摘要: Visible and infrared satellite imagery data are a primary source of global cloud observations. Visible channels measure reflected solar energy and are used to detect clouds and snow. Infrared channels measure emitted thermal energ... 展开 Visible and infrared satellite imagery data are a primary source of global cloud observations. Visible channels measure reflected solar energy and are used to detect clouds and snow. Infrared channels measure emitted thermal energy, and, consequently, the brightness temperatures of clouds and the earth's surface both day and night. It is sometimes difficult to interpret such imagery because of varying conditions encountered on global scales. Snow cover is often confused with clouds in visible imagery because each surface reflects sunlight well. Low clouds are frequently confused with cloudfree land and oceans in infrared imagery because their temperatures can be nearly equal. It is found that more confident discriminations can be performed between such features when DMSP Operational Linescan System (OLS), NOAA Advanced Very High Resolution Radiometer (AVHHR), or Nimbus Scanning Multifrequency Microwave Radiometer (SMMR) data are combined into color image products. A multispectral image display technique is described that simultaneously combines several meteorological satellite images into a color image product. The technique, which has its origin in Landsat Multispectral Scanner image processing, is quick & effective, & clearly reveals many features of meteorological interest. Reprints. (FR) 收起