Study on Ionospheric Depletion and Traveling Ionospheric Disturbances Induced by Rocket Launches Using Multi-Source GNSS Observations and the MRMIT Method

Highlights

What are the main findings?

• Significant ionospheric depletion forms within ~10–15 min post-launch.
• A trajectory-based regional integration framework was constructed, integrating multi-constellation GNSS observations and the innovative MRMIT method, which provides key insights into the impact mechanisms of human space activities on the environment.

What is the implication of the main finding?

• The integration of the MRMIT method with trajectory-based regional integration enhances the identification fidelity of ionospheric depletion, providing actionable observational evidence for assessing the spatial environmental impact of launch activities.
• This study highlights the dominant role of launch mass in governing depletion intensity, while propellant chemistry and local time jointly modulate depletion persistence and recovery, offering insights for ensuring GNSS service reliability.

Abstract

Rocket launches constitute a major anthropogenic source of disturbance in the near-Earth space environment, inducing significant ionospheric perturbations through both chemical and dynamic mechanisms. This study presents a systematic analysis of ionospheric disturbances—specifically, electron density depletion and traveling ionospheric disturbances (TIDs)—triggered by four rocket launches from China’s Jiuquan Satellite Launch Center between 2023 and 2025. Using high-rate, multi-constellation GNSS data from 370 ground stations and BeiDou GEO satellites, we extracted total electron content (TEC) signals and applied advanced detection methods, including the Multi-Rolling-Multi-Image-Tracking (MRMIT) algorithm for depletion identification and a parametric integration framework for quantitative comparison. Our results reveal that all launches produced rapid TEC depletions, evolving along the rocket trajectory and peaking within approximately 30 min. Launch mass was the dominant factor controlling depletion intensity, while propellant chemistry (UDMH-based vs. liquid oxygen/methane) and local time/background TEC levels modulated the recovery rate and spatial extent. Additionally, distinct TIDs exhibiting wave-like and V-shaped structures were observed, propagating outward from the trajectory with latitudinal variations in amplitude and waveform. These findings highlight the critical roles of rocket attributes and ambient ionospheric conditions in shaping disturbance characteristics. The study underscores the value of multi-source GNSS networks and novel methodologies in monitoring anthropogenic space weather effects, with implications for GNSS performance and sustainable space operations.

1. Introduction

Rocket launches represent a significant anthropogenic disturbance source to the near-Earth space environment. The substantial amounts of chemical species, such as water vapor and carbon dioxide, present in the rocket exhaust plume can rapidly react with ions in the ionosphere, triggering a notable reduction in local electron density (depletion). Previous studies have demonstrated that H₂O and CO₂ molecules in the rocket exhaust can greatly enhance electron loss processes through rapid charge exchange and dissociative recombination reactions with oxygen ions (O⁺), leading to the formation of an “electron depletion” or a significant decrease in Total Electron Content (TEC) [1,2,3,4,5,6,7,8]. For instance, Furuya and Heki (2008) [9] utilized a dense GPS network to observe an ionospheric electron density depletion following the launch of an H-IIA rocket from the Tanegashima Space Center, Japan, in 2006. This depletion persisted for over an hour and extended several hundred kilometers spatially. Savastano et al. (2019) [10] discussed the advantages of using Geostationary Earth Orbit (GEO) satellites for studying ionospheric anomalies, particularly the ionospheric depletion caused by the Falcon 9 rocket launch on 24 August 2017. The study employed a real-time GNSS algorithm called VARION, combined with WAAS-GEO satellite data, to analyze the ionospheric depletion triggered by the rocket launch.

Zhao et al. (2024) [2] investigated the vertical structural evolution of an ionospheric depletion observed by the Sanya Incoherent Scatter Radar (SYISR, China) induced by a rocket launch. By combining GNSS and radar observations, the authors found that the rocket-induced depletion underwent three distinct stages: initial depletion in the top ionosphere (10–11 min), rapid expansion to both higher and lower altitudes (extending to 200–700 km altitude within approximately 30 min), and finally a slow recovery phase (with a faster recovery rate at higher altitudes). The study also incorporated water vapor diffusion simulations to explore the influence of the rocket trajectory and water release on the depletion formation. It was further noted that recovery from a midnight launch event was faster than from a daytime event, with a greater maximum electron density depletion amplitude.

Beyond the chemical depletion effect, shock waves and gravity waves generated by rocket launches propagate within the ionosphere, forming Traveling Ionospheric Disturbances (TIDs). Lin et al. (2017) [11] first reported concentric TIDs induced by the 2016 SpaceX Falcon 9 launch, observing disturbances propagating outward at velocities of 241–617 m/s, exhibiting medium-scale gravity wave characteristics with periods of 10–13 min and wavelengths of approximately 200–400 km. Savastano et al. (2019) [10] pointed out that several minutes after liftoff, a transient “V”-shaped wave pattern appeared in TEC imagery, indicating that instantaneous disturbances corresponding to acoustic-gravity waves excited by the ascending rocket were detected hundreds of kilometers away.

Choi and Hong (2019) [8] studied the rapidly propagating ionospheric disturbances triggered by a North Korean missile launch on 28 November 2017. Utilizing GNSS network data from South Korea, they analyzed the dynamic variations in TEC. Their research revealed that within 5 min after the missile launch, ionospheric disturbances propagated rapidly southwestward with a phase velocity of about 2.3 km/s. Furthermore, the TEC depletion amplitude was relatively small, around 3 TECU, which was attributed to the low background electron density.

Wang et al. (2023) [12] investigated the ionospheric disturbances induced by the launch of a Chinese Long March 2D rocket on 3 December 2017, focusing on the shock wave and electron density depletion. Using observational data from 382 GNSS stations in western China, they analyzed the spatial distribution and propagation characteristics of the disturbances. The study found that the shock wave manifested as a V-shaped disturbance, while the electron density depletion reached up to 56% of the background value. These results demonstrate that rocket launches can cause not only local ionospheric disturbances but also shock waves that propagate over long distances.

Yasyukevich et al. (2024) [13] analyzed the significant impact of the SpaceX Starship launch and its subsequent explosion on the ionosphere. The study found that the rocket flight generated wavelike ionospheric disturbances centered on the flight trajectory and propagating northward (with a V-shaped propagation angle of approximately 11 degrees).

Chen et al. (2024) [14] investigated the four-dimensional ionospheric disturbances induced by the Falcon 9 rocket launch on 17 January 2016, focusing on the evolution of plasma density. Employing three-dimensional computerized ionospheric tomography (CIT) techniques and using sliding TEC (dSTEC) data from GNSS, they reconstructed the three-dimensional structure of the plasma density. The study revealed clear propagation characteristics of gravity waves induced by the rocket launch within the ionosphere.

Rajesh et al. (2025) [15] studied the ionospheric effects of two consecutive rocket launches from China and Japan on 11 and 12 January 2024. Comparative analysis showed that both launches generated concentric traveling ionospheric disturbances (CTIDs) and depletions, albeit with differing scales and durations. The study found that the depletion from the Chinese “Gravity-1” rocket had a larger spatial coverage, whereas the depletion from the Japanese H-IIA rocket exhibited greater depth. Through model simulations, it was estimated that the water molecule content released by the “Gravity-1” launch was only 5–7% of that from the H-IIA, yet its steeper flight trajectory resulted in broader coverage.

These studies demonstrate that high temporal and spatial resolution observations of TEC, facilitated by multi-constellation GNSS station networks, enable effective capture of both local depletion and far-field TID features induced by rocket launches [16,17,18,19,20,21,22].

Methodologically, researchers commonly employ detrending and filtering techniques to enhance the identification capability of depletion and TID signals. Standard techniques include applying Savitzky–Golay filters, median filters, and gridding processes to GNSS-TEC time series to suppress background variations and highlight fluctuation signals [23,24,25,26,27]. Furthermore, for the asymmetric depletion caused by rocket exhaust plumes (characterized by a steep leading edge and a gradual trailing edge), methods such as the “Multi-Rolling-Multi-Image-Tracking” (MRMIT) convolution kernel approach have been introduced to better extract the features of the depletion front [28]. The combination of these diverse methods facilitates subsequent parametric analysis and inter-event comparisons.

To date, research on the ionospheric effects of rocket launches has predominantly focused on case studies of specific launch missions, covering various countries such as China, the United States, Russia, and Japan, and involving different types of launch vehicles. While these studies have revealed general characteristics of depletion and TIDs, they are often limited to single events or specific conditions, lacking systematic cross-event comparisons across different propellant types and local times. Factors such as the launch mass of different rockets, the chemical composition of the propellant (e.g., liquid oxygen/methane vs. nitrogen tetroxide/UDMH), and the background ionospheric conditions at the time of launch may collectively modulate the intensity and evolution of disturbances. However, their relative mechanistic roles have not been sufficiently quantified.

Our study focuses on the Jiuquan Satellite Launch Center (geographic coordinates approximately 40.96°N, 100.29°E), which is situated in the mid-latitude ionosphere region, distinct from the Equatorial Ionization Anomaly (EIA). The dynamics of the mid-latitude ionosphere are primarily modulated by mesoscale atmospheric dynamics (such as acoustic-gravity waves and gravity waves) and ionosphere-thermosphere coupling processes, exhibiting characteristics different from those of the equatorial ionosphere. For instance, the mid-latitude ionosphere typically features lower background electron density gradients and weaker electric field-driven effects (e.g., the equatorial electrojet). This implies that rocket launch-induced disturbances (such as depletions and TIDs) are more susceptible to the influence of the background atmospheric structure and geomagnetic field configuration during propagation, rather than plasma drift or fountain effects predominant in the equatorial region. Specifically for our study, the latitude of the Jiuquan center (around 40°N) means the ionospheric background is significantly influenced by solar radiation, seasonal variations, and local time. The local times of the four launch events analyzed (2023–2025) range from 09:00 to 15:08 LT, covering the ascending and descending phases of the daytime ionosphere, leading to differences in background TEC levels and recovery rates. In mid-latitudes, rocket exhaust plumes (e.g., H₂O, CO₂, or NOx) cause depletion through rapid charge exchange and dissociative recombination reactions, while acoustic-gravity wave-driven TIDs exhibit typical mesoscale characteristics propagating along the trajectory, modulated by neutral winds and the inclination of the geomagnetic field. In contrast, the equatorial ionosphere might experience broader spatial extension and longer duration of depletions and TIDs due to higher electron density and electric field effects.

To address this, the present study selects four typical launch events from China’s Jiuquan launch site between 2023 and 2025. Utilizing an extensive multi-constellation GNSS station network covering the continent and novel disturbance identification methods, we systematically analyze the similarities and differences in depletion and TID characteristics from different rocket launches and explore the underlying chemical and dynamic driving mechanisms.

2. Materials and Methods

2.1. Data

This study selected four typical launch events from the Jiuquan Satellite Launch Center between 2023 and 2025 for analysis. The basic information for each mission is as follows: the successful launch of Zhuque-2Yao-2 (liquid oxygen/methane propellant, Day of Year [DOY] 193) on 12 July 2023 at 09:00 LT; the launch of Long March-2C (CZ-2C, DOY 314) which delivered the PIESAT-2 01–04 satellites into orbit on 9 November 2024 at 11:39 LT; the “one rocket, two satellites” mission performed by Long March-2C (DOY 058) on 27 February 2025 at 15:08 LT; and the successful launch of the Shijian-26 satellite by Long March-4B (CZ-4B, DOY 149) on 29 May 2025 at 12:12 LT. Detailed rocket parameters are presented in

Table 1. Key parameters of the launch vehicles for the four mission events. (t (metric ton)).

Indicator	Zhuque-2, LandSpace	CZ-2C	CZ-4B
Lift-off Mass	≈216–219 t	≈233–243 t	≈248–249 t
Propellant Type	Liquid Oxygen/Methane	Dinitrogen Tetroxide/Unsymmetrical Dimethylhydrazine
Propellant Mass	≈180–195 t	≈220.4 t	≈230 t
Primary Combustion Products	The primary combustion products of methane/liquid oxygen are carbon dioxide (CO2) and water vapor (H2O). Under high-temperature, fuel-rich or lean conditions, small amounts of carbon monoxide (CO), unburned methane, and carbon particulates (soot/black carbon), or highly reactive free radicals may also be generated.	The combustion products are complex, comprising CO2, H2O, N2, along with a substantial amount of nitrogen oxide compounds (NOx, NO2), and nitrogenous organic residues resulting from incomplete combustion or decomposition. These pose significant hazards to the ground environment and operational personnel.	Same as above
Propellant Mass (2nd/3rd Stage)	2nd stage propellant mass: 35–45 t (estimated); No third stage	2nd stage propellant mass: 54 t; No third stage	2nd stage propellant mass: 52 t; 3rd stage propellant mass: 12 t

.

These missions were selected based on the following considerations: All four missions targeted Sun-Synchronous Orbit (SSO), with similar orbital types and launch azimuths. This helps control for geometric variables, allowing the analysis to focus on the effects of different rocket attributes (propellant type and launch mass) on ionospheric disturbances. The missions cover two types of propellants—liquid oxygen/methane and nitrogen tetroxide/unsymmetric dimethylhydrazine (UDMH)—with launch masses ranging between 216 and 249 tons, providing an effective gradient for reliable quantitative comparison. The launch times, distributed from local time 09:00–15:08 LT, encompass various background ionospheric conditions such as daytime ascending, near-noon, and afternoon descending phases. This facilitates the investigation of how local time and TEC levels modulate the depletion process. Furthermore, during these events, data from 370 GNSS stations across mainland China and Ionospheric Pierce Point (IPP) data from BeiDou Geostationary Earth Orbit (GEO) satellites were complete, with dense spatial coverage. Particularly, the intensive sampling near the launch site and along the rocket trajectories provides a solid foundation for capturing the fine spatiotemporal characteristics of both depletion and TIDs.

For the raw GNSS station observation data, we utilized IonKit-NH, a MATLAB-based toolkit, which employs a combined carrier phase and pseudorange solution strategy to retrieve the ionospheric Total Electron Content (TEC). A 15° elevation angle threshold was applied during data processing to filter out low-elevation signals and mitigate multipath effects. The influence of the satellite-receiver geometric path was eliminated using the geometry-free combination [29]. Real-time cycle slip detection was implemented through the wide-lane combination (Melbourne–Wübbena, with a threshold of 5 m) and the geometry-free combination (threshold of 0.5 m) to ensure data continuity [30]. The sampling frequency of all GNSS stations is 30 s. The Ionospheric Pierce Point (IPP) calculation was based on a single-layer ionospheric model at a height of 350 km. It is noteworthy that the receiver Differential Code Bias (DCB) was retained (as common calibration methods for receiver DCB inevitably introduce signal smoothing), since subsequent differential processing will eliminate it—given that the DCB of the same receiver is considered constant over short periods [31]. The distribution of the stations is shown in Figure 1a,b, the IPP distribution is illustrated in Figure 1c, and the spatial distribution of IPPs for the BeiDou GEO satellites is presented in Figure 1d.

2.2. Methodology

For Traveling Ionospheric Disturbances (TIDs):

To address potential contamination from the large-amplitude, asymmetric depletion and background trends, a multi-step detrending and filtering approach was adopted, optimized based on methodologies from Liu et al. (2018) [32] for extracting wave-like disturbances in the presence of rocket-induced depletions. First, a fourth-order Savitzky–Golay (SG) filter with a 121-point window was applied solely to estimate and remove the background trend and low-frequency variations from the original TEC time series, rather than directly extracting TID signals. This step helps mitigate contamination from the depletion’s gradual trailing edge and large-scale ionospheric gradients. Subsequently, the detrended residuals were processed using a fourth-order Butterworth bandpass filter with a passband of 2–12 min to isolate medium-scale acoustic-gravity wave signals while suppressing both high-frequency noise and residual trends. This combination effectively enhances the signal-to-noise ratio of TIDs and avoids artificial artifacts that may arise from direct SG filtering on depletion-affected TEC data [33,34,35].

For Ionospheric Depletion Extraction:

The TEC depletion induced by rocket launches exhibits an asymmetric, abrupt characteristic—a steep leading edge followed by a gradual trailing edge. The Multi-Rolling-Multi-Image-Tracking (MRMIT) method is particularly advantageous for identifying such features. This method conceptually simulates a ‘roller’ moving along the TEC time series curve. The roller cannot enter a TEC depletion ‘valley,’ and its trajectory naturally forms a background envelope unaffected by the depletion, thereby enabling precise isolation of the depletion signal [28]. In this study, we introduced a key modification to the standard MRMIT approach by setting the detection threshold to 1 TECU, as opposed to the 3 TECU commonly used in earlier implementations such as Pradipta et al. (2015) [28]. This adjustment significantly improves the sensitivity for capturing smaller yet physically meaningful depletions, which is especially suitable for characterizing rocket-induced ionospheric disturbances.

By simulating a roller of radius R₀ moving across the TEC “terrain,” geometric constraints ensure that the roller bypasses the depletion region, avoiding the “valley-filling effect” associated with traditional filtering methods. The steep leading edge of the depletion is identified as a contact point discontinuity (Rezy Pradipta, 2015 [28]; Linxuan Zhao and Feng Ding, 2024 [2]). Conventional filtering approaches, in the era of frequent rocket launches, have revealed limitations due to their lack of physical mechanism integration and adaptive bottlenecks. In contrast, the MRMIT (roller) method addresses these issues through: a physically driven architecture (the roller model transcends pure mathematical fitting), envelope recognition, and a normalized robust framework, thereby minimizing the aforementioned influences.

Trajectory-Based Parametric Regional Integration Framework:

To quantitatively compare the intensity and spatiotemporal evolution of ionospheric disturbances triggered by different rocket launch events, a unified depletion influence region was defined as the integration area. This aims to eliminate observational geometric disparities and ensure result comparability. The definition of this region is empirically derived from the rocket launch trajectory.

(1)

Definition of the Integration Region:

The rocket’s launch path can be approximated spatially as a great circle trajectory. To encompass the potential diffusion range of the depletion, a band-shaped region was constructed by expanding ±2° in longitude centered on this trajectory. The northern and southern boundaries of this region were fixed at 15°N and 40°N latitude, respectively, thereby delineating a parallelogram-shaped analysis area on the ionospheric single-layer model (IPP height: 350 km). This region is sufficient to cover the primary depletion signals of the four launch events while excluding ionospheric areas far from the trajectory that might be influenced by other factors.

(2)

Parametric Coordinate Transformation and Double Integral:

To perform the integration within this irregular quadrilateral region, a parametric coordinate transformation method was adopted. A vertex of the parallelogram is defined as point A, with two adjacent edge vectors denoted as AB and AC. Any point P within the region can be expressed as follows:

P = A + u ∗ AB + v ∗ AC

where u and v are parametric coordinates within the range [0, 1]. This transformation converts the integration problem from the actual geographic coordinate system (longitude, latitude) into a regular unit square parametric space [0, 1] × [0, 1], significantly simplifying the computation.

(3)

Grid Interpolation of Depletion Values:

The distribution of GNSS Ionospheric Pierce Points (IPPs) within this region is non-uniform. To calculate the total regional depletion integral, the discrete ΔTEC observations must be interpolated onto a regular grid. Linear scattered data interpolation (scatteredInterpolant) was used to compute the depletion values across the entire parametric space grid (e.g., at a resolution of 100 × 100. We tested two grid resolutions: 100 × 100 and 1000 × 1000, corresponding to approximate spatial resolutions of 0.0623° (latitudinal) × 0.25° (longitudinal) and 0.00623° × 0.025°, respectively. As the results showed negligible differences between the two resolutions, the 100 × 100 grid was selected for all subsequent analyses considering computational efficiency, with a final grid size of 0.0623° (latitudinal) × 0.25° (longitudinal).) based on the known ΔTEC values at the parametric coordinates (u, v). For grid points without observational data, the depletion value was set to 0, indicating the absence of disturbance at that point, thereby avoiding extrapolation errors.

(4)

Calculation of the Total Depletion Integral:

After computing the integral on the regular grid, the result from the parametric space was converted back to the actual geographic space using the Jacobian determinant of the double integral. The Jacobian determinant |J| = AB_lat ∗ AC_lonrepresents the conversion factor between a unit area element in parametric space and its corresponding area in the actual geographic space. Therefore, the formula for the total regional depletion integral S_total is as follows:

S_total = |J| ∗ ∬_{[0, 1] × [0, 1]} ΔTEC(u, v) du dv

This integral was efficiently implemented using the trapezoidal numerical integration method (trapz). This integral value quantitatively characterizes the overall intensity of the depletion effect within the region at a specific time, and its time series reveals the complete evolutionary process of the depletion effect.

3. Results

3.1. Ionospheric TEC Depletion

Taking the launch of Zhuque-2Yao-2 on 12 July 2023 at 09:00 LT as an example, the depletion induced by this event was calculated. Through the analysis of a time-series sequence of ionospheric TEC variation maps following the launch (Figure 2), a typical and significant depletion structure triggered by this event is clearly observed. This depletion initiated at the rocket liftoff time, formed and evolved within ~10 min after launch. Its core characteristic manifests as a strong negative phase perturbation, represented by the blue areas in the map sequence, indicating regions of decreased TEC values.

The depletion region exhibits a distinctly asymmetric morphology: its leading edge (i.e., the outward expanding boundary of the depletion) displays an extremely steep gradient, reflecting the intense and instantaneous interaction between the rocket exhaust plume and ionospheric plasma, which causes a rapid decrease in electron density over a short period. In contrast, its trailing edge (i.e., the recovering side of the depletion) is relatively gradual, demonstrating the slower process of electron density gradually returning to background levels after the disturbance. This asymmetric structure—”steep leading edge and gentle trailing edge”—is a key signature distinguishing rocket launch disturbances from other natural phenomena.

Spatiotemporally, the path of the depletion region highly aligns with the rocket’s flight trajectory, visually reproducing the continuous influence process as the rocket traversed the ionosphere. These analytical results robustly validate the unique advantages of the MRMIT method in detecting such abrupt disturbances, completely and reliably revealing the specific perturbation effects on the ionosphere caused by a liquid oxygen/methane propellant rocket.

Furthermore, to investigate the ionospheric depletion characteristics induced by rockets utilizing different propellants, the results are presented in Figure 3.

Figure 3 clearly illustrates the spatiotemporal evolution characteristics of the ionospheric Total Electron Content (TEC) depletion following the four rocket launch events, as well as the differential effects produced by different propellants. Temporally, all four events exhibit a common evolutionary pattern: at 15 min post-launch, the depletion effect rapidly forms and reaches its maximum intensity, manifested as the deepest blue and most concentrated area in the figure, which directly corroborates the intense and instantaneous interaction between the rocket exhaust plume and the ionosphere during the ascent phase. By 30 min post-launch, the core intensity of the depletion region begins to weaken (indicated by lighter blue), but its spatial extent significantly expands and diffuses along the rocket trajectory, exhibiting a more dispersed morphology. At 45 min post-launch, the depletion effect further attenuates, with its contours becoming increasingly blurred and gradually merging into the background ionosphere, revealing the slow recovery process of electron density following the disturbance.

Despite the similar temporal evolution pattern, differences in depletion characteristics exist among the propellants. As observed in Figure 3, the depletion event on DOY 193 at 9:00 local time in the morning during the Zhuque-2 launch exhibits a smaller spatial extent and faster recovery. At 15 min post-launch, its depletion core demonstrates extreme intensity (deep blue) with sharp and well-defined boundaries, consistent with the asymmetric structure featuring a steep leading edge described previously. However, in subsequent periods, the attenuation rate of its depletion intensity and the diffusion rate of its spatial extent are slightly faster than those of the other three events. By 45 min post-launch, the depletion signature has substantially diminished. This may be attributed to the combustion products (primarily H₂O and CO₂), which, despite their strong instantaneous effect, possess relatively simpler composition and lower chemical reactivity, resulting in weaker sustained catalytic effects on electron recombination and thus a faster depletion recovery [35,36].

The numbers in the figure denote the Day of Year (DOY); the correspondence between DOY and launch events is detailed in Section 2.1. From left to right, the panels correspond to DOY 058 (CZ-2C), 149 (CZ-4B), 193 (ZQ-2), and 314 (CZ-2C).

Subsequently, we aim to quantitatively characterize this depletion relationship. The trajectory-based parametric regional integration framework, as detailed in Section 2.2 of this paper, was employed for this purpose.

As shown in Figure 4, among the three launch events utilizing unsymmetric dimethylhydrazine (UDMH) propellant, while their depletion integral curves exhibit consistent overall trends, certain differences remain, indicating that both rocket launch mass and local time jointly modulate the intensity and evolutionary characteristics of ionospheric depletion.

From the perspective of launch mass, the Long March-4B (149) had the highest lift-off mass and propellant mass, and its corresponding peak depletion integral value is also the highest within the group. This aligns with the physical expectation that a larger mass entails more ejected material and energy, leading to stronger ionospheric disturbance. In contrast, the two Long March-2C missions (314, 058) had relatively smaller masses, and their peak depletion values are correspondingly slightly lower than that of 149, demonstrating the dominant role of mass in governing disturbance intensity.

Regarding local time (and the corresponding solar irradiation conditions), the local times of the three launches differed: 149 (12:12 LT) occurred during daytime, when ionospheric electron density is higher and the background recovery effect provided by solar radiation is stronger; 314 (11:39 LT) also occurred close to local noon. As illustrated in Figure 5. In comparison, the launch time of Zhuque-2 (193) was 09:00 LT, during the daytime ascending phase of the ionosphere. The stronger solar irradiation at this time may have further accelerated its post-depletion recovery process. The slowest recovery was observed for 058 15:08 LT, which occurred in the local afternoon when solar irradiation intensity gradually decreases, resulting in a weaker recovery effect.

Overall, the depletion amplitudes induced by the Long March series rockets using UDMH propellant (314, 058, 149) were significantly larger than that caused by the liquid oxygen/methane-propelled Zhuque-2 (193). A comparison between the background TEC levels shown in Figure 5 (058 > 314 > 193 > 149) and the actual depletion magnitudes (149 > 058 > 314 > 193) indicates that, for these four events, rocket launch mass was the primary factor influencing depletion intensity, followed by the background ionospheric electron content (for instance, for the same Long March-2C rocket, the background TEC for 058 was higher than for 314, and its depletion magnitude was also larger).

3.2. Traveling Ionospheric Disturbances (TIDs)

Taking the Zhuque-2launch event as an example, we investigated the TIDs induced by the launch. TIDs generated during rocket launches exhibit considerable complexity, potentially originating from multiple excitation sources and possibly involving interference from acoustic-gravity waves of different origins. Additionally, the magnitude of TIDs is significantly lower than that of depletion events, inevitably introducing data noise. To address this, we applied detrending and Savitzky–Golay filtering to extract anomalous signals, and employed a 0.3° × 0.3° grid median method (Chen et al., 2020) [6] to integrate spatial disturbance information, thereby minimizing noise interference as much as possible.

As shown in Figure 6, panel (a) depicts the spatiotemporal distribution of TIDs 20 min after the Zhuque-2launch, with the blue dashed line indicating the approximate rocket trajectory. Lines b, c, and d represent tangent lines to the trajectory at 35°N, 30°N, and 25°N, respectively. Subpanels (b–d) display TID cross-sections along these three lines. As illustrated, distinct Traveling Ionospheric Disturbances (TIDs) propagating along the rocket trajectory direction are clearly identifiable within 6 min after the Zhuque-2launch. These disturbances exhibit a typical wavelike structure, demonstrating pronounced directionality and spatial expansion characteristics.

Analysis of the disturbance profiles along the 35°N, 30°N, and 25°N tangents (Figure 6b–d) provides detailed insights into the characteristics of Traveling Ionospheric Disturbances (TIDs) induced by the Zhuque-2 rocket launch. The results indicate that TIDs exhibit a consistent propagation trend across these latitude bands, primarily expanding outward along the rocket’s trajectory with a distinct wavelike structure. This propagation pattern aligns with the expected behavior of acoustic-gravity waves triggered by the rocket’s ascent through the ionosphere. However, notable variations in the amplitude and waveform morphology of the TIDs are observed across the different latitudes. These variations are attributed to the complex interplay of several factors, including background ionospheric electron density gradients, neutral atmospheric dynamics, and the geomagnetic field configuration, which collectively modulate the disturbance characteristics during propagation.

Specifically, the TID waveforms display a characteristic “V-shaped” pattern, a hallmark of rocket-induced ionospheric disturbances, reflecting the rapid onset and subsequent recovery of the perturbation as the acoustic-gravity waves propagate. At higher latitudes (e.g., 35°N), the TID amplitudes tend to be more pronounced, likely due to the stronger influence of the geomagnetic field and higher background electron density in the mid-latitude ionosphere. In contrast, at lower latitudes (e.g., 25°N), the amplitudes are relatively subdued, and the waveforms exhibit slight differences in their periodicity and spatial extent, potentially influenced by weaker ionospheric gradients and varying neutral wind patterns. These latitudinal differences underscore the sensitivity of TID morphology to the ionospheric and atmospheric environment through which the disturbances propagate. Furthermore, the V-shaped waveform’s steep leading edge and more gradual trailing edge mirror the asymmetric structure observed in the ionospheric depletion, suggesting a common physical mechanism driven by the rocket’s exhaust plume and associated shock waves. These findings highlight the importance of high-resolution, multi-latitudinal observations to capture the nuanced spatial and temporal evolution of TIDs and their dependence on environmental factors.

To verify the reliability of the multi-step filtering procedure in extracting Traveling Ionospheric Disturbances and to rule out potential artifacts such as Gibbs ringing, a control experiment was designed (for details, see Supplementary Figure S1). In this experiment, the original TEC data from the same station were processed using Gaussian smoothing to generate a “clean” signal devoid of actual physical disturbances, which was then subjected to the same filtering procedure. The results demonstrate that our multi-step filtering method did not introduce artificial TID-like oscillations or significant ringing artifacts near the rocket launch time when applied to the clean signal. This confirms that the wave-like disturbances observed in this study represent genuine physical signals rather than processing-induced methodological artifacts. Furthermore, the TID signals extracted from all Ionospheric Pierce Points (IPPs) exhibit a distinct V-shaped wave structure (Figure 6e), providing additional supporting evidence for this conclusion.

Similarly, we processed the remaining three launch events using the identical gridding and cross-section methods, with the results presented in Figure 7. This figure systematically illustrates the spatiotemporal evolution characteristics of Traveling Ionospheric Disturbances (TIDs) induced by three distinct rocket launch events (Days of Year [DOY]: 058, 149, 314) across different latitudes (25.0°N, 30.0°N, 35.0°N). In all subplots, the horizontal axis represents local time, the vertical axis denotes propagation distance (km), and color indicates the perturbation amplitude of Differential Total Electron Content (DTEC), with red signifying positive disturbances (TEC increase) and blue indicating negative disturbances (TEC decrease).

Collectively, all three launch events excited distinct wavelike disturbance structures, further confirming that rocket launches constitute a significant anthropogenic source of large-scale TIDs in the ionosphere. Significant differences in disturbance morphology are evident both between launch events and across different latitude bands, reflecting the combined modulation by excitation source characteristics, background ionospheric conditions, and wave propagation processes. Additionally, TIDs from the same launch event exhibit systematic variations across latitudes. Typically, the disturbance pattern at low latitudes (25.0°N) differs from those at mid-latitudes (30.0°N, 35.0°N), likely attributable to the collective influence of rocket launch parameters (e.g., trajectory, exhaust dynamics), background electron density gradients, neutral atmospheric structure, and geomagnetic field configuration on acoustic-gravity wave propagation. All TIDs primarily expanded outward along the rocket trajectory direction, consistent with the physical expectation of rocket-excited wave disturbances. Taken together, these results unequivocally demonstrate that rocket launches can excite TIDs with complex spatiotemporal characteristics, whose specific morphology is jointly controlled by excitation source parameters and the ionospheric background environment.

4. Conclusions

This study employed 370 multi-constellation GNSS stations (including BeiDou GEO IPPs) from the Crustal Movement Observation Network of China (CMONOC) and the Chuan-Dian Experimental Region to analyze four representative rocket launches (Days of Year: 058, 149, 193, 314) from the Jiuquan Satellite Launch Center during 2023–2025. Total Electron Content (TEC) was extracted using IonKit-NH, implementing a combined carrier-phase and pseudorange solution strategy with a 15° elevation mask to suppress multipath effects, cycle slip detection via Melbourne–Wübbena (5 m threshold) and Geometry-Free (0.5 m threshold) combinations, and a single-layer ionospheric model at 350 km height for IPP calculation while retaining receiver DCBs for differential processing. For Traveling Ionospheric Disturbances (TIDs), a 4th-order Savitzky–Golay filter with a 121-point window and a 0.3° × 0.3° grid median method was applied. For depletion extraction, the Multi-Rolling-Multi-Image-Tracking (MRMIT, roller/rock method) was adopted, with total depletion magnitude quantified via parametric coordinate transformation, scattered Interpolant-based interpolation (100 × 100 grid), and trapezoidal numerical integration over a band-shaped region (±2° longitude, 15–40° latitude) centered on the launch great-circle trajectory, enabling cross-event quantitative comparisons. The primary ionospheric depletion originates from engine emissions at altitudes above approximately 170 km (a region dominated by O⁺), and mainly stems from the second and higher stages. Through a detailed analysis of the propellant mass of each rocket model’s stages (Zhuque-2 s stage: ≈35–45 t; Long March-2C second stage: 54.7 t; Long March-4B second stage: 52.7 t, third stage: 12.8 t), it is evident that their mass ranges are comparable. This further supports our research conclusion that the mass of the upper stages is the dominant factor driving depletion intensity, while the chemical composition of the propellant and the local time of launch primarily modulate the duration and recovery characteristics of the depletion, which is consistent with the overall findings.

The sources of the stage propellant mass data used in this study are as follows: The propellant mass data for the Long March-2C (CZ-2C) second stage (54,667 kg) were obtained from the standard rocket specifications published by the China Aerospace Science and Technology Corporation (CGWIC), as well as publicly available information from authoritative aerospace databases such as NASA Spaceflight and Astronautix. These are actual published values, not estimates. The data for the Long March-4B (CZ-4B) second and third stages (52,700 kg and 12,814 kg, respectively) also originated from CGWIC and Astronautix, representing actual values under their standard configurations. The Zhuque-2 is a commercial rocket, and the propellant mass of its second stage has not been fully disclosed. The value of 35–45 t presented in the paper is a reasonable estimate based on factors such as the total propellant proportion, engine thrust, and SSO mission payload requirements. Although there is some uncertainty, cross-validation with the design parameters of similar rockets and mission requirements confirms that this estimated value has high credibility, sufficiently supporting the rigor of the analysis regarding the comparability of upper-stage mass and depletion intensity in this paper.

Findings reveal that all events exhibited depletion formation within ~10–15 min post-launch, peaking at ~30 min, followed by attenuation and diffusion over 30–45 min, Quantitatively, launch mass dominated depletion intensity (strongest for the heaviest rocket, DOY 149), while propellant chemistry (UDMH-based propellants > liquid oxygen/methane) and local time/background TEC (higher TEC amplified depletion magnitude but accelerated recovery) jointly modulated depletion amplitude and recovery rate. This time delay phenomenon primarily stems from the interaction mechanism between rocket exhaust and ionospheric plasma: Firstly, it takes a certain amount of time for the rocket to ascend to the main ionospheric altitudes (above approximately 170 km), and components in the exhaust such as water vapor and carbon dioxide require time to consume O⁺ ions through charge exchange and dissociative recombination reactions—the rate of these chemical reactions limits the instantaneous formation of depletion. Finally, the attenuation phase primarily reflects the physical process through which the background ionosphere gradually restores equilibrium via photoionization. Under conditions of intense solar radiation during daytime, photoionization provides a strong and relatively stable source of electrons, whose recovery rate is predominantly determined by solar radiation intensity rather than the initial depth of the depletion event. This observation explains why similar recovery timescales were observed across depletion events of varying depths. Meanwhile, plasma transport effects co-act in the process, but their modulation of the recovery timescale is likely masked by this dominant mechanism of photoionization.

Methodologically, integrating MRMIT for depletion identification and constructing a trajectory-based integral framework constitute primary innovations, while multi-constellation GNSS and GEO IPPs enhanced spatiotemporal resolution. Limitations persist: the single-layer model neglects vertical ionospheric structure; zero-filling unobserved grid points may yield conservative estimates; limited sample size and a single launch site constrain independent decoupling of propellant/mass/local time interactions; and direct neutral/ion chemistry observations are lacking to validate chemical mechanisms. Future work should advance multi-layer height-resolved inversions and multi-source observation integration; conduct coupled chemical-dynamic simulations to elucidate propellant-specific effects on electron recombination; expand event coverage across seasons and launch sites for statistical attribution; perform systematic sensitivity testing of MRMIT parameters and algorithm robustness with blind method comparisons; explore applications in launch site environmental impact assessments and GNSS service safeguards (e.g., real-time disturbance detection algorithms, launch-phase GNSS risk alerts); and foster interdisciplinary collaboration among aerospace engineering, environmental science, and space physics to establish a predictive and operational rocket-ionosphere coupling assessment framework.

5. Discussion

Although this study successfully captured the characteristics of rocket-induced ionospheric disturbances through multi-source GNSS observations and an innovative methodological framework, several limitations remain, which not only affect the precision and generalizability of the current results but also point to directions for future optimization. First, the adoption of a single-layer ionospheric model simplifies vertical structure analysis, potentially underestimating height-dependent dynamics of depletion and TIDs [2,14]. For instance, in the O⁺-dominated region above 170 km altitude, chemical reactions from upper-stage emissions may exhibit significant gradients at different heights, while the 350 km IPP assumption in this study overlooks this vertical heterogeneity, potentially leading to conservative estimates of total depletion intensity in the integration framework. Second, the zero-filling strategy for grids, while avoiding extrapolation errors, may introduce systematic biases in edge regions with sparse IPP coverage, particularly at the low-latitude end of the trajectory band (±2° longitude around 15°N), which could amplify background noise interference on low-amplitude TIDs. Moreover, the limited sample size (only four events) and single launch site (Jiuquan Center) constrain statistical decoupling of variable interactions: the synergistic effects of propellant type, launch mass, and local time are difficult to isolate independently, and variations across seasons/solar activity cycles are not covered, potentially missing comparative effects in regions like the auroral zone or Equatorial Ionization Anomaly [15,18]. Finally, the absence of direct chemical observations (e.g., neutral gas diffusion simulations or in situ ion probes) limits mechanism validation; for example, differences in catalytic pathways between NOx and H₂O are inferred from the literature [36,37] but not confirmed through measured coupled simulations. Furthermore, an important limitation regarding the estimation of depletion duration must be considered. Although the MRMIT method is robust in identifying the steep leading edge of the depletion, it may introduce a systematic bias in determining the precise end time of the depletion. The gentle slope of the recovery phase (trailing edge) means that the ΔTEC signal becomes weak and exhibits a very small temporal gradient as it approaches its end. When analyzing data from GEO satellites with fixed IPPs, the amplitude of this weak signal in the final stage of recovery may be on the same order of magnitude as the background noise and residual trends. Consequently, the MRMIT algorithm may cease tracking the depletion before it has fully recovered to the background level, which could lead to an underestimation of the total depletion lifetime. Future work should incorporate observations from multiple satellite constellations (with moving IPPs) to better constrain the recovery trajectory and employ more sophisticated background modeling techniques to enhance the fidelity of endpoint detection.

These limitations highlight opportunities for methodological and observational enhancements, while underscoring the necessity of interdisciplinary integration. From an applied perspective, the results have practical implications for assessing the impact of frequent rocket launches on GNSS reliability: in the commercial space era, depletion-induced TEC drops can cause positioning errors of several meters [10,22], and far-field TID propagation may disrupt regional aeronautical navigation. Looking ahead, priority should be given to advancing multi-layer height-resolved inversion techniques, such as integrating Incoherent Scatter Radar (ISR) and three-dimensional Computerized Ionospheric Tomography (CIT) [14], to capture vertical evolution; developing coupled chemical-dynamic models (e.g., extending Feng et al. (2021) [5]’s exhaust diffusion simulations) to quantify propellant-specific contributions to electron recombination; expanding datasets to global multi-launch sites and full-seasonal coverage for machine learning-assisted statistical attribution analyses to decouple multifactor interactions [19,20,21]. Additionally, systematic sensitivity testing of MRMIT parameters (e.g., 1 TECU vs. 3 TECU threshold) and blind comparisons with other filtering methods (e.g., Savitzky–Golay or wavelet transforms) should be conducted to enhance algorithmic robustness [28]. On the application front, real-time disturbance monitoring algorithms could be developed and integrated into GNSS augmentation systems (e.g., WAAS) to provide risk alerts during launch phases [38,39]; furthermore, fostering collaboration between aerospace engineering and space physics could establish standardized protocols for rocket-ionosphere impact assessments, including Environmental Impact Assessments (EIA) and guidelines for sustainable space activities. These efforts will not only deepen understanding of anthropogenic space weather but also support policy-making under the United Nations framework for sustainable space utilization.