s_albani@cornell_edu
New Member
We describe here important modifications for dust in CAM4 and CAM5 that we recommend
CAM4 has a Bulk Aerosol Model (BAM) parameterization of the dust size distribution [see model official documentation]. The dust model is described in detail in Zender et al. [2003] and Mahowald et al. [2006].
In summary, dust emissions primarily depend on winds and soil cover, and emitted fluxes have a fixed size distribution partitioning for four size bins. In addition, differences in soils’ susceptibility to erosion are summarized in a multiplicative parameter for the dust flux - the geomorphic soil erodibility - based on the concept of preferential sources, which is represented in the soil_erod input file in CAM. Dust transport is controlled by the CAM4 tracer advection scheme. Modeled dry deposition for dust includes gravitational and turbulent deposition processes. Wet deposition of dust results from both convective and large scale rain and snow precipitation simulated in CAM4, and is dependent on prescribed solubility and parameterized size-independent scavenging coefficients. Dust size distribution (i.e. the relative proportions of mass in each of the size bins) evolves in time in response to transport and deposition processes, whereas the sub-bin size distribution is fixed based on a log-normal distribution with mass median diameter of 3.5 μm. The dust optics is derived from Mie calculations for the size distribution represented by each size bin.
CAM5 uses a Modal Aerosol Model with 3 modes (MAM3) to represent the aerosols cycles. Dust emission works the same way as described above for CAM4-BAM, whereas transport and deposition – and the evolution of dust size distribution as a consequence – follow CAM5-MAM3 parameterizations. Dust in MAM3 is partitioned in 2 modes: accumulation and coarse.
We made several modifications to the code and input data to improve the dust model in the CAM4 and CAM5 releases.
1. First, the size distribution of dust in the 4 bins (CAM4-BAM) and 2 bins/modes (CAM5-MAM3) for the emissions was changed according to the brittle fragmentation theory [Kok, 2011], which shows better agreement with observations.
2. The wet deposition in CAM4-BAM was changed by increasing the solubility for all dust particles from 0.15 to 0.30, similar to that in CAM5, and using a larger below cloud scavenging coefficient for large particles (0.1,0.1,0.3,0.3) [e.g. Andronache, 2003]. This also appears to improve the size distribution and match theory better.
3. For the release version of the model, SW optics from Hess et al. [1998] were accidentally included, instead of the more accurate values from CCSM3 [Yoshioka et al., 2007; Mahowald et al., 2010] for both the CAM4 and CAM5 optics. The release version optics are largely based on old measurements of the dust refractive index that give dust the tendency to be too absorbing compared to observations. In addition, LW interactions were turned off in the CAM4 default version, although they were included in the CAM5 release. Updated dust optics are calculated assuming Maxwell-Garnett theory for mixing optical properties [Albani et al., submitted manuscript].
4. Soil erodibility maps need to be optimized to provide a realistic distribution of the emission from the different source areas. In addition in the release versions the soil erodibility maps are resolution-dependent, which should not be the case. In our new approach, soil erodibility maps were optimized specifically for a few different model configurations and resolutions [Albani et al., submitted manuscript], by applying a set of scale factors for different macro-areas, broadly corresponding to continents or subcontinents. The soil erodibility maps were first objectively optimized by minimizing the squared logarithm in errors in AOD, concentration and deposition compared to observations, but then modified to account for dust provenance information.
New soil erodibility maps that are not resolution dependent have been proposed by others (e.g. Brian Eaton, Phil Rasch and Po-Lun Ma), so if you are using a new resolution, you may want to contact them to obtain more information.
A manuscript describing the modifications listed above is in review:
Albani, S., N. M. Mahowald, A. T. Perry, R. A. Scanza, N. G. Heavens, C. S. Zender, V. Maggi, J. F. Kok, and B. L. Otto-Bliesner. Improved dust representation in the Community Atmosphere Model.
The improvements for CAM4-BAM and CAM5-MAM dust are available to the community – contact us.
References
Andronache, C. (2003). Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions. Atmos. Chem. Phys., 3, 131–143.
Hess, M., P. Koepke, I. Schult, 1998: Optical Properties of Aerosols and Clouds: The Software Package OPAC. Bull. Amer. Meteor. Soc., 79, 831–844.
Kok, J. F. (2011). A scaling theory for the size distribution of emitted dust aerosols suggests climate models underestimate the size of the global dust cycle. Proc. Natl. Acad. Sci. U.S.A., 108, 1016-1021, doi:10.1073/pnas.1014798108.
Mahowald, N. M., D. R. Muhs, S. Levis, P. J. Rasch, M. Yoshioka, C. S. Zender, and C. Luo (2006). Change in atmospheric mineral aerosols in response to climate: Last glacial period, preindustrial, modern, and doubled carbon dioxide climates. J. Geophys. Res., 111, D10202.
Mahowald N. M., S. Kloster, S. Engelstaedter, J. K. Moore, S. Mukhopadhyay, J. McConnell, S. Albani, S. Doney, A. Bhattacharya, M. A. J. Curran, M. G. Flanner, F. M. Hoffman, D. M. Lawrence, K. Lindsay, P. A. Mayewski, J. Neff, D. Rothenberg, E. Thomas, P. E. Thornton, and C. S. Zender (2010). Observed 20th century desert dust variability: impact on climate and biogeochemistry. Atmos. Chem.Phys., 10, 22, 10875-10893.
Yoshioka M., N. Mahowald, A. Conley, W. Collins, D. Fillmore, C. Zender, and D. Coleman (2007). Impact of Desert Dust Radiative Forcing on Sahel Precipitation: Relative importance of dust compared to sea surface temperature variations, vegetation changes and greenhouse gas warming. J. Climate, 20, doi:10.1175/JCLI4056.1,1445-1467.
Zender C.S., H. Bian, and D. Newman (2003). Mineral Dust Entrainment and Deposition (DEAD) model: Description and 1990s dust climatology. J. Geophys. Res., 108, D14, 4416, doi:10.1029/2002JD002775.
CAM4 has a Bulk Aerosol Model (BAM) parameterization of the dust size distribution [see model official documentation]. The dust model is described in detail in Zender et al. [2003] and Mahowald et al. [2006].
In summary, dust emissions primarily depend on winds and soil cover, and emitted fluxes have a fixed size distribution partitioning for four size bins. In addition, differences in soils’ susceptibility to erosion are summarized in a multiplicative parameter for the dust flux - the geomorphic soil erodibility - based on the concept of preferential sources, which is represented in the soil_erod input file in CAM. Dust transport is controlled by the CAM4 tracer advection scheme. Modeled dry deposition for dust includes gravitational and turbulent deposition processes. Wet deposition of dust results from both convective and large scale rain and snow precipitation simulated in CAM4, and is dependent on prescribed solubility and parameterized size-independent scavenging coefficients. Dust size distribution (i.e. the relative proportions of mass in each of the size bins) evolves in time in response to transport and deposition processes, whereas the sub-bin size distribution is fixed based on a log-normal distribution with mass median diameter of 3.5 μm. The dust optics is derived from Mie calculations for the size distribution represented by each size bin.
CAM5 uses a Modal Aerosol Model with 3 modes (MAM3) to represent the aerosols cycles. Dust emission works the same way as described above for CAM4-BAM, whereas transport and deposition – and the evolution of dust size distribution as a consequence – follow CAM5-MAM3 parameterizations. Dust in MAM3 is partitioned in 2 modes: accumulation and coarse.
We made several modifications to the code and input data to improve the dust model in the CAM4 and CAM5 releases.
1. First, the size distribution of dust in the 4 bins (CAM4-BAM) and 2 bins/modes (CAM5-MAM3) for the emissions was changed according to the brittle fragmentation theory [Kok, 2011], which shows better agreement with observations.
2. The wet deposition in CAM4-BAM was changed by increasing the solubility for all dust particles from 0.15 to 0.30, similar to that in CAM5, and using a larger below cloud scavenging coefficient for large particles (0.1,0.1,0.3,0.3) [e.g. Andronache, 2003]. This also appears to improve the size distribution and match theory better.
3. For the release version of the model, SW optics from Hess et al. [1998] were accidentally included, instead of the more accurate values from CCSM3 [Yoshioka et al., 2007; Mahowald et al., 2010] for both the CAM4 and CAM5 optics. The release version optics are largely based on old measurements of the dust refractive index that give dust the tendency to be too absorbing compared to observations. In addition, LW interactions were turned off in the CAM4 default version, although they were included in the CAM5 release. Updated dust optics are calculated assuming Maxwell-Garnett theory for mixing optical properties [Albani et al., submitted manuscript].
4. Soil erodibility maps need to be optimized to provide a realistic distribution of the emission from the different source areas. In addition in the release versions the soil erodibility maps are resolution-dependent, which should not be the case. In our new approach, soil erodibility maps were optimized specifically for a few different model configurations and resolutions [Albani et al., submitted manuscript], by applying a set of scale factors for different macro-areas, broadly corresponding to continents or subcontinents. The soil erodibility maps were first objectively optimized by minimizing the squared logarithm in errors in AOD, concentration and deposition compared to observations, but then modified to account for dust provenance information.
New soil erodibility maps that are not resolution dependent have been proposed by others (e.g. Brian Eaton, Phil Rasch and Po-Lun Ma), so if you are using a new resolution, you may want to contact them to obtain more information.
A manuscript describing the modifications listed above is in review:
Albani, S., N. M. Mahowald, A. T. Perry, R. A. Scanza, N. G. Heavens, C. S. Zender, V. Maggi, J. F. Kok, and B. L. Otto-Bliesner. Improved dust representation in the Community Atmosphere Model.
The improvements for CAM4-BAM and CAM5-MAM dust are available to the community – contact us.
References
Andronache, C. (2003). Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions. Atmos. Chem. Phys., 3, 131–143.
Hess, M., P. Koepke, I. Schult, 1998: Optical Properties of Aerosols and Clouds: The Software Package OPAC. Bull. Amer. Meteor. Soc., 79, 831–844.
Kok, J. F. (2011). A scaling theory for the size distribution of emitted dust aerosols suggests climate models underestimate the size of the global dust cycle. Proc. Natl. Acad. Sci. U.S.A., 108, 1016-1021, doi:10.1073/pnas.1014798108.
Mahowald, N. M., D. R. Muhs, S. Levis, P. J. Rasch, M. Yoshioka, C. S. Zender, and C. Luo (2006). Change in atmospheric mineral aerosols in response to climate: Last glacial period, preindustrial, modern, and doubled carbon dioxide climates. J. Geophys. Res., 111, D10202.
Mahowald N. M., S. Kloster, S. Engelstaedter, J. K. Moore, S. Mukhopadhyay, J. McConnell, S. Albani, S. Doney, A. Bhattacharya, M. A. J. Curran, M. G. Flanner, F. M. Hoffman, D. M. Lawrence, K. Lindsay, P. A. Mayewski, J. Neff, D. Rothenberg, E. Thomas, P. E. Thornton, and C. S. Zender (2010). Observed 20th century desert dust variability: impact on climate and biogeochemistry. Atmos. Chem.Phys., 10, 22, 10875-10893.
Yoshioka M., N. Mahowald, A. Conley, W. Collins, D. Fillmore, C. Zender, and D. Coleman (2007). Impact of Desert Dust Radiative Forcing on Sahel Precipitation: Relative importance of dust compared to sea surface temperature variations, vegetation changes and greenhouse gas warming. J. Climate, 20, doi:10.1175/JCLI4056.1,1445-1467.
Zender C.S., H. Bian, and D. Newman (2003). Mineral Dust Entrainment and Deposition (DEAD) model: Description and 1990s dust climatology. J. Geophys. Res., 108, D14, 4416, doi:10.1029/2002JD002775.