One likely cause of vertical motion of this magnitude is the slowing down of convective bubbles as they encounter decelerating forces. This condition occurs frequently at cloud tops, and is a good explanation of why significant icing is often observed there. An artificial intelligence tool that does very well at pattern recognition is a neural network. A neural network is a simple version of a mammalian brain. A neural network is pure rote learning, like a gradeschooler learning multiplication tables.
Neural networks work well in complex pattern recognition because they are very non-linear.
The maps of icing intensity are composites of the output of two neural networks taught to predict icing intensity from input data of temperature, relative humidity, and convective potential from the Rapid Update Cycle model. Actual output to the Aviation Weather Center forecasters is in layers approximately 1000 ft thick. The output values range from zero to six with zero representing no icing and six severe icing. A two is light icing and a four is moderate icing. The contours begin at the two level.