The Atmospheric Tomography Mission (ATom): Comparing the Chemical Climatology of Reactive Species from Measurements and Global Models

The NASA Atmospheric Tomography Mission (ATom) is building a photochemical climatology of the remote troposphere based on objective sampling and profiling transects over the Pacific and Atlantic Oceans. These statistics provide direct tests of chemistry-climate models. The choice of species focuses on those controlling primary reactivity (a.k.a. oxidative state) of
the troposphere, specifically chemical tendencies of O3 and CH4. These key species include,
inter alia, O3, CH4, CO, C2H6, other alkanes, alkenes, aromatics, NOx, HNO3, HO2NO2, PAN, other organic nitrates, H2O, HCHO, H2O2, CH3OOH. Three of the four ATom deployments are now complete, and data from the first two (ATom-1 & -2) have been released as of this talk (see espoarchive.nasa.gov/archive/browse/atom).

The statistical distributions of key species are presented as 1D and 2D probability densities (PDs) and we focus here on the tropical and mid-latitude regions of the Pacific during ATom-1 (Aug) and -2 (Feb). PDs are computed from ATom observations and 6 global chemistry models over the tropospheric depth (0-12 km) and longitudinal extent of the observations. All data are weighted to achieve equal mass-weighting by latitude regimes to account for spatial sampling biases. The models are used to calculate the reactivity in each ATom air parcel. Reweighting parcels with loss of CH4 or production of O3, for example, allows us to identify which air parcels are most influential, including assessment of the importance of fine pollution layers in the most remote troposphere. Another photochemical climatology developed from ATom, and used to test models, includes the effect of clouds on photolysis rates.

The PDs and reactivity-weighted PDs reveal important seasonal differences and similarities between the two campaigns and also show which species may be most important in controlling reactivities. They clearly identify some very specific failings in the modeled climatologies and help us evaluate the chemical importance of fine-scale laminae with distinct chemical composition that are beyond model simulations.