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Fronts are significant meteorological phenomena of interest. The extraction of frontal systems from observations and model data can greatly benefit many kinds of research and applications in atmospheric sciences. Due to the huge amount of observational and model data available nowadays, automated extraction of front systems is necessary. This paper presents(More)
An initialization method using airborne Doppler wind lidar data was developed and evaluated for a mass-consistent diagnostic wind model over complex terrain. The wind profiles were retrieved from the airborne lidar using a conical scanning scheme and a signal processing algorithm specifically designed for the airborne lidar system. An objective data(More)
An end-to-end point design, including lidar, orbit, scanning, atmospheric, and data processing parameters, for space-based global profiling of atmospheric wind will be presented. The point design attempts to match the recent NASA/NOAA draft science requirements for wind measurement.
data mining using independent component analysis. [3] Mahashweta Das and Srinivasan Parthasarathy. Anomaly detection and spatio-temporal analysis of global climate system. Branstetter. Geographic analysis & visualization of climate extremes for the quadrennial defense review. complex dependence structures in data mining: A case study with anomaly detection(More)
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