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![Page 1: “Contribution of the synergy of ground- and space-borne remote sensing to atmospheric research. " Dr. Juan Carlos Antuña Marrero Senior Researcher, Grupo.](https://reader038.fdocuments.in/reader038/viewer/2022110207/56649d8b5503460f94a71bd1/html5/thumbnails/1.jpg)
“Contribution of the synergy of ground- and space-borne remote sensing to atmospheric research.
"Dr. Juan Carlos Antuña Marrero
Senior Researcher, Grupo de Óptica Atmosférica de Camagüey (GOAC),
Instituto de Meteorología, Cuba
Winter College on Optics: Light: a bridge between Earth and Space
The Abdus Salam
International Centre for Theoretical Physics
February,16th 2015
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Summary
1. Deriving Backscattering to extinction conversion coefficients.
2. Synergism of Lidar and SAGE II aerosols measurements: The Mt. Pinatubo Case.3. Comparing Saharan dust measurements and simulations.4. Lidar Networking
Conference:Contribution of the synergy of ground & space-borne remote sensing to atmospheric research.
Winter College on Optics
Light: a bridge between Earth and SpaceThe Abdus Salam International Centre for Theoretical Physics
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1. Deriving Backscattering to
extinction conversion coefficients.
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Mie Scattering Theory is the most general solution of the interaction between light and particles problem.
Based in the solution of the Maxwell equation’s under imposed boundary and skin conditions.
But the broad spectrum of conditions under which the interaction
takes place (size parameters and refractive index ranging between 0 and and 1 and respectively) make the system of equations
practically insoluble. Only particular cases have been solved analytically.
Two well known cases are :
- Single scattering by independent particles (Van de Hulst, 1957)- Polydispersion scattering (Ddeirmendjian, 1969)
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Single scattering by independent particles:Each particle has its own scattering pattern, not affected by neighbors particles. Also the incident beam of light is considered parallel, that is, coming from a distant source. Combination of the solution for an individual particle for a set of identical particles (named also monodispersers) let to the solution of multiple particles.
Polydispersion scattering:A set of particles of the same composition but different sizes (characterized by its particle size distribution) is considered, leading to a more general solution.
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General solution for single scattering:
Expressions for the vertical profiles of extinction (α) and backscattering (β) coefficients as well as the particle surface area concentration (A) and particle volume concentration (V) are:
α(z) = r2 Qα(m, x) n(r,z) dr [α] = km-1
β(z) = r2 Qβ(m, x) n(r,z) dr [β] = sr-1
km-1
A(z) = 4π n(r,z) r2 dr
V(z) = 4π/3 n(r,z) r3 dr
Where: Qα(m,x) : extinction efficiency factor Qβ(m,x) : backscattering efficiency
factorn(r , z) : particle size distribution
m : refractive index x : size parameter = 2πr/λ
λ : wavelength
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Particular Case: Stratospheric Aerosols
Calculations of Qα(m,x) and Qβ(m,x) require:
• the refractive index [m]• the particle size distribution [n(r)]
m could be calculated combining the values of the refractive index for H2SO4 - H2O mixtures at surface temperature (Palmer and Williams, 1975) with the Lorentz-Lorentz temperature dependence (Steele and Hamill, 1981). Temperature profiles are required Assumptions should be made about the H2SO4 - H2O mixture concentration.
n(r) could be assumed or empirical values from in situ measurements could be used
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Refractive index:
Ratio between the light speed in the two medium (Geometrical optics). Theory of molecular optics explains it based in the scattering properties. If the distance between particles is small compared to the , the scattering by the particles can be characterized using its polarizability.
Then the Lorentz-Lorentz formula is obtained:
n
n
TM
21
22
( )
where :: molar refractivity of the substanceM: molecular weight : density at the temperature T
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2/121
12)(
TA
TATn
is practically independent of T and at the range 190 - 260 K, it is possible to solve for at a predetermined T at which n is well known [ case of Palmer and William data for T = 300 K]It conducts to the expression: (Steele and Hamill, 1981)
)300(2)300(2
1)300(2
n
nAWhere:
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Stele and Hamill, 1981
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Several approaches to infer backscattering to extinction conversion coefficients:
1. Sun photometer measurements [Russell et al., 1993]
2. particle measurements aboard the ER-2 aircraft [Brock et al., 1993]
3. SAGE II satellite extinction profiles [Thomason and Osborn, 1992]
4. Multi wavelength lidar systems [Ansmann et al., 1998]
5. Particle size and concentration data from balloon flights
[Jäger and Hofmann, 1991] [Jäger and Deshler, 2002]
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Converting extinction & backscattering coefficients between wavelengths:
[Jäger and Hofmann, 1991] Period 1979 - 1990[Jäger and Deshler, 2002] Period 1991 – 1999
Method to convert particle backscatter measurements, at the widely used lidar wavelength of 532 nm, to particle extinction, and particle mass and surface areawavelength dependences of backscatter and extinction in the range 355 to 1064 nm are offered, comprising the classical lidar wavelengths of conventional Nd:YAG and ruby lasers.
The method utilizes particle size and concentration data from balloon flights over Laramie, Wyoming at 41ºN
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Particle Size
Distribution
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bBB 12 /
12
eEE 12 /
12
wavelength exponents of particle backscatter (kb)
wavelength exponents of particle extinction (ke)
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Wavelength Exponents:
Backscatter
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Wavelength Exponents:
Extinction
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2. Synergism of Lidar and SAGE II aerosols measurements: The Mt. Pinatubo Case
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Mount Pinatubo Eruption
June 12, 1991
The most intense of the 20th Century
Injected 20 Mt of SO2
into the stratosphere
Better documented ever
But still gaps in datasets
Synergy of Optical Instruments:The Pinatubo case
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Instruments operational at the time
of the
Mt. Pinatubo
Eruption
SAGE IISAGE II
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Aerosol Measurements:vertical profiles of aerosol extinction every 0.5
km from the surface to 40 km
at four wavelengths, 0.386, 0.452, 0.525, and 1.020 m
Also profiles of:ozone (O3) at 0.6 m
nitrogen dioxide (NO2) 0.453 and 0.448 m water vapor at 0.94 m.
Main orbiting parameters:
· Non-sun synchronous orbit
Altitude : 650 km Inclination : 57º
Nodal period : 96.8 minutes
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LIDAR : LIght Detection And RangingSAGE II : Stratospheric Aerosol and Gas
ExperimentOn Board ERBS October 1984Designed for 2 years, it lasted
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15 km
20 km
25 km
SAGE II Derived Aerosol Surface Area
(Thomason, 1998)
“GAPS” in time and space are normally filled by interpolation
Lidar measurements of the S. A. from the Mt. Pinatubo broadly used for studying its
local features,But never had been used for filling the SAGE II gaps. No quantitative comparisons for the whole post-
Pinatubo period held.
No information about the magnitudes:
• of the differences between both instruments.
• of the daily variability of the S. A.
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To explain how volcanic eruptions could cause climatic effects, we need to know precisely the amount of aerosols, their physical properties, and their evolution both in space and time.
Satellites provide better geographical coverage than any ground-based instruments. SAGE II provided the best coverage of all the satellite instruments for the Pinatubo eruption. But…...
It has spotty spatial and temporal sampling. It cannot observe in regions of dense aerosols.
Lidar measurements, being active and vertically pointing, provide vertical profiles with a greater vertical resolution than satellite limb measurements. Time series of lidar measurements are only constrained by weather conditions (cloud free sky). But…. They only have local coverage.
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Synergy between AODMeasured at Mauna
Loa by:SAGE II LidarSun-photometer
Evaluating the results of filling gaps in the SAGE II vertical aerosol extinction profiles using lidar measurements in the core of the Mt Pinatubo aerosol cloud.
The results using the lidar filling method show better agreement with the available lidar profiles (and with the sunphotometer data at Mauna Loa) than the ones filled with downward extrapolation, and produce AOD time series that are less variable in time.
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Evaluating the aerosol natural variability for the Mt Pinatubo aerosol cloud using both lidar and SAGE II datasets.
Lidar Measurements
For the first time ever, magnitudes of the aerosol variability for the 1991 Mount Pinatubo stratospheric cloud have been determined. The variability reaches values between 50 and 150% of the absolute percent differences, for time lapses of 12 to 48 hours, at the core of the cloud.
SAGE II Measurements
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Subvisible cirrus clouds radiative effects
Using GFDL Column RadiativeTransfer Code
PhD Dissertation (2010):
Barja, B., (2009). Characterizing subvisible cirrus cloud in the Wider Caribbean and its effects on solar radiation. (In Spanish).
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a) b)
c)d)
a) Measured extinction profile.
b) Parameterized optical depth profile.
c) HR for homogeneous and non-homogeneous cloud.
d) Fluxes for homogeneous and non-homogeneous cloud.
Adapting the GFDL Radiative Transfer Code: to the resources available at GOAC to the local atmospheric conditionsvalidation with local radiation data clear sky (CS)
Using cirrus lidar measurements taken at Camagüey:• derive cirrus extinction from lidar backscattering• parameterize lidar profiles for feeding RT code
Running RT code under CS and in presence of cirrus
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Diurnal cycle Heating Rate
and Radiative Forcing
A) Heating RateB) Radiative Forcing
August 11th 1998Optical Depth 2.74,Base: 9.39 km ( 320
hPa)Top: 15.24 km (120
hPa)
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Using GFDL Column Radiative Transfer Code
PhD Dissertation (2010):
Estevan, Rene (2009). Radiative effects of the Mt. Pinatubo aerosols over the Wider Caribbean, (In Spanish).
“Mt Pinatubo stratospheric aerosol radiative effects”
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Magnitude 10x 50x 100x 150x 200x
Months 19 23 28 32 34
Time (months) from the eruption to recover to 75 % of the solar radiation levels before the
eruption.
x : magnitude of the Mount Pinatubo eruption
Severe & catastrophic reductions of solar radiation possible by 3 different
events:• Impact of an extraterrestrial object on the earth
surface [Chapman, 2004; McGuire, 2006]• Nuclear War [Sagan, 1985; Robock, 1989;
Robock et al., 2006]• Volcanic Eruptions [McGuire, 2006]
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3. Comparing Saharan dust measurements & simulations
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Saharan dust
AOD (550 nm) MODIS
Summer
Winter
AOD (532 nm) CALIOP
Summer
Winter
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GEOS-Chem (Goddard Earth Observing System –Chem) model
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Generalized Retrieval of Aerosol and Surface Properties (GRASP)
Unified algorithm based on the
synergy of atmospheric
properties gathered from a variety
of remote sensing observations.
(Under development)
http://www.youtube.com/watch?v=PcDeqwDF15A
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4. Lidar Networking
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Lidar Networks• EARLINET: European Aerosol Research Lidar Network
http://www.earlinet.org/• CIS-LiNET: Community of Independent States Lidar Network
http://www.cis-linet.basnet.by/• AD-NET: Asian Dust and aerosol researchers Network
http://www-lidar.nies.go.jp/AD-Net/• REALM: Regional East Atmospheric Lidar Mesonet
http://alg.umbc.edu/REALM/• MPLNET: Micro Pulse Lidar NETwork (GSFC, NASA)
http://mplnet.gsfc.nasa.gov/• LALINET: Latin American Lidar Network
http://lalinet.org/
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Courtesy Dr. Anatoli Chaikovsky
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Courtesy Prof. Raymond Hoff
CREST: Center for Remote Sensing Science and Technology
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GAW: Global Atmospheric Watch
• WMO/GAW was established 1989 • GAW focuses on global networks for GHGs, ozone, UV,
aerosols, selected reactive gases, and precipitation chemistry
• GAW partnership with contributors from 80 countries• GAW coordinated by Environ. Division of WMO/AREP• GAW coordinates activities and data from 24 Global, ~200
Regional, and ~many Contributing stations
http://www.wmo.int/pages/prog/arep/gaw/gaw_home_en.html
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Goals•Establishing a GAW aerosol lidar network in cooperation with existing networks and interested research groups.
Products and Services•Easily accessible data. •Climatology of GAW aerosol variables.•Calibration and comparison of aerosol instruments. •Standard operating procedures for aerosol instruments.•Global coordination of aerosol optical depth and aerosol profiling networks.
Future Products and Services•Near real-time data (selected variables) for assimilation and verification of numerical weather and air quality forecast models.
Extracts from new GAW Strategic Plan
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Lidar data complementary to in-situ AOD
Lidar data provide vertical aerosol structure:dust stormsbiomass burningpollutionvolcanic ash
Lidars particular importance for aerosol models use for:climate assessmentsmodel validationprobable first ingredient to be incorporated in operational chemical weather models
Models assisting lidarsEARLINET already implemented dust predictions warning lidar operators on incoming dust
Lidars and models
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Objective: Long-term monitoring program on a global scale of aerosol vertical distribution combining simultaneous different types of data from lidar instruments
Work plan: • GALION will be based on an agreed cooperation between
existing aerosol lidar networks and individual lidar stations.• GALION will support and coordinate global coverage by
ground-based aerosol lidar through the implementation of standardized instruments at selected observatories in cooperation with experienced research groups.
GALIONGAW Aerosol Lidar Observation Network
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Muchas Gracias.