Ammonia Bidirectional Flux Model Tailored for Satellite Retrieval Parameter Inversions

Abstract. Atmospheric ammonia is an important chemical species for air quality and ecosystem health, and has levels that have been either growing or stagnant in many regions, in contrast to many other pollutants that have been on the decline in recent decades. As bottom-up emissions inventories for ammonia often have large uncertainties, inversions using ammonia retrievals from satellite-borne instruments are an important tool for improving these emissions inventories. Bidirectional flux models for ammonia give a unified model for emission and dry deposition and have recently been incorporated into a number of atmospheric chemistry models. However, there have been relatively few studies using satellite observations in inversions to refine the parameters in bidirectional flux models. A new bidirectional flux model is introduced that is designed specifically for use with inversion systems. This bidirectional flux model reduces the number of redundant parameters, as viewed by the inversions, to yield a model that is both optimized for use with inversion systems and is easy to implement and maintain in atmospheric chemistry models. Inversions using CrIS ammonia retrievals with this bidirectional flux model implemented in the GEM-MACH air quality forecasting model were performed. With parameters set via inversions, significant differences in surface atmospheric ammonia concentrations between the existing unidirectional model and newer bidirectional model were observed in many agricultural regions, varying by as much as 10 ppbv (or between 50 % to 150 %) in these locations. The bidirectional flux model improved the agreement of GEM-MACH with surface observations in the important growing seasons (spring, summer, fall), with biases decreasing between 14 % and 26 % as compared to the unidirectional model and decreased the error standard deviation between 5 % to 20 %, but also degraded this comparison somewhat for the winter.