The Cloud Profiling Radar (CPR) is a 94-GHz nadir-looking radar which
measures the power backscattered by clouds as a function of distance
from the radar. The CPR was developed jointly by NASA/JPL and the
Canadian Space Agency (CSA). The overall design of the CPR is simple,
well understood, and has strong heritage from many cloud radars already
in operation in ground-based and airborne applications.
The design of the CPR is driven by the science objectives. The
original requirements on CPR were:
- sensitivity defined by a minimum
detectable reflectivity factor of -30 dBZ,
- along-track sampling of 2 km,
- a dynamic range of 70 dB,
- 500 m vertical resolution and
- calibration
accuracy of 1.5 dB.
- The minimum detectable reflectivity factor
requirement was reduced to -26 dBZ when the mission was changed to put
CloudSat into a higher orbit for formation flying.
In the CloudSat data, the darkest blues represent areas where clouds
and raindrops reflected the strongest signal back to the satellite radar. These areas had the heaviest precipitation and the largest water droplets. The blue horizontal line across the data is the freezing line; ice particles formed above it, raindrops below it. CloudSat passed just west of the eye, offering a good view of the storm’s outward sloping
eyewall, intense convection and rainfall, and cloud structure. Atsani’s clouds reached about 16 kilometers (10 miles) altitude at their highest point. When CloudSat imaged the storm, Atsani’s maximum sustained winds were about 150 miles (240 kilometers) per hour.
While the satellite has collected over 10 million radar profiles since launching in 2006, it is relatively unusual to capture data of a major storm’s eye. Over its lifespan, the satellite has imaged about 1,200 hurricane or typhoon strength tropical cyclones, according to a
study published recently in the
Bulletin of the American Meteorological Society. Among them, CloudSat has acquired about 30 direct eye overpasses. Scientists are compiling all of the storm overpasses into a
database that they are using to better understand the anatomy and behavior of tropical cyclones.
