Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations
The Aerosol Optical Depth (AOD) and Angstrom Coefficient (AC) predictions in the GISS-TOMAS model of global aerosol microphysics are evaluated against remote sensing data from MODIS, MISR, and AERONET. The model AOD agrees well (within a factor of two) over polluted continental (or high sulfate), du...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2010-03-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | http://www.atmos-chem-phys.net/10/2129/2010/acp-10-2129-2010.pdf |
| _version_ | 1818344646865059840 |
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| author | Y. H. Lee P. J. Adams |
| author_facet | Y. H. Lee P. J. Adams |
| author_sort | Y. H. Lee |
| collection | DOAJ |
| description | The Aerosol Optical Depth (AOD) and Angstrom Coefficient (AC) predictions in the GISS-TOMAS model of global aerosol microphysics are evaluated against remote sensing data from MODIS, MISR, and AERONET. The model AOD agrees well (within a factor of two) over polluted continental (or high sulfate), dusty, and moderate sea-salt regions but less well over the equatorial, high sea-salt, and biomass burning regions. Underprediction of sea-salt in the equatorial region is likely due to GCM meteorology (low wind speeds and high precipitation). For the Southern Ocean, overprediction of AOD is very likely due to high sea-salt emissions and perhaps aerosol water uptake in the model. However, uncertainties in cloud screening at high latitudes make it difficult to evaluate the model AOD there with the satellite-based AOD. AOD in biomass burning regions is underpredicted, a tendency found in other global models but more severely here. Using measurements from the LBA-SMOCC 2002 campaign, the surface-level OC concentration in the model are found to be underpredicted severely during the dry season while much less severely for EC concentration, suggesting the low AOD in the model is due to underpredictions in OM mass. The potential for errors in emissions and wet deposition to contribute to this bias is discussed. |
| first_indexed | 2024-12-13T16:49:48Z |
| format | Article |
| id | doaj.art-6f69f53f53f548dc8d022ef23d7406bb |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-13T16:49:48Z |
| publishDate | 2010-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-6f69f53f53f548dc8d022ef23d7406bb2022-12-21T23:38:04ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242010-03-0110521292144Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observationsY. H. LeeP. J. AdamsThe Aerosol Optical Depth (AOD) and Angstrom Coefficient (AC) predictions in the GISS-TOMAS model of global aerosol microphysics are evaluated against remote sensing data from MODIS, MISR, and AERONET. The model AOD agrees well (within a factor of two) over polluted continental (or high sulfate), dusty, and moderate sea-salt regions but less well over the equatorial, high sea-salt, and biomass burning regions. Underprediction of sea-salt in the equatorial region is likely due to GCM meteorology (low wind speeds and high precipitation). For the Southern Ocean, overprediction of AOD is very likely due to high sea-salt emissions and perhaps aerosol water uptake in the model. However, uncertainties in cloud screening at high latitudes make it difficult to evaluate the model AOD there with the satellite-based AOD. AOD in biomass burning regions is underpredicted, a tendency found in other global models but more severely here. Using measurements from the LBA-SMOCC 2002 campaign, the surface-level OC concentration in the model are found to be underpredicted severely during the dry season while much less severely for EC concentration, suggesting the low AOD in the model is due to underpredictions in OM mass. The potential for errors in emissions and wet deposition to contribute to this bias is discussed.http://www.atmos-chem-phys.net/10/2129/2010/acp-10-2129-2010.pdf |
| spellingShingle | Y. H. Lee P. J. Adams Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations Atmospheric Chemistry and Physics |
| title | Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations |
| title_full | Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations |
| title_fullStr | Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations |
| title_full_unstemmed | Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations |
| title_short | Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations |
| title_sort | evaluation of aerosol distributions in the giss tomas global aerosol microphysics model with remote sensing observations |
| url | http://www.atmos-chem-phys.net/10/2129/2010/acp-10-2129-2010.pdf |
| work_keys_str_mv | AT yhlee evaluationofaerosoldistributionsinthegisstomasglobalaerosolmicrophysicsmodelwithremotesensingobservations AT pjadams evaluationofaerosoldistributionsinthegisstomasglobalaerosolmicrophysicsmodelwithremotesensingobservations |