Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation and Improvement of the KMAPP Surface Wind Speed Prediction over Complex Terrain Areas

복잡 지형 지역에서의 KMAPP 지상 풍속 예측 성능 평가와 개선

  • Keum, Wang-Ho (School of Earth and Environmental Sciences, Seoul National University) ;
  • Lee, Sang-Hyun (Department of Atmospheric Science, Kongju National University) ;
  • Lee, Doo-Il (Department of Atmospheric Science, Kongju National University) ;
  • Lee, Sang-Sam (National Institute of Meteorological Sciences) ;
  • Kim, Yeon-Hee (National Institute of Meteorological Sciences)
  • 금왕호 (서울대학교 지구환경과학부) ;
  • 이상현 (공주대학교 자연과학대학 대기과학과) ;
  • 이두일 (공주대학교 자연과학대학 대기과학과) ;
  • 이상삼 (국립기상과학원 미래기반연구부) ;
  • 김연희 (국립기상과학원 미래기반연구부)
  • Received : 2020.12.12
  • Accepted : 2021.03.05
  • Published : 2021.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

The necessity of accurate high-resolution meteorological forecasts becomes increasing in socio-economical applications and disaster risk management. The Korea Meteorological Administration Post-Processing (KMAPP) system has been operated to provide high-resolution meteorological forecasts of 100 m over the South Korea region. This study evaluates and improves the KMAPP performance in simulating wind speeds over complex terrain areas using the ICE-POP 2018 field campaign measurements. The mountainous measurements give a unique opportunity to evaluate the operational wind speed forecasts over the complex terrain area. The one-month wintertime forecasts revealed that the operational Local Data Assimilation and Prediction System (LDAPS) has systematic errors over the complex mountainous area, especially in deep valley areas, due to the orographic smoothing effect. The KMAPP reproduced the orographic height variation over the complex terrain area but failed to reduce the wind speed forecast errors of the LDAPS model. It even showed unreasonable values (~0.1 m s-1) for deep valley sites due to topographic overcorrection. The model's static parameters have been revised and applied to the KMAPP-Wind system, developed newly in this study, to represent the local topographic characteristics better over the region. Besides, sensitivity tests were conducted to investigate the effects of the model's physical correction methods. The KMAPP-Wind system showed better performance in predicting near-surface wind speed during the ICE-POP period than the original KMAPP version, reducing the forecast error by 21.2%. It suggests that a realistic representation of the topographic parameters is a prerequisite for the physical downscaling of near-ground wind speed over complex terrain areas.

Keywords

References

  1. Beljaars, A. C. M., A. R. Brown, and N. Wood, 2004: A new parametrization of turbulent orographic form drag. Q. J. R. Meteorol. Soc., 130, 1327-1347. https://doi.org/10.1256/qj.03.73
  2. Borge, R., V. Alexandrov, J. J. del Vas, J. Lumbreras, and E. Rodriguez, 2008: A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian peninsula. Atmos. Environ., 42, 8560-8574. https://doi.org/10.1016/j.atmosenv.2008.08.032
  3. Chandrasekar, V., M. A. Vega, S. Joshil, M. Kumar, D. Wolff, and W. Petersen, 2018: Deployment and performance of the NASA D3R during the Ice-Pop 2018 field campaign in South Korea. Proc., IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 8349-8351, doi:10.1109/IGARSS.2018.8517313.
  4. Emery, C., E. Tai, and G. Yarwood, 2001: Enhanced meteorological modeling and performance evaluation for two Texas ozone episodes. ENVIRON International Corporation, Final Report, 235 pp.
  5. Grant, A. L. M., and P. J. Mason, 1990: Observations of boundary-layer structure over complex terrain. Q. J. R. Meteorol. Soc., 116, 159-186. https://doi.org/10.1002/qj.49711649107
  6. Howard, T., and P. Clack, 2007: Correction and downscaling of NWP wind speed forecasts. Meteorol. Appl. 14, 105-116. https://doi.org/10.1002/met.12
  7. In, S.-R., H.-G. Nam, J.-H. Lee, C.-G. Park, J.-K. Shim, and B.-J. Kim, 2018: Verification of planetary boundary layer height for Local Data Assimilation and Prediction System (LDAPS) using the winter season intensive observation data during ICE-POP 2018. Atmosphere, 28, 369-382, doi:10.14191/Atmos.2018.28.4.369 (in Korean with English abstract).
  8. Jackson, P. S., and J. C. R. Hunt, 1975: Turbulent wind flow over a low hill. Q. J. R. Meteorol. Soc., 101, 929-955. https://doi.org/10.1002/qj.49710143015
  9. Jung S.-P., C. Lee, J.-H. Kim, H. J. Yang, J. H. Yun, H. J. Ko, S.-E. Hong, and S.-B. Kim, 2020: Thermodynamic characteristics of snowfall clouds using dropsonde data during ICE-POP 2018. Atmosphere, 30, 31-46, doi:10.14191/Atmos.2020.30.1.031 (in Korean with English abstract).
  10. Lee, S.-H., 2011: Further development of the vegetated urban canopy model including a grass-covered surface. Bound.-Layer Meteor., 140, 315-342, doi:10.1007/s10546-011-9603-7.
  11. Lee, S.-H., and S.-U. Park, 2008: A vegetated urban canopy model for meteorological and environmental modelling. Bound.-Layer Meteor., 126, 73-102. https://doi.org/10.1007/s10546-007-9221-6
  12. Lee, S.-H., S.-W. Kim, W. M. Angevine, L. Bianco, S. A. McKeen, C. J. Senff, M. Trainer, S. C. Tucker, and R. J. Zamora, 2011: Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign. Atmos. Chem. Phys., 11, 2127-2143, doi:10.5194/acp-11-2127-2011.
  13. Lott, F., and M. J. Miller, 1997: A new subgrid-scale orographic drag parametrization: Its formulation and testing. Q. J. R. Meteorol. Soc., 123, 101-127. https://doi.org/10.1002/qj.49712353704
  14. Mason, P. J., and J. C. King, 1985: Measurements and predictions of flow and turbulence over an isolated hill of moderate slope. Q. J. R. Meteorol. Soc., 111, 617-640. https://doi.org/10.1002/qj.49711146818
  15. Oh, J.-S., J.-H. Lee, J.-W. Woo, D.-I. Lee, S.-H. Lee, J. Seo, and N. Moon, 2020: Performance evaluation of the high-resolution WRF meteorological simulation over the Seoul metropolitan area. Atmosphere, 30, 257-276, doi:10.14191/Atmos.2020.30.3.257 (in Korean with English abstract).
  16. Palmer, T. N., 2000: Predicting uncertainty in numerical weather forecasts. Int. Geophys., 83, 3-13. https://doi.org/10.1016/S0074-6142(02)80152-8
  17. Pelland, S., G. Galanis, and G. Kallos, 2013: Solar and photovoltaic forecasting through post-processing of the Global Environmental Multiscale numerical weather prediction model. Prog. Photovoltaics: Res. Appl., 21, 284-296, doi:10.1002/pip.1180.
  18. Porson, A., P. A. Clark, I. N. Harman, M. J. Best, and S. E. Belcher, 2010a: Implementation of a new urban energy budget scheme in the MetUM. Part I: Description and idealized simulations. Q. J. R. Meteorol. Soc., 136, 1514-1529, doi:10.1002/qj.668.
  19. Porson, A., P. A. Clark, I. N. Harman, M. J. Best, and S. E. Belcher, 2010b: Implementation of a new urban energy budget scheme into MetUM. Part II: Validation against observations and model intercomparison. Q. J. R. Meteorol. Soc., 136, 1530-1542, doi:10.1002/qj.572.
  20. Seok, J.-H., H.-W. Choi, Y.-H. Kim, and S.-S. Lee, 2020: Diagnosis of low-level aviation turbulence using the Korea Meteorological Administration Post Processing (KMAPP). J. Korean Soc. Aviat. Aeronaut., 28, 1-11, doi:10.12985/ksaa.2020.28.4.001 (in Korean with English abstract).
  21. Sheridan, P., S. Smith, A. Brown, and S. Vosper, 2010: A simple height-based correction for temperature downscaling in complex terrain. Meteor. Appl., 17, 329-339, doi:10.1002/met.177.
  22. Sheridan, P., S. Vosper, and S. Smith, 2018: A physically based algorithm for downscaling temperature in complex terrain. J. Appl. Meteor. Climatol., 57, 1907-1929, doi:10.1175/JAMC-D-17-0140.1.
  23. Yun, J., Y.-H. Kim, and H.-W. Choi, 2021: Analyses of the meteorological characteristics over South Korea for wind power applications using KMAPP. Atmosphere, 31, 1-15 (in Korean with English abstract). https://doi.org/10.14191/ATMOS.2021.31.1.001
  24. Webster, S., A. R. Brown, D. R. Cameron, and C. P. Jones, 2003: Improvements to the representation of orography in the Met Office Unified Model. Q. J. R. Meteorol. Soc., 129, 1989-2010. https://doi.org/10.1256/qj.02.133
  25. Willmott, C. J. 1981: On the validation of models. Phys. Geogr., 2, 184-194. https://doi.org/10.1080/02723646.1981.10642213