details.
t
% ts e"(t"ts ) /$ X dt
FX M CFC"11 n X
(2)
ODP(t) =
#
FCFC"11 M X 3 % t e"( t"t s ) / $ CFC-11 dt
t
s
Recent experiments have been
conducted to determine how the concentration
of stratospheric CFCs has changed since the
initiation of the Montreal Protocol and
subsequent international agreements, and to
determine the present distribution of CFCs in
the stratosphere.
Methods
Wavelengths that cause photolysis of
CFCs are filtered out by the time radiation
reaches the troposphere. As a result, CFCs
have long lifetimes in the troposphere, so are
well mixed. Therefore, air can be collected at
ground level to measure the tropospheric
Elmegreen et al., 4
concentration of CFCs.
This enables
relatively easy measurement of CFC mixing
ratios in the troposphere. In fact, NOAA
scientists have done this since 1977. At 9
sites around the world, flasks of air have been
collected and analyzed weekly. This has
given a lot of information about how
tropospheric CFC concentrations have
changed over time [NOAA website].
Sampling air in the stratosphere to
measure CFC mixing ratios is less
straightforward. A few analytical techniques
are used to measure the CFC concentrations
in
the
stratosphere,
including
gas
chromatography and infrared absorption or
emission. These techniques can be used on
airplanes or balloons, and infrared techniques
can also be used on satellites.
These
techniques are discussed below in the context
of actual scientific experiments. Many of
these experiments were interested in
determining CFC concentrations not out of
interest in the chemistry of the CFCs, but \
because CFCs make very good tracers due to
their long lifetimes. Therefore, analyzing the
distribution of CFCs can give information
about atmospheric circulation.
Gas Chromatography
In gas chromatography, gas is pumped
through a column with nitrogen (the carrier
gas), and the rate of flow varies with the
chemical depending on its chemical
properties. Therefore, gases elute at different
times, and become separated. As the gases
flow from the column, CFC concentration is
measured with an electron capture detector
(ECD).
One gas chromatograph (GC) used to
measure CFC concentrations is the Airborne
Chromatograph for Atmospheric Trace
Species (ACATS-IV). This GC has been
used in several airplane-based experiments
such as Stratospheric Tracers of Atmospheric
Transport
(STRAT)
in
1996
and
Photochemistry of Ozone Loss in Arctic
Regions in Summer (POLARIS) in 1997. A
balloon-based experiment that used a similar
GC was the Lightweight Airborne
Chromatograph
Experiment
(LACE).
ACATS-IV measures CFC-11 and CFC-113
every 140 seconds, and CFC-12 and halon1211 every 70 seconds [Romashkin et al.,
2001]. The LACE GC measures CFC-11,
CFC-113, CFC-12 and halon-1211 every 70
seconds [Moore et al. 2003].
Both
instruments also measure other trace gases.
Calibrations are made during the experiments
by periodically injecting samples with trace
gases of known concentration. In LACE, the
vertical resolution was 300 m. Samples were
taken at 7°S, 35°N, 65°N, and in the arctic
vortex. Measurements had a 1-4% error, and
showed good correlation with measurements
using ACATS-IV.
Infrared Absorption and Emission
Each CFC absorbs radiation in
specific areas of the infrared (IR) region. As
mentioned above, their unique absorbances in
the atmospheric window make them
particularly potent greenhouse gases, but also
allow their concentrations to be measured
based on the amount of absorbance in a
wavelength region.
Infrared absorption instruments are
useful on satellites, because satellites allow a
large area to be measured for a relatively long
period of time. Also, unlike gas
chromatography, infrared absorption does not
require the physical collection of air samples.
One study that used the IR absorption
technique to measure CFC-12 was the
Improved Limb Atmospheric Spectrometer
(ILAS) on the Advanced Earth Observing
Satellite (ADEOS) [Khosrawi et al., 2004].
ILAS measured CFC-12 concentrations using
absorptions of 850-950 cm-1 and 1050-1200
cm-1.
Measurements were taken from
November 1, 1996 to June 30, 1997, from
57°N to 72°N and 64°S to 89°S.
Comparisons with balloon measurements that
Elmegreen et al., 5
used various types of CFC measurement
techniques
showed
that
the
ILAS
measurements are most valid up to 20-25 km
altitude.
Above this altitude, CFC-12
concentrations are too small to be measured
accurately.
If a molecule can absorb light in a
given region, it can also emit light in that
region. For this reason, another method of
measuring CFCs uses their IR emissions. The
CRyogenic Infrared Spectrometers and
Telescopes for the Atmosphere (CRISTA 2)
experiment measured CFC-11 based on its
emission at 11.7 µm, which corresponds to
the wavenumber of 854 cm-1 used in ILAS
[Kuell et al., 2005]. CRISTA measured CFC
mixing ratios from 8 km up through the
stratosphere and into the mesosphere. The
accuracy of these measurements is 6-8% from
12-18 km, and the precision is 1.8% at 12 km.
Error assessment
As with any experiment, it is
important to have an idea of the error of a
measurement.
One way that these
experiments assessed the validity of their data
was
by
comparing
measured
CFC
concentrations with those of another
Figure 2. Comparison of data from ILAS (lighter
points) and balloon-based infrared absorption (darker
points) (left), and the percent difference between the
two data sets (right) [Khosrawi et al., 2004].
experiment. The ILAS experiment compared
its measurements with those from various
balloon-based measurements to determine
that ILAS results were valid up to 20-25 km,
but at higher altitudes had results that differed
greatly (up to 200%) from the balloon-based
results (Figure 2).
Some of these experiments determined
the error of their data by comparing the ratios
between concentrations of CFCs and a
reference gas with the ratios from another
experiment. Similar experimental methods are
required for this type of comparison. The idea
is that there should be a relationship between
the concentration of CFC and of another gas
with a long lifetime, such as O3 or N2O.
Because O3 and N2O have much higher
concentrations than CFCs (ppb compared to
ppt), O3 and N2O concentrations should be
easier to measure than CFCs, and the
measurements should be more precise.
Therefore, if two experiments show the same
relationship between CFCs and O3 or N2O,
then the data are consistent. The LACE
experiment compared its O3 to CFC
relationships with those from ACATS-IV data
(Figure 3). The ILAS experiment compared
CFC and N2O relationships between ILAS
data and balloon-based data.
Both
experiments showed consistency between the
data sets.
Figure 3. Comparison of LACE (red) and ACATS
(blue) data using the relationship between ozone and
CFC-12 (left) and ozone and CFC-11 (right) [Moore et
al. 2005].
A third way to assess data is by
comparing it with results from a computer
model. The CRISTA experiment compared
Elmegreen et al., 6
its data with results from a model called
EURAD. Unlike the other methods, this
comparison showed problems in the model
rather than in the measured data. Although
this is not helpful for assessing the validity of
a measured data set, it is essential to use
measured data to determine the legitimacy of
assumptions made in a model.
Results
Vertical distribution
Data from LACE, ILAS, and CRISTA
show that the concentration of CFCs
decreases with increasing altitude. For a
given latitude, concentrations do not change
much up to the tropopause, because there are
no CFC sinks in the troposphere and the
lifetime of CFCs is long compared to the
mixing rate of the troposphere (Figure 4). In
the stratosphere, concentrations decrease
rapidly with height (Figure 4). This rapid
decrease is due to photolytic reactions. As
altitude increases, there is more radiation,
particularly more UV radiation that can react
with CFCs. This means there is a larger sink
of CFCs at higher altitudes, so the
concentrations of CFCs decrease [Moore et
al., 2003]. Also, because CFCs move into the
stratosphere from the troposphere, it makes
sense that concentrations would be higher
closer to the troposphere.
Figure 4. Mixing ratios of halon-1211, CFC-11, CFC-113, and CFC-12 versus altitude, for various latitudes. Data
from LACE [Moore et al. 2003].
The concentration varies depending on
the particular CFC. Among CFC-12, CFC-11
and CFC-113, CFC-12 has the highest mixing
ratio, at around 500 pptv at the tropopause
[Khosrawi et al., 2004, Moore et al., 2003].
CFC-11 has a mixing ratio of around 250
pptv, and CFC-113 has a mixing ratio of
around 80 pptv at the tropopause [Kuell et al.,
2005, Moore et al., 2003].
Horizontal distribution
In the troposphere, there is low
variation in CFC concentrations with latitude.
However, at higher altitudes, the variation
with latitude becomes much greater. In the
stratosphere, the concentrations are highest
closest to the equator, and decrease with
latitude (Figure 5) [Kuell et al., 2005, Moore
et al., 2003]. One reason for this trend is that
air enters the stratosphere from the
troposphere in the tropics [Kuell et al., 2005].
Not surprisingly, mixing ratios are greatest
closest to the source. Also, as mentioned
above, photolysis begins to break up CFCs
once they are in the stratosphere. As CFCs
are in the stratosphere longer, their
concentration decreases because there has
been more time for them to react. At higher
Elmegreen et al., 7
latitudes, CFCs have been in the stratosphere
longer because they travel from the tropics.
Therefore, their concentrations are lower.
There is good agreement between the
data from LACE and CRISTA. At 16 km, the
mixing ratio of CFC-11 is around 225 pptv
from 20-40°N, 190 pptv from 40-60°N, and
150pptv and less in the polar region.
Figure 5. Mixing ratio of CFC-11 from 20°N to 80°N
and 80°W to 60°E. Data from CRISTA experiment
[Kuell et al. 2005].
Changes over time: The Halogen Occultation
Experiment
The Halogen Occultation Experiment
(HALOE) was a continuous eight-year,
globally ranging experiment [Anderson et al.,
2000]. The experiment involved satellite
measurements that were weighted by latitude
and globally averaged.
The goal of HALOE was to monitor
CFC concentrations in the stratosphere, to
compare these measurements with the UNEP
scenarios, and to understand the effect of the
new regulations on the CFC levels in the
atmosphere.
HALOE measured species
include HCl, HF, O3, CH4, H2O, NO and
N2O. Previous studies have shown that CFCs
dominate the stratospheric chlorine budget,
and that there is no natural source of HF in
the atmosphere. Therefore HF, a product of
CFC photolysis, is an excellent proxy for
CFC concentration in the stratosphere. From
October of 1991 to May of 1999 these species
were monitored at 55km by solar occultation.
The results of this experiment agree
with previous studies in that there exists a 5.3year time lag from the average tropospheric
altitude to 55km (the stratopause). In addition,
the results also agree with previous
tropospheric measurements of chlorine
concentration. Figure 6b shows the HALOE
chlorine mixing ratio (parts per billion by
volume) compared to several models and 5.3year projected concentrations.
The
concentrations fall directly on top of the 5.3year projected concentrations. These results
illustrate the degree to which scientists
understand the processes that control CFC
lifetime, transport, and sinks. Figure 6a is
from a study by Montzaka et al. [1999]. The
peak in methyl chloroform concentration in
the troposphere occurs between 1992 and
1993, almost exactly five years before the
peak in Figure 6b. Figure 6c is a time series
plot of the UNEP best-case scenarios for the
emission of CFCs. The scenarios progress
alphabetically with each one containing one
more species than the previous scenario.
Scenario G contains methyl chloroform, and
is the only scenario that matches observations.
From these two plots the authors conclude
that methyl chloroform is a critical source of
atmospheric chlorine.
By a similar method, the stratospheric
fluorine concentration was found to be
dominated by the emission of CFC-11 and
CFC-12. Figures 6d and 6e show the time
series measurements and models of HF. The
measured HF concentrations match Scenario
E in Figure 6e, in addition to showing the
approximate 5 year time lag in Figure 4. From
this experiment it is evident that chlorine
concentrations in the stratosphere are
presently
decreasing,
while
fluorine
concentrations are increasing. In order to
more accurately predict future concentrations,
we must consider future emissions and
Elmegreen et al., 8
therefore current
compounds.
stockpiles
of
CFC
Future Emissions
The emission due to these stockpiles, or
banks, of CFCs has been modeled by
comparing industry and regulatory data to the
Refrigerant
Inventory
and
Emission
Previsions (RIEP) database. Ashford et al.
[2004] have used the RIEP database as well
as observations to predict future emissions to
the year 2015 based on three different
scenarios: (1) business as usual, (2) emission
reduction 1st tier, and (3) partial phase-out of
HFCs.
a
b
c
d
e
Figure 1. (a) Methyl chloroform concentrations in the troposphere, peaking in 1992, (b) HALOE inorganic chlorine
measurements compared to models and earlier tropospheric measurements. Darker symbols on the right are the
HALOE 55km measurements, (c) UNEP scenarios over the last twenty years, Scenario G includes methyl
chloroform, (d) HALOE inorganic fluorine measurements compared with tropospheric fluorine measurements and
models, (e) UNEP scenarios for fluorine emission, Scenario E includes CFC-12 [Anderson et al., 2000].
Elmegreen et al., 9
Figure 7. Observations and future emission scenarios
for HCFC-22, a major compound used in refrigeration.
The scenarios are based on future regulations and
known bank sizes [Ashford et al., 2004].
Figure 8. Observations and future emission scenarios
for HFC-134a, a common CFC replacement. Again the
scenarios are based on future regulations and known
bank sizes [Ashford et al., 2004].
Based on the business as usual
scenario, the level of refrigerant-related
emissions would reach 845,000 metric tons,
with the most increase coming from HFCs.
The best-case scenario predicts only 400,000
metric tons of emissions. From these models
we can predict not only future environmental
problems associated with CFCs but we can
also determine the best possible way to reduce
those emissions. For example, Ashford et al.
[2004] have determined that short-term
emissions come from aerosols, solvents, and
open cell foams whereas longer-term
emissions come from refrigerants and closed
cell foams. They have also shown that the
best way to prevent future emissions from
blowing agent banks is to reform end-of-life
procedures.
Refrigerant banks of CFCs, HCFCs,
and HFCs totaled 2.58 million tons in 2002.
For the same year, emissions of those
compounds were larger than 480,000 metric
tons. The release of halons can occur during
manufacturing, servicing, and at the end-oflife stage. The release of these compounds
from blowing agents can occur during
manufacturing and installation, use, and at the
end-of-life stage. Knowing how and when
CFCs and related compounds are released by
refrigerants and blowing agents is crucial for
reducing emissions beyond the present level.
Ashford et al. [2004] have also considered the
effect CFCs have as greenhouse gases. The
predicted emission levels are converted into
Global Warming Potentials (GWPs) by the
relative warming they cause compared to
CO2. From this they estimate that the business
as usual scenario would be equivalent to the
release of 1.53 billion tons of CO2 from
refrigeration and air conditioning alone.
The greatest source of uncertainty in
these models stems from the slow release rate
of blowing agents. Those compounds
produced primarily by blowing agents show
less agreement with models than do those
produced by refrigeration. However, HCFC22 and HFC-134a show a high level of
agreement to models thereby giving
confidence to the 2015 predictions (Figures 7
and 8).
Elmegreen et al., 10
Conclusion
The best understanding of CFCs in the
stratosphere will be gained by combining new
technology, such as satellite measurements
and atmospheric circulation models, with
comprehensive data sets of all CFC sources.
If we know where the most damaging CFC
compounds are being produced and stored,
proper disposal will be much easier to
manage. Recent years have shown a great
deal of progress in this field, and the outlook
for eliminating CFCs from the atmosphere is
promising.
References
Anderson, J., J.M. Russell III, S. Solomon, and L.E.
Deaver,
Halogen
Occultation
Experiment
confirmation of stratospheric chlorine decreases in
accordance with the Montreal Protocol, J.
Geophys. Res., 105, D4, 4483-4490, 2000.
Ashford, P., D. Clodic, A. McCulloch, and L. Kuijpers,
Emission profiles from the foam and refrigeration
sectors
comparison
with
atmospheric
concentrations. Part 2: results and discussion, Int’l
J. Refrigeration, 27, 701-716, 2004.
Finlayson-Pitts, B.J., and J.N. Pitts, Jr, Chemistry of
the Upper and Lower Atmosphere, Academic
Press, San Diego, CA 2000
IPCC and TEAP, 2005: Safeguarding the Ozone Layer
and the Global Climate System. Contribution of
Working Group I and III to the Special Report to
the Intergovernmental Panel on Climate Change
[Anderson, S., L. Kuijpers, J. Pons (TEAP) and S.
Solomon, O. Davidson, B. Metz (IPCC) (steering
committee)]
Cambridge
University
Press,
Cambridge, United Kingdom and New York, NY,
USA, 96pp.
Khosrawi, F. et al., Validation of CFC-12
measurements from the Improved Limb
Atmospheric Spectrometer (ILAS) with the
version 6.0 retrieval algorithm, J. Geophys. Res.,
109, D06311, doi:10.1029/2003JD004325, 2004.
Kuell, V. et al., Tropopause region temperatures and
CFC 11 mixing ratios from CRISTA 2, J.
Geophys.
Res.,
110,
D16104,
doi:10.1029/2004JD005592, 2005.
Montzka, S.A. et al., Present and future trends in the
atmospheric burden of ozone-depleting halogens,
Nature, 398, 690-694, 1999.
Moore, F. L. et al., Balloonborne in situ gas
chromatograph for measurements in the
troposphere and stratosphere, J. Geophys. Res.,
108(D5), 8330, doi:10.1029/2001JD000891, 2003.
NOAA ESRL, Global Monitoring Division, Hats Flask
Sampling
Program,
http://www.cmdl.noaa.gov/hats/flask/flasks.html.
Romashkin, P. A. et al., In situ measurements of longlived trace gases in the lower stratosphere by gas
chromatography, J. Atmos. Ocean Tech., 18, 11951204, 2001.
Russell III, J.M., M. Luo, R.J. Cicerone, and L.E.
Deaver, Satellite confirmation of the dominance of
chlorofluorocarbons in the global stratospheric
chlorine budget, Nature, 379, 526-529, 1996.
Schauffler, S. M., et al., Chlorine budget and
partitioning during the Stratospheric Aerosol and
Gas Experiment (SAGE) III Ozone Loss and
Validation Experiment (SOLVE), J. Geophys.
Res., 108, 2003.
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Progress in Understanding Aerosol-Cloud Interactions: A Review
Keywords- Heterogeneous nucleation, aerosol indirect effect, Twomey effect, Semi-direct effect,
water clouds, climate forcing
Abstract:
The impact that aerosols have on climate is an important, yet poorly understood process. The
aerosol direct effect, indirect effect, and semi-direct effect are three factors with the potential to
significantly influence global climate. This review discusses progress that has been made in
recent years towards understanding the Twomey effect, a subset of the aerosol indirect effect,
and the aerosol semi-direct effect. The Twomey effect is thought to have a 0.5 to 1.9 W m-2
cooling effect. The semi-direct effect is thought to have a warming effect of 0.1 W m-2, but this
result is less certain. Though the understanding of these two effects, and aerosol climate effects
in general, has increased since the last IPCC report, published in 1991, there is still much
progress to be made in the field of aerosol climate science.
1. Introduction
Climate sensitivity is how strongly the earth’s climate system responds to a given perturbation.
Models that estimate climate sensitivity need to be as accurate as possible and depend on
approximate parameters. The relationship of observed climate change to estimated magnitude of
forcing is done through estimates that are uncertain due to incomplete understanding of
atmospheric aerosols. Future changes in the balance of climate forcing factors depend strongly
on the balance of greenhouse gases and aerosol effects. The climate will become more sensitive
to changes as the aerosol concentration is reduced. While there is a very complex relationship of
causes and effects in the atmosphere, this paper will focus on the aerosol aspect of climate
forcing on liquid water clouds. Effects from such aerosol-cloud interactions can result in
modifications to rainfall generation that change thermodynamic processes in the clouds and
dynamics of the atmosphere that drive all weather and climate. Aerosols, greenhouse gases, and
the carbon cycle form a complex mix of disparate effects, the future balance of which is
uncertain (Andreae 2005).
There are three ways in which atmospheric aerosols can significantly affect Earth’s
climate in a number of ways. First, the aerosol direct effect describes how aerosols at the top of
the atmosphere reflect or absorb shortwave radiation causing a cooling effect at Earth’s surface.
Secondly, the aerosol indirect effect is how aerosols as cloud condensation nuclei (CCN) and
change cloud properties. The semi-direct effect explains how shortwave absorbing aerosols cause
a net warming at the surface of the earth. The main focus of this paper is the aerosol indirect
effect, as we will not mention the aerosol direct effect in further detail.
Additionally, aerosols can effect climate forcing by increasing the number of CCN. This
is known as the aerosol indirect effect. Indirect aerosol forcing is defined as the process through
which aerosols perturb the earth’s atmospheric radiation balance by modulating cloud albedo and
cloud amount (IPCC 2001). This occurs through a series of processes linking intermediate
variables such as aerosol mass, CCN, ice nuclei, water phase partitioning, cloud optical depth,
and other factors (IPCC 2001). These observations are supported by remote sensing
measurements and satellite studies. A summary of these effects can be seen in Table 1. We will
go into more detail on these effects in this paper.
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TABLE 1. Summary of Aerosol Indirect Effects and range of the radiative budget perturbation at the top-of-the
atmosphere (FTOA)[Wm−2], at the surface (FSFC) and the likely sign of the change in global mean surface
precipitation (P). (Lohmann and Feichter 2005).
The Twomey effect is a type of indirect aerosol effect for clouds based on the assumption of
fixed water amounts. The Twomey effect is defined as the increase in cloud albedo due to an
increase in cloud droplets (that are smaller), and has a net negative forcing on the climate. The
cloud lifetime effect is for clouds with fixed water amounts. The smaller cloud particles decrease
the precipitation efficiency of the cloud overall and extend the lifetime of the cloud. The semidirect effect is due to absorption of solar radiation by aerosols within a cloud that cause
evaporation of cloud droplet with uncertain effects on climate forcing. This main focus of this
review is the Twomey indirect effect and the semi-direct effect.
Clouds are an important aspect of the regulation of Earth’s radiation balance, as sixty
percent of the earth’s surface is covered by clouds (Lohmann and Feichter 2005). Of the total
incoming solar radiation, 48 W/m2 is reflected back by clouds (Lohmann and Feichter 2005).
Small changes in the macrophysical (coverage, structure, altitude) and microphysical (droplet
size, phase) properties of clouds can have significant effects on climate (Lohmann Feichter
2005).
2. Indirect effect for clouds with fixed water amounts (Cloud Albedo or Twomey effect)
2.1 Introduction
The Twomey effect is the change reflection of solar radiation due to more but smaller cloud
droplets whose liquid water content remains constant (Lohmann and Feichter 2005). According
to the 2001 IPCC report, the Twomey effect of anthropogenic aerosols is between 0 to 2 W/m2,
as can be seen by Figure 1. Other studies show between -1.9 to -0.5 W/m2 (Lohmann and
Feichter 2005). More, but smaller, cloud droplets reduce precipitation efficiency and enhance
cloud lifetime, known as the “second indirect effect,” that we will not discuss. However, the
magnitude of the cloud lifetime effect may be comparable to the Twomey effect (Lohmann and
Feichter 2005). This process involves feedbacks because cloud lifetime and cloud liquid water
content change (Lohmann and Feichter 2005).
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FIG. 1. Graphs of Indirect Aerosol Effect in W m-2 from various models globally (a) and the ratio of Southern
Hemisphere to Northern Hemisphere (b). Red bars are models for anthropogenic sulfate aerosols, anthropogenic
sulfate and organic carbon (blue bars), anthropogenic sulfate and black, and organic carbon (turquoise bars) and the
mean plus standard deviation from all simulations
(olive bars). (Lohmann and Feichter 2005).
Near areas with high emissions of sulfur dioxide, it can be shown that these polluted clouds have
a higher average reflectivity than background clouds (IPCC 2001). Satellites retrieve column
cloud droplet concentrations in low level clouds, which increase substantially from marine to
continental regions (IPCC 2001). Areas of high cloud drop concentrations also occur in tropical
areas where biomass burning is prevalent (IPCC 2001). There is a negative correlation between
aerosol optical depth and the effect of cloud droplets on radiation (IPCC 2001). There is a
positive correlation between aerosol optical depths and cloud optical depths. This can be shown
by an increase in cloud albedo and a decrease in droplet size for optically thick clouds. The
liquid water path determined by cloud dynamics is associated with the absorption of solar
radiation (IPCC 2001).
Observations of the indirect effect on changing cloud albedo can be observed by ships
tracks. Examples of this are evident in Figure 4. This effect is due to the increase of CCN in
polluted clouds. With the same amount of water distributed over a larger number of particles a
smaller droplet size results (Lohmann and Feichter 2005). The difference in top of the
atmosphere (TOA) radiation budget is due to the anthropogenic aerosol effect and its relationship
to the concentration of cloud droplets (Lohmann and Feichter 2005).
Warm clouds form precipitation size particles by collision and coalescence, which in
global climate models (GCM) can be divided into collisions among cloud droplets and
accumulation of rain droplets (Lohmann and Feichter 2005). The automatic conversion rate
depends on the size or number of cloud droplets, Twomey and cloud lifetime effect can then be
calculated separately (Lohmann and Feichter 2005). The relationship between these effects is
uncertain and may depend on background aerosol concentration (Lohmann and Feichter 2005).
2.2 Droplet Size
Droplet size is largest over the oceans and smallest over highly polluted areas where more CCN
force water content to be spread over a larger amount of particles (Breon 2002). Aerosols acting
as CCN cause an increase in droplets thus decreasing the mean radius and increasing cloud
albedo. This increase in cloud albedo is proportional to absorption and the cloud optical
thickness (Breon 2002). The micrometer difference in droplet sizes over the ocean compared to
continental droplets supports the Twomey hypothesis (Breon 2002). Polarization and
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directionality of earth’s reflection (POLDER) can be used to asses Twomey globally (Breon
2002). Spatial and temporal resolutions are most sensitive to biomass burning and anthropogenic
aerosols (Breon 2002). Figure 5 shows the cloud droplet size and optical thickness over the land
and ocean.
FIG. 2. Polarization and directionality of the earth reflectances (POLDER) images of (a) Aerosol Index (unitless)
and (b) Cloud droplet radius (µm). (Breon 2002).
As industrial activity increases, there is a net increase in the number of (CCN) (Barker 2000). A
few micrometer decrease in effective radius can change cloud albedo by up to fifty percent, with
an error fifteen to thirty percent (Barker 2000). The largest overestimates of these models occur
with reductions to effective radius of cloud water droplets (Barker 2000). The homogeneity or
inhomogeneity of these clouds due to cloud variability and liquid water paths relates to the
transport of solar radiation.
2.3 Discussion
A seasonal variation in droplet concentration can cause a seasonable variation in CCN (IPCC
2001). This has a dramatic impact on the cloud precipitation effect (IPCC 2001). This can be
seen through increased cloud albedo with ship tracks (IPCC 2001). Changes in cloud
microstructure due to aerosols can also cause a change in albedo (IPCC 2001).
To quantify the relationship between droplet concentration and CCN, there are currently two
methods. The quantity of aerosols can be empirically related to the quantity of cloud droplets,
however, the accuracy of this strongly depends on cloud type (IPCC 2001). The other method
relates the change in cloud droplet concentration to aerosol concentration through a
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parameterization of cloud droplet formation which assumes certain aerosol properties (IPCC
2001).
Most models suggest an increase in water with increases in anthropogenic aerosol but
new studies may show they have less water (Lohmann and Feichter 2005). These indirect effects
may change occurrences and the frequencies of convection and therefore can be responsible for
droughts and or floods (Lohmann and Feichter 2005).
Factors controlling CCN are their size and response to water (IPCC 2001). How effective
they are depends on their hydrophobic tendencies or if they are water soluble with hydrophilic
sites, which are dependent on the state of mixing of the aerosols (IPCC 2001). Water soluble
aerosols activate at lower relative humidity, which is significant for indirect forcing, however
there are widely varying degrees of solubility (IPCC 2001). Composition effects are well known
for aerosols of sulfates, sodium chloride and other soluble salts, but are poorly understood for
organics, a critical uncertainty in climate forcing by aerosols (IPCC 2001). There is a range in
composition of aerosols, how the different compounds are mixed within the aerosol itself
(internal or external), therefore observations do not always show a constant uptake of water
(IPCC 2001). As a droplet starts to form on an aerosol particle, soluble gases can add to the
growing droplet, greater reducing the critical saturation for the droplet, however this effect has
not be properly evaluated (IPCC 2001).
An increase in albedo occurs due to an increase in reflectivity and a decrease in droplet
size (Albrect 1989). In nature there are fewer CCN over the ocean, therefore any increase will
have a significant impact on microphysics and climate, which can clearly be seen by ship tracks,
as shown in Figure 3 (Albrect 1989). This effect can also be seen by dimethylsulfide (DMS)
(Albrect 1989). The impact on climate from cloud processes not very well understood
quantitatively (Albrect 1989). An assumption made on the Twomey effect is that the liquid water
content remains constant as CCN increase, however this is difficult to quantitate (Albrect 1989).
Changes in global albedo due to cloud amount would be largely offset by changes in long wave
radiation budget (Albrect 1989).
FIG. 3. Ship tracks. (Coakley 1987).
3. The Aerosol Semi-Direct Effect
3.1 Introduction
First reported in 1997 by Hansen et al., the aerosol semi-direct effect describes how aerosols that
absorb solar radiation influence the climate on both a local and global scale. These absorbing
aerosols include dust, organic matter (OM), and black carbon (BC). Dust in the lower
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atmosphere comes mainly from deserts and arid regions. The OM and BC in the atmosphere
however come from the burning of fossil fuels and biomass. Burning of biomass can include
forest fire and other natural processes, but there are also anthropogenic contributions such as
slash and burn agriculture in the Amazon rainforest. The primary source of black carbon in the
atmosphere is from the burning of fossil fuels (Table 2).
TABLE 2. Sources of black carbon and organic carbon in the lower atmosphere, from Lohmann
et al. (1999).
As BC is much more absorbing than either OM or dust and its sources are mainly
anthropogenic, the focus of this paper will be on the climate impacts of the semi-direct effect as
it relates to BC.
In an area of high BC concentration, the main atmospheric impacts of BC are to decrease
low cloud cover and liquid water path (LWP). Absorbing aerosols can decrease cloud cover
either by dissipation of inhibition of cloud formation. In the first process, BC in the atmosphere
absorbs solar radiation, becoming warmer. As the particles come into equilibrium with their
surroundings, they warm the atmosphere. Warmer temperatures are less favorable for the
formation of clouds because the saturation vapor pressure for water is higher at higher
temperatures. Warming of the atmosphere can also cause existing cloud particles to evaporate,
decreasing cloud cover and also LWP (Lohmann and Feichter 2001).
Additionally, when solar radiation is absorbed by BC in the atmosphere, less solar
radiation reaches the surface of the earth. The result is a decrease in warming at the surface and
thus an increase in the static stability of the lower atmosphere. Less warming at the surface
causes the temperature differential between the surface and the lower atmosphere to decrease.
The increased static stability of the lower atmosphere leads to a reduction in the amount and
intensity of convection currents carrying warm air from the surface into the cooler lower layers
of the atmosphere. In addition, as convection decreases so too does the amount of water vapor
transported from the surface to the lower atmosphere, and thus less moisture is available for
cloud formation (Lohmann and Feichter 2001).
Via various routes, the overall impact of the aerosol semi-direct effect is to decrease
cloud cover. Based on standard climate models, a reduction in cloud cover should lead to a
positive climate forcing at the earth’s surface. There is, however, some debate as to the actual
direction of the forcing, due to variations in modeling parameters. Nevertheless, it is agreed that
the atmosphere has a very high sensitivity to absorbing aerosols. That is to say that a small
change in the concentration of absorbing aerosols over a particular region could lead to large
changes in the climate. Several previous studies have estimated the climate sensitivity to
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absorbing aerosols at 2 to 3 times that of CO2 and other green house gases (Hansen et al. 1997,
Cook and Highwood 2004, Jacobson 2002).
3.2 Results
As with most atmospheric processes, determining how the semi-direct effect impacts global
climate is a difficult task. Atmospheric aerosol effects encompass many different and often
competing processes. The effects of one effect are often masked by another, making the exact
magnitude and direction of climate forcing due solely to the semi-direct effect difficult to
determine. In addition processes in the atmosphere are highly interconnected and may cause
chain reactions which mitigate or enhance the effect. Furthermore, BC possesses many variable
properties which could lead to different climate forcings based upon their treatment in climate
models. Among these properties are height of injection, size, composition, mixing state,
concentration, and distribution.
The height of injection of the absorbing aerosols can have a significant effect on not only
the magnitude of climate forcing from the semi-direct effect, but also the sign (Table 3).
Table 3. Modeled semi-direct, direct, and total climate forcing (W m-2) based on aerosol injection
height. BL is the boundary layer and Zinv is the height of the tropopause, from Johnson et al.
(2004).
Using a Large Eddy Model (LEM), Johnson et al. (2004) determined that the climate
forcing from the semi-direct effect would be positive if the absorbing aerosols were within the
boundary layer, but negative if the absorbing aerosols were above the boundary layer.
The composition or mixing state of BC can also change the absorbing properties of the
particles and the resultant climate forcing. It is generally thought that BC exists in three separate
mixing states – an external mixing state where BC particles are equally mixed with nonabsorbing particles, an internal mixing state where an individual particle is a homogeneous
mixture of BC and non-absorbing aerosols, or a BC core surround by layers of non-absorbing
aerosols. Most models have assumed that BC is either well mixed externally or internally
(Johnson 2000). However, in 2000, Jacobson suggested that these two mixing states were not
representative of the physical states of BC in the atmosphere and that a better model would be
one with a BC core and a shell made of non-absorbing aerosols. In 1996, Chylek et al.
postulated that particles with BC cores and non-absorbing shells could absorb up to 2.5 times the
solar radiation of externally mixed BC. This change in absorbance would certainly have an
impact on the magnitude of climate forcing caused by the semi-direct effect, but to this point, no
studies have been done to show exactly what the change in climate forcing would be.
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Absorbing aerosols are not uniformly emitted throughout the globe. The Indian Ocean
Experiment (INDOEX) showed that BC absorption was higher over the Indian subcontinent than
over the ocean due to increase pollution over the land mass (Figure 4).
FIG. 4. Absorption of solar radiation by BC from INDOEX (O’Carroll). The areas of high
absorption and thus high BC concentration correspond to the Indian subcontinent, while the
absorption is much lower over the ocean.
Numerous studies have confirmed that the absorption of solar radiation impacts climate at the
local scale, though the exact forcings are uncertain. Most agree that the semi-direct effect will
cause a positive climate forcing locally, although the magnitudes vary from 0.1 W m-2 (Lohmann
and Feichter, 2001) to 23 W m-2 (Johnson et al. 2004). Penner et al. (2003) used a “relaxed
forcing” model that accounted for changes in longwave emissions due to shortwave absorption
by BC, and found forcing values that ranged from 0.1 W m-2 to –1.24 W m-2, again showing the
uncertainty in the magnitude of the semi-direct effect. Though these studies all prove that the
semi-direct effect is significant on the local scale, Lohmann and Feichter (2001) concluded that
the semi-direct effect was negligible on a global scale when compared with the indirect effect.
Several studies have also shown that the semi-direct effect will decrease LWP over areas
of high BC concentration, but whether this translates to a global impact is unknown. In the same
study, Lohmann and Feichter determined that LWP would decrease by 0.3 g m-2 in polluted
areas, but that LWP increased globally by 10 g m-2 due to the indirect effect.
3.3 Results
Because of high climate sensitivity, the impact of absorbing aerosols, especially BC, will become
increasingly important as concentrations of BC and other absorbing aerosols in the atmosphere
increase. In 2002, Jacobson claimed that controlling BC and OM could be the most effective
way to curb global warming. Conversely, Lohmann and Feichter (2001) maintain that the semidirect effect is insignificant in comparison to other aerosol interactions in the atmosphere though
their assertions come with the caveats that there are high degrees of uncertainty in both BC
emissions and the absorbing properties of BC due to different mixing states. Despite the fact that
the semi-direct effect has known impacts on climate forcing over small areas, the global impact
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has yet to be characterized. Thus further study on the aerosol semi-direct effect is necessary to
ascertain the effects that BC and other absorbing aerosols will have on the global climate.
4. Summary and Conclusion of Current Progress
Atmospheric aerosols have the ability to significantly influence the atmosphere. Changes in the
way light enters the atmosphere causes significant alterations to global radiative forcing. Several
effects contribute to climate forcing by aerosols. Specifically, aerosols are able to alter cloud
amount, formation, and reflective properties. The aerosol indirect effect causes a significant
cooling or negative forcing estimated at -0.5 to -1.9 Wm-2 (Lohmann and Feichter 2005). The
semi-direct effect has largely variant effects on the atmosphere. The semi-direct effect can
induce negative or positive forcing based on a number of factors, but the overall effect is
assumed to be positive. Thus it can be concluded that the indirect effect is slightly mitigated by
the semi-direct effect. There is less uncertainty about the indirect effect, however both effects are
not easily quantified. High interconnectivity between the indirect and semi-direct effects and
other atmospheric processes make modeling and predicting individual effect forcing difficult.
Models are able to provide estimates of the forcing but are calculated based on parameter
assumptions.
It is perhaps most valuable to consider the effects in tandem rather than trying to separate
the aerosol effects individually. Combining both effects leads to empirical observation of a
negative forcing as is suggested in Figure 3.
FIG. 3. Global mean total indirect aerosol effects over the oceans, land and the ratio ocean/land. Anthropogenic
sulfate (red bars) anthropogenic sulfate and black carbon (green bars) anthropogenic sulfate and organic carbon
(blue bars) anthropogenic sulfate and black, and organic carbon (turquoise bars), a combination of satellite results
(black bars) and the mean plus standard deviation from all simulations (olive bars). (Lohmann and Feichter 2005).
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This figure shows several variant observations from multiple sources over both land and ocean.
Although observations differ in magnitude, the overall ocean, land, and global averages result in
negative forcing. This indicates a higher reliance of forcing on the indirect effect in comparison
to the semi-direct. The sources of these aerosols are inferred as anthropogenic. A ratio of ocean
to land forcing of less than unity indicates a larger negative forcing over land, supportive of
increased aerosol concentration over land than ocean. Overall, the magnitude of these effects is
highly uncertain, but generally the direction of climate forcing is known with more confidence.
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References
Albrect, B.A. Aerosols, 1989: Cloud Microphysics, and Fractional Cloudiness. Science, 1989,
245, 1227-1230.
Andreae, M.O.; Jones, C.D.; Cox, P.M. 2005: Strong present-day aerosol cooling implies a hot
future. Nature, 435, 1187-1190.
Barker, H.W. 2000: Indirect Aerosol Forcing by Homogenous and Inhomogenous Clouds.
Journal of Climate, 13, 4042-4049.
Breon, F.M; Tanre, D.; Generoso, S. 2002: Aerosol Effect on Cloud Droplet Size Monitored
from Satellite. Science, 295, 834-838.
Coakley, J.; Bernstein, R.; Durkee, P. 1987: Effect of Ship-Stack Effluents on Cloud Reflectivity
Science, 237, 1020-1022.
Cook J. and Highwood, E., 2004: Climate response to tropospheric absorbing aerosol in an
intermediate general-circulation model. Q. J. R. Meteorol. Soc., 130, 175-191.
Curry, J.A.; Webster, P.J. Thermodynamics of Atmospheres and Oceans. San Diego: Acadamic
Press, 1999.
Chylek, P., Lesins, G., Videen, G., Wong, J., Pinnick, R., Ngo, D., and Klett, J., 1996: Black
carbon and absorption of solar radiation by clouds. J. Geophys. Res., 101, 22336523371.
Hansen, J., Sato, M., and Ruedy, R., 1997: Radiative forcing and climate response. J. Geophys.
Res., 102, 6831-6864.
Jacobson, M., 2002: Control of fossil-fuel particulate black carbon and organic matter, possibly
the most effective method of slowing global warming. J. Geophys. Res., 107, 4410-4431.
Johnson, B., Shine, K., and Forster, P., 2004: The semi-direct aerosol effect: Impact of
absorbing aerosols on marine stratocumulus. Q. J. R. Meteorol. Soc., 130, 1407-1422.
Lohmann, U.; Feichter, J. 2005: Global indirect aerosol effects: A Review. Atmospheric
Chemistry and Physics, 5, 715-737.
Lohmann, U., Feichter, J., Chuang, C., and Penner, J., 1999: Prediction of the number of cloud
droplets in the ECHAM GCM. J. Geophys. Res., 104, 9169-9198.
Lohmann, U. and Feichter, J., 2001: Can the direct and semi-direct aerosol effect compete with
the indirect effect on a global scale? Geophys. Res. Lett., 28, 159-161.
O’Carroll, C., Aguileira, M., and Clark, C. New NASA Satellite Sensor and Field Experiment
Shows Aerosols Cool the Surface but Warm the Atmosphere.
http://earthobservatory.nasa.gov//Newsroom/NasaNews/2001/200108135050.html
Penner, J., Zhang, S., and Chuang, C., 2003: Soot and smoke aerosol may not warm climate. J.
Geophys. Res., 108, 4657-4665.
Penner, J.E., M. Andreae, H. Annegarn, L. Barrie, J. Feichter, D. Hegg, A. Jayaraman, R.
Leaitch, D. Murphy, J. Nganga, G. Pitari In: Climate Change 2001: The Scientific Basis.
Contribution of Working Group I to the Third Assessment Report of the
Intergovernmental Panel on Climate Change [Houghton, J.T.,Y. Ding, D.J. Griggs, M.
Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson (eds.)]. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA, 881pp.
Current Understanding of Changes in Cloud Amount,
its Causes, and Effects
Oliver Sun, Gregg Dobrowalski, Adam Orin, Mike Stukel
November 17, 2005
1
Introduction
Clouds play an important role in our climate. Understanding how clouds interact with
the climate, unfortunately, is a very difficult task [2]. As the climate changes from global
warming, cloud amount is likely to change, and will have important consequences on the
changing climate. In this paper we review our current understanding of cloud change. First
we look at various anthropogenic sources of cloudiness change. Next we examine several
recent studies on cloud amount change over the twntieth century. Finally, we explore the
possible effect of changes in cloud amount.
2
Anthropogenic causes of cloud amount change
When trying to understand change in cloud amount it is worthwhile to consider potential
causes of such change. Two possible anthropogenic effects are the emission of sulfur and
contrails caused by jet aircraft. Parungo [7]. and Myhre [5] will be discuss the topic of
sulfur emissions. Part of the IPCC report[1] will discusses aircraft contrails. A key idea
to remember when thinking about the following information is that correlation does not
necessarily mean causation. Data is presented along with an interpretation but no claim is
made that sulfur emissions are solely responsible for the observed increase in cloud cover.
Some data suggests that cloud cover is changing most over populated regions. Data from
1952-1981 shows a net percent net increase in the global amount of cloud cover normalized
to the 1952 level[7], although we will see there is no consensus on the amount of cloud
change. This increase is not split evenly throughout the world; there was a 2.3 percent
increase in the Northern Hemisphere compared to a 1.2 percent increase in the Southern
Hemisphere. One possible explanation for this is related to population density as well as
density of industrial facilities. Such areas emit sulfur particles from power plants, smelting
plants and fuels containing sulfur. Latitudes between 30 degrees to 50 degrees North show
the greatest increase in cloud cover. This corresponds to the areas of the globe most heavily
populated.
1
Figure 1: Trends of Northern Hemisphere daytime altostratus and altocumulus cloud
amounts over 10 degree latitude bands.
Figure 2: Sulfur emissions as a function of year, for various regions.
2
Sulfur particles are a possible cause of increased cloud cover. The particles act as cloud
condensation nuclei (CCN) which affect cloud formation and the stability of clouds[5]. Heterogeneous nucleation requires a lower saturation level compared to homogeneous nucleation
to form clouds. The clouds that are formed from CCN are colliodially stable; they have
a greater number of smaller droplets which this results in the clouds not producing much
rain and therefore lasting longer. Figure 1 shows the amount of sulfur released into the
atmosphere. Note the three sub-classifications, all are in the latitudes that saw the greatest
increase in cloud cover.
Jet aircraft flying in the upper troposphere (∼10 km) can produce contrails which are
essentially cirrus clouds. A combination of particulate emission from the exhaust as well as
the heat of the exhaust can create cloud forming conditions in the wake of the aircraft[1].
The contrails start small, only a few meters wide and can spread to cover a much larger
area. This was seen on September 12, 2001. As the skies were closed to commercial aircraft
the few contrails left by six high flying military aircraft outside Washington D.C. could be
easily seen. Over the course of a few hours the contrails spread to 20, 000 km2 [8]. If they
had not initially been identified as contrails, it would be difficult for satellites to distinguish
the clouds from ones formed naturally. This is due to the fact that the algorithms used by
the satellites to sort the images rely on the linear nature of contrails to distinguish them
from other clouds. After time has passed and the contrails have spread the linear features
are blurred thus making the distinction difficult.
3
3.1
Observations on changes in cloud amount
Changes in cloudiness over land
Several studies have examined changes in cloud cover over land specifically. In this paper we
will look at two such studies, one by Sun and others[9], and one by Croke and others[2]. Both
papers use human-made observations of cloud amount throughout the twentieth century.
Both papers also find an overall increase in cloud cover.
Croke uses land based observations from 1900-1987 to estimate the change in annual cloud
cover over three regions in the United States: the coastal southwest, the southern plains,
and the coastal northwest. The data was collected by meteorological stations throughout the
United States, and includes estimates of fractional cloud amount. Although not explicitly
defined in the paper, we assume that the “annual fractional cloud cover” for a given region
is the fraction of the region covered by clouds, averaged over a year.
For all three regions, Croke finds that cloud cover increases over the timespan of the
datasets. Figure 3 shows a plot of percent cloud cover over the coastal southwest as a
function of year. As can be seen, there is roughly a ten percent increase in cloud cover over
this region in the twentieth century. The two other regions also show roughly a ten percent
increase in cloud cover over the twentieth century.
Croke also finds that the increase in cloud cover is linearly correlated to both the global
change in surface temperature, and to changes in several high/low pressure systems. Figure
3
Figure 3: Plot of percent cloud cover, and mean global surface temperature anomaly as
a function of year. As can be seen, the percent cloud cover is linearly correlated to the
temperature anomaly.
3 also plots the global mean surface temperature anomaly, ∆T , as a function of year. The
percent cloud cover is found to be linearly related to ∆T with a linear correlation coefficient
of R = .89. Croke also finds that the intensity of the North Pacific High is linearly correlated
to the global surface temperature anomaly, with a negative sense. The global surface temperature anomaly, the percent cloud cover, and the intensity of the North Pacific High all
seem to be linearly correlated. Although this interesting, it is important to remember that
correlation does not imply causation. It is too simple to say that a change in one of the three
features causes the others to change. The climate is a complex system of feedbacks, and it
is hard to isolate one part of the system. Croke does discuss some possible mechanisms for
the North Pacific High to effect cloud cover over the coastal southwest.
Sun uses land based observations, similar to those used by Croke, from the past 40-50
years to estimate the change in cloud frequency and type over the former USSR and the
United States. Rather than focus on the changes in cloud amount over time, Sun focuses
on the changes in the frequency that various cloud types occur. Monitoring changes in the
relative amount of various cloud types, and not just the total cloudiness, may help identify
causes of cloudiness variations, and deepens out understanding of the influence of clouds
on climate change. Figure 4 shows Sun’s conclusions on changes in cloud cover for various
seasons, and for various cloud types. Sun defines cloud type frequency as the ratio of number
of observations where the given cloud type was observed to the total number of observations
made. Sun concludes that there has been a net increase in cloudiness both over the US and
USSR over the past 50 years.
Neither papers offer a significant discussion or a reference to a discussion of the accuracy
of the datasets. Sun does note that an increase in the amount of low level clouds will impair
the ability of observers to determine the amount of high level clouds. Thus, an increase in
low-level clouds causes an apparent decrease in the amount of high level clouds. Sun does not
attempt to estimate the effect of this bias. Instead, if the higher cloud types were obscured
by lower clouds, Sun counted this as an absence of the higher clouds, which will under4
Figure 4: A table that summarizes Sun’s results. Sun finds an overall increase in cloud
amount over both the US and USSR.
report the frequency of the higher clouds. Sun also notes that the differences between cloud
classification schemes and data collecting practices of the American and Russian stations
made it difficult to compare the datasets. Another issue for Sun’s datasets, and possibly
Croke’s, is that 19 cloud types were recorded by the observers. With such a large variety
of cloud types, it is difficult for a human to consistently classify a cloud as the proper type.
Without any quantitative measures or estimates of the inherent inconsistancies of humanbased observations, it is hard to judge the quality of the datasets from which these authors
base their results.
We see that Croke and Sun both offer evidence that cloud cover increases during global
warm periods. Croke’s datasets are more limited in spacial scope, and the observed change
in cloud cover is a roughly ten percent increase. Sun’s datasets span two nations, and his
data is broken into various cloud types. Sun estimates a net increase in annual cloud amount
but does not provide a quantivitave estimate of the increase.
3.2
Changes in cloud amount – a more recent study
The effects of cloud variation on a warming climate are not well known [4]. In light of the
uncertainties in cloud simulation, Norris [6] undertook a survey to compare the decadal trends
in three data sets: the recently-available satellite-observed cloud cover and satellite-observed
outgoing radiation flux, and the surface-observed cloud cover, for which much longer records
exist. If these records were to be in close agreement, then it might be feasible to estimate
the outgoing radiation flux for many decades prior to the satellite era.
Satellite observations were taken from the International Satellite Cloud Climatology
Project (ISCCP), available from 1983 forward, and comprising observations from a variety of polar and geosynchronous weather satellites. This data included low-level, mid-level,
5
and high-level cloud cover fractions, with the divisions at cloud top heights of 440 and 680
hPa, respectively. Due to inconsistencies in infrared-only observations, only the daytime
results were reported.
Long-term surface observations employing a consistent methodology were recorded in
the Extended Edited Cloud Report Archive (EECRA). Land observations were provided by
numbered World Meteorological Organization stations in the period 1971-1996, and ocean
observations from Volunteer Observing Ships were available from 1952-1997, including lowlevel and total cloud cover fractions reported in eighths. A simple model for random occlusion
between lower and upper-layer clouds was employed for the purposes of comparison with
satellite-observed data.
The baseline for radiative flux was established by the Earth Radiation Budget Satellite
(ERBS), operational during 1985-1999. Two instruments were referenced: the wide-area
nonscanner instrument, and the finer scanner instrument, which was only available during
1985-1989. When comparing the 72-day anomaly in cloud cover from the two observation
sets to the radiation flux anomaly, there was a slight decreasing trend over the period when
all three observational sets were available; however, the simple linear correlation was clearly
not a good statistical model for the system (Norris, 2005).
While the upper-layer cloud cover measurements were in good agreement with each other
as well as the ERBS-observed flux, inconsistencies in the total cloud cover due to differences
in low-level cloud cover were not accounted for. Norris [6] cites secular changes in satellite
field makeup (a shift toward high viewing angle, geosynchronous satellites) and errors in lowlevel surface observations of cumulus clouds as possible culprits, but further investigation is
needed to extend these observations into reliable radiation flux estimates.
Norris then attempted a simple linear correlation model for estimating radiation flux,
using the EECRA upper-layer the surface observations to estimate the outgoing long wave
(OLW) radiation. Excluding certain areas which were heavily affected by the lower-level
cloud cloud discrepancy, these results nevertheless show promise for future longer-term estimates of radiation flux derived from surface observed data.
4
Global effects of changes in cloud amount
According to the 2001 IPCC [4], the incredible complexity of cloud dynamics “remains a
dominant source of uncertainty” in models of how the global climate will respond to human
activities [10]. Changing cloud cover patterns are certain to exhibit a strong effect on the
climate and life on Earth. They will effect precipitation patterns as well as the amount
of photosynthetically active radiation reaching the earth’s surface, which will in turn alter
ecosystems as well as regions that are suitable for human farming. Clouds play a huge role
in the earth’s albedo, that varies spatially, as clouds above polar ice caps and snow decrease
the albedo, while clouds over vegetation or ocean increase the albedo. The clouds also can
reflect or absorb outgoing longwave radiation, thus heating the coupled earth-atmosphere
system. The 2001 IPCC Report estimates that the total cloud effect will be a net 10 ∗ 10 −20
W/m2 negative feedback averaged over the globe, yet there is great uncertainty in this figure
6
Figure 5: 72-day anomaly, EECRA (red), ISCCP (blue), ERBS nonscanner (black), ERBS
scanner (green). Reference 1985-1989 mean..
7
Figure 6: 72-day anomaly in LW, SW, and net CCRF. Estimated from EECRA (red) and
reported by ERBS (black), and divided into Region A (30o S-30o except tropical Atlantic
and eastern tropical Pacific) and B (excluded regions).
and in local feedbacks in areas such as the poles, where latitudinal trends in cloud cover
will be important [4]. Ongoing research in many different areas is currently attempting to
address these unknown parameters of global climate change.
The Polar Regions are particularly sensitive to climatic changes, and have an important
role in how humanity will feel changes in the climate system, due to the possibility of
increasing sea levels as the polar ice caps melt. In the Arctic, cloud formation is likely to
have a positive feedback with human induced global warming. In large part, this arises from
the strong reflectivity of ice and snow, which has a higher albedo factor than clouds do.
Clouds also serve to insulate the region, and reduce wintertime cooling by roughly 40 ∗ 10 −50
W/m2 , but only decrease summer heating by 20 to 30 W/m2 . This radiative forcing, however,
is dependent on several different parameters of clouds; cloud coverage, height, thickness, and
water content [11].
Vavrus (2004) attempted to estimate the role that cloud feedback will play on the Arctic
climate. He used an atmosphere-mixed-layer ocean global climate model (GENESIS2) to
model the climate of the region. He found that when CO2 was increased by a factor of two,
the model generated more clouds at high latitudes, but lower cloud coverage at low latitudes,
thus acting as a positive feedback on global warming at all latitudes. To determine the role
that cloud cover changes played in the model he constructed a concurrent model that was
similar in all ways, except that cloud coverage was forced to remain at present levels. It
was prescribed in the model instead of being linked to climate. He then compared the two
models. The results can be found in Figure 7. As the figures show, at all latitudes the tem8
Figure 7: (a) Latitudinal average temperature for a GCM forced by a doubling of CO 2
with a coupled atmosphere-ocean-land system (open dots) or cloud cover fixed at current
concentrations (closed dots). (b) Percentage temperature change due to effect of changes in
cloud cover. (c) Changes in precipitation with and without cloud changes. [11]
9
Figure 8: Sensitivity of LW radiation to threshold optical thickness values. Top graph is of
LW radiation up to the top of the atmosphere. Bottom graph is of LW radiation down to
the surface. Surface radiation increases by roughly 10 W/m2 when optically thin clouds are
treated as clear sky.[12]
perature was higher in the coupled atmosphere-land-ocean model than in the model where
cloud cover remains constant. The models also show that at most latitudes and particularly
high latitudes, precipitation will increase with the cloud changes forced by increased CO2
concentrations.
When cloud-climate models are constructed, it is very important for researchers to
ground-truth their models by comparing their predictions for the current climate to actual measurements made in the real world. Precipitation, temperature, cloud cover, and
many other parameters can be compared, but cloud coverage can be particularly difficult
to determine due to inaccuracies in human estimation of cloud fraction. In particular, thin
clouds are frequently missed by observers, who erroneously score them as clear sky. This
effect is important in Polar Regions, because during the winter a large fraction of the clouds
formed are optically thin.
To address this bias in real-world measurements, Wyser and Jones[12] decided to study
the effect that optically thin clouds had on the surface heat budget of the of the Arctic.
They used data obtained from a Canadian Coast vessel that was frozen in the pack ice for
one year. This data showed a strong dependence on the type of instrument used, whether it
was cloud lidar, radar, or human observations. To correct for the error, Wyser and Jones,
put an optical thickness threshold into their model. They set this threshold as a parameter
for their model, and asked the model to predict the level of cloud cover that would be found
above this threshold. They found that by using this technique they could get much better
agreement between their model and the observed data. Using their model, they determined
that long-wave radiation increases by 10 W/m2 when optically thin clouds are treated as
clear sky. Figure 8 shows the decrease in light-wave radiation at the surface (and increase
above the atmosphere) as the critical threshold for optical thickness increases. This error
in long-wave radiation can have strong effects on the climate as illustrated by one example
10
Figure 9: Changes in LW flux and Baltic Sea ice coverage in a model by Doscher, if forced
by the increased LW radiation seen when optically thin clouds are included.[12]
given by Wyser and Jones. They used their increased long-wave radiation in a coupled model
of the Baltic Sea climate created by Doscher et al. Their data produced a significant increase
in long-wave flux and a concurrent decrease in ice extent as seen in Figure 9.
Kaufmann et al.[3], in contrast, present an example of a negative feedback of cloud cover
changes on anthropogenic global warming. They examined the effect that smoke, dust, and
pollution aerosols have on lower atmosphere clouds over the Atlantic Ocean, by looking at
latitudinal trends in these aerosols. They defined bands where the clouds are dominated by
different types of aerosols: Marine aerosols from 30 degrees S to 20 degrees S, smoke from 20
degrees S to 5 degrees N, mineral dust from 5 degrees N to 25 degrees N, and pollution from
30 degrees N to 60 degrees N. They found that all aerosols lead to smaller water droplets,
which inhibits precipitation and leads to longer cloud residence time, and hence higher cloud
fraction. They then addressed the impact that this effect would have on incoming radiation.
They found that incoming long-wave radiation was reduced by 11 W/m2 due to the presence
of these aerosols, with a third of it coming directly from reflection by the aerosols and the
rest due to the indirect effect of increased cloud cover over the Atlantic.
5
Conclusions
Clouds play an important role in climate change, yet more work must be done to fully understand their role. Both sulfur emissions and aircraft contrails are changing cloud amount.
Although much work has been done to understand how much cloud amount has changed,
there is little consensus amoung the various studies. More quantitative datasets from satellites should improve the ability of researchers to estimate changes in cloud amount. Changes
in cloud amount will have several important effects on the climate, with current estimates
of a net 10 ∗ 10−20 W/m2 cooling effect on the global energy budget. But this number is still
a topic of debate, and likely will remain uncertain until we better understand cloudiness.
11
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12
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13