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The global source of lightning-produced NOx (LNOx) isestimated by assimilating observations of NO2, O3,HNO3, and CO measured by multiple satellite measurements intoa chemical transport model. Included are observations from the OzoneMonitoring Instrument (OMI), Microwave Limb Sounder (MLS), TroposphericEmission Spectrometer (TES), and Measurements of Pollution in the Troposphere(MOPITT) instruments. The assimilation of multiple chemical data sets withdifferent vertical sensitivity profiles provides comprehensive constraints onthe global LNOx source while improving the representations of theentire chemical system affecting atmospheric NOx, including surfaceemissions and inflows from the stratosphere. The annual global LNOxsource amount and NO production efficiency are estimated at6.3 Tg N yr−1 and 310 mol NO flash−1, respectively.Sensitivity studies with perturbed satellite data sets, model and dataassimilation settings lead to an error estimate of about 1.4 Tg N yr−1 on this global LNOx source. Theseestimates are significantly different from those estimated from a parameterinversion that optimizes only the LNOx source from NO2observations alone, which may lead to an overestimate of the sourceadjustment. The total LNOx source is predominantly corrected by theassimilation of OMI NO2 observations, while TES and MLS observationsadd important constraints on the vertical source profile. The resultsindicate that the widely used lightning parameterization based on the C-shapeassumption underestimates the source in the upper troposphere andoverestimates the peak source height by up to about 1 km over landand the tropical western Pacific. Adjustments are larger over ocean than overland, suggesting that the cloud height dependence is too weak over the oceanin the Price and Rind (1992) approach. The significantly improved agreementbetween the analyzed ozone fields and independent observations givesconfidence in the performance of the LNOx source estimation

Global lightning NO&lt;sub&gt;x&lt;/sub&gt; production estimated by an assimilation of multiple satellite data sets

Global lightning NO<sub>x</sub> production estimated by an assimilation of multiple satellite data sets