the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Feb 2023
The “Hydro-ABC model” (Vn 2.0): a simplified convective-scale model with moist dynamics
Jiangshan Zhu
Ross Noel Bannister
Abstract. The prediction of convection (in terms of position, timing, and strength) is important to achieve in high-resolution weather forecasting. This problem not only requires good convective-scale models, but also data assimilation systems to give initial conditions which neither improperly hinders nor hastens convection in the ensuing forecasts. Solving this problem is difficult and expensive using operational-scale numerical weather prediction systems, and so a simplified model of convective-scale flow is under development. This paper extends the “ABC model” of dry convective-scale flow to include mixing ratios of vapour and condensate phases of water. This revised model is called “Hydro-ABC”.
Hydro ABC includes transport of the vapour and condensate mixing ratios within a dynamical core, and transitions between these two phases via a micro-physics scheme. A saturated mixing ratio is derived from model quantities, which helps determine whether evaporation or condensation happens. Latent heat is exchanged with the buoyancy variable (ABC's potential temperature-like variable) in such a way to conserve total energy, where total energy is the sum of dry energy and latent heat. The model equations are designed to conserve the domain-total mass, water, and energy.
An example numerical model integration is performed and analysed, which shows the development of a realistic looking anvil cloud, and excitation of inertio-gravity and acoustic modes over a wide range of frequencies. This behaviour means that Hydro-ABC is a challenging model to allow experimentation with innovative data assimilation strategies in the next stage of work. Further, an ensemble of Hydro-ABC integrations is also performed in order to study the possible forecast error covariance statistics (necessary for data assimilation). These show patterns that are dependent on the presence of convective activity (at any model's vertical column), thus giving a taste of flow-dependent error statistics. Candidate indicators/harbingers of convection are also evaluated (namely relative humidity, hydrostatic imbalance, horizontal divergence, convective available potential energy, and convective inhibition), which appear to be reliable diagnostics concerning the presence of convection. These diagnostics will be useful in the selection of the relevant forecast error covariance statistics when data assimilation for Hydro-ABC is developed.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(1786 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1786 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Jiangshan Zhu and Ross Noel Bannister
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-1436', Anonymous Referee #1, 25 Apr 2023
Review of “The Hydro-ABC model (Vn 2.0): a simplified convective-scale model with moist dynamics” by Zhu and Bannister
This manuscript extends the existing dry ABC model to include mixing ratios of water vapor and cloud water, termed the “hydro-ABC model”. This manuscript introduces and evaluates the extended equations for the “hydro-ABC model”. The success of simulation for a realistic-looking anvil cloud offers the possibility of exploring convective-scale DA strategies within a low-cost model. Investigations of error statistics are also conducted. Generally, this manuscript is a complete work and provides a cheaper approach to studying convective-scale DA. My overall recommendation is for acceptance pending minor revisions.
- Line 7: “-” is missing after “Hydro”.
- Line 101: Check the equation. The first “=” sign seems to be “+”?
- Fig. 5: I am confused about the vertical correlations of w with q and qc at 80 and onward. Both correlations show strong positive values in the low levels. Intuitively, the increased qc means the reduced q. Why do we see positive correlations for both of them?
- The proposed “hydro-ABC model” does not include the precipitation processes. However, the precipitation can lead to the development of cold pools, which facilitate the maintenance of convections. Will the authors have plans to include the processes related to cold pools in the proposed model?
- Figure 6: It is unclear how the authors define the three zones in this figure. Because Figure 7 suggests that the authors attempt to find indicators for determining the three zones.
- Figure 7: I suggest using qc, w, or their variants, and they may be good potential choices for the indicators as well.
Citation: https://doi.org/10.5194/egusphere-2022-1436-RC1 - AC1: 'Reply on RC1', Ross Bannister, 05 Jul 2023
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RC2: 'Comment on egusphere-2022-1436', Anonymous Referee #2, 13 May 2023
Publisher’s note: a supplement was added to this comment on 17 May 2023.
The manuscript of Zhu and Bannister presents a novel, moist-dynamics version of the ABC-model, the new model is called Hydro-ABC, with the aim to perform future DA simulations for testing (new) DA schemes. The Hydro-ABC is a reduced model (no y-derivatives) relative to NWP models and it supports vortical dynamics, gravity and acoustic waves, as well as simplified moist dynamics. The moist dynamics included concerns the dynamics of water vapour and condensate fields and the model is constructed in such a way that the total energy including the moist component is conserved. The authors present preliminary (ensemble) simulations including correlations between various fields of interest. These developments for DA simulations are very interesting and such a reduced moist dynamics approach deserves due attention. So this is excellent news.
Yet the work described to date in the manuscript has some shortcomings. The manuscript requires therefore seemingly some modifications, with the following suggestions for improvement:
- The formulation of the moist dynamics (in section 2.3) is rather implicit and unclear, and immediately leads to a parameterisation that seems to hinge on the discrete time-step splitting between dry and moist dynamics. The dynamics should be described first on a continuum level before mixing it up with the time-step splitting.
- Whether the description is implicit or not, e.g. for S_b’, in the end, a closed-form formulation should be reached/available, otherwise a numerical implementation would not be achieved or possible. (1) What is required is a complete, final closed-form description of the entire continuum dynamics, presumably including implicit relations to be solved. Presently, section 2.3 is rather unclear and it is difficult if not impossible to figure out what the final formulation is. E.g., the implied relation for S_b’ seems to become 0/0 when b’=0, which presumably can be fixed via some l’Hopital rule being invoked implicitly?
(2) In addition, it would be useful to have a (pseudo)code available of the moist-dynamics algorithm, which would presumably involve the split time-stepping. - I cannot follow the second option in (6) at all.
- The time-stepping scheme used and the time-splitting should be defined and as such explained better.
- (1) There is an accumulation of minor issues, including a few sentences and statements which are nearly or completely incomprehensible. An anonymised, annotated manuscript is made available to assess and address these. (2) Also note the various queries and remarks therein on resolution and timestep issues.
- Please consider better explaining figure 6 in the text; please tie statements in the text with a clear pointing out in how the reader can discern the statement from an identifed observational feature in the figure. At the moment it is difficult to link text to features in the figure.
- CIN does not seem to reveal very much in contrast to what is stated.
- In Appendix A, CAPE and CIN for hydro-ABC are defined, after noting that there is no T and T_environmental available in the model; yet in eqn (12) a temperature is defined, used earlier in q_s, which could serve as such? Why is the approach followed to define CAPE and CIN valid and how does this link to an approach using the T of eqn (12) and its T_environmental analog. Why is the algorithm to define “environmental variable” valid; can one prove that (numerically); how does it depend on the chosen averaging?
While the goals and approaches followed in the presented research are great, and the simulations promising, the above queries seem to warrant some revisions to address the above queries.
Kind regards.
- AC2: 'Reply on RC2', Ross Bannister, 05 Jul 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-1436', Anonymous Referee #1, 25 Apr 2023
Review of “The Hydro-ABC model (Vn 2.0): a simplified convective-scale model with moist dynamics” by Zhu and Bannister
This manuscript extends the existing dry ABC model to include mixing ratios of water vapor and cloud water, termed the “hydro-ABC model”. This manuscript introduces and evaluates the extended equations for the “hydro-ABC model”. The success of simulation for a realistic-looking anvil cloud offers the possibility of exploring convective-scale DA strategies within a low-cost model. Investigations of error statistics are also conducted. Generally, this manuscript is a complete work and provides a cheaper approach to studying convective-scale DA. My overall recommendation is for acceptance pending minor revisions.
- Line 7: “-” is missing after “Hydro”.
- Line 101: Check the equation. The first “=” sign seems to be “+”?
- Fig. 5: I am confused about the vertical correlations of w with q and qc at 80 and onward. Both correlations show strong positive values in the low levels. Intuitively, the increased qc means the reduced q. Why do we see positive correlations for both of them?
- The proposed “hydro-ABC model” does not include the precipitation processes. However, the precipitation can lead to the development of cold pools, which facilitate the maintenance of convections. Will the authors have plans to include the processes related to cold pools in the proposed model?
- Figure 6: It is unclear how the authors define the three zones in this figure. Because Figure 7 suggests that the authors attempt to find indicators for determining the three zones.
- Figure 7: I suggest using qc, w, or their variants, and they may be good potential choices for the indicators as well.
Citation: https://doi.org/10.5194/egusphere-2022-1436-RC1 - AC1: 'Reply on RC1', Ross Bannister, 05 Jul 2023
-
RC2: 'Comment on egusphere-2022-1436', Anonymous Referee #2, 13 May 2023
Publisher’s note: a supplement was added to this comment on 17 May 2023.
The manuscript of Zhu and Bannister presents a novel, moist-dynamics version of the ABC-model, the new model is called Hydro-ABC, with the aim to perform future DA simulations for testing (new) DA schemes. The Hydro-ABC is a reduced model (no y-derivatives) relative to NWP models and it supports vortical dynamics, gravity and acoustic waves, as well as simplified moist dynamics. The moist dynamics included concerns the dynamics of water vapour and condensate fields and the model is constructed in such a way that the total energy including the moist component is conserved. The authors present preliminary (ensemble) simulations including correlations between various fields of interest. These developments for DA simulations are very interesting and such a reduced moist dynamics approach deserves due attention. So this is excellent news.
Yet the work described to date in the manuscript has some shortcomings. The manuscript requires therefore seemingly some modifications, with the following suggestions for improvement:
- The formulation of the moist dynamics (in section 2.3) is rather implicit and unclear, and immediately leads to a parameterisation that seems to hinge on the discrete time-step splitting between dry and moist dynamics. The dynamics should be described first on a continuum level before mixing it up with the time-step splitting.
- Whether the description is implicit or not, e.g. for S_b’, in the end, a closed-form formulation should be reached/available, otherwise a numerical implementation would not be achieved or possible. (1) What is required is a complete, final closed-form description of the entire continuum dynamics, presumably including implicit relations to be solved. Presently, section 2.3 is rather unclear and it is difficult if not impossible to figure out what the final formulation is. E.g., the implied relation for S_b’ seems to become 0/0 when b’=0, which presumably can be fixed via some l’Hopital rule being invoked implicitly?
(2) In addition, it would be useful to have a (pseudo)code available of the moist-dynamics algorithm, which would presumably involve the split time-stepping. - I cannot follow the second option in (6) at all.
- The time-stepping scheme used and the time-splitting should be defined and as such explained better.
- (1) There is an accumulation of minor issues, including a few sentences and statements which are nearly or completely incomprehensible. An anonymised, annotated manuscript is made available to assess and address these. (2) Also note the various queries and remarks therein on resolution and timestep issues.
- Please consider better explaining figure 6 in the text; please tie statements in the text with a clear pointing out in how the reader can discern the statement from an identifed observational feature in the figure. At the moment it is difficult to link text to features in the figure.
- CIN does not seem to reveal very much in contrast to what is stated.
- In Appendix A, CAPE and CIN for hydro-ABC are defined, after noting that there is no T and T_environmental available in the model; yet in eqn (12) a temperature is defined, used earlier in q_s, which could serve as such? Why is the approach followed to define CAPE and CIN valid and how does this link to an approach using the T of eqn (12) and its T_environmental analog. Why is the algorithm to define “environmental variable” valid; can one prove that (numerically); how does it depend on the chosen averaging?
While the goals and approaches followed in the presented research are great, and the simulations promising, the above queries seem to warrant some revisions to address the above queries.
Kind regards.
- AC2: 'Reply on RC2', Ross Bannister, 05 Jul 2023
Peer review completion
Journal article(s) based on this preprint
Jiangshan Zhu and Ross Noel Bannister
Model code and software
Hydro ABC Vn 2.0 model code and user documentation Jiangshan Zhu, Ross Bannister, and Ruth Petrie https://doi.org/10.5281/zenodo.7418510
Jiangshan Zhu and Ross Noel Bannister
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1786 KB) - Metadata XML
The model shows the development of an anvil cloud, and excitation of atmospheric waves over many frequencies. The covariances that develop between variables are also studied, together with indicators of convective motion.