使用全球欧拉-拉格朗日耦合大气模式(GELCA)的CO2年代际反演:对地面观测网的敏感性。

IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
T Shirai, M Ishizawa, R Zhuravlev, A Ganshin, D Belikov, M Saito, T Oda, V Valsala, A J Gomez-Pelaez, R Langenfelds, S Maksyutov
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引用次数: 10

摘要

我们提出了一个利用全球欧拉-拉格朗日耦合大气模式(GELCA)的大气二氧化碳(CO2)同化系统,并证明了其捕获观测到的大气CO2混合比和估算CO2通量的能力。利用GELCA中高效的数据处理方案,我们的系统将观测数据产品(如观测包(ObsPack)数据产品)中的非平滑CO2数据吸收为地表通量的约束。我们进行了敏感性测试,以检验地点选择和观测的先前不确定性设置对反演结果的影响。对于这些灵敏度测试,我们从ObsPack产品中选择了五个不同的站点/数据。在所有情况下,全球大气CO2净通量的时间序列与根据观测到的全球平均大气CO2混合比的增长率计算出的值保持接近。在区域尺度上,根据选择同化的CO2数据,估算的季节CO2通量发生了变化。在区域尺度上确定不确定性降低(URs),并在病例之间进行比较。作为模型-数据不匹配的度量,我们使用了模型-数据偏差、均方根误差和线性相关性。对于大多数观测点,模型与数据的不匹配相当小。关于区域通量估算,热带亚洲是受观测网络设置显著影响的区域之一。我们发现,亚洲热带地区的地表通量对太平洋上空飞机测量值的使用最为敏感,当飞机测量值被同化后,季节周期与自下而上的研究结果更加吻合。这些结果证实了这些飞机观测的重要性,特别是对热带地区地表通量的限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A decadal inversion of CO<sub>2</sub> using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network.

A decadal inversion of CO<sub>2</sub> using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network.

A decadal inversion of CO<sub>2</sub> using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network.

A decadal inversion of CO2 using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network.

We present an assimilation system for atmospheric carbon dioxide (CO2) using a Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), and demonstrate its capability to capture the observed atmospheric CO2 mixing ratios and to estimate CO2 fluxes. With the efficient data handling scheme in GELCA, our system assimilates non-smoothed CO2 data from observational data products such as the Observation Package (ObsPack) data products as constraints on surface fluxes. We conducted sensitivity tests to examine the impact of the site selections and the prior uncertainty settings of observation on the inversion results. For these sensitivity tests, we made five different site/data selections from the ObsPack product. In all cases, the time series of the global net CO2 flux to the atmosphere stayed close to values calculated from the growth rate of the observed global mean atmospheric CO2 mixing ratio. At regional scales, estimated seasonal CO2 fluxes were altered, depending on the CO2 data selected for assimilation. Uncertainty reductions (URs) were determined at the regional scale and compared among cases. As measures of the model-data mismatch, we used the model-data bias, root-mean-square error, and the linear correlation. For most observation sites, the model-data mismatch was reasonably small. Regarding regional flux estimates, tropical Asia was one of the regions that showed a significant impact from the observation network settings. We found that the surface fluxes in tropical Asia were the most sensitive to the use of aircraft measurements over the Pacific, and the seasonal cycle agreed better with the results of bottom-up studies when the aircraft measurements were assimilated. These results confirm the importance of these aircraft observations, especially for constraining surface fluxes in the tropics.

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期刊介绍: Tellus B: Chemical and Physical Meteorology along with its sister journal Tellus A: Dynamic Meteorology and Oceanography, are the international, peer-reviewed journals of the International Meteorological Institute in Stockholm, an independent non-for-profit body integrated into the Department of Meteorology at the Faculty of Sciences of Stockholm University, Sweden. Aiming to promote the exchange of knowledge about meteorology from across a range of scientific sub-disciplines, the two journals serve an international community of researchers, policy makers, managers, media and the general public.
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