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Using beryllium-7 to assess cross-tropopause transport in global models

Liu, H., D. Considine, L. W. Horowitz, J. Crawford, J. Rodriguez, S. Strahan, M. Damon, S. Steenrod, X. Xu, J. Kouatchou, C. Carouge, and R. M. Yantosca (2016), Using beryllium-7 to assess cross-tropopause transport in global models, Atmos. Chem. Phys., 16, 4641-4659, doi:10.5194/acp-16-4641-2016.

We use the Global Modeling Initiative (GMI) modeling framework to assess the utility of cosmogenic beryllium-7 (Be-7), a natural aerosol tracer, for evaluating cross-tropopause transport in global models. The GMI chemical transport model (CTM) was used to simulate atmospheric Be-7 distributions using four different meteorological data sets (GEOS1-STRAT DAS, GISS II' GCM, fvGCM, and GEOS4-DAS), featuring significantly different stratosphere–troposphere exchange (STE) characteristics. The simulations were compared with the upper troposphere and/or lower stratosphere (UT/LS) Be-7 climatology constructed from ∼25 years of aircraft and balloon data, as well as climatological records of surface concentrations and deposition fluxes. Comparison of the fraction of surface air of stratospheric origin estimated from the Be-7 simulations with observationally derived estimates indicates excessive cross-tropopause transport at mid-latitudes in simulations using GEOS1-STRAT and at high latitudes using GISS II' meteorological data. These simulations also overestimate Be-7 deposition fluxes at mid-latitudes (GEOS1-STRAT) and at high latitudes (GISS II'), respectively. We show that excessive cross-tropopause transport of Be-7 corresponds to overestimated stratospheric contribution to tropospheric ozone. Our perspectives on STE in these meteorological fields based on Be-7 simulations are consistent with previous modeling studies of tropospheric ozone using the same meteorological fields. We conclude that the observational constraints for Be-7 and observed Be-7 total deposition fluxes can be used routinely as a first-order assessment of cross-tropopause transport in global models.

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Research Program: 
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Modeling Analysis and Prediction Program (MAP)
Atmospheric Composition Campaign Data Analysis and Modeling (ACCDAM) program