Because the y are independent from the funnel parameters tau and phi this is almost surely due to adaptation which in some sense couples the parameters even if they’re probabilistically independent.
The standard normal target for the y motivates a much higher step size than the funnel parameters, and overall this leads to a more aggressive adaptation. The more aggressive adaptation then leads to larger step sizes which limit how deeply the numerical Hamiltonian trajectories can venture into the funnel before diverging. The unstable trajectories explain the divergences while the limited exploration explains why the E-FMI warning doesn’t show up. Increasing adapt_delta leads to a less aggressive adaptation and smaller step size which allows for more refined exploration that will see enough of the funnel to resolve the E-FMI problem.
I mentioned above all of these empirical diagnostics are only as good as our initial exploration (diagnostics that are not transparent about this limitation can be particularly dangerous).