Geometric Modeling for Predicting Severe Weather

I have been doing a great deal of reading and discussing with others about severe weather predictions this summer. It is something I have been interested in for some time and an area that needs some major improvements since the hit rate for predictions is around 25%. As you have noticed by my previous blog posts, I have entered a new phase of my career where in addition to my research as a research psychologist and regulatory scientist, I have added my life long interest in amateur meteorology.

Generally when we talk about severe weather, super-cells are generally part of the conversation. These are those anvil looking menacing clouds that sometimes produce tornadoes. When I look at an anvil, super-cell cloud formation I see an inverted trapezoid where the top portion of the cloud is much longer than the bottom portion of the cloud that is closest to the ground. The other very significant dimension of a supper-cell cloud formation is its vertical height. I have always enjoyed building models, so I take various physical or psychological phenomena and attempt to build a model to explain very complex relationships.

When I see other cloud formations, don’t get me wrong I see these beautiful cloud formations, but I also see very rectangular shapes that are more horizontal than vertical. Generally these clouds don’t produce severe weather, it might be a windy day but you don’t need to worry about your house being ripped off its foundation. You might get some rain from these clouds but nothing that will cause major flooding.

So you may be asking, So What?! Let me try to continue to build this geometric model and add just a small bit of mathematical formulas. I am wondering if the vertical height (V) of the super-cell and the top horizontal portion of the cloud (H2) might provide some clues in predicting severe weather. Is there a potential threshold in which the vertical height and the top horizontal portion of the cloud are so much larger than the bottom horizontal portion of the super-cell cloud (H1) that would help us in predicting the potential for severe weather?

V + H2 > H1 by a factor of 2xs, and the greater the difference, the more severe is the weather.

Also, what does Doppler Radar see when the cloud formation begins to transition into this inverted trapezoid and eventually to more of an inverted triangle which eventually becomes a tornado. Are there threshold values that correspond with this gradual transition which could be observed from a safe distance by storm chasers who send that information to the NWS Doppler Radar site.

Another potential metric that can be used rather than the factor approach above is to actually estimate the area of the cloud trapezoid (CT) in the following manner:

CT = V (H1 + H2) / 2

This formula would provide the area which then could be determined to see if there are specific cut points or thresholds where severe weather is more likely to form. Could it provide a cheat sheet or a macro-view model which along with the sophisticated micro-level models developed using Doppler Radar would help to improve our severe weather forecasting?!

About Dr Fiene

Dr. Rick Fiene has spent his professional career in improving the quality of child care in various states, nationally, and internationally. He has done extensive research and publishing on the key components in improving child care quality through an early childhood program quality indicator model of training, technical assistance, quality rating & improvement systems, professional development, mentoring, licensing, risk assessment, differential program monitoring, and accreditation. Dr. Fiene is a retired professor of human development & psychology (Penn State University) where he was department head and director of the Capital Area Early Childhood Research and Training Institute.
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