Download Aerosol concentrations and hurricanes over the

Aerosol Concentration and
Hurricanes over the Northern
Indian Ocean (NIO)
Jeff Nelson, James Belanger, Laura Griffith
EAS 4740: Atmospheric Chemistry
Dr. Yuhang Wang
Outline of Presentation

Discuss recent studies that suggest aerosols
such as black carbon are changing atmospheric
stability and sea surface temperatures (SSTs).

Discuss recent trends in tropical cyclone activity
and SSTs in the Northern Indian Ocean (NIO).

Is there any evidence to support a connection
between aerosol changes and tropical
circulation changes e.g. monsoon and hurricane
formation?
Background Information on
Black Carbon




Black carbon (BC) is very important because it
absorbs visible light, heats the air, and contributes to
global warming.
BC emissions result from incomplete combustion of
coal, biofuels, diesel engines, and biomass burning.
Increasing population in India and China have caused
an increase in BC emissions throughout South Asia.
During the dry season, anthropogenic BC is
transported into the NIO and envelope the region in a
3 km thick brown cloud layer.
INDOEX Background

INDOEX addresses questions of
climate change that are of high
priority and of great value to the
US and the international
community.

The project's goal was to study
natural and anthropogenic
climate forcing by aerosols and
feedbacks on regional and
global climate.

The experiment was conducted
in a region of the Indian Ocean
where clean southerly air
masses meet dirty continental
masses.
http://www-indoex.ucsd.edu/7
Pollution Statistics over Asia

Graph to the right
shows a dramatic
increase in Asian
emissions specifically
of NOx

Can be extrapolated to
see the scale of
emissions over recent
years.
Alles, D. 20054
Air Pollution Over China
Alles, D. 20054
Black Carbon Statistics

Shown are aerosol particles
over Asia and Africa from
December 8-12, 2004.
Small particles are red and
larger particles are gold.

The red particles are due to
the burning of vegetation
and other sources which
indicates large amounts of
black carbon in the area.
Alles, D. 20054
Black Carbon Statistics (cont.)




The whiter patches indicate
the presence of more black
carbon.
In China, this is mostly due
to the significant amount of
industry in the region.
Over Africa, the white patch
is due to agricultural
burning.
Also, one can see that the
highest concentration of
black carbon exists over
eastern Asia.
Alles, D. 20054
Black Carbon Effects



1. This map shows cooling of 0.5
to 1.0 degrees Celsius (0.9-1.8
degrees Fahrenheit) occurring
over China, and warming
temperatures throughout the rest
of the world (in yellow).
2. The blue colors indicate regions
in which the simulations yield a
tendency for increased rainfall by
as much as 10 inches over the
summer. Other regions (brown
colors) have decreased rainfall by
as much as several inches or
more.
3. Shows the decrease in solar
energy reaching the ground (in
black) during the summer months
(June, July and August). Yellow
shows were the sunlight has
increased.
www.gsfc.nasa.gov/5
Black Carbon Effect (cont.)



Upper figure shows the
effect on albedo due to
black carbon. An outline of
India is evident.
Lower figure shows surface
cooling also due to black
carbon. Most cooler regions
are over land masses and
close to coast lines.
A strong relationship can be
seen between albedo and
surface cooling.
NASA Earth Observatory6
Black Carbon Effect (cont.)

Upper graph shows aerosol
coverage over southeastern
Asia, with the lightest colors
indicating the highest
concentration of aerosols.

The lower graph shows the
amount of atmospheric
warming due to black carbon
emissions.

Another good correlation can
be seen between higher
concentrations of aerosols
and warmer atmospheric
temperatures due to black
carbon absorbing solar
radiation.
NASA Earth Observatory6
Impact of Black Carbon on
Radiative Forcings
Ramanathan et al.1
Time Series of Emission and Forcing terms for annual
mean conditions in South Asia and NIO.
Note: Results are from model simulations using NCAR PCM with INDOEX Black
Carbon and Sulfate concentrations.
Impact of Black Carbon on
Radiative Forcings Cont’d
Simulated JJA change in net
radiation (NR) at the top of the
atmosphere (TOA) → 6 W/m2
over NIO
Simulated JJA change in net
radiation (NR) for surface → -17
W/m2 over NIO
Menon et al.2
Note: Results are from model simulations using GISS with INDOEX Black Carbon
and Sulfate concentrations.
Impact of Black Carbon on
Atmospheric Temperatures
Ramanathan et al.1
Simulated and observed surface temperature changes during the dry
season (October to May). Blue curve includes: greenhouse gases
and sulfate aerosol emissions. Red curve includes: GHG’s, SO4, and
black carbon emissions.
Note: Results are from model simulations using NCAR PCM with INDOEX Black
Carbon and Sulfate concentrations along with greenhouse gas concentrations.
Impact of Black Carbon on
Atmospheric Stability
Ramanathan et al.1
Vertical profile of simulated
temperature trends over India with
black carbon emissions shown with red
curve.
Blue Bar = vertically averaged
temperature of the troposphere using
microwave sounding unit (MSU)
observations ~ 0.7 ± 0.2 K.
Red Bar = vertically integrated
simulation of atmospheric temperature
~ 0.46 ± 0.2 K.
0.3 K
0.27 K
Note: Results are from model simulations using NCAR PCM with INDOEX Black
Carbon and Sulfate concentrations along with greenhouse gas concentrations.
Impact of Black Carbon on
Tropical Cloudiness
With the addition of black
carbon and haze into the
model simulation, tropical
cloudiness decreases
throughout the diurnal profile.
Ackerman et al.9
Note: Results are from model simulations using ATEX meteorology data along
with black carbon concentrations from INDOEX for 1998 and 1999.
Impact of Black Carbon on
Surface Evaporation
Ramanathan et al.1
Annual mean latent heat fluxes for the ABC_1998 simulations.
Figure C shows the change between the 1995-2005 average and
the 1930-1950 average. Regions such as the Bay of Bengal show
the greatest decrease in latent heat flux and surface evaporation.
Note: Results are from model simulations using NCAR PCM with INDOEX Black
Carbon and Sulfate concentrations along with greenhouse gas concentrations.
Impact of Black Carbon on Sea Surface
Temperatures
The
•Blue
simulated
line shows
SSTthe
trends
SST show
increasing
that the
trend
ABC
influenced
counteracts
onlythe
by
influence
Greenhouse
of the
gases
GHGs
and
and
Sulfate.
Sulfate in the NIO :
•Trend
•Red line
is positive
shows the
at all
SST
latitudes
increasing
due to
trend
the forcing
influenced
of GHGs.
by
•The
Greenhouse
NIO warms
gases,
lessSulfate,
than theand
SIOAtmospheric
because of Black
the ABC
Carbon
influence.
•Green line shows observed SST trend.
SST trend for 1930-2000 for the Indian Ocean for pre-monsoon season
March to June, in relation to latitude.
Ramanathan et al.1
Trends in Sea Surface Temperatures
Running 5-year mean
of SST during the
respective hurricane
seasons for the six
principal ocean basins.
Webster et al.8
Sea Surface Temperature Trends
in Bay of Bengal
In the Bay of Bengal region,
an overall positive anomaly
trend is observed from
1970-2005. However, SSTs
in this region show smaller
positive change than the
surrounding areas.
Courtesy of Climate Diagnostics Center
Impact of Black Carbon on
Vertical Motion
The combination of
the increase of
rising motions
south of the
equator and the
subsidence in the
NIO leads to the
southward shift of
the monsoon
circulation.
Figure shows change in meridional circulation due to the ABC from 1985 to 2000
for June and July. Red indicates increased sinking motions, and blue indicates
increased rising motions.
Ramanathan et al.1
Why is all of this important?

By investigating black carbon’s influence on
environmental variables, we have attempted
to establish a link between BC emissions and
NIO tropical cyclonic activity.
Ingredients for Hurricane Formation

Ingredients for a
Cyclone




Warm SSTs, T>25oC or
79oF
Deep moisture at low levels
Light winds throughout
Troposphere
Convergence and triggering
mechanism



ITCZ
Tropical Wave
Weak Frontal Boundary
Courtesy of www.nhoem.state.nh.us
Convective Instability of the Second Kind
(CISK)

CISK is a popular theory that
explains how thunderstorms can
evolve and organize into hurricanes.
This cycle repeats itself, each time
Surface
air
intensifying
the storm until other
spirals
into
the
The decreased
factors
act to weaken it.
center
ofpressure
a low
surface

pressure
causes a larger
system,
pressurecreating
gradient,
convergence.
leading
to surface
convergence.
Since warm air is less
dense than cooler air,
the warmer air
expands, ultimately
causing the surface
Increased
pressure tosurface
decrease.
convergence allows
moist
air rises,
to rise.it This
As air
aircools
then condenses
and
into
clouds,
moisture releasing
more
latent heat.
condenses,
releasing latent
heat.
Courtesy of http://library.thinkquest.org
Trends in Hurricane Frequency
Graph displays regional time
series for 1970-2004 for the
total number of hurricanes.
Thin lines indicate annual
statistics. Dark lines show 5year running averages.
Since the mid 1980s, overall
hurricane frequency in the NIO
has decreased.
Webster et al.8
Conclusions and Take Home Message

Since 1970, black carbon emissions have
influenced the North Indian Ocean






Sea Surface Temperatures
Vertical Motion
Low-level Moisture
Tropical Clouds
Cyclone Frequency
Due to fast-paced industrialization, per capita
emissions of black carbon are expected to
triple by 2020.
References
1. Ramanathan, V., C. Chung, D. Kim, T. Bettge, L.. Buja, J. T. Kiehl, W. M.
Washington, Q. Fu, D. R. Sikka, and M. Wild, PNAS, 102, 5326-2333
(2005).
2. Menon, S., J. Hansen, L. Nazarenko, and L. Yunfeng, Science, 297, 2250
(2002).
3. Krishnamurti, T.N. et al, Tellus, 50B, 512-542, (1998).
4. Alles, D., Asian Air Pollution, (2005).
5. Goddard Space Flight Center,
http://www.gsfc.nasa.gov/topstory/20020822blackcarbon.html,
(2002).
6. Herring, D., NASA Earth Observatory,
http://earthobservatory.nasa.gov/Newsroom/NasaNews/2001/20010813505
0.html, (1999).
7. http://www-indoex.ucsd.edu/, (1999).
8. Webster, P., G. J. Holland, J. A. Curry, and H. R. Chang, Science, 309, 18441846 (2005).
9. Ackerman, A. S., O. B. Toon, D. E. Stevens, A. J. Heymsfield, V.
Ramanathan, E. J. Welton, Science, 288, 1042-1047 (2000).