Transcript larsen

ASU MAT 591: Opportunities in Industry!
Radiative Transfer, MODIS and
VIIRS, and the AERONET system
North Larsen
[email protected]
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ASU MAT 591: Opportunities in Industry!
Todays Presentation
The Radiative Transfer Equation has evolved into a powerful expression
which is used by the community for understanding
problems from global warming to the development of sensors and data
products.
Today an overview of the radiative transfer equation
will be presented and a discussion into some of the NASA MODIS and
NPOESS VIIRS sensors data products. There will also be a discussion
of the AERONET data and the suite of sun photometers globally and
how they are used by NASA.
These topics are at the forefront and cutting edge of the remote sensing
commmunity currently.
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ASU MAT 591: Opportunities in Industry!
Understanding the Earth’s Atmosphere
20-30 km
O3 (0-400 DU)
8–20 km
Clouds
Aerosols
78% N2
99% of
21% O2
Atmosphere
0.8% Ar
< 0.2% trace gases
Water vapor
Temp
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ASU MAT 591: Opportunities in Industry!
Radiative Transfer



Radiative Transfer is the study of the transport of radiant energy
through a scattering, absorbing, and scattering medium.
The Atmosphere is divided into numerous homogeneous layers each
possessing its own optical depth, single scattering albedo,
temperature, and phase function.
The boundary conditions specified at the top of the atmosphere are
solar input, thermal emissivity, solar zenith angle. And at the bottom
of the atmosphere are surface albedo, surface temperature, and the
surface emissive properties.
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ASU MAT 591: Opportunities in Industry!
Radiative Transfer

The Radiative Transfer Equation has evolved into a powerful
expression which is used by the community for understanding
problems from global warming to the development of sensors and
data products.
dI/dt=Ioe-t
IO
I
dt
Earth’s Surface
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ASU MAT 591: Opportunities in Industry!
The Plane Parallel Atmosphere for Radiative Transfer
sensor
Z=100 t=0
m= cos(q)
Q= (m,f;,m’,f’)
a=a(t) T=T(t)
Fs
P(Q)=P(Q,t)
qo
q
Z=0
t=t*
T=T(t*)
Lambertian Surface
f
fo
A=Albedo
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ASU MAT 591: Opportunities in Industry!
Radiative Transfer Equation
The Radiative Trnsfer Equation in Plane Parallel Atmospheres
2
1
dI (t ,q , f )
a(t )
m
= I (t ,q , f ) 
df   dm P(t , m , f ; m , f ) I (t , m , f )

dt
4 0 1
t
a(t ) Fs
 (1  a(t )) B(T (t )) 
P(t , m , f ; m o , fo )e m o
4
In Which:
I
a
P
t
m
B
Fs
Radiance being solved for (W/m2str-1)
Single Scattering Albedo (no units)
Phase Function (no units)
Optical Depth (no units)
Cosine of zenith angle (no units)
Planck function of temperature T (W/m2str-1)
Solar Flux input at the top of atmosphere (W/m2)
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ASU MAT 591: Opportunities in Industry!
Visible to NIR Spectra
Atmospheric Transmittance, Surface Reflectance, Solar Irradiance,
and Imaginary Part of Refractive Index for Water and Ice, Visible (VIS) and Near Infrared
(NIR)
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1.00E-05
0.8
1.00E-06
0.7
H2O
O2
0.6
H2O
O3
0.5
1.00E-07
H2O
0.4
O2
H2O
H2O
0.3
O3
1.00E-08
Imaginary Part of Refractive Index
Transmittance/Reflectance/Irradiance
0.9
0.2
O2
0.1
H2O
0
1.00E-09
0.3
0.4
0.5
0.6
0.7
0.8
0.9
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Wavelength (microns)
T_atm
R_Veg
R_Soil
R_Snow
R_Water
Solar Irr
K_Water
K_Ice
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ASU MAT 591: Opportunities in Industry!
SWIR Spectra
Atmospheric Transmittance, Surface Reflectance, Solar Irradiance,
and Imaginary Part of Refractive Index for Water and Ice, Short Wave Infrared (SWIR)
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1.00E+00
1.00E-01
0.8
Transmittance/Reflectance
H2O
0.7
1.00E-02
0.6
0.5
1.00E-03
CH4
CO2
0.4
1.00E-04
0.3
H2O
0.2
1.00E-05
N2O
0.1
CO2
H2O
Irradiance (W cm-2 um)/Imaginary Part of Refractive Index
0.9
H2O
H2O
0
1.00E-06
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
3
Wavelength (microns)
T_Atm
R_Veg
R_Soil
R_Snow
R_Water
Solar Irr
K_Water
K_Ice
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ASU MAT 591: Opportunities in Industry!
MWIR Spectra
Atmospheric Transmittance, Surface Reflectance, Solar/Emissive Radiance Fraction for
Cloud, and Imaginary Part of Refractive Index for Water and Ice, Mid Wave Infrared
(MWIR)
1.0E+00
0.9
0.8
0.7
N2O
0.6
1.0E-01
CH4
H2O
0.5
CH4
0.4
1.0E-02
0.3
H2O
H2O
0.2
Imaginary Part of Refractive Index
Transmittance/Reflectance/Fraction of Radiance
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0.1
CO2
0
1.0E-03
3
3.2
3.4
3.6
3.8
4
4.2
4.4
4.6
4.8
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Wavelength (microns)
T_Atm
R_Veg
R_Soil
R_Snow
R_Water
Solar
Em issive
K_Water
K_Ice
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ASU MAT 591: Opportunities in Industry!
Thermal Spectra
Atmospheric Transmittance, Surface Emissivity, Blackbody Emittance (300 K),
and Imaginary Part of Refractive Index for Water and Ice, Long Wave Infrared (LWIR)
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1.0E+00
0.8
Transmittance/Emissivity
1.0E-01
0.7
0.6
0.5
1.0E-02
0.4
0.3
H2O
1.0E-03
0.2
O3
0.1
H2O
H2O
Emittance (W cm-2 um)/Imaginary Part of Refractive Index
0.9
CO2
0
1.0E-04
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6
7
8
9
10
11
12
13
14
15
Wavelength (microns)
T_Atm
E_Veg
E_Soil
E_Snow
E_Water
BB 300K
K_Water
K_Ice
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ASU MAT 591: Opportunities in Industry!
Then and Now
First Image from TIROS-1
First Image from EOS-Terra
New Brunskwick and
Nova Scotia (40 Years ago)
Mississippi Delta from MODIS
Feb 24, 2000
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ASU MAT 591: Opportunities in Industry!
MODIS Sensor (2000-2006)
MODIS (or Moderate Resolution Imaging Spectroradiometer) is
a key instrument aboard the Terra (EOS AM) and Aqua (EOS
PM) satellites. Terra's orbit around the Earth is timed so that it
passes from north to south across the equator in the morning,
while Aqua passes south to north over the equator in the
afternoon. Terra MODIS and Aqua MODIS are viewing the entire
Earth's surface every 1 to 2 days, acquiring data in 36 spectral
bands, or groups of wavelengths (0.4 – 15 microns). These
data are improving our understanding of global dynamics and
processes occurring on the land, in the oceans, and in the lower
atmosphere. MODIS is playing a vital role in the development
of validated, global, interactive Earth system models able to
predict global change accurately enough to assist policy makers
in making sound decisions concerning the protection of our
environment.
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ASU MAT 591: Opportunities in Industry!
MODIS Sensors Data Products
Radiance
Aerosol Product
Total Precipitable Water
Atmospheric Profiles
Gridded Atmospheric Product
Cloud Mask and cover
Surface Reflectance
Land Surface Temperature and
Emissivity
Land Cover/Land Cover Change
Gridded Vegetation Indices (Max NDVI
and Integrated MVI)
Thermal Anomalies, Fires, and Biomass
Burning
Leaf Area Index, and FPAR
Evapotranspiration
Net Photosynthesis and Primary
Productivity
Surface Reflectance
Vegetation Cover
Snow Cover
Sea and Lake Ice Cover
Normalized Water-leaving Radiance
Pigment Concentration
Chlorophyll Fluorescence
Chlorophyll a Pigment Concentration
Photosynthetically Available Radiation (PAR
Suspended-Solids Concentration
Organic Matter Concentration
Coccolith Concentration
Ocean Water Attenuation Coefficient
Ocean Primary Productivity
Sea Surface Temperature
Phycoerythrin Concentration
Total Absorption Coefficient
Ocean Aerosol Properties
Clear water Epsilon
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ASU MAT 591: Opportunities in Industry!
The Great Barrier Reef (09/15/03)
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ASU MAT 591: Opportunities in Industry!
Dust Storm Southern Afganistan (09/20/03)
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ASU MAT 591: Opportunities in Industry!
Hurricane Isabel (09/17/03)
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ASU MAT 591: Opportunities in Industry!
Forest Fires in Portugal (09/16/03)
Hurricane Isabel 09/17/2003
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ASU MAT 591: Opportunities in Industry!
AERONET Network
The AERONET (Aerosol Robotic Network) is a global network of sun
Photometers which measure local the atmospheric properties hourly.
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ASU MAT 591: Opportunities in Industry!
AERONET Network
Measurements are taken
Of the AOT in 7 bands, and
Total Column water vapor
Is measured also.
With this data validation of
MODIS and future VIIRS
Algorithms is performed and
Data products are improved
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ASU MAT 591: Opportunities in Industry!
The VIIRS Sensor (2008-2018)
Description
Collects visible/infrared imagery and radiometric data. Data types include atmospheric,
clouds, earth radiation budget, clear-air Visible/Infrared
land/water surfaces,
surface temperature,
Imagersea
Radiometer
Suite
ocean color, and low light visible imagery.
Primary instrument for satisfying 26 EDRs.
VIIRS
Specifications
Multiple VIS and IR channels between 0.3 and 12 microns
Imagery Spatial Resolution: 350m @ NADIR / 700m @ EOS
Heritage and Risk Reduction
POES - Advanced Very High Resolution Radiometer
(AVHRR/3)
DMSP - Operational Linescan System (OLS) - MOLS on
F18-F20
EOS - Moderate Resolution Imaging Spectroradiometer
(MODIS)
NPP - Early validation of operational instrument and
algorithms
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ASU MAT 591: Opportunities in Industry!
VIIRS data products
Radiance
Imagery
Cloud Cover Imagery
Cloud Type Imagery
Ice Edge Location Imagery
Ice Concentration Imagery
Soil Moisture
Aerosol Optical Thickness
Aerosol Size Parameter
Suspended Matter
Cloud Base Height
Cloud Cover/Layers
Cloud Effective Particle Size
Cloud Optical Thickness
Ocean Color/Chlorophyll
Sea Ice Age and Motion
Cloud Top Height
Cloud Top Pressure
Cloud Top Temperature
Albedo (Surface)
Land Surface Temperature
Vegetation Index
Snow Cover/Depth
Surface Type
Currents
Fresh Water Ice
Ice Surface Temperature
Littoral Sediment Transport
Net Heat Flux
Mass Loading
Active Fires
Precipitable Water
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ASU MAT 591: Opportunities in Industry!
Why?
National Importance

Civilian Community
– Timely, accurate, and cost-effective public
warnings and forecasts of severe weather
events, reduce the potential loss of human
life and property and advance the national
economy
– Support of general aviation, agriculture, and
maritime communities aimed at increasing
U.S. productivity

Military Community
– Shift tactical and strategic focus from
“coping with weather” to anticipating and
exploiting atmospheric and space
environmental conditions
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ASU MAT 591: Opportunities in Industry!
Why?
Protect Safety of Life and Property
Improve Accuracy of Severe Weather Warnings
Increase in hurricane
landfall forecast skill will
save an estimated $1
million per mile of
coastline that does not
have to be evacuated
Improved early warnings
mitigate the devastating
effects of floods through
disaster planning and
response
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ASU MAT 591: Opportunities in Industry!
Why?
Benefits to Industry
Maritime industry - Ocean winds,
waves, currents, and marine
warnings and forecasts improve
vessel routing for safety, fuel
savings, and efficient operations
Commercial
fishing industry knowledge of sea
surface winds is
critical to shrimp
yields in the gulf
Agricultural industry - Fire
monitoring, vegetation
index, frost, hail, and flood
warnings critical to
production
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ASU MAT 591: Opportunities in Industry!
Why?
Other Benefits to the World Community
NPOESS will improve ability to predict El Niño. A 60%
increase in El Niño forecast skill will save $183 million per
year over 12 year period
Ice
monitoring
for shipping
and oil
exploration
Snow cover mapping spring flood prediction
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ASU MAT 591: Opportunities in Industry!
Thanks
• MODIS Images and information presented is
from the NASA Goddard MODIS website
• NPOESS information is from the NPOESS IPO
• AERONET information is from the NASA Goddard
AERONET Sun Photometer website
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