Mesoscale modeling of Central American smoke transport to the United States: 1. "Top-down" assessment of emission strength and diurnal variation impacts

As is typical in the Northern Hemisphere spring, during 20 April to 21 May 2003, significant biomass burning smoke from Central America was transported to the southeastern United States (SEUS). A coupled aerosol, radiation, and meteorology model that is built upon the heritage of the Regional Atmosp...

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Veröffentlicht in:Journal of Geophysical Research. D. Atmospheres 2006-03, Vol.111 (D5), p.np-n/a
Hauptverfasser: Wang, Jun, Christopher, Sundar A., Nair, U. S., Reid, Jeffrey S., Prins, Elaine M., Szykman, James, Hand, Jenny L.
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container_issue D5
container_start_page np
container_title Journal of Geophysical Research. D. Atmospheres
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creator Wang, Jun
Christopher, Sundar A.
Nair, U. S.
Reid, Jeffrey S.
Prins, Elaine M.
Szykman, James
Hand, Jenny L.
description As is typical in the Northern Hemisphere spring, during 20 April to 21 May 2003, significant biomass burning smoke from Central America was transported to the southeastern United States (SEUS). A coupled aerosol, radiation, and meteorology model that is built upon the heritage of the Regional Atmospheric Modeling System (RAMS), having newly developed capabilities of Assimilation and Radiation Online Modeling of Aerosols (AROMA) algorithm, was used to simulate the smoke transport and quantify the smoke radiative impacts on surface energetics, boundary layer, and other atmospheric processes. This paper, the first of a two‐part series, describes the model and examines the ability of RAMS‐AROMA to simulate the smoke transport. Because biomass‐burning fire activities have distinct diurnal variations, the FLAMBE hourly smoke emission inventory that is derived from the geostationary satellite (GOES) fire products was assimilated into the model. In the “top‐down” analysis, ground‐based observations were used to evaluate the model performance, and the comparisons with model‐simulated results were used to estimate emission uncertainties. Qualitatively, a 30‐day simulation of smoke spatial distribution as well as the timing and location of the smoke fronts are consistent with those identified from the PM2.5 observation network, local air quality reports, and the measurements of aerosol optical thickness (AOT) and aerosol vertical profiles from the Southern Great Plains (SGP) Atmospheric Radiation Measurements (ARM) site in Oklahoma. Quantitatively, the model‐simulated daily mean near‐surface dry smoke mass correlates well with PM2.5 mass at 34 locations in Texas and with the total carbon mass and nonsoil potassium mass (KNON) at three IMPROVE sites along the smoke pathway (with linear correlation coefficients R = 0.77, 0.74, and 0.69 at the significance level larger than 0.99, respectively). The top‐down sensitivity analysis indicates that the total smoke particle emission during the study period is about 1.3 ± 0.2 Tg. The results further indicate that the simulation with a daily smoke emission inventory provides a slightly better correlation with measurements in the downwind region on daily scales but gives an unrealistic diurnal variation of AOT in the smoke source region. This study suggests that the assimilation of emission inventories from geostationary satellites is superior to that of polar orbiting satellites and has important implications for the modeling of
doi_str_mv 10.1029/2005JD006416
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"Top-down" assessment of emission strength and diurnal variation impacts</title><source>Wiley Online Library Journals Frontfile Complete</source><source>Wiley Free Content</source><source>Wiley-Blackwell AGU Digital Library</source><source>Alma/SFX Local Collection</source><creator>Wang, Jun ; Christopher, Sundar A. ; Nair, U. S. ; Reid, Jeffrey S. ; Prins, Elaine M. ; Szykman, James ; Hand, Jenny L.</creator><creatorcontrib>Wang, Jun ; Christopher, Sundar A. ; Nair, U. S. ; Reid, Jeffrey S. ; Prins, Elaine M. ; Szykman, James ; Hand, Jenny L.</creatorcontrib><description>As is typical in the Northern Hemisphere spring, during 20 April to 21 May 2003, significant biomass burning smoke from Central America was transported to the southeastern United States (SEUS). A coupled aerosol, radiation, and meteorology model that is built upon the heritage of the Regional Atmospheric Modeling System (RAMS), having newly developed capabilities of Assimilation and Radiation Online Modeling of Aerosols (AROMA) algorithm, was used to simulate the smoke transport and quantify the smoke radiative impacts on surface energetics, boundary layer, and other atmospheric processes. This paper, the first of a two‐part series, describes the model and examines the ability of RAMS‐AROMA to simulate the smoke transport. Because biomass‐burning fire activities have distinct diurnal variations, the FLAMBE hourly smoke emission inventory that is derived from the geostationary satellite (GOES) fire products was assimilated into the model. In the “top‐down” analysis, ground‐based observations were used to evaluate the model performance, and the comparisons with model‐simulated results were used to estimate emission uncertainties. Qualitatively, a 30‐day simulation of smoke spatial distribution as well as the timing and location of the smoke fronts are consistent with those identified from the PM2.5 observation network, local air quality reports, and the measurements of aerosol optical thickness (AOT) and aerosol vertical profiles from the Southern Great Plains (SGP) Atmospheric Radiation Measurements (ARM) site in Oklahoma. Quantitatively, the model‐simulated daily mean near‐surface dry smoke mass correlates well with PM2.5 mass at 34 locations in Texas and with the total carbon mass and nonsoil potassium mass (KNON) at three IMPROVE sites along the smoke pathway (with linear correlation coefficients R = 0.77, 0.74, and 0.69 at the significance level larger than 0.99, respectively). The top‐down sensitivity analysis indicates that the total smoke particle emission during the study period is about 1.3 ± 0.2 Tg. The results further indicate that the simulation with a daily smoke emission inventory provides a slightly better correlation with measurements in the downwind region on daily scales but gives an unrealistic diurnal variation of AOT in the smoke source region. 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Qualitatively, a 30‐day simulation of smoke spatial distribution as well as the timing and location of the smoke fronts are consistent with those identified from the PM2.5 observation network, local air quality reports, and the measurements of aerosol optical thickness (AOT) and aerosol vertical profiles from the Southern Great Plains (SGP) Atmospheric Radiation Measurements (ARM) site in Oklahoma. Quantitatively, the model‐simulated daily mean near‐surface dry smoke mass correlates well with PM2.5 mass at 34 locations in Texas and with the total carbon mass and nonsoil potassium mass (KNON) at three IMPROVE sites along the smoke pathway (with linear correlation coefficients R = 0.77, 0.74, and 0.69 at the significance level larger than 0.99, respectively). The top‐down sensitivity analysis indicates that the total smoke particle emission during the study period is about 1.3 ± 0.2 Tg. The results further indicate that the simulation with a daily smoke emission inventory provides a slightly better correlation with measurements in the downwind region on daily scales but gives an unrealistic diurnal variation of AOT in the smoke source region. This study suggests that the assimilation of emission inventories from geostationary satellites is superior to that of polar orbiting satellites and has important implications for the modeling of air quality in areas influenced by fire‐related pollutants from distant sources.</description><subject>Aerosols</subject><subject>Air quality</subject><subject>Assimilation</subject><subject>Atmospherics</subject><subject>Carbon</subject><subject>Computer simulation</subject><subject>diurnal variation</subject><subject>Diurnal variations</subject><subject>Emission analysis</subject><subject>emission uncertainty analysis</subject><subject>Fires</subject><subject>Geostationary satellites</subject><subject>Inventories</subject><subject>Mathematical models</subject><subject>Meteorology</subject><subject>Position (location)</subject><subject>Potassium</subject><subject>Smoke</subject><subject>smoke transport modeling</subject><subject>Springs</subject><subject>Stockpiling</subject><subject>Transport</subject><issn>0148-0227</issn><issn>2156-2202</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNqNkc1uFDEMx0cIJFalNx4g6gFxYEqSyccMt3YLC1UpiLbqMcpmPG3oTLLE2X68CY9LVosQp4Ivtuyf_7blqnrJ6D6jvHvLKZXHR5QqwdSTasaZVDXnlD-tZpSJtqac6-fVLuJ3WkxIJSibVT8_A0Z0dgQyxR5GH65IHMgcQk52JAcTJO9sIDjFGyAlF3AVUyY5knwN5CL4DD05yzYDviNsn-ydx1Xdx7uwRywiIE5FaiMJk0f0sUjlBOEqXxMbetL7dQpl0K1N3uZN2U8r6zK-qJ4NdkTY_e13qosP78_nH-uTL4tP84OT2smOylp1Sw3KtSAcc3bZQCuUZXopaaNL7EDyoXNW9FqWo6llSizZoHrF27Zh3DY71aut7irFH2vAbMqeDsbRBohrNLztJNeC_wdIG9V27T9BppnuBGcFfP04qKRQSjIhC_pmi7oUERMMZpX8ZNODYdRs3m_-fn_Bmy1-50d4eJQ1x4tvR4wLvRlSb7s8Zrj_02XTjVG60dJcni5Mc3h5dniqvhrR_AKMYMBK</recordid><startdate>20060316</startdate><enddate>20060316</enddate><creator>Wang, Jun</creator><creator>Christopher, Sundar A.</creator><creator>Nair, U. 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D. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Jun</au><au>Christopher, Sundar A.</au><au>Nair, U. S.</au><au>Reid, Jeffrey S.</au><au>Prins, Elaine M.</au><au>Szykman, James</au><au>Hand, Jenny L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mesoscale modeling of Central American smoke transport to the United States: 1. "Top-down" assessment of emission strength and diurnal variation impacts</atitle><jtitle>Journal of Geophysical Research. D. Atmospheres</jtitle><addtitle>J. Geophys. Res</addtitle><date>2006-03-16</date><risdate>2006</risdate><volume>111</volume><issue>D5</issue><spage>np</spage><epage>n/a</epage><pages>np-n/a</pages><issn>0148-0227</issn><eissn>2156-2202</eissn><abstract>As is typical in the Northern Hemisphere spring, during 20 April to 21 May 2003, significant biomass burning smoke from Central America was transported to the southeastern United States (SEUS). A coupled aerosol, radiation, and meteorology model that is built upon the heritage of the Regional Atmospheric Modeling System (RAMS), having newly developed capabilities of Assimilation and Radiation Online Modeling of Aerosols (AROMA) algorithm, was used to simulate the smoke transport and quantify the smoke radiative impacts on surface energetics, boundary layer, and other atmospheric processes. This paper, the first of a two‐part series, describes the model and examines the ability of RAMS‐AROMA to simulate the smoke transport. Because biomass‐burning fire activities have distinct diurnal variations, the FLAMBE hourly smoke emission inventory that is derived from the geostationary satellite (GOES) fire products was assimilated into the model. In the “top‐down” analysis, ground‐based observations were used to evaluate the model performance, and the comparisons with model‐simulated results were used to estimate emission uncertainties. Qualitatively, a 30‐day simulation of smoke spatial distribution as well as the timing and location of the smoke fronts are consistent with those identified from the PM2.5 observation network, local air quality reports, and the measurements of aerosol optical thickness (AOT) and aerosol vertical profiles from the Southern Great Plains (SGP) Atmospheric Radiation Measurements (ARM) site in Oklahoma. Quantitatively, the model‐simulated daily mean near‐surface dry smoke mass correlates well with PM2.5 mass at 34 locations in Texas and with the total carbon mass and nonsoil potassium mass (KNON) at three IMPROVE sites along the smoke pathway (with linear correlation coefficients R = 0.77, 0.74, and 0.69 at the significance level larger than 0.99, respectively). The top‐down sensitivity analysis indicates that the total smoke particle emission during the study period is about 1.3 ± 0.2 Tg. The results further indicate that the simulation with a daily smoke emission inventory provides a slightly better correlation with measurements in the downwind region on daily scales but gives an unrealistic diurnal variation of AOT in the smoke source region. This study suggests that the assimilation of emission inventories from geostationary satellites is superior to that of polar orbiting satellites and has important implications for the modeling of air quality in areas influenced by fire‐related pollutants from distant sources.</abstract><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2005JD006416</doi><tpages>21</tpages><oa>free_for_read</oa></addata></record>
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source Wiley Online Library Journals Frontfile Complete; Wiley Free Content; Wiley-Blackwell AGU Digital Library; Alma/SFX Local Collection
subjects Aerosols
Air quality
Assimilation
Atmospherics
Carbon
Computer simulation
diurnal variation
Diurnal variations
Emission analysis
emission uncertainty analysis
Fires
Geostationary satellites
Inventories
Mathematical models
Meteorology
Position (location)
Potassium
Smoke
smoke transport modeling
Springs
Stockpiling
Transport
title Mesoscale modeling of Central American smoke transport to the United States: 1. "Top-down" assessment of emission strength and diurnal variation impacts
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