Airborne and ground-based Pandora spectrometer NO₂ column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO₂ Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO₂. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r²= 0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r²=0.96) than Pandora measurements are with TROPOMI (r²=0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5^∘) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4 %–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19 %–33 % during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12 %–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7 %–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

中文翻译：

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使用纽约市和长岛海峡附近的机载和潘多拉光谱仪评估 Sentinel-5P TROPOMI 对流层 NO2 柱密度

在 2018 年纽约市/长岛声音区域的长岛声音对流层臭氧研究 (LISTOS) 期间收集了机载和地面潘多拉光谱仪 NO ₂柱测量值，这与 Sentinel-5P 对流层监测仪器的早期观测结果一致（ TROPOMI) 仪器。机载和地面测量均用于评估该地区的 TROPOMI NO ₂对流层垂直柱 (TrVC) 产品 v1.2，其在 NO _{2 中}具有高度的时空异质性. 首先，比较机载 TrVC 和 Pandora TrVC，以评估机载 TrVC 的不确定性并建立 Pandora 观测的空间代表性。发现 Pandora 和机载 TrVC 之间的 171 次巧合高度相关（r ² = 0.92 和 1.03 的斜率），最大的个体差异与高时间和/或空间可变性相关。这些参考测量（潘多拉和机载）在时间覆盖和空间代表性方面是互补的。潘多拉光谱仪可以提供连续的长期测量，但在阳光直射模式下运行时可能缺乏区域代表性。机载光谱仪通常只部署很短的时间，但它们的观测在空间上更能代表卫星测量结果，增加 了在它们飞越的整个 TROPOMI 像素上以 250 m × 250 m 的亚像素分辨率进行检索的能力 。因此，机载数据与 TROPOMI 测量更相关（r ² =0.96) 比 Pandora 测量与 TROPOMI ( r ² =0.84 ) 相比。TROPOMI 和参考测量值之间的最大异常值似乎源于在明亮的城市场景中空间过于粗糙的先验表面反射率 (0.5 ^∘ )。在这项工作中，这是在无云场景中产生的结果，有时会受到影响对流层空气质量因子计算的 TROPOMI 云压力反演错误的影响。该因素导致 TROPOMI TrVC 的高偏差为 4%–11%。排除这些受云影响的点，在 2018 年 6 月至 9 月的 LISTOS 时间范围内，TROPOMI 的整体低偏差为 19%–33%。这种低偏差的部分原因是来自 TM5-MP 模型的粗先验剖面输入；替换这些与来自 12 公里北美模型-社区多尺度空气质量 (NAMCMAQ) 分析的轮廓相比，TrVC 增加了 12%–14%。即使有了这种改进，TROPOMI-NAMCMAQ TrVC 仍有 7%–19% 的低偏差，这表明需要改进空气质量因子计算中的先验假设。未来的工作应该探索先验输入的额外影响，以使用这些数据集进一步评估 TROPOMI 中剩余的低偏差。