A quibble with wind direction and humidity. Really, what's needed is to address the kinematic/thermodynamic parameters more generally that might support (a) maintenance of the existing convection and (b) the propagation of new convective cells.
The steering currents really don't change much over 2 hours for an organized system. You can get some rotational motion with a large cyclone but modern OF methods do just fine with that, and you can always remove the divergent component of the flow field. An example of (b) can be found in any Spring season convective outbreak in the Central US; once a squall line congeals along a front you'll see pioneer convection propagate along a vector somewhat orthogonal to the squall line's motion (there are heuristics for the propagation vector that work OK for curved hodographs except in inhomogeneous environments, e.g. Fig 8.10 from Markowski and Richardson). It's the 3D wind shear that matters here, augmented with the lapse rate / profile for (a).
It's hard to bullish on the AI applications here until we see them start to account for these larger input parameter spaces. But of course, where is this data going to come from? Mesoscale or convection-permitting models. And if you already have the capability to run these models in a cost-efficient manner, do you need the AI system in the first place?
The steering currents really don't change much over 2 hours for an organized system. You can get some rotational motion with a large cyclone but modern OF methods do just fine with that, and you can always remove the divergent component of the flow field. An example of (b) can be found in any Spring season convective outbreak in the Central US; once a squall line congeals along a front you'll see pioneer convection propagate along a vector somewhat orthogonal to the squall line's motion (there are heuristics for the propagation vector that work OK for curved hodographs except in inhomogeneous environments, e.g. Fig 8.10 from Markowski and Richardson). It's the 3D wind shear that matters here, augmented with the lapse rate / profile for (a).
It's hard to bullish on the AI applications here until we see them start to account for these larger input parameter spaces. But of course, where is this data going to come from? Mesoscale or convection-permitting models. And if you already have the capability to run these models in a cost-efficient manner, do you need the AI system in the first place?