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GOES

GOES is an acronym for Geostationary Operational Environmental Satellite. The GOES satellites are geosynchronous, their orbits keep them synchronized with Earthês rotation, i.e., they take 24 hours to complete one orbit. The GOES satellites are also geostationary; they remain motionless above a single point on the Earth's surface. This requires that they orbit above the equator, with zero inclination. Geostationary satellites and the Earth rotate in a synchronized fashion relative to the Sun, so that part of each day, the satellite's sensors face the night side. To view the Earth in daylight continuously requires at least three (preferably four) geostationary satellites located equidistantly around the globe above the equator.

Six operational geostationary meteorological satellites are maintained around the globe near five specific positions. They provide a global coverage of the non-polar regions of the Earth. GOES-W (GOES 10) and GOES-E (GOES 8) are United States satellites operated by the National Oceanic and Atmospheric Administration (NOAA). METEOSAT is operated by EUMETSAT, an intergovernmental organisation with 17 European Member States: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey and the UK. METEOSAT images the Earth and its atmosphere every 30 min in three channels: Visible, Infrared and Water Vapour. GMS is operated by NASDA, the space agency of Japan. GMS also images the earth in 30 min intervals in visible, infrared, and water vapor spectral bands. INSAT satellites are geostationary communications and meteorological satellites operated by the the Indian Space Research Organization (ISRO). The last satellite of INSAT-2 series i.e., INSAT-2E, has been operational since May 1999. It is capable of taking 1km resolution images in 3 bands and a water-vapour channel with 8 km resolution. The next satellite of the INSAT series i.e., INSAT-3A, is scheduled for launch sometimes during the 4th quarter of 2001

Fig. 1. The areas viewed by the five geostationary operational meteorological satellites.

Areas viewed by geostationary meteorological satellites. The solid line shows the limb;
a satellite sees nothing outside this area. The dashed line encloses the area of useful data
where the satellite is at least 10ç above the horizon.

GOES-8 and GOES-10

Currently, the United States is operating GOES-8 (or GOES-East) and GOES-10 (or GOES-West). GOES-9, which malfunctioned in 1998, is being stored in orbit as an emergency backup should either GOES-8 or GOES-10 fail. GOES-8 is positioned at 75 W longitude and the equator, while GOES-10 is positioned at 135 W longitude and the equator. GOES-11 was launched on May 3, 2000 and is being stored in orbit as a fully functioning replacement for GOES-8 or GOES-10 on failure. Each satellite views almost a third of the Earth's surface. Coverage extends approximately from 20 W longitude to 165 E longitude. This figure shows the coverage provided by each satellite.

Fig. 2. Fields of view of GOES-10 (West) and GOES-8 (East).

 

Summary of GOES coverage

Each GOES satellite carries two primary instruments: the Imager and the Sounder. The imager is a multichannel instrument that senses radiant energy and reflected solar energy from the Earth's surface and atmosphere. The Sounder provides data to determine the vertical temperature and moisture profile of the atmosphere, surface and cloud top temperatures, and ozone distribution. The satellites scan the continental U.S. every 15 min.; most of the hemisphere, from near the north pole to ~ 20S latitude, every 30 min; and scan the entire hemisphere once every three hours in their "routine" scheduling mode. GOES can also operate in 2 special rapid imaging modes:

RSO = rapid scan operations = 7.5 minute intervals

SRSO = super rapid scan operations = 1 minute or 30 second intervals

The 1- minute SRSO offers 22 images an hour, with 2 segments of 1-minute interval images, allowing for the regularly scheduled 15-minute interval operational scans. Optionally, special imaging schedules are available which allow data collection at more rapid time intervals (~7.5-min and 1-min), over reduced areal sectors.

 

The GOES Imager

The GOES provide frequent images at five different wavelengths, including a visible wavelength channel and four infrared channels.

Channel	Channel Name	Central Wave-length	Resolution km E/W x N/S	Example Meteorological Applications
1	visible	0.65 µm	0.57 x 1.00	Produces high resolution black and white photographs of earth and clouds.
2	shortwave infrared	3.90 µm	2.30 x 4.00	At night, can be used to track low-level cloud fields and thus infer near-surface wind circulation.
3	water vapor channel	6.70 µm	2.30 x 8.00	1. Detects mid- and upper-level water vapor and clouds. 2. Locates and defines synoptic features such as shortwave troughs, ridges, jet streams, etc. via mesoscale regions of moistening/drying at the 300-500 mb height. 3. Can derive upper-level wind vectors (wind barbs) with the winds plotted on the image valid at the time of the winds.
4	window channel	10.70 µm	2.30 x 4.00	Cloud top temperatures, nighttime tracking of storm systems.
5	dirty window/ split window IR	12.00 µm	2.30 x 4.00	Sensitive to low level water vapor.

 

Channel 1, Visible (0.65 µm)

The GOES visible (VIS) wavelength channel produces images which can be thought of as black-and-white photographs of the earth and clouds from outer space. During the daylight hours, it is the most widely used channel because it has the highest resolution of the five imaging channels, and because it approximates what we see with the human eye. The primary utility of the VIS channel imagery is in the day-time monitoring of thunderstorms and tropical cyclones.

Fig. 3. GOES Visible image of Hurricane Georges, 19-Sept-1998.
Image courtesy of the Cooperative Institute for Meteorological Satellite Studies, Space Science & Engineering Center, University of Wisconsin, Madison.

 

Channel 2, Shortwave Infrared Channel (3.9 µm)

The 3.9 µm channel is different from the other imaging channels, in that it responds to both emitted terrestrial radiation, and reflected solar radiation. Since the emissivity of water droplets at 3.9 µm is less than that for longer wavelengths, it is often easier to identify fog and stratiform cloudiness in the channel 2 imagery, and to discriminate between water and ice clouds. Many times fog can be identified on channel 2 imagery as cooler regions, though confusion can occur between stratus or fog, and cold ground. Combining this imagery with other channels resolves most of these problems.

Using Channel 2 (3.9 µm) Imagery at Night. Routine examination of 3.9 µm imagery at night offers a good substitution for visible channel imagery. It can be used to track low-level cloud fields and thus infer near-surface wind circulation. This application is particularly useful in the tropics, where freezing levels are relatively high (~5 km) and conventional low-level wind data are sparse. The ability to track low-level clouds at night using Channel 2 imagery can be particularly useful in the location of low-level circulation centers associated with strongly sheared tropical cyclones.

Channel 3, Water Vapor Channel (6.7 µm)

The 6.7 µm channel responds to mid- and upper-level water vapor and clouds. Because organized atmospheric disturbances usually have large regions of upward (or downward) motion and consequent moistening (or drying), the water vapor data can often be used to locate and define synoptic features such as shortwave troughs, ridges, jet streams, etc. Mesoscale regions of moistening/drying at the 300-500 mb height (such as subsidence associated with thunderstorms' anvils) have also recently come under close scrutiny using this channel's imagery.

Fig. 4. Cyclonic shear vortices detected by GOES Channel 3 water vapor channel.
Image courtesy of the Cooperative Institute for Meteorological Satellite Studies, Space Science & Engineering Center, University of Wisconsin, Madison.

Using Channel 3 (water vapor) Imagery to Derive Winds

GOES Channel 3 imagery sequences can be used to derive upper-level wind vectors, with the winds plotted on the image valid at the time of the winds. The wind speeds and directions are derived from the images while the height assignments are done using model forecasts and quality assurance procedures to correct heights which may not fit the analysis.

Fig. 5. Application of Channel 3 water vapor derived winds, Hurricane Floyd on Sept. 15, 1999, 18:00 UTC.
Image provided by David Stettner, Space Science & Engineering Center, University of Wisconsin, Madison.

In this the white areas and areas where cirrus are present (overlayed with the blue wind barbs) are assigned a height of 100-250 mb. Floyd's cirrus clouds can clearly be seen in the outflow pattern of the hurricane. Cirrus bands provide excellent targets to be tracked by the wind vector generating algorithm. The yellow wind barbs represent cloud heights between 251-350 mb. These clouds are "lower" than the clouds which have colder temperatures in the nearby area. The green barbs represent heights of 351-500 mb, which is the lowest height assignment layer for winds derived from water vapor imagery. The areas with green barbs are often the result of significant sinking and warming as can be seen to the west and north of Floydês circulation.

 

Channel 4, the Window Channel (10.7 µm, "longwave IR")

The 10.7 µm channel is a so-called "window channel" meaning that radiation at this wavelength is not absorbed (to any significant degree) by atmospheric gases. When we look at clouds, or the cloud-free ground, with this channel, we are "seeing" the actual temperature (cold cloud tops versus warm cloud tops) of the scene in the field-of-view. Channel 4 imagery has a wide variety of uses, including determination of cloud top heights, identification of cloud top features, tracking synoptic and mesoscale features at night, etc.

Fig. 6. Colorized GOES longwave IR image of Hurricane Georges, 19-Sept-1998.
Image courtesy of the Cooperative Institute for Meteorological Satellite Studies, Space Science & Engineering Center, University of Wisconsin, Madison.