Editorial Type:
Article
Article Type:
Research Article

The Impacts of Grid Spacing and Station Network on Surface Analyses and Forecasts in Beijing Winter Olympic Complex Terrain

Linye Song aInstitute of Urban Meteorology, China Meteorological Administration, Beijing, China
bBeijing Urban Meteorological Engineering Research Center, Beijing, China

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https://orcid.org/0000-0003-2166-9195
,
Lu Yang aInstitute of Urban Meteorology, China Meteorological Administration, Beijing, China
bBeijing Urban Meteorological Engineering Research Center, Beijing, China

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Conglan Cheng aInstitute of Urban Meteorology, China Meteorological Administration, Beijing, China
bBeijing Urban Meteorological Engineering Research Center, Beijing, China

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Aru Hasi cCenter for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
dCollege of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China

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Mingxuan Chen aInstitute of Urban Meteorology, China Meteorological Administration, Beijing, China

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Online Publication:
22 Nov 2023
Print Publication:
01 Dec 2023
Collections:
Mountain Terrain Atmospheric Modeling and Observations (MATERHORN)
DOI:
https://doi.org/10.1175/JAMC-D-22-0187.1
Page(s):
1761–1781
Restricted access

Abstract

This study investigates the impacts of grid spacing and station network on surface analyses and forecasts including temperature, humidity, and winds in Beijing Winter Olympic complex terrain. The high-resolution analyses are generated by a rapid-refresh integrated system that includes a topographic downscaling procedure. Results show that surface analyses are more accurate with a higher targeted grid spacing. In particular, the average analysis errors of surface temperature, humidity, and winds are all significantly reduced when the grid size is increased. This improvement is mainly attributed to a more realistic simulation of the topographic effects in the integrated system because the topographic downscaling at higher grid spacing can add more details in a complex mountain region. From 1 km to 100 m, 1–12-h forecasts of temperature and humidity are also largely improved, while the wind only shows a slight improvement for 1–6-h forecasts. The influence of station network on the surface analyses is further examined. Results show that the spatial distributions of temperature and humidity at a 100-m space scale are more realistic and accurate when adding an intensive automatic weather station network, as more observational information can be absorbed. The adding of a station network can also reduce forecast errors, which can last for about 6 h. However, although surface winds display better analysis skill when more stations are added, the wind at the mountaintop region sometimes encounters a marginally worse effect for both analysis and forecast. The results are helpful to improve the analysis and forecast products in complex terrain and have some implications for downscaling from a coarse grid size to a finer grid.

This article is included in the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Special Collection.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Lu Yang, lyang@ium.cn

Abstract

This study investigates the impacts of grid spacing and station network on surface analyses and forecasts including temperature, humidity, and winds in Beijing Winter Olympic complex terrain. The high-resolution analyses are generated by a rapid-refresh integrated system that includes a topographic downscaling procedure. Results show that surface analyses are more accurate with a higher targeted grid spacing. In particular, the average analysis errors of surface temperature, humidity, and winds are all significantly reduced when the grid size is increased. This improvement is mainly attributed to a more realistic simulation of the topographic effects in the integrated system because the topographic downscaling at higher grid spacing can add more details in a complex mountain region. From 1 km to 100 m, 1–12-h forecasts of temperature and humidity are also largely improved, while the wind only shows a slight improvement for 1–6-h forecasts. The influence of station network on the surface analyses is further examined. Results show that the spatial distributions of temperature and humidity at a 100-m space scale are more realistic and accurate when adding an intensive automatic weather station network, as more observational information can be absorbed. The adding of a station network can also reduce forecast errors, which can last for about 6 h. However, although surface winds display better analysis skill when more stations are added, the wind at the mountaintop region sometimes encounters a marginally worse effect for both analysis and forecast. The results are helpful to improve the analysis and forecast products in complex terrain and have some implications for downscaling from a coarse grid size to a finer grid.

This article is included in the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Special Collection.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Lu Yang, lyang@ium.cn
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  • Chen, K., L. Song, L. Yang, M. Chen, M. Chen, L. Han, and W. Cao, 2020: Research and application of a three-dimensional interpolation method for high-resolution temperature in complex terrain based on Gaussian fuzzy (in Chinese). Plateau Meteor., 39, 367–377, https://doi.org/10.7522/j.issn.1000-0534.2019.00108.

    • Search Google Scholar
    • Export Citation

  • Chen, M., and Coauthors, 2018: Enhanced weather research and forecasting in support of the Beijing 2022 Winter Olympic and Paralympic Games. WMO Bull., 67, 58–61.

    • Search Google Scholar
    • Export Citation

  • Cheng, C., M. Chen, M. Chen, F. Gao, L. Song, R. Qin, L. Yang, and Y. Wang, 2019: Comparative experiments on two high spatiotemporal resolution blending algorithms for quantitative precipitation nowcasting (in Chinese). Acta Meteor. Sin., 77, 701–714, https://doi.org/10.11676/qxxb2019.017.

    • Search Google Scholar
    • Export Citation

  • Cheng, C., M. X. Chen, J. J. Wang, F. Gao, and H. X. Yang, 2013: Short-term quantitative precipitation forecast experiments based on blending of nowcasting with numerical weather prediction (in Chinese). Acta Meteor. Sin., 71, 397–415, https://doi.org/10.11676/qxxb2013.041.

    • Search Google Scholar
    • Export Citation

  • Chumchean, S., A. Sharma, and A. Seed, 2006: An integrated approach to error correction for real-time radar-rainfall estimation. J. Atmos. Oceanic Technol., 23, 67–79, https://doi.org/10.1175/JTECH1832.1.

    • Search Google Scholar
    • Export Citation

  • Fan, S., H. Wang, M. Chen, and H. Gao, 2013: Study of the data assimilation of radar reflectivity with the WRF 3D-Var (in Chinese). Acta Meteor. Sin., 71, 527–537, https://doi.org/10.11676/qxxb2013.032.

    • Search Google Scholar
    • Export Citation

  • Farr, T. G., and Coauthors, 2007: The Shuttle Radar Topography Mission. Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005RG000183.

    • Search Google Scholar
    • Export Citation

  • Golding, B. W., 1998: Nimrod: A system for generating automated very short range forecasts. Meteor. Appl., 5, 1–16, https://doi.org/10.1017/S1350482798000577.

    • Search Google Scholar
    • Export Citation

  • Hagedorn, R., T. M. Hamill, and J. S. Whitaker, 2008: Probabilistic forecast calibration using ECMWF and GFS ensemble reforecasts. Part I: Two-meter temperatures. Mon. Wea. Rev., 136, 2608–2619, https://doi.org/10.1175/2007MWR2410.1.

    • Search Google Scholar
    • Export Citation

  • Haiden, T., A. Kann, G. Pistotnik, K. Stadlbacher, and C. Wittmann, 2009: Integrated Nowcasting through Comprehensive Analysis (INCA)—System description. ZAMG Rep. 60 pp., http://www.zamg.ac.at/fix/INCA_system.pdf.

  • Haiden, T., A. Kann, C. Wittmann, G. Pistotnik, B. Bica, and C. Gruber, 2011: The Integrated Nowcasting through Comprehensive Analysis (INCA) system and its validation over the eastern Alpine region. Wea. Forecasting, 26, 166–183, https://doi.org/10.1175/2010WAF2222451.1.

    • Search Google Scholar
    • Export Citation

  • Haiden, T., A. Kann, and G. Pistotnik, 2014: Nowcasting with INCA during SNOW-V10. Pure Appl. Geophys., 171, 231–242, https://doi.org/10.1007/s00024-012-0547-8.

    • Search Google Scholar
    • Export Citation

  • Hamill, T. M., J. S. Whitaker, and S. L. Mullen, 2006: Reforecasts: An important dataset for improving weather predictions. Bull. Amer. Meteor. Soc., 87, 33–46, https://doi.org/10.1175/BAMS-87-1-33.

    • Search Google Scholar
    • Export Citation

  • Han, S., and Coauthors, 2017: The simulation and evaluation of soil moisture based on CLDAS (in Chinese). J. Appl. Meteor. Sci., 28, 369–378, https://doi.org/10.11898/1001-7313.20170310.

    • Search Google Scholar
    • Export Citation

  • Kann, A., C. Wittmann, B. Bica, and C. Wastl, 2015: On the impact of NWP model background on very high–resolution analyses in complex terrain. Wea. Forecasting, 30, 1077–1089, https://doi.org/10.1175/WAF-D-15-0001.1.

    • Search Google Scholar
    • Export Citation

  • Kuligowski, R. J., Y. Li, and Y. Zhang, 2013: Impact of TRMM data on a low-latency, high-resolution precipitation algorithm for flash-flood forecasting. J. Appl. Meteor. Climatol., 52, 1379–1393, https://doi.org/10.1175/JAMC-D-12-0107.1.

    • Search Google Scholar
    • Export Citation

  • Li, C., T. Zhao, C. Shi, and Z. Liu, 2020: Evaluation of daily precipitation product in China from the CMA Global Atmospheric Interim Reanalysis. J. Meteor. Res., 34, 117–136, https://doi.org/10.1007/s13351-020-8196-9.

    • Search Google Scholar
    • Export Citation

  • Liu, W., H. You, G. Ren, P. Yang, and B. Zhang, 2014: AWS precipitation characteristics based on k-means clustering method in Beijing area (in Chinese). Meteor. Mon., 10, 844–851.

    • Search Google Scholar
    • Export Citation

  • Liu, Y., Y. Liu, D. Muñoz-Esparza, F. Hu, C. Yan, and S. Miao, 2020: Simulation of flow fields in complex terrain with WRF-LES: Sensitivity assessment of different PBL treatments. J. Appl. Meteor. Climatol., 59, 1481–1501, https://doi.org/10.1175/JAMC-D-19-0304.1.

    • Search Google Scholar
    • Export Citation

  • Lu, B., J. Zhong, W. Wang, S. Tang, and Z. Zheng, 2021: Influence of near real-time green vegetation fraction data on numerical weather prediction by WRF over North China. J. Meteor. Res., 35, 505–520, https://doi.org/10.1007/s13351-021-0163-6.

    • Search Google Scholar
    • Export Citation

  • Overeem, A., I. Holleman, and A. Buishand, 2009: Derivation of a 10-year radar-based climatology of rainfall. J. Appl. Meteor. Climatol., 48, 1448–1463, https://doi.org/10.1175/2009JAMC1954.1.

    • Search Google Scholar
    • Export Citation

  • Pan, Y., J. Gu, J. Yu, Y. Shen, C. Shi, and Z. Zhou, 2018: Test of merging methods for multi-source observed precipitation products at high resolution over China (in Chinese). Acta Meteor. Sin., 76, 755–766, https://doi.org/10.11676/qxxb2018.034.

    • Search Google Scholar
    • Export Citation

  • Pielke, R. A., Sr., 2001: Further comments on “The differentiation between grid spacing and resolution and their application to numerical modeling.” Bull. Amer. Meteor. Soc., 82, 699–700, https://doi.org/10.1175/1520-0477(2001)082<0699:FCOTDB>2.3.CO;2.

    • Search Google Scholar
    • Export Citation

  • Shi, C., and Coauthors, 2019: A review of multi-source meteorological data fusion products (in Chinese). Acta Meteor. Sin., 77, 774–783, https://doi.org/10.11676/qxxb2019.043.

    • Search Google Scholar
    • Export Citation

  • Shuai, S. U. N., C. Shi, X. Liang, S. Han, Z. Jiang, and T. Zhang, 2017: Assessment of ground temperature simulation in China by different land surface models based on station observations (in Chinese). J. Appl. Meteor. Sci., 28, 737–749, https://doi.org/10.11898/1001-7313.20170609.

    • Search Google Scholar
    • Export Citation

  • Song, L., M. Chen, F. Gao, C. Cheng, M. Chen, L. Yang, and Y. Wang, 2019: Elevation influence on rainfall and a parameterization algorithm in the Beijing area. J. Meteor. Res., 33, 1143–1156, https://doi.org/10.1007/s13351-019-9072-3.

    • Search Google Scholar
    • Export Citation

  • Song, L., I. Schicker, P. Papazek, A. Kann, B. Bica, Y. Wang, and M. Chen, 2020: Machine learning approach to summer precipitation nowcasting over the eastern Alps. Meteor. Z., 29, 289–305, https://doi.org/10.1127/metz/2019/0977.

    • Search Google Scholar
    • Export Citation

  • Steppeler, J., H.-W. Bitzer, M. Minotte, and L. Bonaventura, 2002: Nonhydrostatic atmospheric modeling using a z-coordinate representation. Mon. Wea. Rev., 130, 2143–2149, https://doi.org/10.1175/1520-0493(2002)130<2143:NAMUAZ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and Coauthors, 2014: Use of NWP for nowcasting convective precipitation: Recent progress and challenges. Bull. Amer. Meteor. Soc., 95, 409–426, https://doi.org/10.1175/BAMS-D-11-00263.1.

    • Search Google Scholar
    • Export Citation

  • Teakles, A., R. Mo, C. F. Dierking, C. Emond, T. Smith, N. McLennan, and P. I. Joe, 2014: Realizing user-relevant conceptual model for the ski jump venue of the Vancouver 2010 Winter Olympics. Pure Appl. Geophys., 171, 185–207, https://doi.org/10.1007/s00024-012-0544-y.

    • Search Google Scholar
    • Export Citation

  • Virmavirta, M., and J. Kivekäs, 2012: The effect of wind on jumping distance in ski jumping—Fairness assessed. Sports Biomech., 11, 358–369, https://doi.org/10.1080/14763141.2011.637119.

    • Search Google Scholar
    • Export Citation

  • Wang, Y., and Coauthors, 2017: Integrating nowcasting with crisis management and risk prevention in a transnational and interdisciplinary framework. Meteor. Z., 26, 459–473, https://doi.org/10.1127/metz/2017/0843.

    • Search Google Scholar
    • Export Citation

  • Wilson, J. W., Y. Feng, M. Chen, and R. D. Roberts, 2010: Nowcasting challenges during the Beijing Olympics: Successes, failures, and implications for future nowcasting systems. Wea. Forecasting, 25, 1691–1714, https://doi.org/10.1175/2010WAF2222417.1.

    • Search Google Scholar
    • Export Citation

  • Wong, W. K., and E. S. T. Lai, 2006: RAPIDS—Operational blending of Nowcast and NWP QPF. Second Int. Symp. on Quantitative Precipitation Forecasting and Hydrology, Boulder, CO, WMO–NCAR, https://docplayer.net/15225483-Rapids-operational-blending-of-nowcasting-and-nwp-qpf.html.

  • Xie, X. H., Y. Wang, and Q. Guo, 2018: Introduction to the INCA nowcasting system with complex terrain adaptability (in Chinese). Adv. Meteor. Sci. Technol., 8, 70–76.

    • Search Google Scholar
    • Export Citation

  • Yang, L., M. Chen, X. Wang, L. Song, M. Yang, R. Qin, C. Cheng, and S. Li, 2021: Classification of precipitation type in North China using model-based explicit fields of hydrometeors with modified thermodynamic conditions. Wea. Forecasting, 36, 91–107, https://doi.org/10.1175/WAF-D-20-0005.1.

    • Search Google Scholar
    • Export Citation

  • Yang, L., L. Song, H. Jing, M. Chen, W. Cao, and J. Wu, 2022: Fusion prediction and correction technique for high-resolution wind field in Winter Olympic Games area under complex terrain (in Chinese). Meteor. Mon., 48, 162–176, https://doi.org/10.7519/j.issn.1000-0526.2021.092902.

    • Search Google Scholar
    • Export Citation

  • Zang, Z. G., W. Guo, and X. T. Bai, 2017: Winter ground wind field characteristic in the Haituo Mountain Division for the 24th Winter Olympic Games (in Chinese). J. Arid Meteor., 35, 433–438, https://doi.org/10.11755/j.issn.1006-7639(2017)-03-0433.

    • Search Google Scholar
    • Export Citation

  • Zhong, J.-Q., B. Lu, W. Wang, C.-C. Huang, and Y. Yang, 2020: Impact of soil moisture on winter 2-m temperature forecasts in northern China. J. Hydrometeor., 21, 597–614, https://doi.org/10.1175/JHM-D-19-0060.1.

    • Search Google Scholar
    • Export Citation
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