中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and
Geophysical Fluid Dynamics (LASG)
Institute of Atmospheric Physics, Chinese Academy of Sciences
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and
Geophysical Fluid Dynamics (LASG)
Institute of Atmospheric Physics, Chinese Academy of Sciences
![](http://project.lasg.ac.cn/NewsLetter/skin/News Letter.png)
Vol.18/No.18 December 2022
LASG Carbon Cycle and Climate Change Team Participated in OCO2MIP Project and Provided National Scale Carbon Budget Estimation for IPCC
The COLA system integrated state-of-the-science data assimilation techniques such as a four-dimensional local ensemble Kalman filter with a short assimilation window and a long observation window, a constrained ensemble Kalman filter, and a time-lagged prior additive inflation method. COLA can efficiently estimate high spatiotemporal (e.g., daily and grided) carbon flux based on these techniques.
As the only Chinese inversion system, COLA participated in the OCO-2 v10 flux model intercomparison project (OCO2MIP) and conducted several standardized assimilation experiments following the MIP protocol. The assimilation results are then carefully evaluated by the MIP colleagues and compared with those from other inversion systems. Our inversion results are shown to be well consistent with independent evaluation observations. One of the MIP principals said that he was impressed by the performance of COLA, and the results were definitely within the envelope.
The OCO2MIP results were carefully analyzed and were submitted to the UNFCCC as a pilot "top-down" estimation of the country-level carbon budget.
https://ceos.org/gst/carbon-dioxide.html
Add: No.40, Huayanli, Beichen West Road, Chaoyang District, Beijing P.O. Box 9804, 100029, China
E-mail: lasg_newsletter@lasg.iap.ac.cn
Editors: Chuanyi Wang (wangcy@lasg.iap.ac.cn), Kangjun Chen(ckj@lasg.iap.ac.cn)
E-mail: lasg_newsletter@lasg.iap.ac.cn
Editors: Chuanyi Wang (wangcy@lasg.iap.ac.cn), Kangjun Chen(ckj@lasg.iap.ac.cn)