Update analytical methods to estimate greenhouse gas concentrations
1. Background and purpose
1. Background and purpose
The Greenhouse Gas Observation Satellite (GOSAT) which is a joint mission of the Ministry of the Environment, the National Institute for Environmental Studies (NIES), and the Japan Space Exploration Agency has been making observations almost continuously since it was launched and is currently operational.
Thermal and Near Infrared Sensors for Carbon Observation – GOSAT’s onboard Fourier Transform Spectrometer (TANSO-FTS) observes the shortwave infrared (SWIR) spectrum(*1). The concentrations of carbon dioxide (CO2) and methane (CH4) can be estimated by analyzing the spectra. NIES openly provides this concentration as a level 2 product. In the analysis, observations with clouds in the field of view were not processed because atmospheric particles such as clouds and aerosols are a large source of error in the estimation of greenhouse gas concentrations. Only a few percent of data is available as level 2 data because of this filtering. The updated analytical method changes the cloud treatment to provide an optically contaminated view of wispy clouds. In addition, additional information is also updated. This update was made to increase the amount of greenhouse gas concentration data available and to improve its accuracy.
The analytical method for estimating greenhouse gas concentrations from SWIR spectra observed by GOSAT developed at NIES estimates aerosol-related parameters together to account for their influence which is a large source of uncertainty to the analysis (*2). The updated analysis method is improved to approximate cloud parameters instead of optically rejecting views contaminated by wispy clouds. This update allows us to analyze scenes with optically light clouds that were previously excluded from processing. In addition, we updated the TANSO-FTS sensitivity degradation model (*3), solar radiation spectra, and the greenhouse gas absorption strength database.
Approximately 13 years (from April 2009 to December 2021) the observed spectra of the GOSAT were analyzed using an updated analytical method to estimate CO2 and CH4 concentrations. The results were compared with results from the method prior to the update, data from the ground-based FTS network (TCCON), and data from in situ measurements such as aircraft and ships to evaluate data volume and accuracy.
3. Results and Discussion
A comparative study of the results using the updated method with the TCCON data or the results using the pre-update method revealed that the updated method improves approximately 13% of the amount of CO2 concentration data with approximately the same quality as the pre-update method. land. However, the amount of data decreased by about 20% with a greater negative bias in the oceans. The amount of CH4 data is more or less the same as CO2. The estimated CH4 value of the updated method is generally lower and the accuracy is the same or slightly better than the pre-update method.
It is known that the estimated long-term CO2 growth rate of over-ocean CO2 concentrations from pre-renewal methods is less than that of in situ measurements. A similar evaluation using results from the updated method revealed that the decadal CO2 growth rate over the ocean increased from an estimated 1.68 ppm/decade to 0.01 ppm/decade compared to in situ measurements.
The CO2 and CH4 concentrations estimated by the updated method are planned to be published as V03.00. Improved data can contribute to improving the quality of source/sink products, which are higher level products. On the other hand, product V03.00 has a negative bias towards the oceans. Therefore, we plan to release a bias corrected version as V03.05. Bias may be due to the accuracy of the spectrum fitting (*5). We will continue to improve the method through further analysis to address this issue.
*1: TANSO-FTS observes a spectral region called shortwave infrared (SWIR) near 0.7, 1.6, and 2.0 µm in bands 1 – 3 respectively.
*2: Light that enters the Earth’s atmosphere is reflected by the surface and reaches the satellite. Greenhouse gas observations from SWIR spectra obtained from satellites use the absorption of light in these pathways by gases. Atmospheric particles such as clouds and aerosols change the absorption strength of gases in the observed spectrum through interaction, scattering or absorption. Therefore, an accurate estimate of greenhouse gases needs to take into account their contribution.
*3: The radiometric sensitivity of the TANSO-FTS SWIR band has decreased over time since launch. That is, light of the same intensity entering the sensor optics is observed as a different intensity depending on the launch period. The analytical method for estimating greenhouse gas concentrations developed by NIES takes this issue into account using a degradation model.
*4: Estimates of greenhouse gas concentrations from GOSAT and other satellites are validated with the ground-based FTS network, the Total Carbon Column Observing Network (TCCON; http://www.tccon.caltech.edu/) which has around 30 observation sites worldwide. This dataset has higher accuracy than that from satellite and is suitable for validation studies.
*5: Estimates of greenhouse gas concentrations are based on spectral adjustments between observed and theoretical spectra calculated assuming atmospheric and surface conditions. In this procedure, we search for theoretical spectra that are consistent with the observed spectra by changing target parameters such as greenhouse gas concentrations.
Atmospheric Measurement Techniques
Update to GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm
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