Scaling laws in wind speed, particle number and kinetic energy in Gobi sand movement

doi:10.11755/j.issn.1006-7639-2025-02-0195

Abstract

Abstract:

In the extreme arid region of Northwest China, the Gobi desert is widely distributed, with strong winds and abundant sand, leading to frequent disasters. A deep understanding of the basic laws of the aeolian sand-dust movement over Gobi surfaces is an important prerequisite for disaster warning and scientific prevention. Given the current difficulty in accurately predicting the instantaneous aeolian sediment transport rate, exploring the statistical laws of airflow and sand-dust characteristic physical quantities in wind-sand events, and then conducting statistical forecasting, may be a feasible way to establish a quantitative relationship between wind and sand on time scales of seconds or less. This study borrows the ideas and methods from the statistical theory of turbulence, and analyzes four field observation datasets of Gobi sand-dust movement using the Hilbert-Huang transform. The results indicate that the Hilbert marginal spectra of the time series of wind speed, kinetic energy and number of saltation sand particle, and dust concentration in the aeolian events all follow the power scaling law. The scaling exponents of variables, characterizing aeolian sand and dust motions, and wind speed range from 0.78 to 1.51 and 0.59 to 1.47, respectively.

Key words: Gobi, aeolian sand, dust, Hilbert marginal spectra, scaling law

摘要：

中国西北极端干旱区戈壁广布，风大沙多，灾害频发。充分了解戈壁沙尘运动基本规律是灾害预警与科学防治的重要前提。鉴于目前难以精准预测瞬时输沙率，探讨风沙事件中气流与沙尘特征物理量的统计规律，进而开展统计预测，也许是在秒及以下时间尺度上建立风和沙之间定量关系的可行之路。本研究借鉴湍流统计理论的思路和方法，利用Hilbert-Huang变换分析4个戈壁沙尘运动野外观测数据集。结果表明，沙尘事件中的风速、跃移沙粒动能与个数、粉尘浓度等时间序列的Hilbert边际谱均符合幂次标度律，沙尘特征量和风速的标度指数范围分别为0.78~1.51和0.59~1.47。

关键词: 戈壁, 风沙, 粉尘, Hilbert边际谱, 标度律

CLC Number:

K903
O359

WANG Zhenting, MENG Xiaonan, WANG Xuesong, LI Qing. Scaling laws in wind speed, particle number and kinetic energy in Gobi sand movement[J]. Journal of Arid Meteorology, 2025, 43(2): 195-206.

王振亭, 孟小楠, 王雪松, 李庆. 戈壁沙尘运动中风速与颗粒数及动能的标度律[J]. 干旱气象, 2025, 43(2): 195-206.

Figures/Tables 12

References 47

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数据来源	高度/m	物理量	传感器（厂家）	采样频率/Hz	采样精度
Wang et al.，2022	0.30、0.83、3.00	U、V、W	WindMaster Pro（Gill）	20	0.001 m·s^-1
Tan et al.，2020	0.05、0.12、0.38、0.80、1.38	KE、PC	H11-Lin（Sensit）	1	1×10^-7 J·s^-1、s^-1
Tan et al.，2020	0.70、2.00	U、φ、θ	Young-81000（RM Young）	20	0.01 m·s^-1、0.1°
Wang et al.，2023	0.05、0.12、0.38、0.80、1.41	KE、PC	H11-Lin（Sensit）	1	1×10^-7 J·s^-1、s^-1
Wang et al.，2023	1.20、2.80	U、V、W	WindMaster Pro（Gill）	1	0.001 m·s^-1
本研究团队	0.10、0.20、0.50、1.00、1.50、2.00	DA、DN	DustTrak-II（TSI）	0.2	0.001 mg·m^-3
本研究团队	0.50、1.00	U、V、W	Young-81000（RM Young）	20	0.01 m·s^-1

数据来源	高度/m	物理量	传感器（厂家）	采样频率/Hz	采样精度
Wang et al.，2022	0.30、0.83、3.00	U、V、W	WindMaster Pro（Gill）	20	0.001 m·s^-1
Tan et al.，2020	0.05、0.12、0.38、0.80、1.38	KE、PC	H11-Lin（Sensit）	1	1×10^-7 J·s^-1、s^-1
Tan et al.，2020	0.70、2.00	U、φ、θ	Young-81000（RM Young）	20	0.01 m·s^-1、0.1°
Wang et al.，2023	0.05、0.12、0.38、0.80、1.41	KE、PC	H11-Lin（Sensit）	1	1×10^-7 J·s^-1、s^-1
Wang et al.，2023	1.20、2.80	U、V、W	WindMaster Pro（Gill）	1	0.001 m·s^-1
本研究团队	0.10、0.20、0.50、1.00、1.50、2.00	DA、DN	DustTrak-II（TSI）	0.2	0.001 mg·m^-3
本研究团队	0.50、1.00	U、V、W	Young-81000（RM Young）	20	0.01 m·s^-1

数据来源	高度/m	物理量	序列数	均值	标准差	95%置信区间	物理量	序列数	均值	标准差	95%置信区间
Wang et al.，2022	0.30	U	1 724	1.438	0.418	[1.418， 1.457]	W	1 724	1.336	0.491	[1.313， 1.360 ]
	0.83			1.445	0.345	[1.429， 1.461]			1.360	0.456	[1.339， 1.382 ]
	3.00			1.468	0.360	[1.451， 1.485]			1.404	0.508	[1.380， 1.428]
Tan et al.，2020	0.05	KE	37	1.141	0.175	[1.083， 1.200]	PC	34	1.393	0.295	[1.290， 1.496]
	0.12		37	1.110	0.193	[1.046， 1.174]		34	1.380	0.198	[1.311， 1.449]
	0.38		18	1.038	0.165	[0.956， 1.120]		24	1.224	0.212	[1.135， 1.314]
	0.80	PC	1	1.451
	0.70	U	1 006	1.192	0.055	[1.188， 1.195]	W	1 006	1.313	0.143	[1.305， 1.322]
	2.00	U	1 006	1.313	0.143	[1.305， 1.322]	W	1 006	1.134	0.184	[1.123， 1.146]
Wang et al.， 2023	0.05	KE	30	1.021	0.208	[0.943， 1.098]	PC	23	1.234	0.145	[1.172， 1.297]
	0.12		24	0.929	0.215	[0.839， 1.020]		28	1.176	0.186	[1.104，1.248]
	0.38		15	0.992	0.138	[0.916， 1.068]		14	1.055	0.185	[0.948，1.161]
	0.80		21	0.907	0.131	[0.847， 0.966]		15	1.121	0.137	[1.045，1.197]
	1.41		19	0.781	0.183	[0.692， 0.869]		21	1.204	0.216	[1.106，1.302]
	1.20	U	98	0.835	0.106	[0.813， 0.856]	W	98	0.590	0.089	[0.572，0.608]
	2.80	U	98	0.891	0.100	[0.871， 0.911]	W	98	0.629	0.104	[0.608，0.650]
本研究	0.10	DA	11	1.513	0.228	[1.360， 1.665]	DN	12	1.015	0.210	[0.882，1.149]
	0.20		7	1.400	0.192	[1.224， 1.577]		11	1.276	0.185	[1.152，1.401]
	0.50		11	1.276	0.185	[1.152， 1.401]		18	0.965	0.164	[0.883，1.046]
	1.00		23	0.922	0.199	[0.837， 1.008]		12	0.756	0.077	[0.708，0.805]
	1.50		10	1.022	0.216	[0.868， 1.176]
	2.00		15	0.901	0.108	[0.842， 0.961]		11	0.932	0.117	[0.854， 1.010]
	0.50	U	486	1.187	0.043	[1.183， 1.190]	W	486	0.899	0.067	[0.893， 0.905]
	1.00	U	486	1.214	0.042	[1.211， 1.218]	W	486	1.214	0.041	[1.210， 1.218]

数据来源	高度/m	物理量	序列数	均值	标准差	95%置信区间	物理量	序列数	均值	标准差	95%置信区间
Wang et al.，2022	0.30	U	1 724	1.438	0.418	[1.418， 1.457]	W	1 724	1.336	0.491	[1.313， 1.360 ]
	0.83			1.445	0.345	[1.429， 1.461]			1.360	0.456	[1.339， 1.382 ]
	3.00			1.468	0.360	[1.451， 1.485]			1.404	0.508	[1.380， 1.428]
Tan et al.，2020	0.05	KE	37	1.141	0.175	[1.083， 1.200]	PC	34	1.393	0.295	[1.290， 1.496]
	0.12		37	1.110	0.193	[1.046， 1.174]		34	1.380	0.198	[1.311， 1.449]
	0.38		18	1.038	0.165	[0.956， 1.120]		24	1.224	0.212	[1.135， 1.314]
	0.80	PC	1	1.451
	0.70	U	1 006	1.192	0.055	[1.188， 1.195]	W	1 006	1.313	0.143	[1.305， 1.322]
	2.00	U	1 006	1.313	0.143	[1.305， 1.322]	W	1 006	1.134	0.184	[1.123， 1.146]
Wang et al.， 2023	0.05	KE	30	1.021	0.208	[0.943， 1.098]	PC	23	1.234	0.145	[1.172， 1.297]
	0.12		24	0.929	0.215	[0.839， 1.020]		28	1.176	0.186	[1.104，1.248]
	0.38		15	0.992	0.138	[0.916， 1.068]		14	1.055	0.185	[0.948，1.161]
	0.80		21	0.907	0.131	[0.847， 0.966]		15	1.121	0.137	[1.045，1.197]
	1.41		19	0.781	0.183	[0.692， 0.869]		21	1.204	0.216	[1.106，1.302]
	1.20	U	98	0.835	0.106	[0.813， 0.856]	W	98	0.590	0.089	[0.572，0.608]
	2.80	U	98	0.891	0.100	[0.871， 0.911]	W	98	0.629	0.104	[0.608，0.650]
本研究	0.10	DA	11	1.513	0.228	[1.360， 1.665]	DN	12	1.015	0.210	[0.882，1.149]
	0.20		7	1.400	0.192	[1.224， 1.577]		11	1.276	0.185	[1.152，1.401]
	0.50		11	1.276	0.185	[1.152， 1.401]		18	0.965	0.164	[0.883，1.046]
	1.00		23	0.922	0.199	[0.837， 1.008]		12	0.756	0.077	[0.708，0.805]
	1.50		10	1.022	0.216	[0.868， 1.176]
	2.00		15	0.901	0.108	[0.842， 0.961]		11	0.932	0.117	[0.854， 1.010]
	0.50	U	486	1.187	0.043	[1.183， 1.190]	W	486	0.899	0.067	[0.893， 0.905]
	1.00	U	486	1.214	0.042	[1.211， 1.218]	W	486	1.214	0.041	[1.210， 1.218]