Abstract. This work employs ground- and space-based observations, together with model data to study columnar abundances of atmospheric trace gases (XH₂O, XCO₂, XCH₄, and XCO) in two high-latitude Russian cities, St. Petersburg and Yekaterinburg. Two portable COllaborative Column Carbon Observing Network (COCCON) spectrometers were used for continuous measurements at these locations during 2019 and 2020. Additionally, a subset of data of special interest (a strong gradient in XCH₄ and XCO was detected) collected in the framework of a mobile city campaign performed in 2019 using both instruments is investigated. All studied satellite products (TROPOMI, OCO-2, GOSAT, MUSICA IASI) show generally good agreement with COCCON observations. Satellite and ground-based observations at high latitude are much sparser than at low or mid latitude, which makes direct coincident comparisons between remote-sensing observations more difficult. Therefore, a method of scaling continuous CAMS model data to the ground-based observations is developed and used for creating virtual COCCON observations. These adjusted CAMS data are then used for satellite validation, showing good agreement in both Peterhof and Yekaterinburg cities. The gradients between the two study sites (ΔXgas) are similar between CAMS and CAMS-COCCON data sets, indicating that the model gradients are in agreement with the gradients observed by COCCON. This is further supported by a few simultaneous COCCON and satellite ΔXgas measurements, which also agree with the model gradient. With respect to the city campaign observations recorded in St. Petersburg, the downwind COCCON station measured obvious enhancements for both XCH₄ (10.6 ppb) and XCO (9.5 ppb), which is nicely reflected by TROPOMI observations, which detect city-scale gradients of the order 9.4 ppb for XCH₄ and 12.5 ppb XCO, respectively.

中文翻译：

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利用 COCCON 观测研究俄罗斯圣彼得堡和叶卡捷琳堡上空的星载痕量气体产物

摘要。这项工作利用地面和空间观测以及模型数据来研究俄罗斯两个高纬度城市圣彼得堡和叶卡捷琳堡的大气痕量气体（XH ₂ O、XCO ₂、XCH ₄和 XCO）的柱状丰度. 2019 年和 2020 年期间，两台便携式 COllaborative Column Carbon Observing Network (COCCON) 光谱仪用于在这些地点进行连续测量。此外，特别感兴趣的数据子集（XCH _{4 中}的强梯度）并检测到 XCO）在 2019 年使用这两种工具进行的移动城市活动框架中收集的数据进行了调查。所有研究的卫星产品（TROPOMI、OCO-2、GOSAT、MUSICA IASI）都显示出与 COCCON 观测结果的良好一致性。高纬度的卫星和地面观测比低纬度或中纬度的要少得多，这使得遥感观测之间的直接重合比较更加困难。因此，开发了一种将连续 CAMS 模型数据缩放到地面观测的方法，并用于创建虚拟 COCCON 观测。这些调整后的 CAMS 数据随后用于卫星验证，在彼得霍夫和叶卡捷琳堡市显示出良好的一致性。两个研究站点之间的梯度（ΔXgas）在 CAMS 和 CAMS-COCCON 数据集之间相似，表明模型梯度与 COCCON 观察到的梯度一致。这得到了一些同时进行的 COCCON 和卫星 ΔXgas 测量的进一步支持，它们也与模型梯度一致。关于在圣彼得堡记录的城市运动观测，顺风 COCCON 站测量到 XCH 的明显增强₄ (10.6 ppb) 和 XCO (9.5 ppb)，这很好地反映在 TROPOMI 观测中，它们分别检测到 XCH ₄和 12.5 ppb XCO 的城市尺度梯度为 9.4 ppb 。