The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS)
<p>Top-down inversions of China's terrestrial carbon sink are known to be uncertain because of errors related to the relatively coarse resolution of global transport models and the sparseness of in situ observations. Taking advantage of regional chemistry transport models for mesoscale si...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-06-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/23/6719/2023/acp-23-6719-2023.pdf |
| Summary: | <p>Top-down inversions of China's terrestrial carbon sink are known to be uncertain because of errors related to the relatively coarse resolution of
global transport models and the sparseness of in situ observations. Taking advantage of regional chemistry transport models for mesoscale
simulation and spaceborne sensors for spatial coverage, the Greenhouse Gases Observing Satellite (GOSAT) retrievals of column-mean dry mole fraction of carbon dioxide (<span class="inline-formula">XCO<sub>2</sub></span>) were introduced in the Models-3 (a flexible software framework) Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS)-based regional inversion system to constrain China's biosphere sink at a spatiotemporal resolution of 64 <span class="inline-formula">km</span> and 1 <span class="inline-formula">h</span>. In general, the annual, monthly, and daily variation in biosphere flux was reliably delivered, attributable to the novel flux forecast model, reasonable CMAQ background simulation, well-designed observational operator, and Joint Data Assimilation Scheme (JDAS) of <span class="inline-formula">CO<sub>2</sub></span> concentrations and natural fluxes. The size of the assimilated biosphere sink in China was <span class="inline-formula">−</span>0.47 <span class="inline-formula">Pg C yr<sup>−1</sup></span>, which was comparable with most global estimates (i.e., <span class="inline-formula">−</span>0.27 to <span class="inline-formula">−</span>0.68 <span class="inline-formula">Pg C yr<sup>−1</sup></span>). Furthermore, the seasonal patterns were recalibrated well, with a growing season that shifted earlier in the year over central and south China. Moreover, the provincial-scale biosphere flux was re-estimated, and the difference between the a posteriori and a priori flux ranged from <span class="inline-formula">−</span>7.03 <span class="inline-formula">Tg C yr<sup>−1</sup></span> in Heilongjiang to 2.95 <span class="inline-formula">Tg C yr<sup>−1</sup></span> in Shandong. Additionally, better performance of the a posteriori flux in contrast to the a priori flux was statistically detectable when the simulation was fitted to independent observations, indicating sufficient to robustly constrained state variables and improved fluxes estimation. This study serves as a basis for future fine-scale top-down carbon assimilation.</p> |
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| ISSN: | 1680-7316 1680-7324 |