Simulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transport

Abstract. Radon-222 (222Rn) is a short-lived radioactive gas naturally emitted from land surfaces and has long been used to assess convective transport in atmospheric models. In this study, we simulate 222Rn using the GEOS-Chem chemical model improve our understanding of emissions surface concentration seasonality characterize associated with two Goddard Earth Observing System (GEOS) meteorological products, Modern-Era Retrospective analysis for Research Applications (MERRA) GEOS Forward Processing (GEOS-FP). We evaluate four global emission scenarios by comparing results observations at 51 sites. The default scenario yields moderate agreement globally (68.9 % data within factor 2) large underestimate winter concentrations Northern Hemisphere midlatitudes high latitudes due an oversimplified formulation fluxes (1 atom cm−2 s−1 over reduction 3 under freezing conditions). compose new based on Zhang et al. (2011) demonstrate its potential simulated seasonality. regional components include spatially temporally varying derived previous measurements soil radium content exhalation models, which are key factors determining flux rates. However, underestimates still exist Asia, suggesting unusually emissions. therefore propose conservative upscaling 1.2 China, was also constrained observed deposition 210Pb (a progeny 222Rn). With modification, shows better Europe North America (> 80 reasonable Asia (close 70 %). Further constraints would require additional central United States, Canada, Africa, Asia. compare simulations driven MERRA GEOS-FP vertical profiles northern midlatitude summer three short-term airborne campaigns. While both products able capture gradient lower troposphere (0–4 km), neither correctly represents level detrainment, resulting biases middle upper troposphere. Compared GEOS-FP, leads stronger 222Rn, partially compensated weaker large-scale advection, similar distributions between simulations. This important implications models interpret other trace species when these as driving meteorology.