1. GOES Geosynchronus Satellites
Going for Knowledge:
GOES Geosynchronus Satellites
Mr. Timothy J. Schmit
NOAA/NESDIS (National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service)
SaTellite Applications and Research (STAR)
Advanced Satellite Products Team (ASPT)
in collaboration with the
Cooperative Institute for Meteorological Satellite Studies (CIMSS)
Madison, WI
11 March 2003
UW-Madison

2. Wisconsin has a long history with the development and continued improvements of the geostationary satellites.
These space-based satellites are the backbone for observing atmospheric changes on fine time and space scales.
What is a GOES satellite and what does it do?
Sample images and products of clouds, fog, severe weather storms, snow, etc.
Future geostationary capabilities.

3. Global image -- combination of satellite and ground-based observations.

4. This is an overview diagram of CIMSS activities and how they work together to support CIMSS overall activity.

5. Geostationary Satellites
Polar Orbiting Satellites
Geostationary Satellites

7. Geostationary
Operational
Environmental
Satellite

8. Geostationary Satellites
Warnings to U.S. Public -- Detect,
track and characterize
Hurricanes
Severe or possibly tornadic storms
Flash flood producing weather systems
Imagery/soundings for weather forecasting
Information for aviation and numerical models
Environmental data collection – Platforms including buoys, rain gauges…
First operational Solar X-Ray Imager

9. “the clouds moved - not the satellite”
ATS-3 (color)
“the clouds moved -
not the satellite”
Verner Suomi
Click to add notes
From 6 Dec 1966, ATS-1's geostationary spin scan cloud camera provided full disk visible images of the earth and its cloud cover every 20 minutes

10. Verner E. Suomi and Robert J. Parent

11. Geostationary Weather Satellite
The satellite:
The rocket:
September 27, 1995

12. GOES-8/12

13. GOES-N Satellite Imager Sounder Human GOES-N (S/N08)
S-/L- Band Antennas
Star Trackers
Imager
UHF Antenna
Sounder
Human
GOES-N (S/N08)

14. Electromagnetic Spectrum IR

15. GOES Sounder Spectral Bands: 14.7 to 3.7 um & Vis
Eighteen infrared sounding bands (channels) ranging from 14.7 (top left) to 3.9 (bottom middle) microns were selected for the GOES sounder; the channels were patterned after those realized for the polar orbiting High resolution Infrared Radiometer Sounder (HIRS). These multispectral observations yield information about the vertical structure of atmospheric temperature and moisture. The concept of profile retrieval is based on the fact that atmospheric absorption and transmittance are highly dependent on the frequency of the radiation and the amount of the absorbing gas. At frequencies close to the centers of absorbing bands, a small amount of gas results in considerable attenuation in the transmission of the radiation; therefore most of the outgoing radiation arises from the upper levels of the atmosphere. At frequencies far from the centers of the band, a relatively large amount of the absorbing gas is required to attenuate transmission; therefore the outgoing radiation arises from the lower levels of the atmosphere. This is evident moving from 14.7 (ch1, op left) to 11 (ch8, 2nd row middle) microns; features in the lower atmosphere emerge as wavelength moves from the center of the CO2 absorption band. The H2O sensitive bands (ch8 - 12) exhibit similar behavior. The shortwave CO2 sensitive bands (ch ) also detect reflected solar radiation (more at shorter wavelengths)

16. Data Assimilation -- GOES radiances and products have a major role
GOES in NWP, routine and experimental:
Model GOES Data
NCEP Global Sounder Radiance, Imager Winds, Imager Radiances
Eta Model Sounder Radiance, Sounder PW, Imager Winds,
Data for LandDataAssimilationScheme, Sounder Clouds
FSL’s RUC Sounder TPW, Sounder Clouds, rapid-scan winds
CIMSS CRAS Sounder PW, Sounder Clouds
Australia (LAPS) Imager Winds
ECMWF Imager Winds, Imager Radiances
GFDL (experimental) Imager Winds
NOGAPS Imager Winds, Sounder Winds
NAAPS Imager Biomass Fire Product
CSU RAMS Imager Biomass Fire Product
UW ALEXI Change of Sounder Skin Temperature, Imager insolation
(University of Sao Paulo/NASA-Ames) is doing the work with the CSU RAMS model.
The MM-5 has been run experimentally for Hurrican Felix with Sounder radiances.
Data Assimilation -- GOES radiances and products have a major role

17. Effect of GOES (sounder cloud) data on 3-h RUC cloud forecasts
3h 20km RUC cloud-top fcst
w/ GOES cloud assimilation
Verification
Cloud-top pressure
based on NESDIS product
Effect of GOES (sounder cloud)
data on 3-h RUC cloud forecasts
“much improved cloud forecasts”
1800 UTC
Tues 2 Oct 2001
These figures show the improve of short-term forecasts (in the Rapid Update Cycle model) when the GOES sounder cloud-top information product is assimilated.
The circles show 2 areas of improved cloud forecasts.
From Stan Benjamin:
Update to previous Notice of Intent to Change
- 20-km RUC
- Scheduled for implementation 16 April 2002
pending CAFTI approval
Stan Benjamin – NOAA/FSL
3h 40km RUC cloud-top fcst
No GOES cloud assimilation

18. Satellite winds on GFDL Forecasts
Hurricane examples.
Soden, Brian J., Christopher S. Velden, Robert E. Tuleya, 2001: The Impact of Satellite Winds on Experimental GFDL Hurricane Model Forecasts. Monthly Weather Review: Vol. 129, No. 4, pp. 835–852.
GFDL is Geophysical Fluid Dynamics Laboratory
GOES-8 1km visible
Soden et al.
Former National Hurricane Center director Robert Sheets once said that if he had only one tool to do his forecasting job, it would be the geostationary weather satellite.

19. Snow: 21 December 2000 | Blowing Snow Across Iowa
“Sundogs” (refraction off ice crystals)

20. GOES Split-window Difference
Dust Detection
GOES Visible
GOES Split-window Difference
(10.7 µm - 12 µm)

21. GOES WFABBA Monitors Rapid Intensification of Wildfires
20 June :15 UTC
18:15 UTC
21:15 UTC
Rodeo
Chediski
Smoke
Arizona
QUEBEC
ONTARIO
6 July :45 UTC
17:45 UTC
Quebec
One of the primary advantages of using geostationary data for fire monitoring is the ability to detect and monitor rapidly growing fires. Two examples are shown in this slide.
On 20 June 2002, the GOES Wildfire ABBA monitored the Chedeski and Rodeo fires in Arizona. The rapid intensification of the Rodeo/Chediski complex was one of the most extreme examples ever documented with the GOES WF_ABBA.
On 6 July 2002, the GOES Wildfire ABBA monitored the rapid growth and intensification of numerous fires in Quebec. UW-Madison CIMSS is collaborating with M. Moreau (Environment Canada/Meteorological Services/Quebec Region) to evaluate the capability of the WF_ABBA for detecting and monitoring wildfires in remote regions at northerly latitudes in the province of Quebec, Canada. During the recent outbreak of wildfires in Quebec, M. Moreau indicated that the GOES WF_ABBA served as an excellent tool for monitoring fires in real-time especially in the restricted protection zone in Northern Quebec where conventional fire monitoring is limited. He indicated that the latest version of WF_ABBA has significantly fewer false alarms with good agreement with ground truth verification.

22. The Advance Baseline Imager:
ABI Current
Spatial resolution
0.64 mm Visible 0.5 km Approx. 1 km
Other Visible 1.0 km n/a
IR bands 2 km Approx. 4 km
Spatial coverage
Full disk 4 per hour Every 3 hours
CONUS per hour 4 per hour
Operation during eclipse
Yes No
Spectral Coverage
15/16 bands 5 bands

23. Visible and near-IR channels on the ABI
Cirrus
Snow
Haze
Clouds
Veg.
Part. size

24. IR channels on the current GOES and on the ABI
This is from Mat G.

25. ABI Bands Current GOES Imagers MSG or Sounder MODIS or MTG, etc
Band pass are approximate
Current GOES Imagers
MSG or Sounder
MODIS or MTG, etc

26. ABI (3.9 m) Based on GOES Imager Ch 2 useful for fog, snow, cloud, and fire detection
5 March Nocturnal Fog/Stratus Over the Northern Plains
GOES minus 11 μm Difference
ABI 4 minus 11 μm Difference
Both images are shown in
the GOES projection.
Fog
UW/CIMSS
ABI image (from MODIS) shows greater detail in structure of fog.

27. Water/Ice Clouds and Snow/Lake Ice
ABI Simulations (from MODIS data)
3-color composite (Visible/1.6 μm/ μm)
12 February 2001; 1627 UTC
Vis/1.6um/8.5-11um
Water cloud
Ice cloud
Lake Ice
Snow
Super-Cooled cloud
UW/CIMSS
UW/CIMSS

28. Haze Detection MODIS (True Color) GOES
GOES was 18UTC image
MODIS was from 14-Aug-02 (~15Z) and via the SSEC direct broadcast.
Look at the region off the coast of the upper-Atlantic states. Note that the GOES visible sensor was designed so as to minimize its ability to sense haze. (Of course 18Z is the worse time (due to view angles) for GOES to observe this.)
GOES image has not been enhanced.

29. Severe convection: IR windows 25 February 2001
MODIS (1 km)
ABI (2 km)
Severe convection:
IR windows
25 February 2001
GOES-8 (4 km)
The simulated ABI clearly captures the over-shooting (cold) cloud tops, while the current GOES Imager does not.
Images shown in GOES projection.

30. MODIS Detects Burn Scars in Louisiana
01 September Pre-burning
17 September Post-burning
Burn Scars
Scars (dark regions) caused by biomass burning in early September are
evident in MODIS 250 m NIR channel 2 (0.85 μm) imagery on the 17th.
MODIS Data from GSFC DAAC
ABI will allow for diurnal characterizations of burn areas, this has implications for re-growth patterns.
CIMSS, UW

31. Solar X-Ray Imager on GOES-12

32. Current GOES Imagers -- a wide variety of Applications
Oceanographic
Weather
Numerical
Weather
Prediction
Natural Hazards
Hydrology/
Land Surface UW
Climate