抄録
We introduce a Multi-mOdel Multi-cOnstituent Chemical data assimilation (MOMO-Chem) framework that directly accounts for model error in transport and chemistry, and we integrate a portfolio of data assimilation analyses obtained using multiple forward chemical transport models in a state-of-the-art ensemble Kalman filter data assimilation system. The data assimilation simultaneously optimizes both concentrations and emissions of multiple species through ingestion of a suite of measurements (ozone, <span classCombining double low line"inline-formula">NO2</span>, CO, <span classCombining double low line"inline-formula">HNO3</span>) from multiple satellite sensors. In spite of substantial model differences, the observational density and accuracy was sufficient for the assimilation to reduce the multi-model spread by 20 %-85 % for ozone and annual mean bias by 39 %-97 % for ozone in the middle troposphere, while simultaneously reducing the tropospheric <span classCombining double low line"inline-formula">NO2</span> column biases by more than 40 % and the negative biases of surface CO in the Northern Hemisphere by 41 %-94 %. For tropospheric mean OH, the multi-model mean meridional hemispheric gradient was reduced from <span classCombining double low line"inline-formula">1.32±0.03</span> to <span classCombining double low line"inline-formula">1.19±0.03</span>, while the multi-model spread was reduced by 24 %-58 % over polluted areas. The uncertainty ranges in the a posteriori emissions due to model errors were quantified in 4 %-31 % for <span classCombining double low line"inline-formula">NOx</span> and 13 %-35 % for CO regional emissions. Harnessing assimilation increments in both <span classCombining double low line"inline-formula">NOx</span> and ozone, we show that the sensitivity of ozone and <span classCombining double low line"inline-formula">NO2</span> surface concentrations to <span classCombining double low line"inline-formula">NOx</span> emissions varied by a factor of 2 for end-member models, revealing fundamental differences in the representation of fast chemical and dynamical processes. A systematic investigation of model ozone response and analysis increment in MOMO-Chem could benefit evaluation of future prediction of the chemistry-climate system as a hierarchical emergent constraint.
.本文言語 | 英語 |
---|---|
論文番号 | 9312020 |
ページ(範囲) | 931-967 |
ページ数 | 37 |
ジャーナル | Atmospheric Chemistry and Physics |
巻 | 20 |
号 | 2 |
DOI | |
出版ステータス | 出版済み - 1月 24 2020 |
!!!All Science Journal Classification (ASJC) codes
- 大気科学