Raymond K Garcia David Hoese Jordan J Gerth Scott S Lindstrom Kathleen I Strabala UWMadison Cooperative Institute for Meteorological Satellite Studies Timothy J Schmit NOAANESDISASPB ID: 645958
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GOES-R ABI and Himawari-8 AHI Training using SIFT
Raymond K. Garcia, David Hoese, Jordan J. Gerth, Scott S. Lindstrom, Kathleen I. StrabalaUW-Madison Cooperative Institute for Meteorological Satellite StudiesTimothy J. SchmitNOAA/NESDIS/ASPBBill WardNOAA/National Weather ServiceSlide2
SIFT
Satellite Information and Familiarization ToolCreated to facilitate training of Himawari-8 data in the Pacific Region of the NWS2Satellite Meteorology Madison Wisconsin 2016Slide3
Where has SIFT been used?
NWS Day-1 Ready Training for Guam WFO (Himawari)NWS Training at Honolulu WFOSatellite Liaison Training in Kansas CityGraduate Student Training in Madison3Satellite Meteorology Madison Wisconsin 2016Slide4
System Requirements
Compatible with Windows/Linux/MacFaster I/O the betterDoes a lot on the Graphics Card500 Mb (8.5 Gb) workspace needed for 2 km (0.5 km) imagerySample datasets (pre-projected mercator GeoTIFF files) require up to 1TB of storage.Coming soon: Data in Native Formats!4Satellite Meteorology Madison Wisconsin 2016Slide5
Why is SIFT good for training?Quick access to multiple bands for visual inspection/comparison
Density Diagrams/Scatterplots to compare two channelsEasy and seamless zoom and roam capabilitiesDatasets are pre-selected and loadedWhen you compare bands, you learn something about both bands being compared5Satellite Meteorology Madison Wisconsin 2016Slide6
The SIFT DisplayAMS Satellite Meteorology Madison Wisconsin 2016
6Area Probe Graphs (Density Diagrams, Bar Graphs)Layers – List of data that are loadedLayer DetailsSlide7
SIFT Example 1
7First, just load up one image, then load up all bands for a different timeAsk a simple question: Why is Image #2 brighter?#1#2Satellite Meteorology Madison Wisconsin 2016Slide8
SIFT Example 1
Discuss Probe Features of SIFT ToolWhat does this tell you about your scene?Why is Band 5 reflectance small?Why is Band 7 so much warmer?Why is band 13 warmer than band 14?Why is Band 12 Warmer than most other IR bands?Day or Night?Visible and near-IR: Reflectance valuesshown and they increase to the right
Infrared: Brightness temperature
shown and they increase to the right
0.47
mm, “blue”0.51 mm, “green”
0.64
m
m “red”
0.86
m
m, “veggie”
1.6
m
m, “cirrus”
2.2
m
m, “phase”
3.9
m
m, “shortwave IR”
6.2
m
m, “high
wv
”
6.9
m
m, “middle
wv
”
7.3
m
m, “low
wv
”
8.6
m
m, “SO2 window”
9.6
m
m, “ozone”
10.4
m
m, “clean window”
11.2 mm, “window”12.1 mm, “dirty window”13.2 mm, “CO2”
8Slide9
SIFT Example 2:AHI Band 3 Versus Band 4
9AHI Band 3 (0.64 μm)AHI Band 4 (0.86 μm)Easy to toggle between these two to really accentuate the differences
Satellite Meteorology Madison Wisconsin 2016Slide10
SIFT Example 2
10Load up all Bands, and create a histogram & density diagram of a region – those are shown below. Explain what you see!Band 3 Reflectance is mostly small, with a few higher valuesConclusion: Mostly clear
Why is there a region of relatively high Band 4 Reflectance?Slide11
SIFT Example 3
Describe what you see in this Density Diagram (Band 3 v. Band 14)This is an excellent way to make sure the students really do understand the capabilities of each individual band11Note there are two distributions: Fairly Warm and Highly ReflectiveColder with Increasing ReflectivitySatellite Meteorology Madison Wisconsin 2016Slide12
SIFT Example 4a
What are the different bands telling you here?Is it day or night?Is it cloudy? Thick clouds? Thin clouds?What do the Water Vapor Bands Tells you?Which two (that’s a hint) bands are most important in describing what’s going on?12Satellite Meteorology Madison Wisconsin 2016Slide13
SIFT Example 4b
13Which Probe Matches Which Scene?Which Two Channels help most?
Infrared Bands
Visible/Near IR Bands
Satellite Meteorology Madison Wisconsin 2016Slide14
SIFT Example 4c
14Behold the Power of Band 4 in highlighting Land!Reflectivity is much greaterSatellite Meteorology Madison Wisconsin 2016Slide15
SIFT Example 515
At which two channels are you looking?Visible or Infrared?Cirrus/Ice BandVeggie BandSlide16
Sift Example 5
16Which probe corresponds to the Ocean Location you just saw?
0.47
mm, “blue”0.51 mm, “green”
0.64 mm “red”0.86
mm, “veggie”1.6 m
m, “cirrus”
2.2
m
m, “phase”
3.9
m
m, “shortwave IR”
6.2
m
m, “high
wv
”
6.9
m
m, “middle
wv
”
7.3
m
m, “low
wv
”
8.6
m
m, “SO2 window”
9.6
m
m, “ozone”
10.4
m
m, “clean window”
11.2
m
m, “window”
12.1
m
m, “dirty window”
13.2
m
m, “CO2”Satellite Meteorology Madison Wisconsin 2016Slide17
Sift Example 5
17Of the remaining three probes, which corresponds to this point
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Sift Example 5
18Match the Probe on the left to the Scene. Which goes with the ‘x’?
Satellite Meteorology Madison Wisconsin 2016Slide19
Sift Example 5
19Satellite Meteorology Madison Wisconsin 2016Slide20
SIFT Example 6
20131415
Satellite Meteorology Madison Wisconsin 2016Slide21
SIFT Example 6
21Satellite Meteorology Madison Wisconsin 2016Slide22
Questions asked in Lab
What AHI visible reflectance band is best for detecting/identifying low clouds?What AHI visible reflectance band is best for detecting/identifying high clouds?What AHI thermal infrared band is best for detecting/identifying low clouds?What AHI thermal infrared band is best for detecting/identifying high clouds?What AHI visible reflectance band is best for detecting/identifying land surface features?What AHI thermal infrared band is best for detecting/identifying land surface features?What AHI band or bands are best for detecting/identifying mid atmosphere features?22Satellite Meteorology Madison Wisconsin 2016Slide23
What does this scene represent?
Day or Night?Water or Land?Cloudy or Clear?If cloudy: Thick clouds or Thin?This forces the student to understand how each Band might be used.23(This is thin cirrus over land)Visible/Near IR Bands
Infrared BandsSatellite Meteorology Madison Wisconsin 2016Slide24
What’s the chief difference between these two probes?
24Satellite Meteorology Madison Wisconsin 2016Slide25
SIFT Training always referred back to Spectral Response FunctionsWhy are the channels placed where they are?
What can you expect the bands to view given the Spectral Response Functions?Handouts provided to facilitate learning25Satellite Meteorology Madison Wisconsin 2016Slide26
AHI
Band
AHI
Approximate Central
Wavelength (
μm
)
ABI
Approximate Central
Wavelength (
μm
)
ABI
Band
Type
Nickname
1
0.47
0.47
1
Visible
Blue
2
0.51
Visible
Green
3
0.64
0.64
2
Visible
Red
4
0.86
0.86
3
Near-Infrared
Veggie
1.4
4
Near-Infrared
Cirrus
5
1.6
1.6
5
Near-Infrared
Snow/Ice
6
2.3
2.2
6
Near-Infrared
Cloud Particle Size
7
3.9
3.9
7
Infrared
Shortwave Window
8
6.2
6.2
8
Infrared
Upper-level Water Vapor
9
6.9
6.9
9
Infrared
Mid-level Water Vapor
10
7.3
7.3
10
Infrared
Lower-level Water Vapor
11
8.6
8.4
11
Infrared
Cloud-Top
Phase
12
9.6
9.6
12
Infrared
Ozone
13
10.4
10.3
13
Infrared
“Clean”
Longwave
W
indow
14
11.2
11.2
14
Infrared
Longwave
Window
15
12.4
12.3
15
Infrared
“Dirty”
Longwave
Window
16
13.3
13.3
16
Infrared
CO
2
Longwave
Advanced Baseline Imager Spectral Bands
Handout
26
Satellite Meteorology Madison Wisconsin 2016Slide27
AHI
Handout27Satellite Meteorology Madison Wisconsin 2016Slide28
ABI
Handout28Satellite Meteorology Madison Wisconsin 2016Slide29
US Standard Atmosphere (1976) Brightness Temperature Difference
as a result of water vapor (H2O) absorption29Why isn’t the window channel here?Credit: Mat Gunshor
, Cong Zhou, Tim Schmit, Allen Huang
Satellite Meteorology Madison Wisconsin 2016Slide30
US Standard Atmosphere (1976) Brightness Temperature Difference
as a result of ozone (O3) absorption30Credit: Mat Gunshor, Cong Zhou, Tim Schmit, Allen HuangSatellite Meteorology Madison Wisconsin 2016Slide31
Once more: What does this scene represent?
Day or Night?Water or Land?Cloudy or Clear?If cloudy: Thick clouds or Thin?This is a trick question31Infrared BandsVisible/Near IR BandsSatellite Meteorology Madison Wisconsin 2016Slide32
Questions?
32Satellite Meteorology Madison Wisconsin 2016