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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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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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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