implementing online marine organic aerosol emissions into geos-chem implementing online marine...
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Implementing Online Marine Organic Aerosol Emissions into GEOS-Chem
NASA Ames Research Center7th International GEOS-Chem Meeting
May 5, 2015
B. Gantt1, M. S. Johnson2, M. Crippa3, A. S. H. Prévôt3, and N. Meskhidze1
Funding: Office of Science (BER), US Department of Energy Grant No. DE-FG0208ER64508, and the NASA Ames Research Center Earth Science Division
1 North Carolina State University2 NASA Ames Research Center 3 Laboratory of Atmospheric Chemistry, Paul Scherrer Institute
Importance of Marine Organic Aerosols (MOA)
Need for improved climate assessments has led to increased emphasis on understanding emission sources and concentrations of natural aerosols
The majority of the Earth’s surface is covered by oceans Oceanic emissions of sea salt and organic matter, in particulate form, and of sulfur, halogens, and
volatile organic compounds, in gaseous form, affect the formation, number concentration, and composition of atmospheric cloud condensation nuclei (CCN) and ice nuclei (IN)
Rinaldi et al. (2010)
Using GEOS-Chem v8-01-01 Presented at the 6th Annual
GC Meeting
Evaluated 5 different organic sea spray emission schemes against hourly to monthly observations
Global MOA emission rates ranged from 0.1 to 11.9 Tg yr -1
Gantt et al. (2012)
Annual Average Emission Rates
Previous GEOS-Chem MOA Emission Modeling
Gantt et al. (2012)
GEOS-Chem-predicted Global MOA Emissions
Applying top-down emission scheme from Gantt et al. (2012)
Annual submicron MOA emissions of ~9.0 Tg was predicted for 2009
Falls within the range of previously predicted totals of MOA emissions
Emissions range from < 0.1 to > 10 ng m-2 s-1
Largest emission rates in high-latitude waters during the respective spring/summer seasons
Gantt et al. (2015)
GEOS-Chem-predicted Global MOA Concentrations
MOA surface concentrations range from < 0.1 µg m-3 to > 1.0 µg m-3
MOA concentrations are largest over regions of highest emission sources which are correlated with [chl-a] spatial distribution
The fraction of total submicron OA made up by primary MOA are largest (>80%) over marine regions and decreases rapidly over terrestrial regions
Gantt et al. (2015)
Improved Prediction of Global Total Organic Aerosol Concentrations in Clean Marine Regions
With online MOA emissions
Without online MOA emissions
GEOS-Chem without MOA emissions tends to under-predict (normalized mean bias -79%) in situ measurements and displays poor correlation (0.16) when compared to observations Model simulations with MOA emissions included in the comparison had substantially lower model bias (normalized mean bias -12%) and improved correlation (0.28)
Gantt et al. (2015)
*Data is considered “clean marine” when [BC] < 50 ng m-3 and upwind fetch over the ocean
Conclusions
Online emission parameterization of submicron primary MOA was implemented into the GEOS-Chem model (v9-02)
This model development was designed to be used in the default setting of GEOS-Chem with the following characteristics: (1) adds minimal computational expense, (2) capable of being used for all GEOS-Chem model domains/simulation periods, and (3) treated with unique tracers for explicit atmospheric aging and tracking
GEOS-Chem predicts an annual submicron MOA total of ~9.0 Tg which is comparable to past predictions Emission rates range from < 0.1 ng m-2 s-1 to > 10 ng m-2 s-1, with largest values in high-latitude oceans
during the summer season Model-predicted MOA concentrations range from < 0.1 µg m-3 to > 1.0 µg m-3 and make up the majority of
total submicron OA over oceanic regions Model results are comparable with existing data sets and have been extensively discussed in scientific
literature; therefore proposed to be implemented in the default code
Please see our publication in Geosci. Model Dev.: http://www.geosci-model-dev.net/8/619/2015/gmd-8-619-2015.pdf
Additional Slides
Gantt et al. (2011) Emission Parameterization
Gantt et al. (2011) Atmos. Chem. Phys.
Marine Primary Organic Aerosol Emission Rate (EPOA)OMSSA(chl a, U10, Dp) =
sea-salt emissions based on Jaeglé et al. (2011)
Gantt et al. (2012)
10m winds (U10) [chl-a]
GEOS-Chem (v9-02) Model Online sea-salt emissions
Power relationship with 10m winds speeds (Gong 2003) and 3rd order polynomial dependence on sea surface temperature (Jaeglé et al., 2011)
Two bin sizes: fine mode (0.02 to 1.0 µm diameter) and coarse mode (1.0 to 16.0 µm diameter)
Online MOA emission schemeTop-down emission parameterization developed
from Gantt et al. (2012) applying in situ data at Mace Head, Ireland
Dependence on:Monthly-averaged Aqua MODIS [chl-a] at 1/12°
which is spatially averaged online GEOS-5 10m wind speeds 2 additional tracers: 1) hydrophobic and 2)
hydrophilic which is formed with an e-folding time of 1.15 days (identical to terrestrial OA)
3-D global chemical transport model (v9-02)Developed at Harvard University and other
institutions around the world Full chemistry configuration
SMVGEAR II chemistry solver package w/ SOA formation (Pye et al., 2010)
GEOS-5 meteorologyGoddard Earth Observing System (GEOS) of
the NASA Global Modeling Assimilation Office Detailed emission inventories
Fossil fuel, biomass burning, biofuel burning, biogenic and anthropogenic aerosols
State-of-the-art transport (TPCORE) and deposition routines
2⁰ x 2.5⁰ global grid resolution 0.5⁰ x 0.67⁰ nested regional grid resolution 47 vertical grids
GEOS-Chem-predicted Nested MOA Concentrations
Nested-grid simulations (0.5° x 0.67°) for July 2009 demonstrate a sharp concentration gradient over Europe
Data from Paris (Crippa et al., 2013; AMS-derived MOA concentrations) was used to evaluate high-resolution GEOS-Chem simulations
The model demonstrates the ability to capture the temporal pattern and magnitude of observed inland MOA concentrations
Correlation of 0.62 Mean bias of -120 ng m-3
Normalized mean bias of -36%
Gantt et al. (2015)