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Observations of trace gases from space-based instruments offer theopportunity to constrain chemical and weather forecast and reanalysis modelsusing the tools of data assimilation. In this study, observing systemsimulation experiments (OSSEs) are performed to investigate the potential ofhigh space- and time-resolution column measurements as constraints on urbanNOx emissions. The regional chemistry–meteorology assimilation systemwhere meteorology and chemical variables are simultaneously assimilated iscomprised of a chemical transport model, WRF-Chem, the Data AssimilationResearch Testbed, and a geostationary observation simulator. We design OSSEsto investigate the sensitivity of emission inversions to the accuracy anduncertainty of the wind analyses and the emission updating scheme. Wedescribe the overall model framework and some initial experiments that pointout the first steps toward an optimal configuration for improving ourunderstanding of NOx emissions by combining space-based measurements anddata assimilation. Among the findings we describe is the dependence of errorsin the estimated NOx emissions on the wind forecast errors, showing thatwind vectors with a RMSE below 1 m s−1 allow inference of NOxemissions with a RMSE of less than 30 mol/(km2  ×  h) at the3 km scale of the model we use. We demonstrate that our inference ofemissions is more accurate when we simultaneously update both NOxemissions and NOx concentrations instead of solely updating emissions.Furthermore, based on our analyses, we recommend carrying out meteorologyassimilations to stabilize NO2 transport from the initial wind errorsbefore starting the emission assimilation. We show that wind uncertainties(calculated as a spread around a mean wind) are not important for estimatingNOx emissions when the wind uncertainties are reduced below1.5 m s−1. Finally, we present results assessing the role of separatevs. simultaneous chemical and meteorological assimilation in a modelframework without covariance between the meteorology and chemistry

Assimilation of satellite NO&lt;sub&gt;2&lt;/sub&gt; observations at high spatial resolution using OSSEs

Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs