Obtaining the full spatial coverage of daily surface ozone fields is challenging because of the sparsity of the surface monitoring network and the difficulty in direct satellite retrievals of surface ozone. We propose an indirect satellite retrieval framework to utilize the information from satellite-measured column densities of tropospheric NO₂ and CH₂O, which are sensitive to the lower troposphere, to derive surface ozone fields. The method is applicable to upcoming geostationary satellites with high-quality NO₂ and CH₂O measurements. To prove the concept, we conduct a simulation experiment using a 3-D chemical transport model for July 2011 over the eastern US. The results show that a second order regression using both NO₂ and CH₂O column densities can be an effective predictor for daily maximum 8-h average ozone. Furthermore, this indirect retrieval approach is shown to be complementary to spatial interpolation of surface observations, especially in regions where the surface sites are sparse. Combining column observations of NO₂ and CH₂O with surface site measurements leads to an improved representation of surface ozone over simple kriging, increasing the R² value from 0.53 to 0.64 at a surface site distance of 252 km. The improvements are even more significant with larger surface site distances. The simulation experiment suggests that the indirect satellite retrieval technique can potentially be a useful tool to derive the full spatial coverage of daily surface ozone fields if satellite observation uncertainty is moderate.

由于地表监测网络的稀疏性以及直接卫星检索地表臭氧的难度，获取每日地表臭氧领域的完整空间覆盖面具有挑战性。我们提出了一个间接卫星检索框架，以利用对流层低层敏感的对流层NO ₂和CH ₂ O的卫星测量列密度信息得出地面臭氧场。该方法适用于即将进行的高质量NO ₂和CH ₂ O测量的对地静止卫星。为了证明这一概念，我们在2011年7月使用3-D化学物质运输模型在美国东部进行了模拟实验。结果表明，使用两个NO的二阶回归₂和CH ₂ O色谱柱密度可以有效预测每天最大8小时的平均臭氧浓度。此外，这种间接检索方法被证明是对地面观测值的空间插值的补充，尤其是在地面站点稀疏的区域。将NO ₂和CH ₂ O的柱观测值与表面位置测量结果相结合，可以通过简单的克里格法改进表面臭氧的表示，从而增加R ^2。地表距离252 km时，该值从0.53到0.64。较大的地面站点距离，改进效果更为显着。仿真实验表明，如果卫星观测不确定性中等，则间接卫星检索技术可能会成为推导每日地表臭氧领域完整空间覆盖的有用工具。