the Creative Commons Attribution 4.0 License.
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| 19 Dec 2024
Coupling the TKE-ACM2 Planetary Boundary Layer Scheme with the Building Effect Parameterization Model
Abstract. Understanding and modeling the turbulent transport of surface layer fluxes plays a critical role in a numerical weather forecasting model. The presence of heterogeneous surface obstacles (buildings) that have dimensions comparable to the model vertical resolution requires further complexity and design in the planetary boundary layer (PBL) scheme. In this study, we develop the numerical method to couple one of the recently validated PBL schemes, TKE-ACM2, with the multi-layer Building Effect Parameterization (BEP) model in WRF. Subsequently, the performance of TKE-ACM2+BEP has been examined under idealized convective atmospheric conditions with a simplified building layout. Furthermore, its reproducibility is benchmarked with one of the state-of-the-art large-eddy simulation models, PALM, which can explicitly resolve the building aerodynamics. The result indicates that TKE-ACM2+BEP outperforms the other operational PBL scheme (Boulac) coupled with BEP by reducing the bias in both the potential temperature (θ) and wind speed (u). Following this, real case simulations are conducted for a highly urbanized domain, i.e., the Pearl River Delta (PRD) region in China. The high-resolution wind speed LiDAR observations suggest that TKE-ACM2+BEP can mitigate the overestimation in the lower part of the boundary layer compared to the Bulk method at a LiDAR site located in a densely built environment. In addition, the surface temperature and relative humidity can be improved in TKE-ACM2+BEP at surface stations in urbanized areas compared to TKE-ACM2 without BEP. However, it is revealed that BEP may not always imply a better reproduction of surface wind speed as it could exert excessive aerodynamic drag.
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RC1: 'Comment on gmd-2024-205', Anonymous Referee #1, 12 Jan 2025
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Interactive reviewer comment on the manuscriptCoupling the TKE-ACM2 Planetary Boundary Layer Scheme with the Building Effect Parameterization Model
GMD-2024-205
By Zhang et al.
General considerations
In this contribution the authors present the coupling approach of an urban ‘building effect parameterization’ (i.e., the surface exchange parameterization) to a recently proposed (improved) boundary layer parameterization scheme for atmospheric RANS type models. The new coupled scheme is compared to a version with a bulk surface exchange treatment, and to the results from another PBL parameterization (one of the ‘standard schemes in the literature), once with the bulk surface exchange and once with the ‘building effect parameterization’. The approach is evaluated on two case study scenarios with an idealized surface characterization (regular cubes) and an LES (PALM-4U) as a reference. Then, a month-long simulation for the Pearl River Delta (China) with a number of mega-cities (including Hong-Kong) is performed. Data from three lidars (wind profiles), and 31 surface stations (urban and rural) are used for validation.
The study is well designed, and pretty well described (the ‘plan’ for the paper is good, and much of what needs to be known, can be found somewhere). I cannot say, however, that it is well written (I have added quite a number of ‘detailed comments’ – mostly related to language or formulations, etc.). A serious language/style update by a native speaker would certainly greatly improve the value of the paper.
Even if I have labelled one of the comments as ‘major’, I think its resolution is straight forward – so that I can recommend the paper to be published subject to minor modifications.
Major comments
- Real case simulations & data: the presentation of the data is not complete. The lidars, when introduced should be characterized (urban, rural) and some basic information on vertical resolution and accuracy should be provided. Also, for the surface stations, information should be provided on the explicit meaning of the different LCZ classes (‘compact high rise, LCZ1, etc.), and how many are available for each type (how many urban, how many non-urban), what ‘G class’ (e.g., Fig. 17, 18, ..) means. Much of this can be found somewhere (I can, for example add the different numbers in each panel in Fig. 17) but the authors could support the reader in providing this information. Furthermore, Figs. 14-16 have 10 urban classes, plus ‘water cells’ plus ‘natural cells’, while Figs. 17-19 have 7 urban classes (the remaining three are probably not available) plus ‘G stations’ and ‘rural stations’: how do the latter translate to the water cells and natural cells? I suggest to add a sub-section in Section 2 with some of this information.
Minor comments
l.48 ‘…they work with few…’: maybe better ‘they have only been coupled to a few … (I think they would also work with all the other schemes – btu it has not been done)
l.60 ‘have shown that the TKE-ACM2….’
l.62 ‘at the urban station….’: this suggests that the reader knows which urban station is meant. Please rephrase.
l.72 ‘…from the high-resolution lidar’: same as before (this suggests that the lidar had been introduced before). Reformulate to ‘….from a high-resolution lidar’.
l.87 Energy conserving
l.84 ‘…K is the eddy viscosity….’. Do I have to assume that K is equal for all ‘zeta’ (l. 91). If not (what would be better supported by the literature) , K should also get an index zeta.
l.115 ’C_eps is an empirical constant and l_eps corresponds to….’
l.162 uniformly distributed in the vertical: this may be a good idea in a CBL but how about the near surface?
l.164 ‘…one corresponding to a moderately…’
Fig. 2, caption: the different types of lidars should be referenced (UTSS, HT, KP), and briefly explained (possibly in the text) what their strengths weaknesses are.
l.215 ‘…it is found that quasi-….’
l.215 ‘….when LES…’: how is the time for having reached quasi-equilibrium diagnosed?
l.223 usually called ‘turbulent fluxes’. However, it would be better to delete ‘outputted’ - these are just the ‘turbulent fluxes from PALM‘.
l.224 very often, what we can see in a figure has been plotted… (so, the verb ‘to plot’ is somewhat obsolete in this context). May be ‘….schemes are contrasted in …’.
Fig. 6, caption: please add for which case this RMSE is determined and what ‘the truth’ is (assumed to be). Fig. 6: I would find it ‘more convincing’ if the black dots would be displayed as a ‘dotted line’ (and not as a dot at each level) – then it would not appear as a black line in the lower parts of the panels……
- 231 ‘a smaller warm bias’ would possibly sound better
l..234 ‘becomes stable….’: this is indeed a feature of the CBL. Some authors have even defined a ‘neutral level’, i.e. the height where slightly unstable transits into slightly stable (formally, there might even be such a height in the LES)
l.241 ‘….within [the] UCL and near [the ]PBL height where the relatively constant w′θ′ in the middle UCL is not exhibited [reproduced?] in either BEP simulation.’. Here, I think this is a little ’underselling’ the BEP simulations. They at least to some degree reproduce a strong deviation in the profile at canopy height (the two others cannot reproduce this), the relax in the middle of the CBL (and yes, the vertical gradient is too small)…..
l. 249 ‘This has shown the wind shear at the roof level is underestimated…’: I am not sure what the authors want to say with this. Maybe this is just a matter of wording? – ‘thus it appears that the BEP parameterization results in an underestimation of wind shear at roof level, when compared to the LES’.
l. 250 ‘it is discovered…’: first of all I suggest to start a new paragraph. Second, momentum flux decreases (increases in magnitude…) with height. Third, ‘at some height’ (as it appears in the LES) seems to be some 2-4 canopy heights (in b) and d), respectively). Fourth, this cannot be called ‘discovered’ here – this was even one of the reasons for the development of the BEP scheme (i.e., that it had been discovered earlier, that momentum flux was not constant with height in urban canopies).
l.260 ‘similar behavior of the two schemes is found…’
l.275 I think the dashed line is blue in Fig. 5d
l.279 top of the RSL, rather
Fig 7 I suggest to repeat the definition of delta_U (i.e., BEP-Bulk) in the caption. Same in Fig. 8 for theta
l.300 beginning a new sentence: Figure 8…..
Fig. 9, caption: delete ‘plots the’ ; ‘at USTSS, HT and KP’: are these locations? I recall too have seen different symbols in Fig. 2 – and thought this to be different types of instruments. I suggest to add an ultra-short sub-section in Section 2, describing the instrument type, vertical resolution and some accuracy statements from the manufacturer.
l.306 …the rural lidar station HT (first, I learn now that the different symbols are different sites (see previous comment), but also I learn that at least one of the lidars is ‘rural’. Why not giving them an extension in the acronym?
l.306 at the LCZ 5 USTSS lidar location: wouldn't it be perfect to add this LCZ information to the section suggested in ‘comment to Fig. 9’?
l.308 ‘has been reduced’: the authors probably mean ‘is smaller in the BEP schemes….’
l.309 I don’t think there is a Fig. A51… Can the authors adjust?
l.312 starting at an altitude of 50 m agl?
Fig.10/11/12, captions: are these instantaneous values at the given times or 1-hour averages (in both, the observations and the simulation? Also, the caption may remind the reader that the panels start at 8 pm (why is this so?)
Fig. 13: RMSE and mean bias of WHAT? What is the data base? What are the ‘error bars’ referring to?
l.330 convective thermals
l.331 the smallest RMSE and the smallest negative bias….
l.332 Boulac+BEP, which increased the deviations with respect to the Boulac+bulk simulations.
l.334 I cannot locate Section 44.1. please adjust.
l.337 this is not predictability, rather ‘accuracy’
l.342 who is collaborating here with whom?
l.359 as small as…
l.359 ‘…is more likely to be found at around 06LT in TKE-ACM2….’: I don’t think this can be said like that. Do the authors want to say that ‘delta_U10 starts to be larger (in absolute terms) starting from about 06 LT’?
l.366 slightly altered?
l.369 the ‘supplementary Zhang (2024) is not a proper citation (in the supplementary material to Zhang….)
l.377 LC1…stations are …lower than the observed values’: this is, first of all, not a correct sentence (the simulated wind speed at these stations is smaller than…). Second this is a very important observation, which suggests that the authors should (maybe in the appendix) produce a table where the LCZ codes are described in words (having read the sentence, I, for example would wonder what LCZ2 is (it is also having much lower wind speeds than observed….). I suggest to add this finding explicitly to the conclusions (in the present form it states that LCZ1,4, 10 etc. are underestimating – but it is more relevant to state that high-rise and heavy industry types are underestimating.
l.383 ‘at the hill whose…..’: replace by ‘at a hill with a spatial scale of 50 m’.
l.388 ‘Coinciding with Fig. 15’? Maybe: ‘As can be seen in Fig. 15, T2….’?
l.391 ‘their predictability’: it is accuracy and not predictability
Figs17-19: what are ‘G’ stations?
l.400 again, it is not the predictability that is improved, but the prediction (i.e., its accuracy). Predictability is a property of the atmosphere (which is assessed using ensemble prediction approaches)
l.401 should read: ….BEP produces larger RH2 when ….
l.409 building-resolving
Figure 20, caption: Please add the information (in the caption) where the number of sites contributing to a LCZ type can be found.
l.419 BEP suggests that the buildings act..
l.421 …observations are used to…
l.425 …LIDAR station, compared to..
l.430 no predictability
Citation: https://doi.org/10.5194/gmd-2024-205-RC1
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