高影响天气下3种数值模式总辐射预报效果检验与评估

袁彬; 申彦波; 张金满; 艾力亚尔&#x; 艾海提; 赵增保; 王雪琪

doi:doi:10.19912/j.0254-0096.tynxb.2025-0014

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高影响天气下3种数值模式总辐射预报效果检验与评估

更新时间：2026-07-22

- 高影响天气下3种数值模式总辐射预报效果检验与评估
- Vol. 47, Issue 4, Pages: 11-19(2026)
- 作者机构：
- 作者简介：
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- DOI：doi:10.19912/j.0254-0096.tynxb.2025-0014
  CLC： P45
- Online First：08 May 2026，
  
  Published：2026
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袁彬, 申彦波, 张金满, et al. 高影响天气下3种数值模式总辐射预报效果检验与评估[J]. 2026, 47(4): 11-19.
DOI：

袁彬, 申彦波, 张金满, et al. 高影响天气下3种数值模式总辐射预报效果检验与评估[J]. 2026, 47(4): 11-19. DOI： doi:10.19912/j.0254-0096.tynxb.2025-0014.

摘要

检验评估2022年CMA-WSP、CMA-MESO、NCEP-GFS这3种数值预报模式在河北省30个光伏电站的总辐射辐照度（GHI）预报效果。结果表明：CMA-WSP预报误差最低

Abstract

This study evaluates the performance of 3 numerical prediction models： CMA-WSP

CMA-MESO and NCEP-GFS

of the global horizontal irradiance （GHI） at 30 PV stations in Hebei Province in 2022. The results show that the CMA-WSP has the lowest forecasting error and the highest correlation coefficient

followed by CMA-MESO. The CMA-WSP exhibits a systematic overestimation

while both CMA-MESO and NCEP-GFS show a systematic underestimation. The CMA-MESO has the lowest large error ratio （with a deviation of over 200 W/m）

while the CMA-WSP coming second. All models show samples with deviation of more than 700 W/m. During fog

haze

and sandstorm weather processes

the CMA-WSP performs the best

while the CMA-MESO performs the best during rainfall

snowfall

continuous rainy periods

and severe convective weather processes. For PV stations at different locations

the forecasting performance of the three models varies significantly across different weather processes. For some stations

the overall forecasting errors of all numerical models are relatively small across different weather processes

while for others

the overall errors are larger.

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Keywords

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