Applications of Advanced Imagers
James F.W. Purdom
CIRA
Colorado State University
Fort Collins, CO
Applications of Advanced Imagers
in synergy with other space based
observing capabilities
(It’s a system of space based
observations, but we will focus on
imagers)
Environmental Satellite Sensor Synergy
Goal and Challenge:
Dynamic Tasking and Adaptive Sensing
 Observing system characteristics
– Polar is global and fixed (well determined orbit and
sensor operational capability)
– Geostationary is quasi-hemispheric and adaptive
(point and shoot)
 Selected sensors will operate over very similar
spectral regions (visible to infrared)
 The spatial, spectral and radiometric resolutions of
future geostationary satellite systems’ sensors will in
some cases approach and in other cases surpass
those of the polar orbiting satellite systems’ sensors.
Example of Synergy in GOES-R Era
Goal and Challenge:
Dynamic Tasking and Adaptive Sensing
 Intra-Satellite (USA Operational)
– GOES: ABI and HES (adaptive)
– NPOESS: VIIRS and CrIS (fixed)
 Intra-System (USA Geo + operational polar)
– GOES-E and GOES-W (or other possibilities)
– NPOESS AM and PM, METOP, FY-3, METEOR-3
 Inter-System
– GOES-R and NPOESS (ABI, VIIRS, HES and CrIS)
– GOES-R, NPOESS and other operational and research
satellites
Intra-Satellite (USA Operational)
GOES: ABI and HES (adaptive)
Evolving instability field
from HES triggers super
rapid scan over severe
storm area
Example: Use ABI Data to Task HES VNIR
GOES-8 loop from 1615 to 2345: this loop illustrates the changes that occur in the cloud
field after the MODIS pass and the need to dynamically task HES.
Despite increasing cloud cover, the Florida Bay and Northern Keys
could be successfully imaged over several hours which will allow for
observations of ocean color as well as changes due to tidal effects.
Florida Bay
Northern
Keys
Intra-System (USA Geo + operational polar)
GOES-E and GOES-W (or other possibilities)
Intra-System (USA Geo + operational polar)
NPOESS AM and PM, METOP, FY-3,
METEOR-3
Inter-System (USA Geo + operational polar)
NPOESS AM and PM, METOP, FY-3, METEOR-3,
etc
Intra-System (USA Geo + operational polar)
NPOESS AM and PM, METOP, FY-3,
METEOR-3
EO-1
Landsat-7
SAC-C
Terra
 “True color” movie made
from multispectral
images from the A.M.
Constellation
 While this movie focuses
on storm development,
one can imagine how
high spatial and spectral
resolution imagery from
Terra and EO-1,
separated in time by 39
minutes could be used
to investigate the
development and
evolution of ocean and
coastal zone phenomena
Inter-System
GOES-R, NPOESS and other satellites
• Can you imagine the impact
of Radio Occultation when
combined with the frequency
of GOES-R for applications
such as nowcasting severe
weather ?
•
Collard and Healy, QJRMS, 129,
p.2741, 2003
Inter-System
GOES-R, NPOESS and other satellites
• Can you imagine the impact
of Radio Occultation when
combined with the frequency
of GOES-R for applications
such as nowcasting or
hurricane analysis ?
•
Collard and Healy, QJRMS, 129,
p.2741, 2003
Inter-System
GOES-R, NPOESS and other satellites
 GOES-R total HES can serve as stable reference basis for
other satellites (operational polar and other LEO)
– Contiguous and high resolution spectral measurements
required for inter-calibration
 Spectral flexibility (adaptability) allows for spectral
matching with other systems’ instrumentation
 GOES-R total HES is a baseline
 Already looking at AIRS and
LEO channel calibration
 GOES-R ability to track diurnal cycle
– Simultaneity with LEO constellation
– Contribution to GPM (Global Precipitation Mission)
 High spectral resolution radiance matching for scenes over
long time periods by one fixed system at the same viewing
angle and from the same altitude (Goody concept)
– Detect and monitor long term changes (trends) in water
vapor and other gasses
The spatial and temporal domains
of the phenomena being
observed drive the satellite
systems’ spectral needs as a
function of space, time, and
signal to noise.
Synergy in its infancy – hurricane analysis :
geostationary, polar and other
Synergy in its infancy – hurricane analysis:
geostationary, polar and other
Synergy in its infancy – hurricane analysis
:
geostationary, polar and other
Synergy in its infancy – hurricane analysis
: geostationary, polar and other
Synergy in its infancy – hurricane analysis
: geostationary, polar and other
Synergy in its infancy – hurricane analysis
:
geostationary, polar and other
Synergy in its infancy – hurricane analysis
: geostationary, polar and other
Synergy in its infancy – hurricane analysis
: geostationary, polar and other
ENTERING AN AGE OF
MULTI-PLATFORM
MULTI-SENSOR
PRODUCTS
But we’re
not there
yet
To assure full
utilization we
need to
capitalize on
the adaptive
observing
nature of the
geostationary
system in
synergy with
the fixed polar
system
Period
Climate
Long term
Seasonal
Interan’l
Spatial
Temporal
Spectral
Radiometric
Issue
L
Weekly*
H
vH
Climate
Year Months
M/L
Days to
Weekly*
M
M
Climate
NWP
1-14 day
M/L (obs)
M (surface)
4 hr
Sounder: H
Image: M
H
Weather,
Transportation
Regional
NWP
6-24 hr
M (obs)
H (surface)
1 hr
Sounder: H
Image: M
H
Weather,
Trans.
Nowcast
Severe Wx
0-6 hours
H
Sounder: 0.5 Sounder: H
hr
Image: M
Image: 1min
H
Weather,
Trans.
Coastal
Littoral
Hr to daily
H to vH
1-3 hr
H – VNIR
vH
Littoral,
Weather,
Trans.
Rapid
Action
Disaster
Immediate
vH
1 min
H – VNIR
Image: M
H
Homeland
Security
+ L~100km, M~10km, H~1 km, vH~100m
*cumulative from more freq obs system where instrument stability over very long time period is important
The spatial and temporal domains
of the phenomena being
observed drive the satellite
systems’ spectral needs as a
function of space, time, and
signal to noise.
Spectral Awareness In Terms of
Space, Time, Signal to Noise and
Scene Characteristics
Today we’re digital - Basic Premise
Spectral Awareness In Terms of Space,
Time, S/N and Scene Properties
AVIRIS spectral
movie from 0.4 to
2.4 microns
Fire scene
Spectral Awareness In Terms of Space,
Time, S/N and Scene Properties
AVIRIS spectral
movie from 0.4 to
2.4 microns
Fire scene
AVIRIS Spectral Information from the Scene Depicting Cloud, Smoke
and Active Burn Areas
AVIRIS Image - Linden CA 20-Aug-1992
224 Spectral Bands: 0.4 - 2.5 mm
Pixel: 20m x 20m Scene: 10km x 10km
Spectral Signatures of Selected Pixels
1
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.
0
C
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F
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H
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a
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e
S
o
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l
S
m
o
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e
(
s
m
.
p
a
r
t
.
)
S
m
o
k
e
(
l
g
.
p
a
r
t
.
)
S
h
a
d
o
w
Smoke - large part.
Shadow
1
.
0
Fire
Hot Area
Soil
Cloud
AparentRflcane
Grass
Lake
Smoke small part.
0
.
1
4
0
0 7
0
0 1
0
0
01
3
0
01
6
0
01
9
0
02
2
0
02
5
0
0
W
a
v
e
l
e
n
g
t
h
(
n
m
)
The need to filter atmospheric effects:
note water vapor change every 15 minutes
HES VIS/NIR at high resolutions will be able to monitor pre-cumulus cloud moisture
and moisture convergence – this will be enhanced by HES-IR
Note water vapor change every 15 minutes
HES VIS/NIR at high resolutions will be able to monitor pre-cumulus cloud moisture
and moisture convergence – this will be enhanced by HES-IR
VIIRS, MODIS, FY-1C, AVHRR
Reality:
CO2
O2
O3
H2O
O2
H2O
H2O
H2O
O2
H2O
H2O
CO2
Spectral Awareness In Terms of Space,
Time, S/N and Scene Properties
VIIRS
MODIS
Channel Positions of Various Ocean-Color
Sensors, 1978-2000* (380 – 950 nm)
For a multi spectral
sensor
 Many spectral
bands are
identified for
various
applications
 Selection of
band location
and width are
also important
* IOCCG Report #1
GOES Sounder spectral coverage - Example of spectral variability
Associated with channel radiometry
High Spectral
Resolution
(AIRS)
resolves
H2O
spectral
Features (right)
GOES-I/M era
sounder H20
Channels
(above)
With satellite remote sensing, there are four
basic questions that need to be addressed
 They all deal with
resolution:
– temporal (how often)
– spatial (what size)
– spectral (what
wavelengths and their
width)
– radiometric (signal-tonoise)
With satellite remote sensing, there are four basic
questions that need to be addressed
Spectral Awareness
Spectral Awareness
Scattering from water versus ice
particles at 3.9 microns
Response of 3.9 vs. 10.7 microns to
Temperature variability in a FOV
Visible loop (left) and 3.9 micron reflective component loop (right)
from GOES-West (aspect ratio not 1:1)
Clouds separate into classes
when multispectral radiance information is viewed
Hi cld
Mid cld
vis
1.6 um
Lo cld
Snow
Clear
LSD
1.6 um
8.6-11 um
11 um
11 um
Cloud Composition
Contrails
Image Over Kansas - 21 April 1996
Ice Cloud
Infrared Temperature Difference - 8.6 mm (Band 29) - 11.0 mm (Band 31)
Contrails
Water Cloud
Infrared Temperature Difference - 11.0 mm (Band 31) - 12.0 mm (Band 32)
Focus
 Maximizing utilization from the satellite systems
available in the 2010 era
– The amount of data and potential products will be so
massive that it can swamp the ordinary user
– Growth in applications and sophistication
 What we can do today to improve current
utilization
– User requirements versus system capability
– Educating the user
– Keeping science and vision in play
The spatial and temporal domains of the
phenomena being observed drive the
satellite systems’ spectral needs as a
function of space, time, and signal to
noise.
GOES-R: Unique in spectral, spatial and
temporal domains
GOES-R sensors spatial and spectral
resolutions approach and in some
instances surpass those of its operational
polar orbiting counterparts
Spatial, Spectral, Temporal Improvements:
 Predicting when and
where severe weather
will occur (better location
accuracy)
– Severe storms
– Hurricanes
GOES I-P
 Increased lead-times for
severe weather warning
helping meet NWS goals
 Track path of severe
weather more accurately
 Greatly enhanced
hurricane monitoring
GOES-R
Temporal
Comparison of animation sequences of severe thunderstorm over western
Kansas. Movies at 30, 15, 5 and 1 minute intervals. While 5 minute
interval imaging is routine for GOES-R, special imaging like this is
possible at 1 minute intervals or less at 4(ABI) to 30 (HES-VNIR) times
better spatial resolution than today.
Spatial
1 Km to 250 m
Hurricane Erin
09/09/01 ~1530 Z
•Note the detail in the eye wall (you can see
up its side), improving the resolution of
visible imagery provides enhanced ability
to analyze a cloud field
GOES-8: ~1 km
Spectral - ABI
Simulated GOES-R Imagery
Intra-satellite
Intra-satellite
Spectral
Intra-satellite
Observe Phenomena With Greater
Information Content
Simulated GOES-R Multi-channel Product
Intra-satellite
Water And Wet
Ground
Middle
Level
Moisture
Boundary Between
Dry And Unstable Air
Cirrus Cloud
Severe
Thunderstorms
New products based on mathematical analysis of multi-channel images –
every 5 minutes or less!
Different Combinations Of Mathematically Derived Images
Highlight Different Features:
Adaptive Observing Leading To Adaptive Analysis
The phenomena
being analyzed
defines the
spectral, spatial
and temporal
requirements of
the satellite
observing system.
For satellite
applications that
employ animation
that means that
different
applications and
procedures
depending on
scale
Roles of various sensors (Polar are basically 4 hr repeat;
since Geo may do adaptive observing, delta time may be
varied to optimize strategy)
Cloud Base, Top and Layer related products
– Daytime cloud base & top
 stereo ABI and/or HES-VNIR
– VIIRS with GOES imagers every 4 hrs
 shadow from ABI or HES-VNIR, VIIRS at 4 hrs
 HES-VNIR reflectance and HES-IR radiances
– Day or night cloud base
 Derived HES-IR, CrIS, IASI augmented by GPS for stability, ABI surface
temperature
– daytime HES-VNIR for moisture in cloudy regions over land)
– Day or night cloud top
 Multispectral slicing methods
– HES-IR and ABI every 5 to 60 minutes global
– CrIS and VIIRS every 4 hours global
– Cloud layer
 high resolution imager within sounder using n* type methods (requires
model baseline), cloud phase with ABI to delineate ice from water cloud,
stereo improvement and limited layer thickness using ABI and HES-VNIR
Adaptive observational needs of NWP and nowcasting will help
define sensor activity and application in GOES-R era
Atmospheric Motion Products



Cloud and plume motion vectors (Cloud height from prior chart)
– ABI
 5-min interval for hemispheric cmv’s
 Rapid scan for special applications
– HES-VNIR (10 to 36x improvement in spatial resolution over ABI)
 < 300 m and 1 min intervals for severe weather and hazard
applications
Moisture motion vectors
– VIIRS in polar regions - need interim polar sounder & imager gap filler
– Routine ABI @ 5-min intervals
 Hemispheric and local scale
– Routine HES-IR @ 30-60 min intervals
 Hemispheric and local scale
– Improved vertical definition for certain applications with HESVNIR and ABI
– HES-VNIR @ 300 m and ~10 min intervals
 moisture motion in convective boundary layer in synergy with HES-IR
Ocean surface winds
– CMIS @ 4 hr intervals
Viewing Perspective, dt and l, determine what we
see




Differences in scattering as a function of sun-scatterer-detector
geometry allow for a variety of atmospheric, land, costal zone
and ocean applications (think of MISR)
Stereo cloud height determinations: accuracy is in large part a
function of spatial resolution (shadows can also provide
exceptionally accurate cloud height depending on time of day
and viewing geometries)
Exceptional CMV’s (u, u', v, v', w') in complex situations:
potential for nearly 50 times higher resolution than today (150m
vs 1000m) and over 10 times higher than GOES-R’s ABI (150m
vs 500m)
Pre-cumulus moisture field and its changes in time
Adaptive observational needs of NWP and nowcasting will help
define sensor activity and application in GOES-R era
Atmospheric Profile Products
Resolutions of various sensors
 CrIS/IASI 4 hr T and H2O profiles, globally, 14 km clear and above cloud
top
 GPS/OS – very accurate profiles above tropopause around 100 km spatial
 ATMS/AMSU 4 hr T and H2O, globally, ~30 km through cloud over ocean
 HES-IR 15 min to hourly T and H2O profiles, clear and above cloud
 HES-VNIR mesoscale TCM (total column moisture), 300m best used in
conjunction w/ HES-IR and ABI (surface temperature)
Sounding applications should be in synergy
 Global scale analysis and modeling
– 4 hr radiances and GPS OS
 Regional scale modeling
– 1-4 hr sounding/radiances and GPS OS
 Local scale/ mesoscale for severe storm prediction
– <hourly radiances, sounding, with GPS OS
 Surface parameters from sounder (in conjunction w/ VIIRS and ABI)
– SST 4 hr over open ocean and hourly to 5 minutes* over coastal
waters
– Surface Temperature and moisture hourly to 5 minutes*
– (*cloud cover, temporal and spatial requirement play crucial role)
Increased Sounder
Coverage
60 Minutes
GOES I & N
GOES R HES
Improved Clear Radiance Data
from Combining Imager and Sounder Observations
RMS radiance differences between true clear radiance and cloud re-moved clear column
Note improvement in sounder clear column radiance estimation when
higher resolution imager data is used in synergy with sounder data
(Smith et al. 2003)
Inter-System
GOES-R, NPOESS and other satellites
•
A major challenge that will be
faced when trying to achieve
such high resolution will be
combining information from
sensors with highly differing
horizontal resolutions. For
example IR sounders in the 2010
era will have horizontal
resolutions around 10 km, while
GPS at the surface represents a
traverse across around 200 km.
•
Another challenge will be NWP
models ability to handle clouds
and moisture so that the entire
radiance information is utilized.
•
Collard and Healy, QJRMS, 129, p.2741,
2003
Nowcasting requires detailed information on mesoscale thermodynamic
structure of atmosphere, cloud type and vertical wind shear
Convection and Severe
Weather
Important for Nowcasting
Convection and Severe Weather
• Vertical wind shear
• Evolving instability field
• Strength of storm
produced cold pool
• Updraft strength
• Anvil characteristics
Development
Temperature structure





• Storm-environment
interaction
• Cloud top rotation
• Storm damage


Vertical shear
– ABI (cloud motion)
– HES-IR (moisture motion)
– HES-VNIR (cloud and moisture motion)
Evolving instability field
– ABI (surface heating)
– HES-IR (instability and surface heating)
– HES-VNIR (detailed moisture field)
Cold pool production
– HES-IR
Updraft strength
– ABI (IR top temperature)
– ABI and HES-VNIR (overshooting top
height)
– Above with HES-IR (updraft efficiency)
Anvil characteristics & storm environment
interaction
– ABI (growth and detailed upper level
atmospheric motion and water vapor
behavior)
– HES-IR and VNIR (as ABI but with better
spectral definition)
Rotating overshooting top
– ABI and HES-VNIR
Storm damage
– HES-VNIR
The development and evolution of
deep convection
GOES-R: Unique in
spectra, space and time
The spatial and temporal
domains of the phenomena drive
the spectral needs as a function
of space, time, and signal to
noise. Nowcasting severe
convection requires frequent
imaging and sounding that can
only be provided by
geostationary satellites.
GOES Lightning Mapper
 New NOAA
instrument
– Severe storm
warning times
– Lightning danger
alerts
– Disaster team
response
– Nitrogen
production
 Hemispheric or
CONUS Coverage
 Parameters
– 10 km spatial resolution
(1 km goal)
– 1 km vertical resolution
 Increased coverage
over oceans and lands
– Currently No Ocean
Brightness Temperature (K)
Detection of Temperature Inversions Possible with Interferometer
Texas
Spikes down cooling with height
(No inversion)
Ontario
Spikes up warming with height
(low-level inversion)
Wavenumber (cm-1)
Detection of inversions is critical for severe weather
forecasting. Combined with improved low-level moisture
depiction, key ingredients for night-time severe storm
development can be monitored.
Ocean Color Products
Coastal: At-sensor radiances for ocean color products including
chlorophyll, CDOM, suspended matter, and bottom properties
 HES-VNIR optimal for multiple cloud free views /day @ <300 m
– Hourly best for modeling coastal ocean dynamics and currents
by feature tracking
– Tasked by ABI defined “cloud free” (%TBD) FOV every 5 min
 VIIRS Not optimal, spatial, spectral or temporal for coastal zone
– 4 hourly fixed views @ 1000 m not adequate to resolve tidal
related features
– May not be cloud free FOV
– Complex features and atmospheric correction best resolved
by HES (different satellites-solar-atmosphere scattering
angles)
 Selected commercial high-spatial resolution data may be available
Open Ocean (chlorophyll major constituent)
 VIIRS 4 hourly fixed views @ 1000 m appears adequate
 HES-VNIR may be tasked for selected cloud free views @ <300 m
– Tasked by ABI defined cloudy FOVs
 Selected international data may be available
Example: Use ABI Data to Task HES VNIR
GOES-8 loop from 1615 to 2345: this loop illustrates the changes that occur in the cloud
field after the MODIS pass and the need to dynamically task HES.
Despite increasing cloud cover, the Florida Bay and Northern Keys
could be successfully imaged over several hours which will allow for
observations of ocean color as well as changes due to tidal effects.
Florida Bay
Northern
Keys
Then along came Floyd
It will be important to monitor
such disasters hourly at very
high resolution as will be
available from HES’VNIR
capability
Ocean color showing result of flooding
interacting with pig farms. You want to be
able to make daily cloud free images of this
consequence of a natural disaster
immediately and blend with SST, ocean
currents and other information.
Climate products require long term, stable and accurate
sensor measurements
 GOES-R total HES can serve as stable reference basis for
other satellites (operational polar and other LEO)
– Contiguous and high resolution spectral measurements required
for inter-calibration
 Spectral flexibility (adaptability) allows for spectral matching
with other systems’ instrumentation
 GOES-R total HES is a baseline
 GOES-R ability to track diurnal cycle
– Simultaneity with LEO constellation
– Contribution to GPM (Global Precipitation Mission)
 High spectral resolution radiance matching for scenes over
long time periods by one fixed system at the same viewing
angle and from the same altitude (Goody concept)
– Detect and monitor long term changes (trends) in water vapor
and other gasses
 GPS - 1st order measurement
Climate products require long term, stable and accurate
sensor measurements
 GOES-R ability to track
diurnal cycle spectrally with
both ABI and HES!
Hourly Vis
Average
Animation
for 31 Days
in January
2001 over
Australia
Seasonal to
Interannual
Range - are
we missing
something?
Hourly Vis
Average
Animation
for 31 Days
in May 2001
over Western
Pacific
Seasonal to
Inter-annual
Range: multi
information
Daily cloud free SST
anomaly from cloud
cleared GOES IR data
(1998) showing return
current with la Nina
Hourly
Average
Animation
for 31 Days
in May 2001
over Western
Pacific
Seasonal to
Inter-annual
Range: multi
information
Daily cloud free SST
anomaly from cloud
cleared GOES IR data
(1998) showing return
current with la Nina
Aerosol Products
 Primary VIIRS/APS global product every 4 hours
 Marine environment
– ABI adds more frequent observations for variation as
function time
– HES VNIR provides more frequent and @ <300 m
resolution (less cloud effects)
– Moisture effect on aerosols (particle size)
– Water leaving radiance for coastal water algorithms
– CrIS/ 4 hr and HES-IR/ 1 hr provides better definition of
moisture profile at 4-10-12 km scale
 Over land
– ABI adds more frequent observations for variation as
function time
– HES VNIR provides more frequent and @ 300 m resolution
(less cloud effects)
– Moisture effect on aerosols (particle size)
– CrIS/ 4 hr and HES-IR/ 1 hr provides better definition of
moisture profile at 4-10-12 km scale
Aerosol Products – Dust storm during daylight
Filling the gaps between 4 hourly APS
Aerosol Products – Dust storm day and night
Filling the gaps between 4 hourly APS
Rapid Response!!
Catastrophic Products
 Catastrophic (on demand): utilize baseline information – every
5 min update required
 Accurate plume location and tracking
– ABI @ 1 min
– HES VNIR @ 1-5 min w/ <300 m resolution (less cloud
effects)
 Dual satellite HES VNIR better plume depth
 HES-IR 15 min characterization of moisture profile and trace
gases
 Damage area identification and possible assessment
Fire and Plumes, as below, can be rapidly detected and assessed
So can other type plumes
•VIIRS every 4 hrs at various resolutions
•ABI every 1 to 5 minutes at various resolutions
•HES often, depending on aerial extent, at 300 meters or less
This damage was due to a tornado, it could have occurred over a similar or larger
area due to explosions from various causes. Do you want to wait for conventional
monitoring methods to begin damage assessment? With HES you can view
immediately with exceptionally high spatial, spectral and temporal resolutions.
LaPlata tornado damage
path at 120 m resolution
LaPlata tornado damage
path at 240 m resolution
LaPlata Tornado Damage – 1
from EO-1
30 m 60 m
120 m
240 m
The Satellite System of the GOES-R
Era Will Lead To Improvements . .
 Improved prediction
accuracy from
improved observations
– Observe phenomena
with greater clarity
– Observe phenomena
with greater
information content
– Observe phenomena
with greater
frequency
 Observe the previously
unobserved
Particularly when:
we capitalize on the
adaptive observing
nature of the
geostationary
system in synergy
with the fixed polar
system