the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 31 Aug 2026
GIFT-BDS: A high-resolution TEC and Gradient Ionospheric Index dataset over China derived from BeiDou GEO fixed-geometry observations
Abstract. High-resolution ionospheric total electron content (TEC) gradient observations are well-suited for characterizing ionospheric spatial structure and for assessing ionospheric effects on Global Navigation Satellite System (GNSS) positioning applications. Existing global ionospheric products provide valuable information on large-scale ionospheric conditions, but their spatial and temporal sampling is generally not sufficient to resolve fine-scale TEC gradient structures over China. We present GIFT-BDS (Gradient Ionospheric index from Fixed-geometry TEC observations using BDS GEO satellites), a high-resolution regional ionospheric dataset derived from a dense ground-based GNSS network and BeiDou geostationary Earth orbit (GEO) fixed-geometry observations. The network consists of more than 200 ground-based GNSS receivers and five BeiDou GEO satellites, providing stable receiver-satellite geometries and repeated sampling of nearly fixed ionospheric pierce points. The released dataset contains two product levels. Level-1 provides 30 s GEO-derived slant TEC (STEC) time series for individual receiver-satellite links. Level-2 provides gridded vertical TEC (VTEC), rate of TEC index (ROTI), Gradient Ionospheric Index (GIX), and directional TEC gradient components. The TEC-gradient products are provided on a 0.25° × 0.25° grid with a temporal resolution of 15 min. The dataset is assessed using STEC stability statistics, internal consistency diagnostics, and comparison with Global Ionospheric Map (GIM) derived gradients. Selected examples illustrate the use of GIFT-BDS for studies of daytime Equatorial Ionization Anomaly (EIA) morphology, nighttime Equatorial Plasma Bubble (EPB) evolution, and ionospheric effects on Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) positioning performance. The dataset is available at https://doi.org/10.5281/zenodo.21090695 (Li et al., 2026a), with daily updates provided at https://data.bdsmart.cn/pub/campaign/iono/. GIFT-BDS extends the currently available ionospheric data resources over China by providing continuous high-resolution observations of TEC and TEC gradients, enabling investigations of ionospheric dynamics, space-weather effects, and GNSS positioning error characterization.
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Status: final response (author comments only)
- RC1: 'Comment on essd-2026-532', Anonymous Referee #1, 11 Sep 2026
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AC1: 'Reply on RC1', Zhiyao Li, 29 Sep 2026
We thank the referee for reviewing our manuscript and for the constructive comments. We have revised the manuscript accordingly and addressed all comments in detail. Please find attached our point-by-point response, including the corresponding revisions made to the manuscript.
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RC2: 'Comment on essd-2026-532', Anonymous Referee #2, 30 Sep 2026
This manuscript presents GIFT-BDS, a regional ionospheric dataset that uses the quasi-fixed geometry of BeiDou GEO observations to provide continuous STEC records and TEC-gradient products over China. The relatively stable ionospheric pierce point geometry offers advantages for monitoring temporal ionospheric variations. The manuscript is generally clear and well organized, and the authors appropriately distinguish short-term STEC stability, internal consistency, and morphological comparisons with GIM-derived products. The application examples illustrate the dataset’s potential for studying regional ionospheric structures and their relationship with GNSS positioning performance. The dataset is of interest to the community, although several aspects of the product definitions, processing procedures, and interpretation would benefit from clarification.
(1) Equation (9) defines GIX using the absolute value of the along-baseline TEC gradient, which is appropriate for describing gradient intensity. However, GIXx and GIXy are subsequently interpreted as signed directional components. Please clarify how the baseline orientation is defined and how the direction of TEC increase is retained when calculating these components. This is particularly relevant to the interpretation of the GIXy sign reversal around the EIA crest.
(2) GIXstd represents the dispersion of pairwise gradient samples within a grid cell. Its value may also depend on the number and geometry of the contributing inter-IPP pairs, and some pairs may share common IPPs. Please clarify that GIXstd is a descriptive measure of within-cell sample variability rather than the statistical uncertainty of the grid-cell mean.
(3) Please explain how the 15-min Level-2 products are generated from the 30-s Level-1 observations. Are they instantaneous samples at 15-min intervals, averages over 15-min windows, or products of another aggregation procedure? The temporal aggregation, time-tag convention, and treatment of missing observations should be specified. Please also clarify whether the minimum requirement of two valid samples per grid cell refers to distinct inter-IPP pairs or includes repeated observations of the same pair.
(4) The positioning examples show an association between enhanced GIX and degraded PPP/NRTK performance. Please clarify whether GIX is intended primarily as an indicator of regional ionospheric conditions or as a quantitative measure of the ionospheric errors affecting these positioning solutions. This distinction matters because the relationship depends on the positioning strategy, observing geometry, and treatment of ionospheric delays. The potential use of GIX for positioning quality control or observation weighting could also be mentioned, while noting that these applications would require further evaluation.
(5) Please clarify whether the same quality-control procedures and thresholds are applied under quiet and disturbed ionospheric conditions. Strong disturbances can produce genuine rapid TEC variations as well as increased tracking problems, making it important to distinguish physical signals from observational errors. It would be helpful to discuss whether these fixed thresholds may reduce data availability during strong disturbances.
Citation: https://doi.org/10.5194/essd-2026-532-RC2 -
AC2: 'Reply on RC2', Zhiyao Li, 03 Oct 2026
We thank the referee for reviewing our manuscript and for the constructive comments. We have revised the manuscript accordingly and addressed all comments in detail. Please find attached our point-by-point response, including the corresponding revisions made to the manuscript.
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AC2: 'Reply on RC2', Zhiyao Li, 03 Oct 2026
Data sets
GIFT-BDS: A high-resolution TEC and Gradient Ionospheric Index dataset over China derived from BeiDou GEO fixed-geometry observations Zhiyao Li et al. https://doi.org/10.5281/zenodo.21090695
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This manuscript introduces GIFT‑BDS, a new regional high‑resolution ionospheric dataset over China built upon more than 200 ground GNSS stations and five BeiDou GEO satellites. Taking advantage of the nearly‑fixed observation geometry of BDS‑GEO, the dataset provides Level‑1 slant TEC time series and Level‑2 gridded products including VTEC, ROTI, and multi‑component Gradient Ionospheric Index (GIX) with 0.25° × 0.25° spatial resolution and 15‑min temporal cadence. The authors comprehensively document network configuration, full processing workflow, quality‑control schemes, internal consistency diagnostics, and benchmark comparison against CAS GIM. Representative science cases further demonstrate its capability for investigating Equatorial Ionization Anomaly (EIA), Equatorial Plasma Bubble (EPB), as well as quantifying ionospheric impacts on PPP and network RTK positioning performance. The paper is well‑structured; methods are clearly described, validation metrics are properly defined, and example applications are illustrative. Overall, this work is suitable for publication in Earth System Science Data after addressing the following minor points.
1. It lacks external independent validation. This might be difficult.
2. The link, Index of /pub/campaign/iono/GIFT-BDS, has no up to date products. It has the same time period as zenodo link. If there is no operational data product available to the users, the significance of the paper is limited.
3. The authors used the CAS-GIM to estimate the receiver bias. I am not sure i understand correctly or not, this might introduce extra errors in the sTEC and TEC gradient estimation since the GIM is relatively smooth. The authors should emphasize this point.
4. In the inter‑IPP pair‑selection, different distance means smooth the gradient in different scale. When the threshold has a wide range, this is also an error source.