Sub-grid variability (SGV) in atmospheric trace gases within satellite pixels is a key issue in satellite design and interpretation and validation of retrieval products. However, characterizing this variability is challenging due to the lack of independent high-resolution measurements. Here we use tropospheric NO₂ vertical column (VC) measurements from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument with a spatial resolution of about 250 m×250 m to quantify the normalized SGV (i.e., the standard deviation of the sub-grid GeoTASO values within the sampled satellite pixel divided by the mean of the sub-grid GeoTASO values within the same satellite pixel) for different hypothetical satellite pixel sizes over urban regions. We use the GeoTASO measurements over the Seoul Metropolitan Area (SMA) and Busan region of South Korea during the 2016 KORUS-AQ field campaign and over the Los Angeles Basin, USA, during the 2017 Student Airborne Research Program (SARP) field campaign. We find that the normalized SGV of NO₂ VC increases with increasing satellite pixel sizes (from ∼10 % for 0.5 km×0.5 km pixel size to ∼35 % for 25 km×25 km pixel size), and this relationship holds for the three study regions, which are also within the domains of upcoming geostationary satellite air quality missions. We also quantify the temporal variability in the retrieved NO₂ VC within the same hypothetical satellite pixels (represented by the difference of retrieved values at two or more different times in a day). For a given satellite pixel size, the temporal variability within the same satellite pixels increases with the sampling time difference over the SMA. For a given small (e.g., ≤4 h) sampling time difference within the same satellite pixels, the temporal variability in the retrieved NO₂ VC increases with the increasing spatial resolution over the SMA, Busan region, and the Los Angeles Basin.The results of this study have implications for future satellite design and retrieval interpretation and validation when comparing pixel data with local observations. In addition, the analyses presented in this study are equally applicable in model evaluation when comparing model grid values to local observations. Results from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model indicate that the normalized satellite SGV of tropospheric NO₂ VC calculated in this study could serve as an upper bound to the satellite SGV of other species (e.g., CO and SO₂) that share common source(s) with NO₂ but have relatively longer lifetime.

中文翻译：

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使用机载测绘光谱仪测量评估城市区域卫星像素内的子网格可变性

卫星像素内大气痕量气体的子网格变异性 (SGV) 是卫星设计以及检索产品解释和验证的关键问题。然而，由于缺乏独立的高分辨率测量，表征这种可变性具有挑战性。在这里，我们使用来自地球静止微量气体和气溶胶传感器优化 (GeoTASO) 机载仪器的对流层NO ₂垂直柱 (VC) 测量值，空间分辨率约为250 m×250 m量化城市区域不同假设卫星像素大小的归一化 SGV（即采样卫星像素内的子网格 GeoTASO 值的标准偏差除以同一卫星像素内的子网格 GeoTASO 值的平均值）。我们在 2016 年 KORUS-AQ 实地活动期间以及在 2017 年学生机载研究计划 (SARP) 实地活动期间在韩国首尔市区 (SMA) 和釜山地区使用 GeoTASO 测量值。我们发现，的归一化SGV NO ₂ VC增加随卫星的像素尺寸（从〜10  ％为0.5公里×0.5公里像素尺寸约35  ％，持续25公里×25公里像素大小），并且这种关系适用于三个研究区域，这些区域也属于即将到来的地球静止卫星空气质量任务的领域。我们还量化了相同假设卫星像素内检索到的NO ₂ VC的时间变异性（由一天中两个或多个不同时间检索到的值的差异表示）。对于给定的卫星像素大小，相同卫星像素内的时间可变性随着 SMA 上的采样时间差异而增加。对于 相同卫星像素内给定的小（例如，≤ 4 h）采样时间差，检索到的NO ₂的时间变异性VC 随着 SMA、釜山地区和洛杉矶盆地空间分辨率的增加而增加。本研究的结果在将像素数据与本地观测进行比较时对未来的卫星设计和反演解释和验证具有重要意义。此外，当将模型网格值与局部观测值进行比较时，本研究中提出的分析同样适用于模型评估。天气研究和预报模型结合化学 (WRF-Chem) 模型的结果表明，本研究计算的对流层NO ₂ VC的归一化卫星 SGV可以作为其他物种（例如CO和SO ₂ ) 与NO ₂但寿命相对较长。