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An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO2 Retrievals
Earth and Space Science ( IF 3.1 ) Pub Date : 2021-03-12 , DOI: 10.1029/2020ea001343
Dustin Roten 1 , Dien Wu 2 , Benjamin Fasoli 1 , Tomohiro Oda 3, 4 , John C Lin 1
Affiliation  

A growing constellation of satellites is providing near‐global coverage of column‐averaged CO2 observations. Launched in 2019, NASA’s OCO‐3 instrument is set to provide XCO2 observations at a high spatial and temporal resolution for regional domains (100 × 100 km). The atmospheric column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model is an established method of determining the influence of upwind sources on column measurements of the atmosphere, providing a means of analysis for current OCO‐3 observations and future space‐based column‐observing missions. However, OCO‐3 is expected to provide hundreds of soundings per targeted observation, straining this already computationally intensive technique. This work proposes a novel scheme to be used with the X‐STILT model to generate upwind influence footprints with less computational expense. The method uses X‐STILT generated influence footprints from a key subset of OCO‐3 soundings. A nonlinear weighted averaging is applied to these footprints to construct additional footprints for the remaining soundings. The effects of subset selection, meteorological data, and topography are investigated for two test sites: Los Angeles, California, and Salt Lake City, Utah. The computational time required to model the source sensitivities for OCO‐3 interpretation was reduced by 62% and 78% with errors smaller than other previously acknowledged uncertainties in the modeling system (OCO‐3 retrieval error, atmospheric transport error, prior emissions error, etc.). Limitations and future applications for future CO2 missions are also discussed.

中文翻译:

一种减少空间密集 XCO2 反演随机拉格朗日粒子弥散建模计算时间的插值方法

越来越多的卫星正在提供几乎覆盖全球的柱平均 CO 2观测结果。NASA 的 OCO-3 仪器于 2019 年推出,旨在为区域(100 × 100 km)提供高时空分辨率的XCO 2观测。随机时间反演拉格朗日输运 (X-STILT) 模型的大气柱版本是一种确定迎风源对大气柱测量影响的既定方法,为当前 OCO-3 观测和未来空间提供了一种分析方法基于纵队的观察任务。然而,OCO-3 预计每次目标观测都会提供数百次探测,这给这项计算密集型技术带来了压力。这项工作提出了一种与 X-STILT 模型一起使用的新颖方案,以较少的计算费用生成逆风影响足迹。该方法使用 X-STILT 从 OCO-3 探测的关键子集生成的影响足迹。对这些足迹应用非线性加权平均,以为剩余的探测构建额外的足迹。在两个测试地点(加利福尼亚州洛杉矶和犹他州盐湖城)调查了子集选择、气象数据和地形的影响。对 OCO-3 解释的源敏感性进行建模所需的计算时间减少了 62% 和 78%,误差小于建模系统中其他先前承认的不确定性(OCO-3 检索误差、大气传输误差、先验排放误差等) .)。还讨论了未来 CO 2任务的局限性和未来应用。
更新日期:2021-04-02
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