Preprints
https://doi.org/10.5194/egusphere-2025-4569
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-4569
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
15 Jan 2026
| 15 Jan 2026
Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Dynamic and Thermal Analysis of Sandstorm Processes Based on Vertical Observation Data
Abstract. The Taklamakan Desert (TD) is a key source of dust storms in East Asia, frequently impacting China and neighboring countries. Based on dual-gradient observational experiments in the central and peripheral regions of the TD, combined with ERA5 data and HYSPLIT analysis, eight dust storms from April to June 2024 were studied. The findings include: (1) Dust storm trajectories in the TD fall into three types: (a) east-to-west movement, (b) transport across the Tianshan and Pamir Mountains, and (c) west-to-east movement driven by thermal factors in summer. (2) Spring dust storms (March–April) are dominated by dynamic factors, while summer storms (May–June) are influenced by thermal factors. Significant pressure and temperature changes 12–6 hours before a storm provide a critical prediction window. (3) Horizontal dust flux (Q) at XiaoTang (peripheral region) follows a parabolic pattern, while at TaZhong (central region), terrain plays a key role. High Q values result in larger fluctuations, while low Q values show relative stability. Seasonal temperature differences, convective intensity, and flat terrain drive alternating wind speed trends at XiaoTang before storms, with stronger fluctuations observed in summer due to rising temperatures.
How to cite. Wang, Y., Huo, W., Liu, Y., Maihamuti, M., Yang, F., Zhou, C., Yang, X., and Mamtimin, A.: Dynamic and Thermal Analysis of Sandstorm Processes Based on Vertical Observation Data, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4569, 2026.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Latest update: 07 Feb 2026
Yifei Wang
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Yongqiang Liu
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Mayibaier Maihamuti
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Fan Yang
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Chenglong Zhou
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Xinghua Yang
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
School of Geographical Sciences, Shanxi Normal University, Taiyuan 030032, China
Ali Mamtimin
Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi 830002, China
Taklimakan Desert Meteorology Field Experiment Station, China Meteorological Administration, Urumqi 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi 830002, China
Short summary
his study explores why dust storms in the Taklamakan Desert differ by season. We find that heat changes drive storms in spring, while wind dynamics dominate in summer. The hours before a storm show the sharpest shifts in temperature and pressure, making them a key warning period. Wind strength and dust transport also vary greatly between spring and summer, especially on flat terrain. These results improve understanding of storm drivers and support better forecasting and environmental protection.
his study explores why dust storms in the Taklamakan Desert differ by season. We find that heat...
The manuscript uses a valuable observational dataset by integrating
dual-site (TZ/XT) vertical measurements with ERA5 and HYSPLIT
backward trajectories to investigate dust transport pathways, dynamical
and thermal mechanisms, and dust flux/profile characteristics over the
Taklimakan Desert. The study provides useful evidence for understanding
the seasonally varying controls on dust-storm development and helps
bridge site-based observations with regional-scale atmospheric
conditions. These results are also relevant for improving process-based
interpretation and short-lead monitoring of dust-storm occurrence in arid
regions. I recommend that the paper be published after the following
comments are addressed.
1. Main comments
a) The study period and event sample are described inconsistently in
the Abstract, Table 1, and the main text. Please unify the time span, total
number of observed events, any excluded cases (with a brief reason), the
final sample used for analysis, event numbering (Dust1–Dust8), and the
definition of spring and summer throughout the manuscript.
b)The Introduction provides a solid background, but the narrative
could be made more coherent. I suggest refining the logical progression
from motivation to knowledge gaps and then to the specific
objectives/contributions of this study, and updating the citations with the
most relevant literature published in the last five years.
c) Please streamline the Methods and clarify how each method
supports the study objectives and key conclusions. A short
method–objective mapping paragraph at the beginning is sufficient.
Briefly state the role of HYSPLIT (pathway classification and source
indication), ERA5 diagnostics (dynamical: ΔP/wind/geopotential;
thermal: ΔT/instability/BLH), and flux/profile calculations (vertical
structure and terrain effects).
d) Please improve reproducibility by clarifying key definitions and
settings. Define the anomaly baseline used for “anomalous wind/anomaly
wind field”. Specify whether the 24/12/6/3 h windows are referenced to
event onset or storm time/peak. Provide the spatial averaging domain and
essential HYSPLIT settings (starting height, back-trajectory duration, and
pathway classification criteria).
e) Please correct the inconsistency in Table 3 where ΔP appears in
the header while the text discusses ΔT. Ensure the table title/header, in-
text description, and any related figures/citations are consistent after
revision, and confirm that Table 3 matches the variables plotted and
discussed in the Results.
f) Please strengthen the Discussion by adding comparisons with
previous studies from the Taklimakan Desert and other deserts. Focus on
seasonal dynamical and thermal controls, profile differences over flat and
undulating surfaces, and transport-pathway classifications. Reduce
repetition of the Results, and consider organizing Sect. 4 as: summary,
highlights, limitations, and outlook.
2. Technical comments
a) Replace “HYSPIT” with HYSPLIT in the Sect. 2.4 title.
b) Standardize terminology throughout (e.g., use “850 hPa
geopotential height” consistently). In the flux/parameter section, unify
units (cm s⁻¹ and m s⁻¹) and clearly state any conversions where
needed.
c) Several figure captions show numbering or formatting issues
(e.g., “Fig.11 10 …”). Please verify figure order/numbering and
standardize caption style and wording.
d) The reference list includes clearly irrelevant items and possible
duplicates. Please remove unrelated references, merge duplicates where
appropriate, and ensure one-to-one consistency between in-text citations
and the reference list.
e) The keywords include “Causation Analysis”, but corresponding
methods/results are not clearly presented. Please remove this term from
the keywords and any related statements to avoid overstating the scope.