Open AccessImproved dust representation in the Community Atmosphere Model
Author(s) -
Albani S.,
Mahowald N. M.,
Perry A. T.,
Scanza R. A.,
Zender C. S.,
Heavens N. G.,
Maggi V.,
Kok J. F.,
OttoBliesner B. L.
Publication year - 2014
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1002/2013ms000279
Subject(s) - radiative forcing , mineral dust , forcing (mathematics) , environmental science , radiative transfer , atmosphere (unit) , aerosol , atmospheric sciences , climate model , earth's energy budget , longwave , atmospheric model , climatology , deposition (geology) , climate change , meteorology , physics , geology , sediment , paleontology , oceanography , quantum mechanics , radiation
Abstract Aerosol‐climate interactions constitute one of the major sources of uncertainty in assessing changes in aerosol forcing in the anthropocene as well as understanding glacial‐interglacial cycles. Here we focus on improving the representation of mineral dust in the Community Atmosphere Model and assessing the impacts of the improvements in terms of direct effects on the radiative balance of the atmosphere. We simulated the dust cycle using different parameterization sets for dust emission, size distribution, and optical properties. Comparing the results of these simulations with observations of concentration, deposition, and aerosol optical depth allows us to refine the representation of the dust cycle and its climate impacts. We propose a tuning method for dust parameterizations to allow the dust module to work across the wide variety of parameter settings which can be used within the Community Atmosphere Model. Our results include a better representation of the dust cycle, most notably for the improved size distribution. The estimated net top of atmosphere direct dust radiative forcing is −0.23 ± 0.14 W/m 2 for present day and −0.32 ± 0.20 W/m 2 at the Last Glacial Maximum. From our study and sensitivity tests, we also derive some general relevant findings, supporting the concept that the magnitude of the modeled dust cycle is sensitive to the observational data sets and size distribution chosen to constrain the model as well as the meteorological forcing data, even within the same modeling framework, and that the direct radiative forcing of dust is strongly sensitive to the optical properties and size distribution used.