干旱气象 ›› 2025, Vol. 43 ›› Issue (6): 953-966.DOI: 10.11755/j.issn.1006-7639-2025-06-0953

• 论文 • 上一篇    下一篇

WRF模式的陆面过程方案对积雪的敏感性分析

周燕艳1(), 王颖1,2(), 魏瑞瑞1, 赵天一1   

  1. 1.兰州大学大气科学学院甘肃 兰州 730000
    2.兰州大学半干旱气候变化教育部重点实验室甘肃 兰州 730000
  • 收稿日期:2025-07-08 修回日期:2025-09-30 出版日期:2025-12-31 发布日期:2026-01-19
  • 通讯作者: 王颖(1975—),女,吉林四平人,教授,主要从事空气污染数值模拟、边界层气象特征及生态环境保护研究。E-mail: yingwang@lzu.edu.cn
  • 作者简介:周燕艳(2001—),女,广西南宁人,硕士生,主要从事陆气相互作用研究。E-mail: zhyanyan2023@lzu.edu.cn

Sensitivity of land surface schemes to snow cover in the WRF model

ZHOU Yanyan1(), WANG Ying1,2(), WEI Ruirui1, ZHAO Tianyi1   

  1. 1. College of Atmospheric SciencesLanzhou UniversityLanzhou 730000, China
    2. Key Laboratory of Semi-Arid Climate Change with the Ministry of EducationLanzhou UniversityLanzhou 730000, China
  • Received:2025-07-08 Revised:2025-09-30 Online:2025-12-31 Published:2026-01-19

摘要:

积雪对地表能量过程的复杂影响是冬季复杂地形区数值模拟的关键不确定源,亟待深入研究。利用WRF v4.3模式,针对兰州新区2014年有雪期(2月18—26日)与无雪期(1月11—19日)开展模拟对比试验,基于4座测风塔观测数据,系统评估了SLAB、Pleim-Xiu、RUC和NoahMP 4种陆面方案对近地面气象要素的模拟性能,揭示了积雪对模拟精度的影响及其对陆面方案的敏感性。结果表明,无雪期模拟效果良好:气温模拟相关系数(R)为0.80~0.97,归一化中心均方根误差(Normalized Centered Root Mean Square Errors,NCRMSE)为0.27~0.60;风速模拟R为0.46~0.82,绝对偏差普遍低于0.5 m·s-1,且能较好地再现坡风环流特征。而在积雪期,模拟精度显著下降:约半数方案气温R低于0.80,最大冷偏差超过5.00 ℃,NCRMSE升至0.38~0.79;风速NCRMSE增至0.77~2.52,风向频率误差可达无雪期的2倍。泰勒图分析进一步表明,积雪增强了模拟结果对陆面方案的敏感性,有雪期各方案归一化标准差的离散性显著大于无雪期。在4种方案中,NoahMP在积雪期表现最优,其气温R稳定在0.9左右,冷偏差最小,且NCRMSE多低于0.5。准确表征积雪过程对提升冬季复杂地形区的气象模拟能力具有重要意义。

关键词: 兰州新区, WRF模式, 积雪效应, 陆面过程参数化方案, 近地面气象场

Abstract:

The complex influence of snow cover on surface energy processes constitutes a critical source of uncertainty in wintertime numerical simulations over complex terrain and therefore warrants further investigation. Comparative simulation experiments were conducted for a snow-covered period (18-26 February) and a snow-free period (11-19 January) in 2014 over the Lanzhou New Area using the Weather Research and Forecasting (WRF) model version 4.3. Four land surface models (LSMs), SLAB, Pleim-Xiu, RUC, and NoahMP were systematically evaluated against observations from four meteorological towers to reveal the impact of snow cover on simulation accuracy and scheme sensitivity. Satisfactory performance was achieved during the snow-free period: correlation coefficients (R) of air temperature ranged from 0.80 to 0.97, with normalized centered root mean square errors (NCRMSE) of 0.27-0.60. The R of wind speed ranged from 0.46 to 0.82, and the absolute bias was generally below 0.5 m·s-1, successfully reproducing slope wind circulation. Conversely, simulation accuracy declined significantly during the snow-covered period. R of air temperature for half of the LSMs decreased below 0.80, cold biases exceeded 5.00 ℃, and NCRMSE increased to 0.38-0.79. Wind speed NCRMSE increased to 0.77-2.52, while wind direction frequency errors doubled. Taylor diagram analysis demonstrated that snow cover enhanced the sensitivity to LSMs, indicated by increased dispersion in normalized standard deviation among the schemes. NoahMP exhibited the superior performance with the lowest cold bias under snow-covered conditions (R≈0.9; NCRMSE<0.5), emphasizing the significance of accurate snow process representation for improving winter meteorological simulation in complex terrain.

Key words: Lanzhou New Area, WRF simulation, snow cover, land surface scheme, near-surface meteorological fields

中图分类号: