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Biogenic NO emissions from soils (SNOx) play important direct and indirect roles in tropospheric chemistry. The most widely applied algorithm to calculate SNOx in global models was published 15 years ago by Yienger and Levy (1995), and was based on very few measurements. Since then, numerous new measurements have been published, which we used to build up a compilation of world wide field measurements covering the period from 1978 to 2010. Recently, several satellite-based top-down approaches, which recalculated the different sources of NOx (fossil fuel, biomass burning, soil and lightning), have shown an underestimation of SNOx by the algorithm of Yienger and Levy (1995). Nevertheless, to our knowledge no general improvements of this algorithm, besides suggested scalings of the total source magnitude, have yet been published. Here we present major improvements to the algorithm, which should help to optimize the representation of SNOx in atmospheric-chemistry global climate models, without modifying the underlying principals or mathematical equations. The changes include: (1) using a new landcover map, with twice the number of landcover classes, and using annually varying fertilizer application rates; (2) adopting a fraction of 1.0 % for the applied fertilizer lost as NO, based on our compilation of measurements; (3) using the volumetric soil moisture to distinguish between the wet and dry states; and (4) adjusting the emission factors to reproduce the measured emissions in our compilation (based on either their geometric or arithmetic mean values). These steps lead to increased global annual SNOx, and our total above canopy SNOx source of 8.6 Tg yr−1 (using the geometric mean) ends up being close to one of the satellite-based top-down approaches (8.9 Tg yr−1). The above canopy SNOx source using the arithmetic mean is 27.6 Tg yr−1, which is higher than all previous estimates, but compares better with a regional top-down study in eastern China. This suggests that both top-down and bottom-up approaches will be needed in future attempts to provide a better calculation of SNOx

Improvement and evaluation of simulated global biogenic soil NO emissions in an AC-GCM