Abstract
A WRF (Weather Research and Forecasting Model)/CALMET (California Meteorological Model) coupled system is used to investigate the impact of physical representations in CALMETon simulations of the near-surface wind field of Super Typhoon Meranti (2016). The coupled system is configured with a horizontal grid spacing of 3 km in WRF and 500 m in CALMET, respectively. The model performance of the coupled WRF/ CALMET system is evaluated by comparing the results of simulations with observational data from 981 automatic surface stations in Fujian Province. The root mean square error (RMSE) of the wind speed at 10 m in all CALMET simulations is significantly less than the WRF simulation by 20%–30%, suggesting that the coupled WRF/CALMET system is capable of representing more realistic simulated wind speed than the mesoscale model only. The impacts of three physical representations including blocking effects, kinematic effects of terrain and slope flows in CALMET are examined in a specified local region called Shishe Mountain. The results show that before the typhoon landfall in Xiamen, a net downslope flow that is tangent to the terrain is generated in the west of Shishe Mountain due to blocking effects with magnitude exceeding 10 m/s. However, the blocking effects seem to take no effect in the strong wind area after typhoon landfall. Whether being affected by the typhoon strong wind or not, the slope flows move downslope at night and upslope in the daytime due to the diurnal variability of the local heat flux with magnitude smaller than 3 m/s. The kinematic effects of terrain, which are speculated to play a significant role in the typhoon strong wind area, can only be applied to atmospheric flows in stable conditions when the wind field is quasi-nondivergent.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Al-Yahyai S, Charabi Y, Gastli A (2010). Review of the use of Numerical Weather Prediction (NWP) models for wind energy assessment. Renew Sustain Energy Rev, 14(9): 3192–3198
Allwine K J, Whiteman C D (1985). MELSAR: A mesoscale air quality model for complex terrain. Volume 1—Overview, technical description and user’s guide. Pacific Northwest Laboratory: Richland, Washington
Arakawa A, Jung J H, Wu C M (2011). Toward unification of the multiscale modeling of the atmosphere. Atmos Chem Phys, 11(8): 3731–3742
Black T L (1994). The new NMC mesoscale Eta model: description and forecast examples. Weather Forecast, 9(2): 265–278
Chen F, Dudhia J (2001). Coupling an advanced land surface hydrology model with the Penn State-NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev, 129(4): 569–585
GB/T 35237–2017. Specifications for Surface Meteorological Observation-automatic Observatrion. Beijing: China Standards Press, 2017 (in Chinese)
Gioli B, Gualtieri G, Busillo C, Calastrini F, Gozzini B, Miglietta F (2014). Aircraft wind measurements to assess a coupled WRFCALMET mesoscale system. Meteorol Appl, 21(1): 117–128
González J A, Hernández-Garcés A, Rodriguez A, Saavedra S, Casares J J (2015). Surface and upper-air WRF-CALMET simulations assessment over a coastal and complex terrain area. Int J Environ Pollut, 57(3–4): 249–260
Goodin W R, Mcrae G J, Seinfeld J H (1980). An objective analysis technique for constructing three-dimensional urban-scale wind fields. J Appl Meteorol, 19(1): 98–108
Grell G A, Dudhia J, Stauffer D R (1995). A description of the fifth generation Penn State/NCAR mesoscale model (MM5). Tech Note NCAR/TN-398 + STR. NCAR: Boulder, CO
Holtslag A A M, Van Ulden A P (1983). A Simple scheme for daytime estimates of the surface fluxes from routine weather data. J Appl Meteorol, 22(4): 517–529
Horst T W, Doran J C (1986). Nocturnal drainage flow on simple slopes. Boundary-Layer Meteorol, 34(3): 263–286
Iacono M J, Delamere J S, Mlawer E J, Shephard M W, Clough S A, Collins W D (2008). Radiative forcing by long–lived greenhouse gases: calculations with the AER radiative transfer models. J Geophy Res-atmos, 113(D13)
Kain J S (2004). The Kain-Fritsch convective parameterization: an update. J Appl Meteorol, 43(1): 170–181
Lam H, Kok M H, Shum K K Y (2012). Benefits from typhoons–the Hong Kong perspective. Weather, 67(1): 16–21
Lin Y L, Farley R D, Orville H D (1983). Bulk parameterization of the snow field in a cloud model. J Clim Appl Meteorol, 22(6): 1065–1092
Liu M K, Yocke M A (1980). Siting of wind turbine generators in complex terrain. J Energy, 4(1): 10–16
Lu Y X, Tang J P, Wang Y, Song L L (2012). Validation of near-surface winds obtained by a hybrid WRF/CALMET modeling system over a coastal island with complex terrain. J Trop Meteorol, 18(3): 284–296
Ludwig F L, Miller D K, Gallaher S G (2006). Evaluating a hybrid prognostic-diagnostic model that improves wind forecast resolution in complex coastal topography. J Appl Meteorol Climatol, 45(1): 155–177
Mahrt L (1982). Momentum balance of gravity flows. J Atmos Sci, 39 (12): 2701–2711
Mortensen N G, Landberg L (1993). Wind altas analysis and application program (WAsP) user’s guide. Riso National Laboratory: Roskilde, Denmark
Pielke R A, CottonW R, Walko R L, Tremback C J, Lyons W A, Grasso L D, Nicholls M E, Moran M D, Wesley D A, Lee T J, Copeland J H (1992). A comprehensive meteorological modeling system—RAMS. Meteorol Atmos Phys, 49(1–4): 69–91
Scire J S, Robe F R, Fernau M E, Yamartino R J (1998). A user’s guide for the CALMET meteorological model (Version 5). Earth Tech Inc: Concord, MA
Skamarock W C, Klemp J B, Dudhia J, Gill D O, Barker D M, Duda M G, Huang X Y, Wang W, Powers J G (2008). A description of the advanced research WRF version 3. Tech Note NCAR/TN-475 + STR. NCAR: Boulder, CO.
Sukoriansky S, Galperin B, Perov V (2005). Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice. Boundary-Layer Meteorol, 117(2): 231–257
US EPA (2004). User’s Guide for the AERMOD meteorological preprocessor (AERMET). EPA–454/B–03e002. U.S. Environmental Protection Agency: Research Triangle Park, NC
Wang W, Shaw W J, Seiple T E, Rishel J P, Xie Y (2008). An evaluation of a diagnostic wind model (CALMET). J Appl Meteorol Climatol, 47(6): 1739–1756
Wyngaard J C (2004). Toward numerical modeling in the “terra incognita”. J Atmos Sci, 61(14): 1816–1826
Yim S H L, Fung J C H, Lau A K H, Kot S C (2007). Developing a highresolution wind map for a complex terrain with a coupled MM5/CALMET system J Geophy Res-atmos, 112 (D5)
Ying M, Zhang W, Yu H, Lu X Q, Feng J X, Fan Y X, Zhu Y T, Chen D Q (2014). An overview of the China Meteorological Administration tropical cyclone database. J Atmos Ocean Technol, 31(2): 287–301
Zhao Y, Wang Y, Chen J, Huang H (2018). Numerical investigation on detailed structure of typhoon“Meranti”(2016) and extreme heavy rainfall event induced by it before and after landfall in Fujian. Torrential Rain Disa, 37(2): 135–148
Acknowledgements
This research was supported by the National Basic Research Program of China (No. 2015CB452806), the National Natural Science Foundation of China (Nos. 41805088, 41875080), Natural Science Foundation of Shanghai (No. 18ZR1449100), and Fundamental Research Foundation of Shanghai Typhoon Institute of the China Meteorological Administration (Nos. 2018JB05, 2019JB06).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Huang, S., Tang, S., Yu, H. et al. Impact of physical representations in CALMET on the simulated wind field over land during Super Typhoon Meranti (2016). Front. Earth Sci. 13, 744–757 (2019). https://doi.org/10.1007/s11707-019-0769-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11707-019-0769-5