the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
WRF (v4.0)-SUEWS (v2018c) Coupled System: Development, Evaluation and Application
Hamidreza Omidvar
Zhenkun Li
Ning Zhang
Wenjuan Huang
Simone Kotthaus
Helen C. Ward
Zhiwen Luo
Abstract. The process of coupling the Surface Urban Energy and Water Scheme (SUEWS) into the Weather research and forecasting (WRF) model is presented, including pre-processing of model parameters to represent spatial variability of surface characteristics. Fluxes and mixed layer height observations in the southern UK are used to evaluate a two-week period in each season. Mean absolute errors, based on all periods, are smaller in residential Swindon than central London for turbulent sensible and latent heat fluxes (QH, QE) with greater skill on clear days at both sites (for incoming and outgoing short- and longwave radiation, QH and QE). Clear seasonality is seen in the model performance: with better absolute skill for QH and QE in autumn and winter, when there is a higher frequency of clear days, than in spring and summer. As the WRF-modelled incoming shortwave radiation has large errors, we apply a bulk transmissivity derived from local observations to reduce the incoming short-wave radiation input to the land surface scheme – this could correspond to increased presence of aerosols in cities. We use the coupled WRF-SUEWS system to investigate impacts of the anthropogenic heat flux emissions on boundary layer dynamics by comparing areas with contrasting human activities (central-commercial and residential areas) in Greater London - larger anthropogenic heat emissions not only elevate the mixed layer heights but also lead to a warmer and drier near-surface atmosphere.
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Ting Sun et al.
Status: final response (author comments only)
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RC1: 'Comment on gmd-2023-117', Anonymous Referee #1, 11 Sep 2023
The manuscript presents the coupling Surface Urban Energy and Water Scheme (SUEWS) into the Weather Research and Forecasting (WRF) model. The coupled WRF-SUEWS system shows good performance in simulating fluxes and mixed layer height compared to observations in two UK sites as well as other urban-focused WRF research. The integrated system has also been employed to investigate the impacts of anthropogenic heat flux emissions on the boundary layer dynamics within Greater London. The research is systematically structured and well presented. However, before endorsing for publication, the following points should be addressed:1. Lines 53-54: Please elucidate the distinction between SUEWS and the land surface mentioned. Does SUEWS replace the entire land surface module in WRF?2. Lines 217-219: The notation τWREE seems ambiguous. Is it intended to be τWRF? Also, ensure that each term in Eq. 20 is clearly defined, especially if not introduced earlier.3. Line 245: Table 2 seems to lack blue dots. Are you referring to Figure 6?4. Figure 6: Is IMP indicative of impervious surfaces? Kindly specify.5. Lines 275-276: Which observational forcings are utilized for the SUEWS spin-up? Please clarify.6. Lines 296-298: Could you elaborate on the rationale behind selecting aerosol-derived MLH observation and WRF MH as evaluative metrics for the boundary layer depth?7. Figure 7: The bulk transmissivity difference seems to rise progressively from sunrise to sunset. Could you elucidate the underlying reason?8. Lines 345-346: The authors methiond that the offline mode outperforms the online mode due to the model’s performance in incoming shortwave radiation. Given the study's primary objective of evaluating the coupled system (i.e., the online mode), what prompts the emphasis on reducing offline shortwave radiation errors? Would such corrections augment the online mode's efficacy?9. Lines 358-359: Why does the accurate partitioning of turbulent heat fluxes makes radiation performance less critical?10. Figure 14: The model seems to inadequately represent the Bowen ratio compared to observations, especially during nights in July and October in SWD. Could you shed light on this inconsistency?11. Line 391: Change QF to QF?12. Line 418: Rectify flus to flux.13. Lines 420-422: The 30% discrepancy in vegetation fraction—does it signify an annual or monthly average? If it's an annual average, could you specify the discrepancy for April? Furthermore, could you expound on the decision to spotlight April when investigating the effects of anthropogenic heat on the atmospheric boundary layer? Are other summer or winter months considered?14. Figure 16: Please provide more details regarding the computation of anthropogenic heat (QF), particularly the exact meaning of Qmax and Qmin. Furthermore, the use of normalized anthropogenic heat in Figures (a) and (b) is puzzling. This format complicates direct comparisons of anthropogenic heat during daytime and nighttime.15. Lines 424-425: The air appears to become wetter aloft with PBL as shown in Figure 17.16. Lines 435-436: Kindly remove the redundant “explored”.Citation: https://doi.org/
10.5194/gmd-2023-117-RC1 -
RC2: 'Comment on gmd-2023-117', Anonymous Referee #2, 02 Oct 2023
This manuscript described the structure and key physics of the coupled WRF-SUEWS system,and evaluated WRF-SUEWS at two UK sites and explored its application in modelling dynamics and impacts of anthropogenic heat emissions at the city scale. The topic is very interesting and has important implications in urban climate. However, there are major concerns which lead me to request a minor revision of this manuscript before publish.
The urban boundary layer fluctuates with weather scenario changes, especially for synoptic pattern. Synoptic patterns modulate local weather condition in boundary layer, e.g., SUEWS, boundary layer height, wind, RH and temperature, or even cloud. Therefore, the limitation and applicability of present coupled WRF-SUEWS system should be discussed, especially for some special synoptic patterns.
In addition, for clear sky, the role of AHR and land use and their impacts on local climate in the London should be compared with other regions.
Effects of anthropogenic heat release upon the urban climate in a Japanese megacity
A High-Resolution Monitoring Approach of Canopy Urban Heat Island using Random Forest Model and Multi-platform ObservationsSimulating the Regional Impacts of Urbanization and Anthropogenic Heat Release on Climate across China
Modulation of wintertime canopy Urban Heat Island (CUHI) intensity in Beijing by synoptic weather pattern in planetary boundary layerMoreover, the observed boundary layer height should be described detailly and the accuracy should be pointed out for model validation
Citation: https://doi.org/10.5194/gmd-2023-117-RC2
Ting Sun et al.
Data sets
WRF(v4.0)-SUEWS(2018c): input data for the evaluation at two UK sites Ting Sun; Hamidreza Omidvar; Sue Grimmond https://doi.org/10.5281/zenodo.7957903
Model code and software
WRF-SUEWS source code for GMD submission Ting Sun; Hamidreza Omidvar; Zhenkun Li; Sue Grimmond https://zenodo.org/record/8137708
Ting Sun et al.
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