| 12 Feb 2026
Parameterization and Evaluation of Nonhydrostatic Effect in the Orographic Gravity Wave Drag in China Meteorological Administration Global Forecast System (CMA-GFS) v4.0 Model
Abstract. The China Meteorological Administration Global Forecast System (CMA-GFS) v4.0 model was upgraded to a higher resolution of 0.125° in May 2023. To be compatible with its fine resolution, the parameterization scheme of orographic gravity wave drag (OGWD) in CAM-GFS is revised herein by accounting for the nonhydrostatic effect (NHE) on the wave momentum flux of subgrid-scale orographic gravity waves. The performance of the revised OGWD scheme is then evaluated for the 10-day medium-range forecast in December 2023. Results show that the revised OGWD scheme can better capture the large-scale circulation in the Northern Hemisphere (NH), particularly in the high latitudes. The easterly (westerly) wind biases in the NH polar stratosphere (troposphere) are decreased. The underestimation of East Asia subtropical jet is also alleviated. Quantitative evaluation shows that the revised OGWD scheme reduces both the mean bias and root mean square error of 500-hPa geopotential height in the NH after the 6th forecast day, reaching 11.59 % and 5.06 %, respectively, by day 10. The decrease of easterly biases in the polar stratosphere is owing to the weakening of stratospheric zonal OGWD by the NHE. It is also contributed by the secondary circulation induced by the weakened OGWD, which increases the thermal contrast between middle and high latitudes by adiabatic warming/cooling. For the decrease of westerly biases in the NH polar troposphere, it is due to the fact that the enhanced stratospheric winds suppress the upward propagation of Rossby waves into the stratosphere, resulting in greater convergence of Eliassen-Palm flux in the mid-upper troposphere.
Review of Parameterization and Evaluation of Nonhydrostatic Effect in the Orographic Gravity Wave Drag in China Meteorological Administration Global Forecast System (CMA-GFS) v4.0 Model by Zhang et al
The manuscript under consideration describes the implementation of the non-hydrostatic correction of the parameterized orographic gravity wave drag (OGWD) in the China Meteorological Administration Global Forecast System (CMA-GFS) v4.0 model. The results show that this implementation has an overall positive impact on the accuracy of the model forecast, however tiny the effect is, and the authors further analyze the dynamical mechanisms behind the imporvements. The paper is very well written and the justification for the non-hydrostatic correction is very well motivated based on the theory and previous work. That said, I have some major comments regarding the sections discussing the dynamical impact that must be resolved before the paper can be considered for publication.
Major comments:
A) The figures 1, 6, 9 and 10 do not go down to the surface (terminate at 500 or 200 hPa), which is in my eyes unjustifiable. The results section then completely omits the possible near surface dynamical impacts, which will be of the first order importance, as can be seen from the tip of Himalayas in Fig. 6. Without considering low-level processes (near surface breaking; the impact of the near surface drag modifications on resolved wave EPFz at at least 850hPa) the analysis of the dynamical mechanisms cannot be complete. An illustrative example of this bad praxis is the referenced catalytic wave-mean-flow positive feedback by White et al. (2021) - more on this in a minor comment.
B) Wave-induced secondary circulation - I suggest to omit this subsection in the revision, because the explanation invoking the Downward Control Principle by Haynes et al. (1991) is conceptually flawed. Eq. 6 uses the steady state version of the principle, which is completely unjustified for the 10-day forecasts, i.e. of a length comparable to a few radiative timescales in the stratosphere. In the original Haynes et al. (1991) paper you can find results of numerical experiments documenting how the transient response differs from the steady state response you assume in your explanations.
Minor comments:
L70-L73 - Delete the sentences in brackets. They add no new information.
L73-74 - I know what you mean but this statement about horizontal propagation has to be rephrased more carefully, because it can be misleading in a sense that nonhydrostatic GWs can propagate equally oblique as for example near-inertia oGWs that can travel hundreds to thouasand of kilometers horizontally.
L106 subgrid orographic ->subgrid scale orography effects
L154 and L172 and 173FR0 is in fact an inverse Froude number, which is another important distinction from your horizontal Fr
L193 Beljaar's->modified Beljaar's?
L199 write the time and date indication according to a proper English grammar
L213 and 218 tropospheric jet -> upper tropospheric lower stratospheric jet
because the subtropical jet is located in UTLS
L220 Given in the summer - rephrase.
Fig. 1 - see my comment A)
Fig. 2 - adjust the color scale to better visualize the differences in plot d).
L299-L300 ...which are significantly reduced in EXP_NHE... Please add some significance indicator to the Fig. 3
Fig. 6 - see my comment A)
L389 - delete the By the way statement
L405-442 see my comment B, because I think that this section should be deleted.
L447-450 see also my comment A. The term catalytic wave-mean-flow positive feedback (White et al., 2021) is very vague and possibly erroneous, because White et al., (2021) absolutely fail to account any compensating or amplifying dynamical interaction between the processes from SSO and resolved orography, which can also play a big role in your study. can you for example simply check the differences in EPFz at 850 hPa? Moreover, the original reference has nowhere proven that indeed the width of the wave spectrum that can enter the stratosphere plays a role in their results. You are welcome to prove this in your manuscript. But, I think that the Cohen et al compensation mechanism or related numerous works by other authors on parameterized GWD effects on the refractive index in the valve layer should be used as a reference here.
L490 From eq. 7 -> Why don't you plot the RFI differences?
L493 Is inhabiting the right word here?
Overall comment to the whole results section: The differences are small, but go generally in a good direction towards improvement of the forecast (except situation, where small changes in location can regionally lead also to worsening of the skill). I am not an NWP developer or forecaster to be able to judge how significant this improvement is. But I highlight this fact for the editor to notice.