In November 2007, the dynamic, near realtime global cloud layer for the “Weather” layer of Google Earth™ was implemented. Built from a composite of 11-um data from merged geostationary (GEO) and low Earth orbiting (LEO) satellite imagers combined with a surface temperature analysis, the layer depicts clear and mid-to-high level cloudy areas in a visually intuitive fashion. For the cloudy areas, the brightness and transparency are approximated based upon the cloud top temperature relative to the local radiometric surface temperatures (corrected for surface emissivity variations) at the time of the satellite observation. However, due their proximity to the Earth's surface, low level clouds such as stratocumulus and stratus clouds are poorly represented, since warmer brightness temperatures do not necessarily correspond to increased cloud transparency.

In this presentation, we describe an improved technique which combines additional imaging channels in the visible (0.65 um) and near-infrared (3.9-um) to improve the depiction of low clouds during day and night. During daytime, the 0.65-um channel is compared against a lookup table of background reflectance values as a proxy for cloud transparency, whereas during night hours the 3.9-11-um difference is used to assign cloud transparency as the 11-um brightness temperature approaches that of the underlying surface. In practice, the use of these additional channels must be adjusted for each particular satellite imaging sensor, owing to inter-satellite differences in calibration, center wavelength, and sensitivity to stray light near the Earth disk edges. The multi-channel cloud layer technique reduces to the single channel technique when the additional channels are unavailable (e.g, in the case of the Meteosat-7 imager over the Indian Ocean region). Improvements to the depiction of low level cloudiness are readily noted with the improved, multi-channel cloud layer compared to its single-channel companion.