Extreme Rainfall Simulations with Changing Resolution of Orography Based on the Yin-He Global Spectrum Model: A Case Study of the Zhengzhou 20·7 Extreme Rainfall Event
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Overview of the Study Area
3.1.1. Circulation Background
3.1.2. Orographic Features
3.2. Rainfall Analysis
3.3. Sensitivity of the Rainfall to the Orographic Resolution
3.4. Analysis of Element Fields Related to Orography and Rainfall
4. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Roe, G.H. Orographic precipitation. Annu. Rev. Earth Planet. Sci. 2005, 33, 645–671. [Google Scholar] [CrossRef]
- Chao, W.C. Correction of Excessive Precipitation over Steep and High Mountains in a GCM. J. Atmos. Sci. 2012, 69, 1547–1561. [Google Scholar] [CrossRef]
- Alpert, P.; Jin, F.; Shafir, H. Orographic Precipitation Simulated by a Super-High Resolution Global Climate Model over the Middle East. NATO Sci. Peace Secur. Ser. C Environ. Secur. 2012, 125, 301–306. [Google Scholar] [CrossRef]
- Kunz, M.; Kottmeier, C. Orographic Enhancement of Precipitation over Low Mountain Ranges. Part I: Model Formulation and Idealized Simulations. J. Appl. Meteorol. Climatol. 2006, 45, 1025–1040. [Google Scholar] [CrossRef]
- Colle, B.A.; Mass, C.F.; Westrick, K.J. MM5 Precipitation Verification over the Pacific Northwest during the 1997–99 Cool Seasons. Weather Forecast. 2000, 15, 730–744. [Google Scholar] [CrossRef]
- Moya-Álvarez, A.S.; Martínez-Castro, D.; Kumar, S.; Estevan, R.; Silva, Y. Response of the WRF model to different resolutions in the rainfall forecast over the complex Peruvian orography. Theor. Appl. Climatol. 2019, 137, 2993–3007. [Google Scholar] [CrossRef]
- Yáñez-Morroni, G.; Gironás, J.; Caneo, M.; Delgado, R.; Garreaud, R. Using the Weather Research and Forecasting (WRF) Model for Precipitation Forecasting in an Andean Region with Complex Topography. Atmosphere 2018, 9, 304. [Google Scholar] [CrossRef] [Green Version]
- Stohl, A.; Forster, C.; Sodemann, H. Remote sources of water vapor forming precipitation on the Norwegian west coast at 60° N-a tale of hurricanes and an atmospheric river. J. Geophys. Res. Atmos. 2008, 113, D05102. [Google Scholar] [CrossRef] [Green Version]
- Xia, Z.; Hui, Y.; Xinmin, W.; Lin, S.; Di, W.; Han, L. Analysis on characteristic and abnormality of atmospheric circulations of the July 2021 extreme precipitation in Henan. Trans. Atmos. Sci. 2021, 44, 672–687. [Google Scholar] [CrossRef]
- Wenru, S.; Xin, L.; Mingjian, Z.; Bing, Z.; Hongbin, W.; Kefeng, Z.; Xiaoyong, Z. Multi-model comparison and high-resolution regional model forecast analysis for the “7·20” Zhengzhou Severe Heavy Rain. Trans. Atmos. Sci. 2021, 44, 688–702. [Google Scholar] [CrossRef]
- Aifang, S.; Xiaona, L.; Liman, C.; Zhou, L.; Le, X.; Han, L. The basic observational analysis of “7.20” extreme rainstorm in Zhengzhou. Torrential Rain Disasters 2021, 40, 445–454. [Google Scholar]
- Sethunadh, J.; Jayakumar, A.; Mohandas, S.; Rajagopal, E.; Nagulu, A. Impact of Cartosat-1 orography on weather prediction in a high-resolution NCMRWF unified model. J. Earth Syst. Sci. 2019, 128, 110. [Google Scholar] [CrossRef] [Green Version]
- Caccamo, M.T.; Castorina, G.; Colombo, F.; Insinga, V.; Maiorana, E.; Magazù, S. Weather forecast performances for complex orographic areas: Impact of different grid resolutions and of geographic data on heavy rainfall event simulations in Sicily. Atmos. Res. 2017, 198, 22–33. [Google Scholar] [CrossRef]
- Nunalee, C.G.; Horváth, Á. High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data. Geosci. Model Dev. 2015, 8, 2973–2990. [Google Scholar] [CrossRef] [Green Version]
- Dimri, A.P. Impact of horizontal model resolution and orography on the simulation of a western disturbance and its associated precipitation. Meteorol. Appl. 2004, 11, 115–127. [Google Scholar] [CrossRef]
- Torma, C.; Giorgi, F. On the evidence of orographical modulation of regional fine scale precipitation change signals: The Carpathians. Atmos. Sci. Lett. 2020, 21, e967. [Google Scholar] [CrossRef] [Green Version]
- Webster, S.; Brown, A.R.; Cameron, D.R.; Jones, C.P. Improvements to the representation of orography in the Met Office Unified Model. Q. J. R. Meteorol. Soc. 2003, 129, 1989–2010. [Google Scholar] [CrossRef]
- Davini, P.; Fabiano, F.; Sandu, I. Orographic resolution driving the improvements associated with horizontal resolution increase in the Northern Hemisphere winter mid-latitudes. Weather Clim. Dynam. Discuss. 2021, 2021, 1–25. [Google Scholar] [CrossRef]
- Peng, J.; Wu, J.; Zhang, W.; Zhao, J.; Zhang, L.; Yang, J. A modified nonhydrostatic moist global spectral dynamical core using a dry-mass vertical coordinate. Q. J. R. Meteorol. Soc. 2019, 145, 2477–2490. [Google Scholar] [CrossRef]
- Yin, F.; Wu, G.; Wu, J.; Zhao, J.; Song, J. Performance Evaluation of the Fast Spherical Harmonic Transform Algorithm in the Yin–He Global Spectral Model. J. Mon. Weather Rev. 2018, 146, 3163–3182. [Google Scholar] [CrossRef]
- Jiang, T.; Guo, P.; Wu, J. One-sided on-demand communication technology for the semi-Lagrange scheme in the YHGSM. Concurr. Comput. Pract. Exp. 2020, 32, e5586. [Google Scholar] [CrossRef]
- Peng, J.; Zhao, J.; Zhang, W.; Zhang, L.; Wu, J.; Yang, X. Towards a dry-mass conserving hydrostatic global spectral dynamical core in a general moist atmosphere. Q. J. R. Meteorol. Soc. 2020, 146, 3206–3224. [Google Scholar] [CrossRef]
- Yang, J.; Song, J.; Wu, J.; Ying, F.; Peng, J.; Leng, H. A semi-implicit deep-atmosphere spectral dynamical kernel using a hydrostatic-pressure coordinate. Q. J. R. Meteorol. Soc. 2017, 143, 2703–2713. [Google Scholar] [CrossRef]
- Yang, J.; Song, J.; Wu, J.; Ren, K.; Leng, H. A high-order vertical discretization method for a semi-implicit mass-based non-hydrostatic kernel. Q. J. R. Meteorol. Soc. 2015, 141, 2880–2885. [Google Scholar] [CrossRef]
- Jianping, W.; Jun, Z.; Junqiang, S.; Weiming, Z. Preliminary design of dynamic framework for global non-hydrostatic spectral mode. Comput. Eng. Des. 2011, 32, 3539–3543. [Google Scholar] [CrossRef]
- Chenghai, W.; Xiao, L.; Yi, Y. Atmospheric Numerical Model and Simulation; China Meteorological Press: Beijing, China, 2011; pp. 109–110. [Google Scholar]
- Kirshbaum, D.J.; Adler, B.; Kalthoff, N.; Barthlott, C.; Serafin, S. Moist Orographic Convection: Physical Mechanisms and Links to Surface-Exchange Processes. Atmosphere 2018, 9, 80. [Google Scholar] [CrossRef] [Green Version]
- Khodayar, S.; Kalthoff, N.; Kottmeier, C. Atmospheric conditions associated with heavy precipitation events in comparison to seasonal means in the western mediterranean region. Clim. Dyn. 2018, 51, 951–967. [Google Scholar] [CrossRef]
- Kirthiga, S.M.; Patel, N.R. Impact of updating land surface data on micrometeorological weather simulations from the WRF model. Atmosfera 2018, 31, 165–183. [Google Scholar] [CrossRef] [Green Version]
- Moya-Álvarez, A.S.; Gálvez, J.; Holguín, A.; Estevan, R.; Kumar, S.; Villalobos, E.; Martínez-Castro, D.; Silva, Y. Extreme Rainfall Forecast with the WRF-ARW Model in the Central Andes of Peru. Atmosphere 2018, 9, 362. [Google Scholar] [CrossRef] [Green Version]
- Chawla, I.; Osuri, K.K.; Mujumdar, P.P.; Niyogi, D. Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin. Hydrol. Earth Syst. Sci. 2018, 22, 1095–1117. [Google Scholar] [CrossRef] [Green Version]
- Shrestha, R.; Connolly, P.; Gallagher, M. Sensitivity of WRF Cloud Microphysics to Simulations of a Convective Storm over the Nepal Himalayas. Open Atmos. Sci. J. 2017, 11, 29–43. [Google Scholar] [CrossRef] [Green Version]
- Orr, A.; Listowski, C.; Couttet, M.; Collier, E.; Immerzeel, W.; Deb, P.; Bannister, D. Sensitivity of simulated summer monsoonal precipitation in Langtang Valley, Himalaya, to cloud microphysics schemes in WRF. J. Geophys. Res. Atmos. 2017, 122, 6298–6318. [Google Scholar] [CrossRef] [Green Version]
- Rama Rao, Y.V.; Alves, L.; Seulall, B.; Mitchell, Z.; Samaroo, K.; Cummings, G. Evaluation of the weather research and forecasting (WRF) model over Guyana. Nat. Hazards 2012, 61, 1243–1261. [Google Scholar] [CrossRef]
Experiment Name | Truncated Wave Number | Horizontal Resolution |
---|---|---|
T1279 orography | 1279 | ~16 km |
T799 orography | 799 | ~25 km |
T639 orography | 639 | ~31 km |
T511 orography | 511 | ~40 km |
Start Time | Time Range | Interval | |
---|---|---|---|
Experiment 1 | 0000 UTC 18 July 2021 | 0000 UTC 19 July 2021–0000 UTC 19 July 2021 | 24 h |
Experiment 2 | 1200 UTC 18 July 2021 | 1200 UTC 19 July 2021–1200 UTC 20 July 2021 | 24 h |
Rainfall Level | 24 h Total Rainfall (mm) |
---|---|
Light rain | 0.1–9.9 |
Moderate rain | 10.0–24.9 |
Big rain | 25.0–49.9 |
Heavy rain | 50.0–99.9 |
Big heavy rain | 100.0–249.9 |
Extraordinarily heavy rain | ≥250.0 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wang, Y.; Wu, J.; Peng, J.; Yang, X.; Liu, D. Extreme Rainfall Simulations with Changing Resolution of Orography Based on the Yin-He Global Spectrum Model: A Case Study of the Zhengzhou 20·7 Extreme Rainfall Event. Atmosphere 2022, 13, 600. https://doi.org/10.3390/atmos13040600
Wang Y, Wu J, Peng J, Yang X, Liu D. Extreme Rainfall Simulations with Changing Resolution of Orography Based on the Yin-He Global Spectrum Model: A Case Study of the Zhengzhou 20·7 Extreme Rainfall Event. Atmosphere. 2022; 13(4):600. https://doi.org/10.3390/atmos13040600
Chicago/Turabian StyleWang, Yingjie, Jianping Wu, Jun Peng, Xiangrong Yang, and Dazheng Liu. 2022. "Extreme Rainfall Simulations with Changing Resolution of Orography Based on the Yin-He Global Spectrum Model: A Case Study of the Zhengzhou 20·7 Extreme Rainfall Event" Atmosphere 13, no. 4: 600. https://doi.org/10.3390/atmos13040600
APA StyleWang, Y., Wu, J., Peng, J., Yang, X., & Liu, D. (2022). Extreme Rainfall Simulations with Changing Resolution of Orography Based on the Yin-He Global Spectrum Model: A Case Study of the Zhengzhou 20·7 Extreme Rainfall Event. Atmosphere, 13(4), 600. https://doi.org/10.3390/atmos13040600