Hi everyone!
First blog post for the Satellite Convective Applications Experiment – Week 1, let’s go!
The loop below shows an example of this from the Corpus Christi, Texas. Notice the convection moving out of the frame to the northeast is bounded by prob-lightning contours (Gif 1). My desire would be to have these better matched to the storms. Right now, the contours are too nebulous.
GIF one: MRMS reflectivity at -10 C overlaid with lightning cast 60-min probability.
Why do I care about it’s nebulousness? When I am providing decision support to an event, I want to know which cell is driving the highest probability, which is building and be able to anticipate the lightning threat based on the cells movement.
As my partner in the testbed pointed out, the anvil(s) (see image one below) were merging and this was likely causing the nebulousness.
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Image one: GOES East Day Cloud Phase RBG channel.
Our discussion began to expand to others in the testbed and an idea emerged to try and reduce the nebulousness. The idea was to use the GREMLIN Radar Emulation product to further train the lightning cast dataset so that the probabilities become anchored by the emulated MRMS product.
Below is a GIF of the GREMLIN and MRMS product. With the GREMLIN product using some of the same satellite features as the lightning cast; the two products have some base level of compatibility. And so my challenge to the developers of these products is, an these two be combined such that lightning cast is mapped to the convective feature causing the probability.
GIF Two: GREMLIN Emulated Radar on the left, and MRMS composite reflectivity on the right.
-Kilometers