4.6 Article

Sensitivity of tropical tropospheric composition to lightning NOx production as determined by replay simulations with GEOS-5

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 120, Issue 16, Pages 8512-8534

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2014JD022987

Keywords

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Funding

  1. NASA Modeling and Analysis Program [NASA/NNX09AJ37G]
  2. NASA's Modeling, Analysis and Prediction (MAP) program

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The sensitivity of tropical tropospheric composition to the source strength of nitrogen oxides (NOx) produced by lightning (LNOx) is analyzed for September through November 2007 using the NASA GEOS-5 model constrained by MERRA fields, with full GMI stratospheric-tropospheric chemistry and an LNOx algorithm that is appropriate for use in a climate modeling setting; satellite retrievals from OMI, TES, and OMI/MLS; and in situ measurements from SHADOZ ozonesondes. Global mean LNOx production rates of 0 to 492 mol NO flash(-1) and the subsequent responses of NOx, ozone (O-3), hydroxyl radical (OH), nitric acid (HNO3), peroxyacetyl nitrate (PAN), and NOy (NOx + HNO3 + PAN) are investigated. The radiative implications associated with LNOx-induced changes in tropospheric O-3 are assessed. Increasing the LNOx production rate by a factor of 4 (from 123 to 492 mol flash(-1)) leads to tropical upper tropospheric enhancements of greater than 100% in NOx, OH, HNO3, and PAN. This increase in LNOx production also leads to O-3 enhancements of up to 60%, which subsequently yields a factor-of-three increase in the mean net radiative flux at the tropopause. An LNOx source of 246 mol flash(-1) agrees reasonably well with measurements, with an approximate factor-of-two uncertainty due to the short length of the study, inconsistencies in the observational data sets, and systematic biases in modeled LNOx production. Further research into the regional dependencies of lightning flash rates and LNOx production per flash, along with improvements in satellite retrievals, should help resolve the discrepancies that currently exist between the model and observations.

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