Assessing the consistency of X CO ₂ products from DQ-1 ACDL and passive satellites using a unified comparison framework
- 1Wuhan University (Wuhan, China)
Abstract
Da Qi-1 (DQ-1) carries the Aerosol and Carbon Dioxide Lidar (ACDL), a spaceborne integrated path differential absorption (IPDA) lidar that retrieves the column-averaged dry-air mole fraction of carbon dioxide ( X CO ₂ ) using active laser measurements. Unlike passive near-infrared/shortwave-infrared sensors that rely on reflected sunlight, ACDL can observe at night and high latitudes, but its sampling and effective column definition differ from passive X CO ₂ products. Evaluation is therefore needed before active and passive observations can be interpreted jointly. We compare DQ-1 ACDL with the Orbiting Carbon Observatory (OCO-2 and OCO-3) and Greenhouse gases Observing SATellite (GOSAT and GOSAT-2) missions from June 2022–December 2024 using a unified framework that combines Copernicus Atmosphere Monitoring Service (CAMS)-based coherence assessment, sampling availability, daily 2° aggregation, spatiotemporal collocation, and correction for X CO ₂ column-definition differences. Validation against the Total Carbon Column Observing Network (TCCON) gives R =0.92, a mean bias of 0.21 ppm, and a root-mean-square error (RMSE) of 1.49 ppm for daytime DQ-1, comparable to GOSAT. Over coherent and well-sampled regions, DQ-1 is broadly consistent with OCO-2 and OCO-3, with mean differences generally below 0.5 ppm and similar spatial and meridional structures. Over ocean, the DQ-1–OCO differences vary with surface reflectance and wind speed, with different reflectance relationships for OCO-2 and OCO-3. Nighttime DQ-1 is also broadly consistent with CAMS-derived X CO ₂ . Regional analyses show complementary DQ-1 coverage where passive observations are limited. These results support DQ-1 ACDL as a quantitatively comparable and complementary component of the satellite X CO ₂ observing system.
Versions
Related
- Quality Consistency Assessment among MODIS, MERSI, and VIIRS Cloud Mask Products using China’s Space-borne Lidar ACDL
- Hydrometeorological Consistency and Structural Differences in High-Resolution Atmospheric Forcing Products over the Gulf Coast
- From manual classification to transformer-based language models: assessing the quality and consistency of historical convective event records
- Evapotranspiration in tropical basins of Madagascar: A water-balance consistency assessment of different products
- GLAMODAT (v1.0): a model-data comparison tool for assessing transient palaeoglacier simulations
BibTeX
@article{wang2026assessing,
title = {{Assessing the consistency of X CO ₂ products from DQ-1 ACDL and passive satellites using a unified comparison framework}},
author = {Yike Wang and Ge Han and Hongyuan Zhang and Yiyang Huang and Kangjie Zhou and Wei Gong},
journal = {Atmospheric Chemistry and Physics},
year = {2026},
month = oct,
doi = {10.5194/acp-26-14793-2026},
url = {https://acp.copernicus.org/articles/26/14793/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Assessing the consistency of X CO ₂ products from DQ-1 ACDL and passive satellites using a unified comparison framework
AU - Yike Wang
AU - Ge Han
AU - Hongyuan Zhang
AU - Yiyang Huang
AU - Kangjie Zhou
AU - Wei Gong
PY - 2026
DA - 2026/10/21
JO - Atmospheric Chemistry and Physics
DO - 10.5194/acp-26-14793-2026
UR - https://acp.copernicus.org/articles/26/14793/2026/
AB - Da Qi-1 (DQ-1) carries the Aerosol and Carbon Dioxide Lidar (ACDL), a spaceborne integrated path differential absorption (IPDA) lidar that retrieves the column-averaged dry-air mole fraction of carbon dioxide ( X CO ₂ ) using active laser measurements. Unlike passive near-infrared/shortwave-infrared sensors that rely on reflected sunlight, ACDL can observe at night and high latitudes, but its sampling and effective column definition differ from passive X CO ₂ products. Evaluation is therefore needed before active and passive observations can be interpreted jointly. We compare DQ-1 ACDL with the Orbiting Carbon Observatory (OCO-2 and OCO-3) and Greenhouse gases Observing SATellite (GOSAT and GOSAT-2) missions from June 2022–December 2024 using a unified framework that combines Copernicus Atmosphere Monitoring Service (CAMS)-based coherence assessment, sampling availability, daily 2° aggregation, spatiotemporal collocation, and correction for X CO ₂ column-definition differences. Validation against the Total Carbon Column Observing Network (TCCON) gives R =0.92, a mean bias of 0.21 ppm, and a root-mean-square error (RMSE) of 1.49 ppm for daytime DQ-1, comparable to GOSAT. Over coherent and well-sampled regions, DQ-1 is broadly consistent with OCO-2 and OCO-3, with mean differences generally below 0.5 ppm and similar spatial and meridional structures. Over ocean, the DQ-1–OCO differences vary with surface reflectance and wind speed, with different reflectance relationships for OCO-2 and OCO-3. Nighttime DQ-1 is also broadly consistent with CAMS-derived X CO ₂ . Regional analyses show complementary DQ-1 coverage where passive observations are limited. These results support DQ-1 ACDL as a quantitatively comparable and complementary component of the satellite X CO ₂ observing system.
SN - 1680-7324
ER -