Nivar

Nivar

Investigating the Impact of Horizontal and Vertical Resolution of the WRF Model on Precipitation Forecast: Several Cases Study

Document Type : Original Article

Authors
Sakineh Khansalari 1
Majid Azadi 2
1 Assistant professor
2 Associate professor, Atmospheric Science and Meteorological Research Center, Tehran, Iran
10.30467/nivar.2021.298864.1199
Abstract
In this study, the effect of horizontal and vertical resolution on the precipitation forecast has been investigated. For this purpose, in this study, heavy rainfall occurred in the western region of Iran using GFS data as boundary and initial conditions in the WRF mesoscale numerical forecasting model with two horizontal resolutions and four combinations of position and number of vertical levels has been simulated. The results of this study show that on days when the intensity of precipitation is significant, the results of precipitation simulation improve with increasing horizontal resolution. Also, increasing the resolution of the model in the vertical direction does not necessarily lead to an increase in precipitation forecasting skills and sometimes over-predicted rainfall. Skills of forecasting improved for all rainfall thresholds when the resolution above the melting level was increased. And this is because of better prediction microphysical processes. Also, increasing the resolution of the model in the lower layer of troposphere only in heavy rainfall leads to an increase in forecasting skills. Therefore, the effect of increasing the resolution of the model on forecasting skills is strongly related to the height of added levels and rainfall intensity. In addition, the factor separation methodology shows that with increasing the resolution of the model throughout the troposphere layer, the prediction skill generally decreases in the mean state, and this subject is due to the negative interaction between lower-tropospheric processes and microphysical processes above melting level.
Keywords
Extreme rainfall
Horizontal resolution
Vertical resolution
WRF
Melting layer
Factor separation
Subjects
  1. آزادی، م.، و خان­سالاری، س.، 1398، خدمات مشاوره،پشتیبانی سامانه هشدار سریع سیل حوضه­های مرزی
  2. غرب ایران، طرح پژوهشی (شماره طرح: 1704-16L0014132996324)، پژوهشگاه هواشناسی و علوم جو.
  3. آزادی، م.، رضازاده، پ.، میرزایی، ا.، و وکیلی، غ.، 1382، پیش­بینی عددی سیستم­های زمستانی روی ایران: مطالعه مقایسه پارامترهای فیزیکی. هشتمین کنفرانس دینامیک شاره­ها، شهریور ماه، دانشگاه تبریز.
  4. امینی ل.، پرهیزکار، د.، و خاکیان، غ. ر. ، 1393، نقش مدل عددی WRF در عددی نمودن پیش­بینی بارش­های سنگین در استان اصفهان با درجه تفکیک 27 و 9 و 3 کیلومتر، دومین کنفرانس ملی مدیریت و مهندسی سیلاب با رویکرد سیلاب­های شهری.
  5. خورشیددوست، ع. م.، مفیدی، ع.، رسولی، ع. ا.، و آزرم، ک.،
  6. 1396، ارزیابی میزان حساسیت مدل RegCM4 به طرحواره‌های پارامترسازی همرفت در مدل‌سازی بارش‌های بهارۀ شمال‌غرب ایران: (مطالعۀ موردی سال 2004) فیزیک زمین و فضا، (3) 43، 671-651.
  7. صفر، م.، و احمدی گیوی، ف.، 1396، گزینش طرحوارۀ همرفت بهینه برمبنای داده‌‌‌های رادار در حین اجـــرای مدل WRF برای پیش‌‌‌بینی کوتاه‌مدت بارش: فیزیک زمین و فضا، (3) 43، 585-600.
  8. کریم­خانی، م.، جمشیدی خزلی، ت.، آزادی، م.، و فتاحی، ا.، 1396، تاثیر تفکیک افقی بر دقت پیش­بینی بارش با استفاده
  9. از مدل WRF منطقه مورد مطالعه: حوضه­های آبریــز کرخه و کارون، فصلنامه علمی پژوهشی اکوبیولوژی تالاب، سال نهم، شماره 34، 74-55.
  10. گودرزی، ل.، بنی حبیب، م. ا.، و غفاریان، پ.، 1397، ارزیابی عملکرد مدل WRF در شبیه­سازی بارش­های سنگین (مطالعه
  11. موردی: حوضه آبریز رودخانه کن)، نشریه پژوهش­های حفاظت آب و خاک، (1) 25.
  12. Aligo, E., Gallus Jr., W., and Segal, M., 2009, On the impact of WRF model vertical grid resolution on Midwest summer rainfall forecasts: Weather and Forecasting, 24, 575–594.
  13. Chen, S. H., and Sun, W. Y., 2002, A one-dimensional time dependent cloud model: Meteorological Society of Japan, 80 (1), 99-118.
  14. Chu, Q., Xu, Z., Chen, Y., and Han, D., 2018, Evaluation of the ability of the Weather Research and Forecasting model to reproduce a sub-daily extreme rainfall event in Beijing, China using different domain configurations and spin-up times: Hydrol. Earth Syst. Sci., 22, 3391–3407.
  15. Dudhia, J., 1989, Numerical study of convection
  16. observed during the Winter Monsoon Experiment using a mesoscale two–dimensional model: Journal of the Atmospheric Sciences, 46, 3077-3107.
  17. Hamill, T. M., Whitaker, J. S., and Mullen, S. L., 2006, Reforecasts: An important dataset for improving weather predict ions. Bull. Amer. Meteor. Soc., 87, 33-46. 
  18. Iga, S., Tornita, H., Satoh, M., and Goto, K., 2007, Mountain-wave-like spurious waves associated with simulated cold fronts due to inconsistencies between horizontal and vertical resolutions: Monthly Weather Review, 135, 2629-2641.
  19. Janjic, Z. , 1994, The Step–Mountain Eta Coordinate Model: Further developments of the convection, viscous sublayer, and turbulence closure schemes: Monthly Weather Review, 122, 927–945.  
  20. Janjic, Z. I., 2002, Nonsingular implementation of the Mellor-Yamada Level 2.5 Scheme in the NCEP Meso model: NCEP Office Note No. 437, 61 pp.
  21. Kain, John S., 2004, The Kain–Fritsch convective parameterization, An update: Applied Meteorology and Climatology, 43, 170–181.

 

  1. Konor, C. S., and Randall, D. A., 2018: Impacts of the horizontal and vertical grids on the numerical solutions of the dynamical equations – Part 2: Quasi-geostrophic Rossby modes: Geoscientific Model Development, 11, 1785-1797.
  2. Lindzen, R. S., and Fox-Rabinovitz, M., 1989, Consistent vertical and horizontal resolution: Monthly Weather Review, 117, 2575–2583.
  3. Martius, O., Schwierz, C., and Davies, H. C., 2006, A refined Hovmoller diaram: Tellus, 58, 221-226.
  4. Mlawer, Eli. J., Taubman, Steven. J., Brown, Patrick. D., Iacono, M. J., and Clough, S. A., 1997, Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated–k model for the longwave: Geophysical Research, 102, 16663–16682.
  5. A. H., 1993, What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting: Weather and Forecasting, 8, 281-293.Pecnick, M. J., and Keyser, D., 1989, The effect
  6. of spatial resolution on the simulation of upper-tropospheric frontogenesis using a sigma-coordinate
  7. Primitive-equation model: Meteorology and Atmospheric Physics, 40,137–149.
  8. Persson, P. O. G., and Warner, T. T., 1991, Model generation of spurious gravity waves due to the inconsistency of the vertical and horizontal resolution: Monthly Weather Review, 119, 917–935.
  9. Shin, H. H., Ming, Y., Zhao, M., Chen, X., Lin, S., 2019, Improved Surface Layer Simulation Using Refined Vertical Resolution in the GFDL Atmospheric General Circulation Model: Journal of Advances in Modeling Earth Systems, 11 (1), 905-917.
  10. Snyder, C., Skamarock, W. C., and Rotunno, W. C., 1993, Frontal dynamics near and following frontal collapse: Atmospheric Sciences, 50, 3194-3211.
  11. Stein, U., and Alpert, P., 1993, Factor separation in numerical simulations: Journal of the Atmospheric Sciences, 50, 2107-2115.
  12. Warner, T. T., 2011, Numerical Weather and Climate Prediction: Cambridge University Press, Cambridge, UK. ISBN: 978-0-521-51389-0. Hardback, 526 PP.
  13. Wu, Z., Jiang, C., Deng, B. et al., 2019, Sensitivity of WRF simulated typhoon track and intensity over the South China Sea to horizontal and vertical resolutions: Acta Oceanologica Sinica, 38, 74–83.

 

 

Nivar
Volume 45, 114-115 - Serial Number 114
September 2021
Pages 29-43

  • Receive Date 08 August 2021
  • Revise Date 10 October 2021
  • Accept Date 10 November 2021
  • Publish Date 23 September 2021