山岳森林における風況および炭素フラックスの理解を向上させるマルチタワー観測（Multi-Tower Observations Improve Understanding of Wind Regimes and Carbon Fluxes in Mountainous Forests）

2026-02-06 中国科学院（CAS）

＜関連情報＞

• https://english.cas.cn/newsroom/research-news/202602/t20260224_1151128.shtml
• https://link.springer.com/article/10.1007/s11430-024-1723-y
• https://www.sciencedirect.com/science/article/abs/pii/S0168192325001650

山岳森林の渦共分散CO2フラックスシリーズにおけるフィルタリングとギャップフィリング戦略：清遠-ケルタワーの測定に基づく比較 Filtering and gap-filling strategies in eddy covariance CO2 flux series of mountainous forests: Comparison based on measurements from Qingyuan-Ker Towers

Tongtong Li,Tian Gao,Dexiong Teng,Zhi Chen,Bai Yang,Xingchang Wang,Changming Zhao,Jinsong Zhang,Hui Huang,Chao Guan,Jiabing Wu,Fengyuan Yu,Jinxin Zhang,Yirong Sun,Shuangtian Li,Xinhua Zhou & Jiaojun Zhu
Science China Earth Sciences  Published:17 December 2025
DOI:https://doi.org/10.1007/s11430-024-1723-y

Abstract

Although the eddy covariance (EC) technique has been widely adopted to measure the CO₂ and water vapor exchanges between ecosystems and the atmosphere, challenges remain for its applications in mountainous regions. Ideally, the EC technique requires homogeneous canopies and flat underlying surfaces. Over complex terrain, heterogeneity of source/sink areas across wind directions complicates data analysis, particularly quality control (filtering) and gap-filling of nocturnal CO₂ flux data. In this study, we evaluated the performance of nocturnal CO₂ flux filtering in mountainous forests (comparing cases with or without wind direction sector partitioning) and assessed different gap-filling methods for the analyzed data that were measured from the Qingyuan-Ker Towers in Northeast China from January 2020 to December 2022. Results showed that surface roughness varied across wind direction sectors, leading to reduced accuracy in nocturnal CO₂ fluxes filtering if the conventional friction velocity (u*) threshold method (a single threshold for all wind sectors) was applied. Alternative to the conventional method, identifying the u* threshold (u^*_c) based on wind sectors could significantly improve the accuracy of nighttime CO₂ flux filtering. The gaps in the CO₂ flux series of forest ecosystems over complex terrain are filled using four methods: mean diurnal course (MDC), look-up table (LUT), marginal distribution sampling (MDS), and random forest (RF). Biases in the filled nocturnal net ecosystem carbon exchange (NEE) were substantially reduced by 16%, in comparison to the adopted conventional method, following a treatment of data filtering based on wind-sector-specific u^*_c values. In general, the accuracy of all four gap-filling methods decreased with increasing gap length; however, the RF method consistently outperforms the others, yielding more robust and reliable estimates of annual NEE. Through extensive analyses in this study, we recommend identifying u^*_c values for canopies in different directions surrounding a flux tower, with a moving window and a careful selection of gap-filling methods when processing EC data from a mountainous forest. These findings advance methodologies in handling flux data from forest ecosystems over complex terrains.

山岳森林における風況とその要因：清遠ケルタワーズによる共同観測 Wind regimes and their drivers in mountainous forests: collaborative observations by Qingyuan Ker Towers

Tian Gao, Jiaojun Zhu, Yixuan Xu, Xiufen Li, Xingchang Wang, Fengyuan Yu, Dexiong Teng, Yirong Sun, Jinxin Zhang
Agricultural and Forest Meteorology  Available online: 12 April 2025
DOI:https://doi.org/10.1016/j.agrformet.2025.110545

Highlights

• Wind regimes and their drivers were investigated using three towers in a valley.
• Wind regimes did not exhibit typical traits of a thermal-induced wind circulation.
• Weak solar radiation and strong weather wind are the main drivers.
• Different degrees of drainage flows may occur at the observation sites.
• The results help us understand flux measurements.

Abstract

The thermal-induced wind regime is an important feature of mountain meteorology, which affects energy and scalar transports over complex terrains. Understanding wind regimes allows us to better interpret eddy covariance flux measurements and its data quality control. Due to a high spatial heterogeneity in wind features over complex terrains, single site-based measurement limits understanding of wind regimes. Here, we demonstrated wind regimes and their drivers using the Qingyuan Ker Towers (three towers in a valley: T1, mixed broadleaved forest; T2, Mongolian oak forest; T3, larch plantation forest) in mountainous forests of Northeast China.

In the daytime, down-slope winds dominated above the canopy at T1 and T3, while up-slope winds dominated at T2; in the nighttime, T1, T2 and T3 were dominated by down-valley, up-slope and down-slope winds, respectively. Along vertical gradients, different degrees of wind direction shears were observed, indicating frequently decoupling wind directions between above- and below-canopy. The profiles of wind speed at T1 and T2 were similar, showing a monotonical increase as height increases, whereas T3 showed an “S”-shaped profile with a secondary maximum in the trunk space. In general, the wind regimes did not exhibit traits of a typical thermal-induced wind circulation during the peak growing season. The similarity analysis suggested that the wind regimes were influenced by the strong background wind. Additionally, frequent cloudy weather with weak solar radiation is unfavorable to thermal-induced circulation. The wind regimes, thermal gradient and pattern of CO₂ concentration and flux jointly suggested that strong shallow drainage flows may occur frequently at T3, probably leading to an underestimation of net ecosystem exchange of CO₂ (NEE) during the nighttime, whereas drainage flows are expected to be weaker at T1 and T2. These analyses improve our understanding when NEE is reliably measured and provide an insight for correcting the flux data.