Evaluate transport processes in MERRA driven chemical transport models using updated 222Rn emission inventories and global observations

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dc.contributor.authorZhang, Ben_AU
dc.contributor.authorLiu, HYen_AU
dc.contributor.authorCrawford, Jen_AU
dc.contributor.authorFairlie, TDen_AU
dc.contributor.authorChen, Gen_AU
dc.contributor.authorChambers, SDen_AU
dc.contributor.authorKang, CHen_AU
dc.contributor.authorWilliams, AGen_AU
dc.contributor.authorZhang, Ken_AU
dc.contributor.authorConsidine, DBen_AU
dc.contributor.authorSulprizio, MPen_AU
dc.contributor.authorYantosca, RMen_AU
dc.date.accessioned2016-05-20T00:55:58Zen_AU
dc.date.available2016-05-20T00:55:58Zen_AU
dc.date.issued2015-12-14en_AU
dc.date.statistics2016-05-20en_AU
dc.description.abstractConvective and synoptic processes play a major role in determining the transport and distribution of trace gases and aerosols in the troposphere. The representation of these processes in global models (at ~100-1000 km horizontal resolution) is challenging, because convection is a sub-grid process and needs to be parameterized, while synoptic processes are close to the grid scale. Depending on the parameterization schemes used in climate models, the role of convection in transporting trace gases and aerosols may vary from model to model. 222Rn is a chemically inert and radioactive gas constantly emitted from soil and has a half-life (3.8 days) comparable to synoptic timescale, which makes it an effective tracer for convective and synoptic transport. In this study, we evaluate the convective and synoptic transport in two chemical transport models (GMI and GEOS-Chem), both driven by the NASA’s MERRA reanalysis. Considering the uncertainties in 222Rn emissions, we incorporate two more recent scenarios with regionally varying 222Rn emissions into GEOS-Chem/MERRA and compare the simulation results with those using the relatively uniform 222Rn emissions in the standard model. We evaluate the global distribution and seasonality of 222Rn concentrations simulated by the two models against an extended collection of 222Rn observations from 1970s to 2010s. The intercomparison will improve our understanding of the spatial variability in global 222Rn emissions, including the suspected excessive 222Rn emissions in East Asia, and provide useful feedbacks on 222Rn emission models. We will assess 222Rn vertical distributions at different latitudes in the models using observations at surface sites and in the upper troposphere and lower stratosphere. Results will be compared with previous models driven by other meteorological fields (e.g., fvGCM and GEOS4). Since the decay of 222Rn is the source of 210Pb, a useful radionuclide tracer attached to submicron aerosols, improved understanding of emissions and transport of 222Rn will provide insights into the transport, distribution, and wet deposition of 210Pb aerosols.en_AU
dc.identifier.citationZhang, B., Liu, H., Crawford, J. H., Fairlie, D., Chen, G., Chambers, S. D., Kang, C. H., Williams, A. G., Zhang, K., Considine, D. B., Sulprizio, M. P. & Yantosca, R. (2015). Evaluate transport processes in MERRA driven chemical transport models using updated 222Rn emission inventories and global observations. Paper presented at 2015 AGU Fall Meeting 14-18 December 2015, San Francisco, CA.en_AU
dc.identifier.conferenceenddate18 December 2015en_AU
dc.identifier.conferencename2015 AGU Fall Meetingen_AU
dc.identifier.conferenceplaceSan Fransisco, Californiaen_AU
dc.identifier.conferencestartdate14 December 2015en_AU
dc.identifier.govdoc6411en_AU
dc.identifier.urihttps://agu.confex.com/agu/fm15/meetingapp.cgi/Paper/62602en_AU
dc.identifier.urihttp://apo.ansto.gov.au/dspace/handle/10238/6838en_AU
dc.language.isoenen_AU
dc.publisherAGUen_AU
dc.subjectEvaluated dataen_AU
dc.subjectGasesen_AU
dc.subjectAerosolsen_AU
dc.subjectClimate modelsen_AU
dc.subjectSoilsen_AU
dc.subjectGlobal aspectsen_AU
dc.titleEvaluate transport processes in MERRA driven chemical transport models using updated 222Rn emission inventories and global observationsen_AU
dc.typeConference Presentationen_AU
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