DATASTREME WES SUPPLEMENTAL INFORMATION

DataStreme WES Week Two: 8-12 September 2008

ENVIRONMENTAL SATELLITE IMAGE INTERPRETATION


Sensors onboard environmental satellites continually monitor the Earth system. Their perspective from space is unique; a satellite image or composite of images can provide broad-scale views of the ocean, snow and ice cover, and weather systems. Instruments onboard essentially all environmental satellites sense the intensity of electromagnetic radiation coming from the planet in many wavelength bands (channels) within the electromagnetic spectrum. Some satellites are equipped with sensors that detect electromagnetic signals (e.g., microwaves) that were emitted by devices onboard the satellite and are reflected by Earth's surface back to the satellite.

While polar orbiting satellites are used for certain environmental monitoring purposes, the geostationary (or geosynchronous) satellite is often used for nearly continuous monitoring of the ocean and atmosphere. Geostationary satellites, situated high above the equator at an altitude of 37,000 km (23,000 mi), remain fixed over the same scene on Earth. Sensors onboard a geostationary satellite make "full disk" images of a hemisphere every half hour, or in a rapid scan mode, the sensors concentrate on a selected area for more detail in shorter time intervals. Information collected by these sensors is transmitted as a series of digital signals to a receiving station on Earth, where the information is processed to form a recognizable image. Rapid sequencing of such images can be used for animation of cloud motions. Computer generated map outlines are superimposed on the finished images for orientation purposes. Three types of satellite images are available from the Atmospheric Information section of the DataStreme WES website and the following are some hints that aid in the interpretation of satellite images:

Visible Satellite Imagery

Some satellite sensors operate within the visible range of the electromagnetic spectrum, sensing the sunlight reflected back to the satellite from the Earth-atmosphere system. Like a black and white photograph, the brightest and whitest elements appearing in these visible images indicate the most reflective surfaces, where a greater intensity of sunlight is reflected back into space, such as from clouds or a fresh snow cover. Conversely, the darkest parts of the image indicate the least reflective surfaces, such as the nearly black ocean surface where much of the sunlight penetrates the surface and is not reflected back. Land surfaces tend to appear gray.

Differences in shading of clouds usually relate to cloud thickness. Often a cloud that appears bright on a visible image is a thick cloud (e.g., cumulonimbus) that scatters back most of the solar radiation that strikes the cloud.

One way to identify a visible satellite image is to look for the dark region of space on the edge (limb) of the Earth's disk when observing a full-disk image. [The satellite images that you can access from the Atmospheric Information section of the DataStreme WES website are limited to the sector that focuses upon the continental United States.] A major limitation to visible imagery is that it is essentially limited to the illuminated (daylight) regions of the planet below the satellite.

Some of the interesting features that may appear on visible satellite images include:

Infrared Satellite Imagery

This type of image is produced by infrared satellite sensors that detect long wave radiation emitted by Earth's surface, atmosphere, and clouds. Infrared (IR) represents that portion of the electromagnetic energy spectrum that is emitted by essentially all objects at a rate directly proportional to the fourth power of its temperature. In other words, the warmer the body, the more infrared radiation that surface emits. By looking at an IR image, one can detect the relative temperatures of the ocean, land, and clouds. To examine the relationship between temperature and IR emission, go to Atmospheric Information on the DataStreme WES website and click on Infrared Surface Temperature Application.

Objects with the lowest temperatures appear in IR imagery as the brightest white features, whereas the warmest bodies are the darkest. For example, interplanetary space beyond the limb of the planetary disk appears white on the full disk IR images because of the extremely low temperatures of space; this feature can be used to distinguish IR imagery from visible (where deep space beyond the limb of the disk is black because of the absence of reflected sunlight).

The infrared sensors typically used on satellites respond to IR radiation within one of the narrow IR windows of the atmosphere. Hence, IR radiation emitted from Earth's surface in a cloud-free area passes through the atmosphere and can be detected by the satellite sensor. Surface features can be detected in IR imagery by noting subtle shading contrasts resulting from differences in surface temperatures. One example is the relative temperature difference between large water bodies and adjacent land surfaces. Warm land surfaces tend to be dark. Typically, cloud free ocean regions appear more uniform because of more uniform sea surface temperatures. On the other hand, large differences in surface temperature over continents produce images with dark regions over hot deserts and lighter regions over colder mountainous terrain.

Because the troposphere cools with increasing altitude, cloud tops usually appear on IR imagery as bright areas whereas land surfaces usually are dark. Differences in IR cloud image shading often relate to subtle differences in cloud top temperature. Meteorologists often enhance these images to study the differences in cloud top temperature by assigning various color schemes for television and computer display. Thus, infrared imagery can be used to help distinguish between high, middle, and low clouds. Usually, fog and low clouds will be grayer because they are warm, whereas higher cold clouds will appear bright white. Because fog may be at the same temperature as the surface, fog banks may not be readily distinguishable from land areas in the IR. Towering thunderstorm clouds appear bright and white. A milky white appearance over an otherwise cloud free region may indicate a cold air mass.

A principal advantage of IR is that useful images can be produced regardless of local darkness. The animated loops that are used on television weather shows usually represent a sequence of IR images. However, detail is lost due to lower resolution of IR sensors as compared to visible sensors.

Water Vapor Channel Imagery

The images produced from water vapor channel sensors represent a slight modification of traditional IR images. The wavelength bands used by this vapor channel are at a slightly different wavelength interval than those used by the IR sensors. The IR radiation that is detected by the water vapor channel sensors is in a region of strong emission (and absorption) by invisible water vapor.

The amount of radiation in this channel depends upon the total amount of water vapor in a vertically oriented atmospheric column, especially weighted toward the mid- to upper troposphere between altitudes of 6000 and 9000 m (20,000 and 30,000 ft). Hence, the vapor images depict water vapor concentrations in the mid-troposphere.

Differences in shading of this type of image typically relate to subtle differences in mid-tropospheric moisture, with white regions on the imagery representing more moisture than dark regions. Clouds also show as bright white in water vapor images. Additionally, white regions probably indicate rising air, whereas dark regions indicate sinking air. Light gray streaks typically indicate upper tropospheric jet streams transporting large amounts of moisture.

Later in DataStreme WES, we will examine active satellite sensors, that is, sensors that send radiation signals and receive these reflected signals. Such sensors, for example, are used to monitor sea level and snow packs.


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Prepared by WES Central Staff and Edward J. Hopkins, Ph.D., email hopkins@meteor.wisc.edu
© Copyright, 2008, The American Meteorological Society.