mplnor > Normalized Backscatter Profiles from the Micropulse LidarVAP Type(s) > Baseline

This VAP has two primary purposes: to apply the appropriate corrections to create normalized backscatter profiles from the MPL, and to detect all significant cloud boundaries from this normalized data set. The corrections in the normalization process include background subtraction, a correction for the afterpulsing (ringing) of the detector, a correction for the disparity between the laser’s and the detector’s field of view (overlap), and an adjustment to the pulse energy of the laser. The steps in the correction are outlined by Campbell et al. (1998). Part of the complexity of this VAP is the determination of these corrections (particularly the overlap and afterpulse corrections). These corrections are unique for each instrument/detector, and can change over time. This can lead to periods of reprocessing as it is discovered via analysis that one or more of these corrections is inadequate.

After the backscatter data has been normalized, a cloud boundary height algorithm is applied to it. This algorithm computes bi-directional vertical differences of adjacent bins in both the profile being analyzed and a clear-sky baseline profile. Significant differences between the profile and the baseline are then further analyzed for possible cloud boundaries, and a cloud mask is created. More information on this technique is given by Campbell et al. (1998). This algorithm is very sensitive, especially with the high-resolution MPL data sets, and thus there are some occasional false positives and false negatives. To reduce such occurrences, the initial “sensitive” cloud mask is filtered with a 7-minute, 210-meter window to create a more “robust” cloud mask.


  • Fixed
  • AMF1
  • AMF2
  • AMF3


mpl: Micropulse Lidar