Abstract. The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations. Greenhouse gas satellites that are designed to retrieve atmospheric carbon concentrations can help observe seasonal to interannual variations and sources of carbon dioxide. Recent work has shown that these satellites are further applicable beyond their design specifications for directly identifying and quantifying surface emissions at various spatial and temporal scales. For example, simple model translations of atmospheric carbon concentrations to surface carbon exchanges have been used to rapidly estimate surface methane fluxes from satellite observations of methane in the atmosphere. However, less attention has been placed on using satellite column CO₂ retrievals to evaluate surface CO₂ fluxes from the terrestrial biosphere at shorter timescales without more complex inversion models. Such applications could be useful to monitor, in near-real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) satellite retrievals of column-averaged dry air CO₂ (XCO₂) to directly detect and estimate terrestrial biosphere CO₂ flux anomalies using a simple mass balance approach. Using a regional model simulation (CarbonTracker reanalysis) as a testbed, we first demonstrate that a previously developed, simple model can rapidly estimate monthly surface CO₂ flux anomalies from atmospheric XCO₂ estimates in the Western United States. The method is optimal when the chosen study domain is spatially extensive enough to account for atmospheric mixing and has favorable wind conditions with incoming wind contributions primarily from the same region. While errors in individual satellite measurements partially reduce the ability of OCO-2 satellite XCO₂ to estimate more frequent, smaller surface CO₂ flux anomalies, we find that OCO-2 XCO₂ can often detect and estimate larger surface flux anomalies that are due to droughts and heatwaves. OCO-2 is thus useful for near real time monitoring of the monthly ecosystem behavior and health. Any noise reduction in forthcoming greenhouse gas satellites and/or the existence of large surface carbon anomalies will likely enhance the ability to rapidly estimate surface fluxes at shorter timescales scales.

中文翻译：

---

使用 OCO-2 柱 CO2 反演快速检测和估计生物圈表面碳通量异常

摘要。由于大气中碳浓度的增加，全球碳循环正在经历持续的扰动。旨在检索大气碳浓度的温室气体卫星可以帮助观察二氧化碳的季节性到年际变化和来源。最近的工作表明，这些卫星在其设计规范之外进一步适用于直接识别和量化各种空间和时间尺度的表面排放。例如，大气碳浓度到地表碳交换的简单模型转换已被用于根据对大气中甲烷的卫星观测快速估计地表甲烷通量。然而，对使用卫星柱 CO _{2的关注较少}在没有更复杂的反演模型的情况下，在更短的时间尺度上评估来自陆地生物圈的表面 CO _2通量。在更复杂的陆地生物圈模型输出可用之前，此类应用可用于近实时监测干旱、热浪和洪水等气候异常期间的生物圈碳通量。在这里，我们探讨了轨道碳观测站 2 (OCO-2) 卫星反演柱平均干燥空气 CO ₂ (XCO ₂ ) 直接探测和估计陆地生物圈 CO _2的能力通量异常使用简单的质量平衡方法。使用区域模型模拟（CarbonTracker 再分析）作为试验台，我们首先证明了以前开发的简单模型可以根据美国西部大气 XCO _{2估计值快速估计月表面 CO 2通量异常。}当所选的研究域在空间上足够广泛以说明大气混合并具有有利的风条件，并且主要来自同一区域的风能贡献时，该方法是最佳的。虽然单个卫星测量的误差部分降低了 OCO-2 卫星 XCO ₂估计更频繁、更小的表面 CO ₂通量异常的能力，但我们发现 OCO-2 XCO ₂通常可以检测和估计由干旱和热浪引起的更大的地表通量异常。因此，OCO-2 可用于近乎实时地监测每月的生态系统行为和健康状况。即将到来的温室气体卫星的任何降噪和/或大型地表碳异常的存在都可能增强在较短时间尺度范围内快速估计地表通量的能力。