Processes controlling the seasonal variations in 210Pb and 7Be at the Mt....

The core information for this publication's citation.: 
Brattich, E., H. Liu, L. Tositti, D. Considine, and J. Crawford (2017), Processes controlling the seasonal variations in 210Pb and 7Be at the Mt. Cimone WMO-GAW global station, Italy: a model analysis, Atmos. Chem. Phys., 17, 1061-1080, doi:10.5194/acp-17-1061-2017.
Abstract: 

We apply the Global Modeling Initiative (GMI) chemistry and transport model driven by NASA's MERRA assimilated meteorological data to simulate the seasonal variations in two radionuclide aerosol tracers (terrigenous 210Pb and cosmogenic 7Be) at the WMO-GAW station of Mt. Cimone (44°12′N, 10°42′E; 2165m a.s.l.; Italy), which is representative of free-tropospheric conditions most of the year, during 2005 with an aim to understand the roles of transport and precipitation scavenging processes in controlling their seasonality. The total precipitation field in the MERRA data set is evaluated with the Global Precipitation Climatology Project (GPCP) observations, and generally good agreement is found. The model reproduces reasonably the observed seasonal pattern of 210Pb concentrations, characterized by a wintertime minimum due to lower 222Rn emissions and weaker uplift from the boundary layer and summertime maxima resulting from strong convection over the continent. The observed seasonal behavior of 7Be concentrations shows a winter minimum, a summer maximum, and a secondary spring maximum. The model captures the observed 7Be pattern in winter–spring, which is linked to the larger stratospheric influence during spring. However, the model tends to underestimate the observed 7Be concentrations in summer, partially due to the sensitivity to spatial sampling in the model. Model sensitivity experiments indicate a dominant role of precipitation scavenging (vs. dry deposition and convection) in controlling the seasonality of 210Pb and 7Be concentrations at Mt. Cimone.

PDF of Publication: 
Download from publisher's website.
Research Program: 
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Modeling Analysis and Prediction Program (MAP)