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tokens: gas density was measured from either the neutral or ionized hydrogen and includes a correction factor of 1.36 in order to account for the contribution from helium. Since we are interested in a comparison with our 1D cosmic ray transport models, we neglect the error contribution from the variance of the density; thus, the error is solely determined by uncertainty of the velocity dispersion and is δ U kin = 2δσ v /σ v , equivalent to 50 per cent. We find that the kinetic energy densities are within a factor of a few in energy equipartition with the magnetic field. This is the expected result since the magnetic field in dwarf galaxies is usually assumed to be amplified by the turbulent gas motions via the ‘fluctuating dynamo’, which saturates when the energy densities become comparable (Schleicher Beck 2013 ). Interestingly in the central part, the magnetic energy density shows a peak that corresponds best to kinetic energy density of the ionized gas, whereas that of the atomic gas is practically constant. The cosmic ray energy density is important everywhere. Such a behaviour has been suggested by theoretical works of cosmic ray-driven galactic winds (e.g. Salem Bryan 2014 ), where the cosmic rays can diffuse outwards from star formation sites and thus create an overpressure in the surrounding area. A galactic wind can then be launched in the disc–halo interface, where the cosmic rays dominate the energy density and are able to transfer some of their energy and momentum to the ionized gas via the streaming instability. Figure 5. Minor axis profiles with distances from the major axis as seen on the sky. Shown are the energy densities of the magnetic field, warm neutral medium (H i ), warm ionized medium (Hα), and cosmic rays (CRs). The blue line shows the magnetic energy density for the accelerating wind model. The blue-shaded area indicates the range of magnetic field strengths for which we tested our models, where the upper limit is for energy equipartition and the lower limit is for almost freely escaping CREs (only radiation losses). Error bars show ±1σ uncertainties, which are assumed to be 50 per cent stemming solely from the uncertainty of the velocity dispersion (see text for details). While the diffusion model (Model I) fits our data best, the resulting diffusion coefficients are at least one order of magnitude lower than both estimates for the expected diffusion coefficient. On the other hand, the projected extent of CRE injection sources due to the mild inclination can account for the parabolic shape of the spectral index profile, where the spectral index remains flat out to distances of up to 0.5 kpc away from the major axis; so the abrupt steepening of the spectral index at | z | > 0.5 kpc that distinguishes diffusion from advection may be the result of geometry. Hence, we explored the possibility of dominating advection and found that constant wind speeds are only a factor of 2 below the escape velocity – the expected advection