1. Figure 3; The MMS data fit yields an exponent of 0.92_−0.29^+0.39, which is statistically consistent with both 1.0 (linear) and 0.63 (nonlinear). Given this large uncertainty, how can the authors confidently claim support for the linear scaling over, say, a quadratic scaling? The simulation’s tighter constraint (0.94±0.15) still allows for deviations from unity.
2. Simulation mean magnetic field: The simulation uses B0=0 and a turbulent dynamo to generate δb, resulting in β∼1/8. However, the weakly compressible MHD theory (Bhattacharjee et al. 1998) assumes an inhomogeneous background magnetic field. Is a zero-mean-field dynamo-generated field a valid proxy for an inhomogeneous mean field? The absence of a guide field fundamentally alters wave modes (Alfvén vs. magnetosonic) and compressible behavior.
3. Scale-dependent analysis interpretation: The authors claim that bb changes from 1/3 at large scales to 1 at small scales, suggesting driving parameter “contamination” by the cascade. However, their method integrates power spectra from kk to kuku to compute cumulative scale-dependent rms values. This inherently mixes contributions from all larger scales. Does this integration artificially force a convergence toward a linear relation at small scales, rather than reflecting true local physics?
4. Taylor hypothesis in magnetosheath: The MMS data rely on Taylor’s frozen-in hypothesis to interpret temporal fluctuations as spatial scales. In the magnetosheath, flow speeds can be comparable to or lower than wave speeds (e.g., slow/fast magnetosonic speeds). Have the authors checked the validity of Taylor’s hypothesis for their high-ββ, compressible intervals? Violations would directly impact the computed Mt and δρ/ρ0.
