the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sensitivity of simulating Typhoon Haiyan (2013) using WRF: the role of cumulus convection, surface flux parameterizations, spectral nudging and initial and boundary conditions
- 1Department of Meteorology, University of Reading, Reading, United Kingdom
- 2Institute of Environmental Science and Meteorology, University of the Philippines-Diliman, Quezon City, Philippines
- 1Department of Meteorology, University of Reading, Reading, United Kingdom
- 2Institute of Environmental Science and Meteorology, University of the Philippines-Diliman, Quezon City, Philippines
Abstract. Typhoon (TY) Haiyan was one of the most intense and highly destructive tropical cyclones (TCs) to affect the Philippines. As such, it is regarded as a baseline for extreme TC hazards. Improving the simulation of such TCs will not only improve the forecasting of intense TCs but will also be essential in understanding the potential sensitivity of future intense TCs with climate change. In this study, we investigate the effects of model configuration in downscaling TY Haiyan using the Weather Research Forecasting (WRF) Model. Sensitivity experiments were conducted by systematically altering the choice of cumulus schemes, surface flux options, and spectral nudging. In addition to using the European Centre for Medium-Range Weather Forecasts Re-analysis 5th Generation (ERA5) single high resolution realization as initial and boundary conditions, we also used four of the ten lower resolution ERA5 Data Assimilation System (EDA) ensemble members as initial and boundary conditions. Results indicate a high level of sensitivity to cumulus schemes, with a trade-off between using Kain-Fritsch and Tiedtke schemes that have not been mentioned in past studies of TCs in the Philippines. The Tiedtke scheme simulates the track better (with a lower mean Direct Positional Error (DPE) of 33 km), while the Kain-Fritsch scheme produces stronger intensities (by 15 hPa minimum sea level pressure). Spectral nudging also resulted in a reduction in the mean DPE by 20 km and varying the surface flux options resulted in the improvement of the simulated maximum sustained winds by up to 10 ms−1. Simulations using the EDA members initial and boundary conditions revealed low sensitivity to the initial and boundary conditions, having less spread than the simulations using different parameterization schemes. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in the track and intensity of simulating intense tropical cyclones.
Rafaela Jane Delfino et al.
Status: final response (author comments only)
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RC1: 'Comment on nhess-2021-400', Anonymous Referee #1, 24 Feb 2022
It is an interesting and well-written article that investigates the impact of (a) two different cumulus convection schemes (Kain-Fritsch and Tiedtke), (b) three surface flux formulations, (c) spectral nudging and (d) initial and boundary conditions from ERA deterministic and Ensemble of Data Assimilations system, on the WRF simulations of super Typhoon Haiyan (2013) in Western North Pacific. The model results are compared against the International Best Track Archive for Climate Stewardship, satellite data and ERA5 reanalyses.
The use of English is very good. The figures/tables are clearly produced and necessary. The abstract is concise and the conclusions are supported by the results.
It is suggested to accept this article for publication after some minor corrections are performed.
Suggested corrections:
Section 2.4: (a) Did you use one or two-way nesting? (b) Please justify the location of the southern boundary of the inner domain so close to the track of the tropical cyclone. Errors from the boundary conditions are expected to influence the simulation. (c) Why did you extend the inner domain so much north of the track? Please justify it in the manuscript. Was it necessary in order to simulate appropriately the subtropical ridge? (d) Please clearly state whether all the model results of this article are based on the output of the inner domain.
Lines 167-170: How do you explain your result that the simulation with the longer lead-time was the best?
Line 182: Was the cumulus convection scheme employed in both domains? Please state it clearly.
Lines 289-290 and 297-298: the mean DPE of KF simulations is not the same in the former and latter lines. The same happens for the TK simulations. Please make the necessary corrections and update lines 562-563 accordingly.
Figure 3, x-axes: is it the simulation time or the 72-hour verification time (as it was stated in line 171)?
Line 319: in Figure 4 the control simulation (KFsnOFFsf0) has a minimum mslp of about 940 hPa (not 934 hPa) and maximum wind speed less than 50 hPa (not 53.69 m/s).
Figure 4: For consistency with the symbols of the other experiments, it is suggested to change the pattern of TKsnOFFsf1 to dotted line. In the current figure it is difficult to distinguish it from TKsnOFFsf0.
Lines 349-350: in figure 6 the RMSE of KFsnOFFsf1 is about 10 m/s and its correlation is between 0.8 and 0.85 (i.e. lower than 0.89).
Lines 351-352: in figure 6 the RMSE of TKsnONsf0 is about 15 m/s and its correlation is about 0.69.
Line 409: The simulation with the closest landfall time is not shown in Table 3, but it can be derived by Figure 11 (as far as the experiments without spectral nudging are concerned).
Line 464: Please justify your choice to present only the runs without nudging in figure 11.
Line 488: the steering flow bias has not been shown in figure 12.
Figures 12 and 14: Did you interpolate the WRF output to the coarser ERA5 grid? Which interpolation method did you use? Please include this information in the article.
Figures 12, 13, 14: (a) Please justify the use of the KFsnOFFsf1 and TKsnOFFsf1 experiments instead of all the KF and TK runs. (b) are these figures based on 6-hourly ERA5 and WRF output?
Lines 501-502: Please clarify in the article whether the vertical wind shear was computed (a) from time-averaged u and v winds at 200 and 850 hPa (i.e. firstly calculating the time-averaged u and v at each grid-point and then using them to calculate the vertical wind shear), or (b) by averaging the instantaneous values of the vertical wind shear (i.e. firstly calculating the instantaneous vertical wind shear at each grid-point and then calculating its time-average value).
Line 536: (a) do you mean that KF shows a higher relative humidity along the track? Otherwise, it disagrees with the previous discussion in this paragraph. (b) for clarity it is suggested to draw the tracks of the simulated and actual tracks on both panels of figure 14.
Technical corrections:
Line 152: “… and model physics (Isaksen et al., 2010).”
Line 158: “… different parameterization …”
Line 165: It is a 180-hour period (not 174-hour) from 00 UTC 4 November to 12 UTC 11 November.
Line 175: “… is bounded by 100-170 degrees East …”
Line 251: “… maximum 10m winds to evaluate …”
Line 268: “… relative vorticity maxima …”
Line 286: “… without nudging (snOFF) …”
Line 312: “… of the DPE (km) …”
Line 473: “… the KF scheme shows …”
Lines 496, 527, 543: KFsnOFFsd1 and TKsnOFFsd1 must be corrected to KFsnOFFsf1 and TKsnOFFsf1, respectively.
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AC1: 'Reply on RC1', Rafaela Jane Delfino, 11 May 2022
Dear Referee,
Thank you very much for the overall positive feedback on the submitted manuscript and for giving us the opportunity to submit an improved version of the manuscript. We appreciate the thoroughness and objectiveness of the comments and have addressed the specific concerns raised. And all changes are highlighted in the revised manuscript. All line numbers refer to the revised manuscript with tracked changes.
Please see in the attached file our specific responses and kindly refer to the attached revised manuscript and supplementary file for more details.
- AC2: 'Reply on RC1', Rafaela Jane Delfino, 11 May 2022
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AC1: 'Reply on RC1', Rafaela Jane Delfino, 11 May 2022
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RC2: 'Comment on nhess-2021-400', Anonymous Referee #2, 28 Mar 2022
Manuscript #: NHESS-2021-400
Title: Sensitivity of simulating Typhoon Haiyan (2013) using WRF: the role of cumulus convection, surface flux parameterizations, spectral nudging and initial and boundary conditions
Authors: Rafaela Jane Delfino, Gerry Bagtasa, Kevin Hodges, and Pier Luigi Vidale
Recommendation: Major Revision
General Comments:
The authors utilized WRF-ARW to simulate Typhoon Haiyan and investigate the role of cumulus convection (KF and TK schemes), surface flux parameterizations, spectral nudging, and initial and boundary conditions (ERA5 and EDA). They concluded that the TK scheme and spectral nudging improve track simulations with lower mean DPE than the other model configurations. On the other hand, KF scheme and varying the surface flux options improve the intensity.This type of study will definitely be of a great addition to works that optimize a model’s configuration of TC simulations in the Philippines, but in its current form is not yet ready for publication. Major parts of the paper should be rewritten due to the following major concerns:
1. (Line 55~Line 105, Line 125…) Although a future plan for conducting pseudo-global warming simulations was mentioned, WRF-ARW was used in the paper as a numerical weather prediction (NWP) model to simulate a weather event (TC Haiyan). However, the literature review (introduction) seems to interchange regional climate models (climatological simulations) with numerical weather prediction models (short-term weather events) resulting in mixed and improper citations of papers that use RCMs and NWPs. Event simulations are different from climatological runs. Although WRF and other NWPs can also be used as RCM, they are usually modified to efficiently work for climatological simulations (e.g. CLWRF, RegCM --RCM version of MM5, NHRCM – RCM version of JMA/MRI NHM). NHRCM, and not WRF, is the model used by Cruz et al., 2016 in Line 132.
The paper literature review should focus on studies that conduct TC short-term simulations using models (e.g. WRF, NHM) that are considered as NWP and not RCM. The literature review also fell short in terms of discussing studies that tackle the other sensitivity parameters such as spectral nudging, surface flux, and ICBC. The reviewer hopes to see a clearer revised Introduction with an additional review on the said parameters.2. The objective and analysis of this paper are very promising but the initial forcing is also very critical to consider it as a sensitivity analysis. Kindly clarify if the researchers downscaled only one mother domain (D1) for all D2 sensitivity runs? If not, then it will be inappropriate and difficult to compare the sensitivity of TC track and intensity to parameterizations if the initial forcing (D1) for each experiment have different model physics. This might explain the different (or larger differences of) values of intensities at t=0 in Figure 4. The reviewer strongly suggests to reconsider rerunning all simulations using only one D1 simulation as forcing to all D2 experiments.
With this 2nd major concern, it will be difficult to give meaningful comments on the results and discussions.3. (Line 155-163, 166). Kindly provide supplementary materials for the results of the other domain configurations that led the authors to select the control run model setup. These supplementary materials are very important to justify the model setup of the control run.
Minor comments:
(Line 113): Correct the year “2012” to “2013”.
(Line 125): Kindly reconsider “NWP” instead of “RCM”.
There is no “Powers 2016” in the references.
(Line 132): Cruz et al., 2016 uses NHRCM and not WRF to make temperature and rainfall projections in the Philippines.(Line 155-170): Kindly provide a table for your control run’s model setup as indicated in this section. Make sure to clarify if you performed one-way or two-way nesting, specify the input forcing, temporal and spatial resolutions (dt,dx,dy,dz), model physics, and so on.
(Line 180): “These cumulus schemes are used because PAGASA uses KF …”. Does PAGASA also uses TK? Does the writer mean “The KF cumulus scheme was used because …”?
(Line 185): There is no Sun et al., 2019 in the references.
The discussion on TK is too short and vague. The author should also provide short discussion of the main output of the cited references. Same comment for Lines 194-195, 205.
(Line 206): Check repeating phrases in the sentence with “Charnock’s (1995)”.-
AC3: 'Reply on RC2', Rafaela Jane Delfino, 11 May 2022
Dear Referee,
Thank you very much for highlighting the importance of our work, the useful feedback on the submitted manuscript, and for giving us the opportunity to submit a much improved version of the manuscript. We have addressed the major and minor concerns raised. All changes are highlighted in the revised manuscript and line numbers refer to the revised manuscript with tracked changes.
Please see in the attached file our specific responses and kindly refer to the attached revised manuscript and supplementary file for more details.
- AC4: 'Reply on RC2', Rafaela Jane Delfino, 11 May 2022
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AC3: 'Reply on RC2', Rafaela Jane Delfino, 11 May 2022
Rafaela Jane Delfino et al.
Rafaela Jane Delfino et al.
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