Online tools, such as those pioneered by Google Earth (GE), are changing the way in which scientists and the general public interact with three-dimensional geospatial data in a virtual environment. However, while GE provides a number of features to facilitate geospatial data visualization, there is currently no readily available method for rendering vertical geospatial data derived from Earth-viewing remote sensing satellites as an orbit curtain seen from above. Here, a solution (one of many possible) is demonstrated to render vertical profiles of atmospheric data from the A-Train satellite formation in GE, using as a proof-of-concept data from one of the instruments-the NASA CloudSat satellite. CloudSat carries a nadir-viewing Cloud Profiling Radar that produces data revealing the vertical distribution of cloud characteristics along the satellite track. These data are first rendered into a long vertical image for a user-selected spatial range through the NASA Goddard Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) system (http://giovanni.gsfc.nasa.gov/). The vertical image is then chopped into small slices representing 15s of satellite time (~103km long ground distance). Each small piece, as a texture, is fed into a generalized COLLAborative Design Activity (COLLADA) three-dimensional (3-D) model. Using the satellite orbit coordinates, the repeated 15s ''3-D model slices'' are spliced together to form a vertical ''curtain'' image in Keyhole Markup Language (KML) format. Each model slice is geolocated along the CloudSat orbit path based on its size, scale and angle with the longitude line that are precisely calculated on the fly. The resulting vertical cloud data can be viewed in GE, either transparently or opaquely, superimposed above the Earth's surface with an exaggerated vertical scale. Since CloudSat is just a part of the A-Train formation, the full utility of this tool can be explored within the context of the A-Train Data Depot (ATDD, http://disc.gsfc.nasa.gov/atdd/) and the corresponding Giovanni instance (http://disc1.sci.gsfc.nasa.gov/daac-bin/G3/gui.cgi?instance_id=atrain). The latter portal allows scientists and the general public to access and visualize complex A-Train datasets without having to delve into data formats specific to a given mission.
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