Averaging Scheme for the Aerosol and Carbon Detection Lidar Onboard DaQi-1 Satellite

Atmospheric carbon dioxide (CO 2 ) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing (ERF). Active remote-sensing technique using differential absorption Lidar (DIAL) is recognized as the most promising remote sensing means...

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Published inIEEE transactions on geoscience and remote sensing Vol. 62; p. 1
Main Authors Cao, Xifeng, Zhang, Xingying, Zhang, Lu, Zhou, Minqiang, Jiang, Yuhan, Liu, Jiqiao, Cheng, Tiantao, Fan, Chuncan, Chen, Cheng, Chen, Lin
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract Atmospheric carbon dioxide (CO 2 ) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing (ERF). Active remote-sensing technique using differential absorption Lidar (DIAL) is recognized as the most promising remote sensing means for atmospheric carbon dioxide measurements. The Aerosol and Carbon Detection Lidar (ACDL) instrument onboard the DQ-1 is dedicated to quantifying the global spatial distribution of atmospheric CO 2 . To meet the requirement of accuracy and precision, a reasonable averaging scheme for ACDL measurements is needed to minimize the effect of random noise of observations on CO 2 retrievals. In this study, three averaging schemes were conducted in the retrieval process: averaging of CO 2 columns (AVX), averaging of differential absorption optical depth (AVD), and averaging of signals (AVS). The performances were compared at three representative sites. The experiments were first carried out on simulations. The results show that the optimal size of the averaging window is 50 km, corresponding to an averaging of measurements over 150 pulse pairs. In addition, the AVX and AVD schemes are less affected by altitude variations and can be applied to surfaces with moderate and severe topographic variation, such as hills and mountains. Whereas the AVS method is more suitable for surfaces with slight topographic variation, such as oceans, plains, and terraces. Furthermore, the ACDL observations were also retrieved by applying three averaging schemes and validated against ground-based TCCON measurements at Xianghe station. The AVS scheme exhibits better performance than the AVX and AVD methods with the lowest biases of less than 0.5 ppm, which is consistent with the simulation results.
AbstractList Atmospheric carbon dioxide (CO2) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing (ERF). Active remote-sensing technique using differential absorption light detection and ranging (LiDAR) (DIAL) is recognized as the most promising remote sensing means for atmospheric CO2 measurements. The aerosol and carbon detection LiDAR (ACDL) instrument onboard the DaQi-1 (DQ-1) is dedicated to quantifying the global spatial distribution of atmospheric CO2. To meet the requirement of accuracy and precision, a reasonable averaging scheme for ACDL measurements is needed to minimize the effect of random noise of observations on CO2 retrievals. In this study, three averaging schemes were conducted in the retrieval process: averaging of CO2 columns (AVX), averaging of differential absorption optical depth (AVD), and averaging of signals (AVS). The performances were compared at three representative sites. The experiments were first carried out on simulations. The results show that the optimal size of the averaging window is 50 km, corresponding to an averaging of measurements over 150 pulse pairs. In addition, the AVX and AVD schemes are less affected by altitude variations and can be applied to surfaces with moderate and severe topographic variation, such as hills and mountains, whereas the AVS method is more suitable for surfaces with slight topographic variation, such as oceans, plains, and terraces. Furthermore, the ACDL observations were also retrieved by applying three averaging schemes and validated against ground-based Total Carbon Column Observing Network (TCCON) measurements at the Xianghe station. The AVS scheme exhibits better performance than the AVX and AVD methods with the lowest biases of less than 0.5 ppm, which is consistent with the simulation results.
Atmospheric carbon dioxide (CO 2 ) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing (ERF). Active remote-sensing technique using differential absorption Lidar (DIAL) is recognized as the most promising remote sensing means for atmospheric carbon dioxide measurements. The Aerosol and Carbon Detection Lidar (ACDL) instrument onboard the DQ-1 is dedicated to quantifying the global spatial distribution of atmospheric CO 2 . To meet the requirement of accuracy and precision, a reasonable averaging scheme for ACDL measurements is needed to minimize the effect of random noise of observations on CO 2 retrievals. In this study, three averaging schemes were conducted in the retrieval process: averaging of CO 2 columns (AVX), averaging of differential absorption optical depth (AVD), and averaging of signals (AVS). The performances were compared at three representative sites. The experiments were first carried out on simulations. The results show that the optimal size of the averaging window is 50 km, corresponding to an averaging of measurements over 150 pulse pairs. In addition, the AVX and AVD schemes are less affected by altitude variations and can be applied to surfaces with moderate and severe topographic variation, such as hills and mountains. Whereas the AVS method is more suitable for surfaces with slight topographic variation, such as oceans, plains, and terraces. Furthermore, the ACDL observations were also retrieved by applying three averaging schemes and validated against ground-based TCCON measurements at Xianghe station. The AVS scheme exhibits better performance than the AVX and AVD methods with the lowest biases of less than 0.5 ppm, which is consistent with the simulation results.
Author Zhang, Lu
Zhang, Xingying
Fan, Chuncan
Chen, Lin
Chen, Cheng
Liu, Jiqiao
Cao, Xifeng
Cheng, Tiantao
Zhou, Minqiang
Jiang, Yuhan
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Snippet Atmospheric carbon dioxide (CO 2 ) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative...
Atmospheric carbon dioxide (CO2) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing...
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SubjectTerms Absorption
ACDL instrument
Aerosols
Anthropogenic factors
Anthropomorphism
Atmospheric measurements
averaging scheme
Carbon dioxide
Climate change
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Detection
Differential absorption lidar
Ground-based observation
Laser radar
Lidar
Mountains
Oceans
Optical analysis
Optical thickness
Radiative forcing
Random noise
Remote sensing
Sea measurements
Simulation
Size measurement
Spatial distribution
Surface chemistry
Surface topography
Terraces
Terrain mapping
Topography
Variation
Title Averaging Scheme for the Aerosol and Carbon Detection Lidar Onboard DaQi-1 Satellite
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