| DOI: | 10.2172/1144723
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| 报告号: | DOE-UCB-64436
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| 报告题名: | Final report on "Carbon Data Assimilation with a Coupled Ensemble Kalman Filter" |
| 作者: | Kalnay, Eugenia; Kang, Ji-Sun; Fung, Inez
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| 出版年: | 2014
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| 发表日期: | 2014-07-23
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| 国家: | 美国
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| 语种: | 英语
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| 英文关键词: | LETKF
; ensemble Kalman filter
; CAM
; assimilation
; carbon fluxes
|
| 中文主题词: | 碳
; 铅
|
| 主题词: | CARBON
; LEAD
|
| 英文摘要: | We proposed (and accomplished) the development of an Ensemble Kalman Filter (EnKF) approach for the estimation of surface carbon fluxes as if they were parameters, augmenting the model with them. Our system is quite different from previous approaches, such as carbon flux inversions, 4D-Var, and EnKF with approximate background error covariance (Peters et al., 2008). We showed (using observing system simulation experiments, OSSEs) that these differences lead to a more accurate estimation of the evolving surface carbon fluxes at model grid-scale resolution. The main properties of the LETKF-C are: a) The carbon cycle LETKF is coupled with the simultaneous assimilation of the standard atmospheric variables, so that the ensemble wind transport of the CO2 provides an estimation of the carbon transport uncertainty. b) The use of an assimilation window (6hr) much shorter than the months-long windows used in other methods. This avoids the inevitable âblurringâ of the signal that takes place in long windows due to turbulent mixing since the CO2 does not have time to mix before the next window. In this development we introduced new, advanced techniques that have since been adopted by the EnKF community (Kang, 2009, Kang et al., 2011, Kang et al. 2012). These advances include âvariable localizationâ that reduces sampling errors in the estimation of the forecast error covariance, more advanced adaptive multiplicative and additive inflations, and vertical localization based on the time scale of the processes. The main result has been obtained using the LETKF-C with all these advances, and assimilating simulated atmospheric CO2 observations from different observing systems (surface flask observations of CO2 but no surface carbon fluxes observations, total column CO2 from GoSAT/OCO-2, and upper troposphere AIRS retrievals). After a spin-up of about one month, the LETKF-C succeeded in reconstructing the true evolving surface fluxes of carbon at a model grid resolution. When applied to the CAM3.5 model, the LETKF gave very promising results as well, although only one month is available. |
| URL: | http://www.osti.gov/scitech/servlets/purl/1144723
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| Citation statistics: |
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| 资源类型: | 研究报告
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/41475
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| Appears in Collections: | 过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响
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| 1144723.pdf（1115KB） | 研究报告 | -- | 开放获取 | | View
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| Recommended Citation: | |
Kalnay, Eugenia,Kang, Ji-Sun,Fung, Inez. Final report on "Carbon Data Assimilation with a Coupled Ensemble Kalman Filter". 2014-01-01.
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