Evaluation of the surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States
We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for...
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Published in | Atmospheric environment (1994) Vol. 125; pp. 100 - 111 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.01.2016
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Subjects | |
Online Access | Get full text |
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Abstract | We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero) developed by the Global Modeling Assimilation Office (GMAO). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua satellites. By combining the spatial and temporal coverage of GEOS-5 with observational constraints on AOD, MERRAero has the potential to provide improved estimates of PM2.5 compared to the model alone and with greater coverage than available observations.
Importantly, assimilation of AOD data constrains the total column aerosol mass in MERRAero subject to assumptions about optical properties for each of the species represented in GOGART. However, single visible wavelength AOD data does not contain sufficient information content to correct errors in either aerosol vertical placement or composition, critical elements for a proper characterization of surface PM2.5. Despite this, we find that the data-assimilation equipped version of GEOS-5 better represents observed PM2.5 between 2003 and 2012 compared to the same version of the model without AOD assimilation. Compared to measurements from the EPA-AQS network, MERRAero shows better PM2.5 agreement with the IMPROVE network measurements, which are composed essentially of rural stations. Regardless the data network, MERRAero PM2.5 are closer to observation values during the summer while larger discrepancies are observed during the winter. Comparing MERRAero to PM2.5 data collected by the Chemical Speciation Network (CSN) offers greater insight on the species MERRAero predicts well and those for which there are biases relative to the EPA observations. Analysis of this speciated data indicates that the lack of nitrate emissions in MERRAero and an underestimation of carbonaceous emissions in the Western US explains much of the reanalysis bias during the winter. To further understand discrepancies between the reanalysis and observations, we use complimentary data to assess two important aspects of MERRAero that are of relevance to the diagnosis of PM2.5, in particular AOD and vertical structure.
•Full evaluation of MERRAero PM2.5 diagnostics: PM2.5, AOD and vertical structure.•Impact of MODIS AOD assimilation on the simulation of surface PM2.5.•Quality control of PM2.5 in situ-measurements to minimize error of representativeness.•Part of the bias between MERRAero and PM2.5 observations are species dependent. |
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AbstractList | We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero) developed by the Global Modeling Assimilation Office (GMAO). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua satellites. By combining the spatial and temporal coverage of GEOS-5 with observational constraints on AOD, MERRAero has the potential to provide improved estimates of PM2.5 compared to the model alone and with greater coverage than available observations. Importantly, assimilation of AOD data constrains the total column aerosol mass in MERRAero subject to assumptions about optical properties for each of the species represented in GOGART. However, single visible wavelength AOD data does not contain sufficient information content to correct errors in either aerosol vertical placement or composition, critical elements for a proper characterization of surface PM2.5. Despite this, we find that the data-assimilation equipped version of GEOS-5 better represents observed PM2.5 between 2003 and 2012 compared to the same version of the model without AOD assimilation. Compared to measurements from the EPA-AQS network, MERRAero shows better PM2.5 agreement with the IMPROVE network measurements, which are composed essentially of rural stations. Regardless the data network, MERRAero PM2.5 are closer to observation values during the summer while larger discrepancies are observed during the winter. Comparing MERRAero to PM2.5 data collected by the Chemical Speciation Network (CSN) offers greater insight on the species MERRAero predicts well and those for which there are biases relative to the EPA observations. Analysis of this speciated data indicates that the lack of nitrate emissions in MERRAero and an underestimation of carbonaceous emissions in the Western US explains much of the reanalysis bias during the winter. To further understand discrepancies between the reanalysis and observations, we use complimentary data to assess two important aspects of MERRAero that are of relevance to the diagnosis of PM2.5, in particular AOD and vertical structure. We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero) developed by the Global Modeling Assimilation Office (GMAO). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua satellites. By combining the spatial and temporal coverage of GEOS-5 with observational constraints on AOD, MERRAero has the potential to provide improved estimates of PM2.5 compared to the model alone and with greater coverage than available observations. Importantly, assimilation of AOD data constrains the total column aerosol mass in MERRAero subject to assumptions about optical properties for each of the species represented in GOGART. However, single visible wavelength AOD data does not contain sufficient information content to correct errors in either aerosol vertical placement or composition, critical elements for a proper characterization of surface PM2.5. Despite this, we find that the data-assimilation equipped version of GEOS-5 better represents observed PM2.5 between 2003 and 2012 compared to the same version of the model without AOD assimilation. Compared to measurements from the EPA-AQS network, MERRAero shows better PM2.5 agreement with the IMPROVE network measurements, which are composed essentially of rural stations. Regardless the data network, MERRAero PM2.5 are closer to observation values during the summer while larger discrepancies are observed during the winter. Comparing MERRAero to PM2.5 data collected by the Chemical Speciation Network (CSN) offers greater insight on the species MERRAero predicts well and those for which there are biases relative to the EPA observations. Analysis of this speciated data indicates that the lack of nitrate emissions in MERRAero and an underestimation of carbonaceous emissions in the Western US explains much of the reanalysis bias during the winter. To further understand discrepancies between the reanalysis and observations, we use complimentary data to assess two important aspects of MERRAero that are of relevance to the diagnosis of PM2.5, in particular AOD and vertical structure. •Full evaluation of MERRAero PM2.5 diagnostics: PM2.5, AOD and vertical structure.•Impact of MODIS AOD assimilation on the simulation of surface PM2.5.•Quality control of PM2.5 in situ-measurements to minimize error of representativeness.•Part of the bias between MERRAero and PM2.5 observations are species dependent. |
Author | Hostetler, C. Hair, J. Buchard, V. Colarco, P. Randles, C.A. Tackett, J. Winker, D. da Silva, A.M. Ferrare, R. |
Author_xml | – sequence: 1 givenname: V. surname: Buchard fullname: Buchard, V. email: virginie.buchard@nasa.gov organization: NASA/Goddard Space Flight Center, Greenbelt, MD, USA – sequence: 2 givenname: A.M. orcidid: 0000-0002-3381-4030 surname: da Silva fullname: da Silva, A.M. organization: NASA/Goddard Space Flight Center, Greenbelt, MD, USA – sequence: 3 givenname: C.A. surname: Randles fullname: Randles, C.A. organization: NASA/Goddard Space Flight Center, Greenbelt, MD, USA – sequence: 4 givenname: P. surname: Colarco fullname: Colarco, P. organization: NASA/Goddard Space Flight Center, Greenbelt, MD, USA – sequence: 5 givenname: R. surname: Ferrare fullname: Ferrare, R. organization: NASA Langley Research Center, Hampton, VA, USA – sequence: 6 givenname: J. surname: Hair fullname: Hair, J. organization: NASA Langley Research Center, Hampton, VA, USA – sequence: 7 givenname: C. surname: Hostetler fullname: Hostetler, C. organization: NASA Langley Research Center, Hampton, VA, USA – sequence: 8 givenname: J. surname: Tackett fullname: Tackett, J. organization: NASA Langley Research Center, Hampton, VA, USA – sequence: 9 givenname: D. surname: Winker fullname: Winker, D. organization: NASA Langley Research Center, Hampton, VA, USA |
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Cites_doi | 10.1016/j.atmosenv.2013.08.050 10.1029/2003GL018174 10.1029/2000JD000053 10.5194/acp-13-4265-2013 10.1029/2005JD006898 10.1029/93JD02916 10.1175/1520-0493(1999)127<1822:MLEOFA>2.0.CO;2 10.1002/2013JD020937 10.1029/2007GL030135 10.5194/gmd-7-2709-2014 10.5194/acp-9-909-2009 10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2 10.1029/2008JD011497 10.1002/qj.49712757714 10.1073/pnas.1310925110 10.5194/amt-8-3647-2015 10.5194/amt-7-2313-2014 10.1175/JCLI-D-11-00015.1 10.5194/acp-14-2139-2014 10.1029/2009JD012820 10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2 10.1080/10473289.2004.10471005 10.1029/2005JD006996 10.5194/gmd-5-709-2012 10.1289/ehp.0901623 10.1080/10473289.2011.603998 10.1175/2009JTECHA1281.1 10.1364/AO.47.006734 10.1016/S0034-4257(98)00031-5 10.5194/acp-14-1929-2014 10.1029/2003GB002079 10.1029/2008JD011496 10.1029/2003JD004248 10.1056/NEJMsa0805646 10.1016/j.atmosenv.2006.02.039 10.1002/2014GL062089 10.5194/acp-15-5743-2015 10.1109/LGRS.2009.2023605 10.1002/2013JD020328 10.5194/acp-11-3137-2011 10.5194/acp-7-3385-2007 10.5194/acp-14-6049-2014 10.1109/LGRS.2014.2352630 10.1289/ehp.1408646 10.1021/es049352m |
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References | Schaap, Apituley, Timmermans, Koelemeijer, Leeuw (bib38) 2009; 9 Derber, Purser, Wu, Treadon, Pondeca, Parrish, Kleist (bib12) 2003 Toth, Zhang, Campbell, Hyer, Reid, Shi, Westphal (bib40) 2014; 14 Saide, Kim, Song, Choi, Cheng, Carmichael (bib37) 2014; 41 Kishcha, da Silva, Starobinets, Alpert (bib25) 2014; 119 Jaeglé, Quinn, Bates, Alexander, Lin (bib23) 2011; 11 Schwartz, Liu, Lin, Cetola (bib39) 2014; 119 Dee, Da Silva (bib10) 1999; 127 Buchard, da Silva, Colarco, Darmenov, Randles, Govindaraju, Torres, Campbell, Spurr (bib2) 2015; 15 Pope, Ezzati, Dockery (bib34) 2009; 360 Liu, Sarnat, Kilaru, Jacob, Koutrakis (bib29) 2005; 39 Colarco, Kahn, Remer, Levy (bib7) 2014; 7 Pope, Dockery (bib33) 2013; 110 Gupta, Christopher (bib18) 2009; 114 Chen, Liu, Schwartz, Lin, Cetola, Gu, Xue (bib3) 2014; 7 van Donkelaar, Martin, Brauer, Kahn, Levy, Verduzco, Villeneuve (bib41) 2010; 118 Yi, Yang, Dessler, da Silva (bib48) March 2015; 12 Colarco, da Silva, Chin, Diehl (bib5) 2010; 115 Colarco, Schoeberl, Doddridge, Marufu, Torres, Welton (bib6) 2004; 109 Li, Zang, Li, Chao, Chen, Ye, Liu, Liou (bib27) 2013; 13 Winker, Vaughan, Omar, Hu, Powell, Liu, Hunt, Young (bib46) 2009; 26 Wu, Purser, Parrish (bib47) 2002; 130 Gupta, Christopher (bib19) 2009; 114 Winker, Hunt, McGill (bib45) 2007; 34 Holben, Eck, Slutsker, Tanre, Buis, Setzer, Vermote, Reagan, Kaufman, Nakajima (bib22) 1998; 66 Zhang, Reid (bib49) 2006; 111 Ginoux, Chin, Tegen, Prospero, Holben, Dubovik, Lin (bib16) 2001; 106 Lary, Remer, MacNeill, Roscoe, Paradise (bib26) 2010; 6 Freitas, Longo, Chatfield, Latham, Silva Dias, Andreae, Prins, Santos, Gielow, Carvalho (bib15) 2007; 7 Wang, Christopher (bib44) 2003; 30 Chin, Ginoux, Kinne, Torres, Holben, Duncan, Martin, Logan, Higurashi, Nakajima (bib4) 2002; 59 Hand, Copeland, Day, Dillner, Indresand, Malm, McDade, Moore, Pitchford, Schichtel (bib21) 2011 Nowottnick, Colarco, Welton, da Silva (bib32) 2015; 8 Rienecker, Suarez, Todling, Bacmeister, Takacs, Liu, Gu, Sienkiewicz, Koster, Gelaro (bib35) 2008; vol. 27 Rienecker, Suarez, Todling, Bacmeister, Takacs, Liu, Gu, Sienkiewicz, Koster, Gelaro, Stajner, Nielsen (bib36) 2011; 24 Hair, Hostetler, Cook, Harper, Ferrare, Mack, Welch, Izquierdo, Hovis (bib20) 2008; 47 Liu, Easter, Ghan, Zaveri, Rasch, Shi, Lamarque, Gettelman, Morrison, Vitt, Conley, Park, Neale, Hannay, Ekman, Hess, Mahowald, Collins, Iacono, Bretherton, Flanner, Mitchell (bib28) 2012; 5 Darmenov, da Silva (bib9) 2015 van Donkelaar, Martin, Brauer, Boys (bib43) 2015; 123 Malm, Schichtel, Pitchford (bib30) 2011; 61 Engel-Cox, Hoff, Rogers, Dimmick, Rush, Szykman, Al-Saadi, Chu, Zell (bib14) 2006; 40 Buchard, da Silva, Colarco, Krotkov, Dickerson, Stehr, Mount, Spinei, Arkinson, He (bib1) 2014; 14 Kessner, Wang, Levy, Colarco (bib24) 2013; 81 Malm, Sisler, Huffman, Eldred, Cahill (bib31) 1994; 99 Dee, Rukhovets, Todling, da Silva, Larson (bib11) 2001; 127 Gong (bib17) 2003; 17 Crumeyrolle, Chen, Ziemba, Beyersdorf, Thornhill, Winstead, Moore, Shook, Hudgins, Anderson (bib8) 2014; 14 Engel-Cox, Hoff, Haymet (bib13) 2004; 54 van Donkelaar, Martin, Park (bib42) 2006; 111 Buchard (10.1016/j.atmosenv.2015.11.004_bib1) 2014; 14 Toth (10.1016/j.atmosenv.2015.11.004_bib40) 2014; 14 van Donkelaar (10.1016/j.atmosenv.2015.11.004_bib42) 2006; 111 Schwartz (10.1016/j.atmosenv.2015.11.004_bib39) 2014; 119 Lary (10.1016/j.atmosenv.2015.11.004_bib26) 2010; 6 Pope (10.1016/j.atmosenv.2015.11.004_bib33) 2013; 110 Malm (10.1016/j.atmosenv.2015.11.004_bib30) 2011; 61 Yi (10.1016/j.atmosenv.2015.11.004_bib48) 2015; 12 Li (10.1016/j.atmosenv.2015.11.004_bib27) 2013; 13 Darmenov (10.1016/j.atmosenv.2015.11.004_bib9) 2015 Gupta (10.1016/j.atmosenv.2015.11.004_bib19) 2009; 114 Pope (10.1016/j.atmosenv.2015.11.004_bib34) 2009; 360 Chen (10.1016/j.atmosenv.2015.11.004_bib3) 2014; 7 Engel-Cox (10.1016/j.atmosenv.2015.11.004_bib13) 2004; 54 Winker (10.1016/j.atmosenv.2015.11.004_bib45) 2007; 34 Zhang (10.1016/j.atmosenv.2015.11.004_bib49) 2006; 111 Buchard (10.1016/j.atmosenv.2015.11.004_bib2) 2015; 15 Wu (10.1016/j.atmosenv.2015.11.004_bib47) 2002; 130 Derber (10.1016/j.atmosenv.2015.11.004_bib12) 2003 Dee (10.1016/j.atmosenv.2015.11.004_bib10) 1999; 127 Winker (10.1016/j.atmosenv.2015.11.004_bib46) 2009; 26 Dee (10.1016/j.atmosenv.2015.11.004_bib11) 2001; 127 Liu (10.1016/j.atmosenv.2015.11.004_bib29) 2005; 39 Malm (10.1016/j.atmosenv.2015.11.004_bib31) 1994; 99 Wang (10.1016/j.atmosenv.2015.11.004_bib44) 2003; 30 Hair (10.1016/j.atmosenv.2015.11.004_bib20) 2008; 47 Liu (10.1016/j.atmosenv.2015.11.004_bib28) 2012; 5 Engel-Cox (10.1016/j.atmosenv.2015.11.004_bib14) 2006; 40 Colarco (10.1016/j.atmosenv.2015.11.004_bib6) 2004; 109 Jaeglé (10.1016/j.atmosenv.2015.11.004_bib23) 2011; 11 van Donkelaar (10.1016/j.atmosenv.2015.11.004_bib41) 2010; 118 Crumeyrolle (10.1016/j.atmosenv.2015.11.004_bib8) 2014; 14 van Donkelaar (10.1016/j.atmosenv.2015.11.004_bib43) 2015; 123 Ginoux (10.1016/j.atmosenv.2015.11.004_bib16) 2001; 106 Gupta (10.1016/j.atmosenv.2015.11.004_bib18) 2009; 114 Saide (10.1016/j.atmosenv.2015.11.004_bib37) 2014; 41 Nowottnick (10.1016/j.atmosenv.2015.11.004_bib32) 2015; 8 Rienecker (10.1016/j.atmosenv.2015.11.004_bib36) 2011; 24 Chin (10.1016/j.atmosenv.2015.11.004_bib4) 2002; 59 Kessner (10.1016/j.atmosenv.2015.11.004_bib24) 2013; 81 Schaap (10.1016/j.atmosenv.2015.11.004_bib38) 2009; 9 Kishcha (10.1016/j.atmosenv.2015.11.004_bib25) 2014; 119 Gong (10.1016/j.atmosenv.2015.11.004_bib17) 2003; 17 Freitas (10.1016/j.atmosenv.2015.11.004_bib15) 2007; 7 Colarco (10.1016/j.atmosenv.2015.11.004_bib5) 2010; 115 Holben (10.1016/j.atmosenv.2015.11.004_bib22) 1998; 66 Hand (10.1016/j.atmosenv.2015.11.004_bib21) 2011 Rienecker (10.1016/j.atmosenv.2015.11.004_bib35) 2008; vol. 27 Colarco (10.1016/j.atmosenv.2015.11.004_bib7) 2014; 7 |
References_xml | – volume: 12 start-page: 597 year: March 2015 end-page: 600 ident: bib48 article-title: Response of aerosol direct radiative effect to the east asian summer monsoon publication-title: Geosci. Remote Sens. Lett. IEEE – volume: 7 start-page: 3385 year: 2007 end-page: 3398 ident: bib15 article-title: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models publication-title: Atmos. Chem. Phys. – volume: 14 start-page: 1929 year: 2014 end-page: 1941 ident: bib1 article-title: Evaluation of GEOS-5 sulfur dioxide simulations during the Frostburg, MD 2010 field campaign publication-title: Atmos. Chem. Phys. – volume: 7 start-page: 2709 year: 2014 end-page: 2715 ident: bib3 article-title: The impact of aerosol optical depth assimilation on aerosol forecasts and radiative effects during a wild fire event over the United States publication-title: Geosci. Model Dev. – volume: 15 start-page: 5743 year: 2015 end-page: 5760 ident: bib2 article-title: Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis publication-title: Atmos. Chem. Phys. – volume: 81 start-page: 136 year: 2013 end-page: 147 ident: bib24 article-title: Remote sensing of surface visibility from space: a look at the United States east coast publication-title: Atmos. Environ. – volume: 106 start-page: 20255 year: 2001 end-page: 20273 ident: bib16 article-title: Sources and distributions of dust aerosols simulated with the GOCART model publication-title: J. Geophys. Res. Atmos. – volume: 123 start-page: 135 year: 2015 end-page: 143 ident: bib43 article-title: Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter publication-title: Environ. Health Perspect. – volume: 11 start-page: 3137 year: 2011 end-page: 3157 ident: bib23 article-title: Global distribution of sea salt aerosols: new constraints from in situ and remote sensing observations publication-title: Atmos. Chem. Phys. – volume: 41 start-page: 9188 year: 2014 end-page: 9196 ident: bib37 article-title: Assimilation of next generation geostationary aerosol optical depth retrievals to improve air quality simulations publication-title: Geophys. Res. Lett. – volume: 14 start-page: 6049 year: 2014 end-page: 6062 ident: bib40 article-title: Impact of data quality and surface-to-column representativeness on the PM publication-title: Atmos. Chem. Phys. – year: 2011 ident: bib21 article-title: Improve (Interagency Monitoring of Protected Visual Environments): Spatial and Seasonal Patterns and Temporal Variability of Haze and Its Constituents in the United States – volume: 99 start-page: 1347 year: 1994 end-page: 1370 ident: bib31 article-title: Spatial and seasonal trends in particle concentration and optical extinction in the United States publication-title: J. Geophys. Res. Atmos. – volume: 61 start-page: 1131 year: 2011 end-page: 1149 ident: bib30 article-title: Uncertainties in PM2.5 gravimetric and speciation measurements and what we can learn from them publication-title: J. Air Waste Manag. Assoc. – volume: 39 start-page: 3269 year: 2005 end-page: 3278 ident: bib29 article-title: Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing publication-title: Environ. Sci. Technol. – volume: 114 year: 2009 ident: bib19 article-title: Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: multiple regression approach publication-title: J. Geophys. Res. Atmos. – start-page: 32 year: 2015 ident: bib9 article-title: The Quick Fire Emissions Dataset (QFED) – Documentation of Versions 2.1, 2.2 and 2.4 – volume: 59 start-page: 461 year: 2002 end-page: 483 ident: bib4 article-title: Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements publication-title: J. Atmos. Sci. – volume: 127 start-page: 2451 year: 2001 end-page: 2471 ident: bib11 article-title: An adaptive buddy check for observational quality control publication-title: Q. J. R. Meteorol. Soc. – volume: 119 start-page: 1555 year: 2014 end-page: 1570 ident: bib25 article-title: Air pollution over the Ganges basin and northwest Bay of Bengal in the early postmonsoon season based on NASA MERRAero data publication-title: J. Geophys. Res. Atmos. – volume: 8 start-page: 3647 year: 2015 end-page: 3669 ident: bib32 article-title: Use of the CALIOP vertical feature mask for evaluating global aerosol models publication-title: Atmos. Meas. Tech. – volume: vol. 27 start-page: 1 year: 2008 end-page: 118 ident: bib35 article-title: The GEOS-5 data assimilation system-documentation of versions 5.0.1, 5.1.0, and 5.2.0 publication-title: Technical Report Series on Global Modeling and Data Assimilation – volume: 9 start-page: 909 year: 2009 end-page: 925 ident: bib38 article-title: Exploring the relation between aerosol optical depth and PM 2.5 at Cabauw, The Netherlands publication-title: Atmos. Chem. Phys. – volume: 47 start-page: 6734 year: 2008 end-page: 6752 ident: bib20 article-title: Airborne high spectral resolution lidar for profiling aerosol optical properties publication-title: Appl. Opt. – volume: 360 start-page: 376 year: 2009 end-page: 386 ident: bib34 article-title: Fine-particulate air pollution and life expectancy in the United States publication-title: N. Engl. J. Med. – volume: 5 start-page: 709 year: 2012 end-page: 739 ident: bib28 article-title: Toward a minimal representation of aerosols in climate models: description and evaluation in the community atmosphere model CAM5 publication-title: Geosci. Model Dev. – volume: 130 start-page: 2905 year: 2002 end-page: 2916 ident: bib47 article-title: Three-dimensional variational analysis with spatially inhomogeneous covariances publication-title: Mon. Weather Rev. – volume: 119 start-page: 4043 year: 2014 end-page: 4069 ident: bib39 article-title: Assimilating aerosol observations with a hybrid variational-ensemble data assimilation system publication-title: J. Geophys. Res. Atmos. – volume: 127 start-page: 1822 year: 1999 end-page: 1834 ident: bib10 article-title: Maximum-likelihood estimation of forecast and observation error covariance parameters. Part I: methodology publication-title: Mon. Weather Rev. – volume: 54 start-page: 1360 year: 2004 end-page: 1371 ident: bib13 article-title: Recommendations on the use of satellite remote-sensing data for urban air quality publication-title: J. Air Waste Manag. Assoc. – volume: 114 year: 2009 ident: bib18 article-title: Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: 2. A neural network approach publication-title: J. Geophys. Res. Atmos. – volume: 110 start-page: 12861 year: 2013 end-page: 12862 ident: bib33 article-title: Air pollution and life expectancy in china and beyond publication-title: Proc. Natl. Acad. Sci. – volume: 34 start-page: L19803 year: 2007 ident: bib45 article-title: Initial performance assessment of CALIOP publication-title: Geophys. Res. Lett. – volume: 14 start-page: 2139 year: 2014 end-page: 2153 ident: bib8 article-title: Factors that influence surface PM publication-title: Atmos. Chem. Phys. – volume: 40 start-page: 8056 year: 2006 end-page: 8067 ident: bib14 article-title: Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization publication-title: Atmos. Environ. – volume: 24 start-page: 3624 year: 2011 end-page: 3648 ident: bib36 article-title: MERRA: NASA's modern-era retrospective analysis for research and applications publication-title: J. Clim. – volume: 118 start-page: 847 year: 2010 end-page: 855 ident: bib41 article-title: Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application publication-title: Environ. Health Perspect. – volume: 26 start-page: 2310 year: 2009 end-page: 2323 ident: bib46 article-title: Overview of the CALIPSO mission and CALIOP data processing algorithms publication-title: J. Atmos. Ocean. Technol. – volume: 13 start-page: 4265 year: 2013 end-page: 4278 ident: bib27 article-title: A three-dimensional variational data assimilation system for multiple aerosol species with WRF/Chem and an application to PM publication-title: Atmos. Chem. Phys. – year: 2003 ident: bib12 article-title: Flow dependent Jb in a global grid-point 3D-var publication-title: Proc. ECMWF Annual Seminar on Recent Developments in Data Assimilation for Atmosphere and Ocean – volume: 111 year: 2006 ident: bib49 article-title: Modis aerosol product analysis for data assimilation: assessment of over-ocean level 2 aerosol optical thickness retrievals publication-title: J. Geophys. Res. Atmos. – volume: 66 start-page: 1 year: 1998 end-page: 16 ident: bib22 article-title: Aeronet—A federated instrument network and data archive for aerosol characterization publication-title: Remote Sens. Environ. – volume: 6 start-page: 694 year: 2010 end-page: 698 ident: bib26 article-title: Machine Learning and Bias Correction of MODIS aerosol optical depth publication-title: Geosci. Remote Sens. Lett. IEEE – volume: 7 start-page: 2313 year: 2014 end-page: 2335 ident: bib7 article-title: Impact of satellite viewing-swath width on global and regional aerosol optical thickness statistics and trends publication-title: Atmos. Meas. Tech. – volume: 17 year: 2003 ident: bib17 article-title: A parameterization of sea-salt aerosol source function for sub- and super-micron particles publication-title: Glob. Biogeochem. Cycles – volume: 115 year: 2010 ident: bib5 article-title: Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth publication-title: J. Geophys. Res. – volume: 111 year: 2006 ident: bib42 article-title: Estimating ground-level PM2.5 using aerosol optical depth determined from satellite remote sensing publication-title: J. Geophys. Res. Atmos. – volume: 30 year: 2003 ident: bib44 article-title: Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: implications for air quality studies publication-title: Geophys. Res. Lett. – volume: 109 year: 2004 ident: bib6 article-title: Transport of smoke from canadian forest fires to the surface near Washington, DC: injection height, entrainment, and optical properties publication-title: J. Geophys. Res. Atmos. – volume: 81 start-page: 136 year: 2013 ident: 10.1016/j.atmosenv.2015.11.004_bib24 article-title: Remote sensing of surface visibility from space: a look at the United States east coast publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2013.08.050 – volume: 30 issue: 21 year: 2003 ident: 10.1016/j.atmosenv.2015.11.004_bib44 article-title: Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: implications for air quality studies publication-title: Geophys. Res. Lett. doi: 10.1029/2003GL018174 – volume: 106 start-page: 20255 issue: D17 year: 2001 ident: 10.1016/j.atmosenv.2015.11.004_bib16 article-title: Sources and distributions of dust aerosols simulated with the GOCART model publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2000JD000053 – volume: 13 start-page: 4265 issue: 8 year: 2013 ident: 10.1016/j.atmosenv.2015.11.004_bib27 article-title: A three-dimensional variational data assimilation system for multiple aerosol species with WRF/Chem and an application to PM2.5 prediction publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-13-4265-2013 – volume: 111 issue: D22 year: 2006 ident: 10.1016/j.atmosenv.2015.11.004_bib49 article-title: Modis aerosol product analysis for data assimilation: assessment of over-ocean level 2 aerosol optical thickness retrievals publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2005JD006898 – volume: 99 start-page: 1347 issue: D1 year: 1994 ident: 10.1016/j.atmosenv.2015.11.004_bib31 article-title: Spatial and seasonal trends in particle concentration and optical extinction in the United States publication-title: J. Geophys. Res. Atmos. doi: 10.1029/93JD02916 – volume: 127 start-page: 1822 issue: 8 year: 1999 ident: 10.1016/j.atmosenv.2015.11.004_bib10 article-title: Maximum-likelihood estimation of forecast and observation error covariance parameters. Part I: methodology publication-title: Mon. Weather Rev. doi: 10.1175/1520-0493(1999)127<1822:MLEOFA>2.0.CO;2 – volume: 119 start-page: 4043 issue: 7 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib39 article-title: Assimilating aerosol observations with a hybrid variational-ensemble data assimilation system publication-title: J. Geophys. Res. Atmos. doi: 10.1002/2013JD020937 – volume: 34 start-page: L19803 year: 2007 ident: 10.1016/j.atmosenv.2015.11.004_bib45 article-title: Initial performance assessment of CALIOP publication-title: Geophys. Res. Lett. doi: 10.1029/2007GL030135 – volume: 7 start-page: 2709 issue: 6 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib3 article-title: The impact of aerosol optical depth assimilation on aerosol forecasts and radiative effects during a wild fire event over the United States publication-title: Geosci. Model Dev. doi: 10.5194/gmd-7-2709-2014 – volume: 9 start-page: 909 issue: 3 year: 2009 ident: 10.1016/j.atmosenv.2015.11.004_bib38 article-title: Exploring the relation between aerosol optical depth and PM 2.5 at Cabauw, The Netherlands publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-9-909-2009 – volume: 130 start-page: 2905 issue: 12 year: 2002 ident: 10.1016/j.atmosenv.2015.11.004_bib47 article-title: Three-dimensional variational analysis with spatially inhomogeneous covariances publication-title: Mon. Weather Rev. doi: 10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2 – volume: 114 issue: D20 year: 2009 ident: 10.1016/j.atmosenv.2015.11.004_bib18 article-title: Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: 2. A neural network approach publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2008JD011497 – volume: 127 start-page: 2451 issue: 577 year: 2001 ident: 10.1016/j.atmosenv.2015.11.004_bib11 article-title: An adaptive buddy check for observational quality control publication-title: Q. J. R. Meteorol. Soc. doi: 10.1002/qj.49712757714 – volume: 110 start-page: 12861 issue: 32 year: 2013 ident: 10.1016/j.atmosenv.2015.11.004_bib33 article-title: Air pollution and life expectancy in china and beyond publication-title: Proc. Natl. Acad. Sci. doi: 10.1073/pnas.1310925110 – volume: 8 start-page: 3647 issue: 9 year: 2015 ident: 10.1016/j.atmosenv.2015.11.004_bib32 article-title: Use of the CALIOP vertical feature mask for evaluating global aerosol models publication-title: Atmos. Meas. Tech. doi: 10.5194/amt-8-3647-2015 – volume: 7 start-page: 2313 issue: 7 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib7 article-title: Impact of satellite viewing-swath width on global and regional aerosol optical thickness statistics and trends publication-title: Atmos. Meas. Tech. doi: 10.5194/amt-7-2313-2014 – volume: 24 start-page: 3624 issue: 14 year: 2011 ident: 10.1016/j.atmosenv.2015.11.004_bib36 article-title: MERRA: NASA's modern-era retrospective analysis for research and applications publication-title: J. Clim. doi: 10.1175/JCLI-D-11-00015.1 – volume: 14 start-page: 2139 issue: 4 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib8 article-title: Factors that influence surface PM2.5 values inferred from satellite observations: perspective gained for the US Baltimore–Washington metropolitan area during DISCOVER-AQ publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-14-2139-2014 – volume: 115 issue: D14 year: 2010 ident: 10.1016/j.atmosenv.2015.11.004_bib5 article-title: Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth publication-title: J. Geophys. Res. doi: 10.1029/2009JD012820 – volume: 59 start-page: 461 issue: 3 year: 2002 ident: 10.1016/j.atmosenv.2015.11.004_bib4 article-title: Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements publication-title: J. Atmos. Sci. doi: 10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2 – volume: 54 start-page: 1360 issue: 11 year: 2004 ident: 10.1016/j.atmosenv.2015.11.004_bib13 article-title: Recommendations on the use of satellite remote-sensing data for urban air quality publication-title: J. Air Waste Manag. Assoc. doi: 10.1080/10473289.2004.10471005 – volume: 111 issue: D21 year: 2006 ident: 10.1016/j.atmosenv.2015.11.004_bib42 article-title: Estimating ground-level PM2.5 using aerosol optical depth determined from satellite remote sensing publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2005JD006996 – volume: 5 start-page: 709 issue: 3 year: 2012 ident: 10.1016/j.atmosenv.2015.11.004_bib28 article-title: Toward a minimal representation of aerosols in climate models: description and evaluation in the community atmosphere model CAM5 publication-title: Geosci. Model Dev. doi: 10.5194/gmd-5-709-2012 – volume: 118 start-page: 847 issue: 6 year: 2010 ident: 10.1016/j.atmosenv.2015.11.004_bib41 article-title: Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application publication-title: Environ. Health Perspect. doi: 10.1289/ehp.0901623 – volume: 61 start-page: 1131 issue: 11 year: 2011 ident: 10.1016/j.atmosenv.2015.11.004_bib30 article-title: Uncertainties in PM2.5 gravimetric and speciation measurements and what we can learn from them publication-title: J. Air Waste Manag. Assoc. doi: 10.1080/10473289.2011.603998 – volume: 26 start-page: 2310 issue: 11 year: 2009 ident: 10.1016/j.atmosenv.2015.11.004_bib46 article-title: Overview of the CALIPSO mission and CALIOP data processing algorithms publication-title: J. Atmos. Ocean. Technol. doi: 10.1175/2009JTECHA1281.1 – volume: 47 start-page: 6734 issue: 36 year: 2008 ident: 10.1016/j.atmosenv.2015.11.004_bib20 article-title: Airborne high spectral resolution lidar for profiling aerosol optical properties publication-title: Appl. Opt. doi: 10.1364/AO.47.006734 – volume: 66 start-page: 1 issue: 1 year: 1998 ident: 10.1016/j.atmosenv.2015.11.004_bib22 article-title: Aeronet—A federated instrument network and data archive for aerosol characterization publication-title: Remote Sens. Environ. doi: 10.1016/S0034-4257(98)00031-5 – volume: 14 start-page: 1929 issue: 4 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib1 article-title: Evaluation of GEOS-5 sulfur dioxide simulations during the Frostburg, MD 2010 field campaign publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-14-1929-2014 – volume: 17 issue: 4 year: 2003 ident: 10.1016/j.atmosenv.2015.11.004_bib17 article-title: A parameterization of sea-salt aerosol source function for sub- and super-micron particles publication-title: Glob. Biogeochem. Cycles doi: 10.1029/2003GB002079 – volume: 114 issue: D14 year: 2009 ident: 10.1016/j.atmosenv.2015.11.004_bib19 article-title: Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: multiple regression approach publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2008JD011496 – volume: vol. 27 start-page: 1 year: 2008 ident: 10.1016/j.atmosenv.2015.11.004_bib35 article-title: The GEOS-5 data assimilation system-documentation of versions 5.0.1, 5.1.0, and 5.2.0 – volume: 109 issue: D6 year: 2004 ident: 10.1016/j.atmosenv.2015.11.004_bib6 article-title: Transport of smoke from canadian forest fires to the surface near Washington, DC: injection height, entrainment, and optical properties publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2003JD004248 – year: 2011 ident: 10.1016/j.atmosenv.2015.11.004_bib21 – volume: 360 start-page: 376 issue: 4 year: 2009 ident: 10.1016/j.atmosenv.2015.11.004_bib34 article-title: Fine-particulate air pollution and life expectancy in the United States publication-title: N. Engl. J. Med. doi: 10.1056/NEJMsa0805646 – volume: 40 start-page: 8056 issue: 40 year: 2006 ident: 10.1016/j.atmosenv.2015.11.004_bib14 article-title: Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2006.02.039 – volume: 41 start-page: 9188 issue: 24 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib37 article-title: Assimilation of next generation geostationary aerosol optical depth retrievals to improve air quality simulations publication-title: Geophys. Res. Lett. doi: 10.1002/2014GL062089 – volume: 15 start-page: 5743 issue: 10 year: 2015 ident: 10.1016/j.atmosenv.2015.11.004_bib2 article-title: Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-15-5743-2015 – volume: 6 start-page: 694 issue: 4 year: 2010 ident: 10.1016/j.atmosenv.2015.11.004_bib26 article-title: Machine Learning and Bias Correction of MODIS aerosol optical depth publication-title: Geosci. Remote Sens. Lett. IEEE doi: 10.1109/LGRS.2009.2023605 – volume: 119 start-page: 1555 issue: 3 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib25 article-title: Air pollution over the Ganges basin and northwest Bay of Bengal in the early postmonsoon season based on NASA MERRAero data publication-title: J. Geophys. Res. Atmos. doi: 10.1002/2013JD020328 – year: 2003 ident: 10.1016/j.atmosenv.2015.11.004_bib12 article-title: Flow dependent Jb in a global grid-point 3D-var – volume: 11 start-page: 3137 issue: 7 year: 2011 ident: 10.1016/j.atmosenv.2015.11.004_bib23 article-title: Global distribution of sea salt aerosols: new constraints from in situ and remote sensing observations publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-11-3137-2011 – volume: 7 start-page: 3385 issue: 13 year: 2007 ident: 10.1016/j.atmosenv.2015.11.004_bib15 article-title: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-7-3385-2007 – volume: 14 start-page: 6049 issue: 12 year: 2014 ident: 10.1016/j.atmosenv.2015.11.004_bib40 article-title: Impact of data quality and surface-to-column representativeness on the PM2.5/satellite AOD relationship for the contiguous United States publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-14-6049-2014 – volume: 12 start-page: 597 issue: 3 year: 2015 ident: 10.1016/j.atmosenv.2015.11.004_bib48 article-title: Response of aerosol direct radiative effect to the east asian summer monsoon publication-title: Geosci. Remote Sens. Lett. IEEE doi: 10.1109/LGRS.2014.2352630 – volume: 123 start-page: 135 issue: 2 year: 2015 ident: 10.1016/j.atmosenv.2015.11.004_bib43 article-title: Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter publication-title: Environ. Health Perspect. doi: 10.1289/ehp.1408646 – start-page: 32 year: 2015 ident: 10.1016/j.atmosenv.2015.11.004_bib9 – volume: 39 start-page: 3269 issue: 9 year: 2005 ident: 10.1016/j.atmosenv.2015.11.004_bib29 article-title: Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing publication-title: Environ. Sci. Technol. doi: 10.1021/es049352m |
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SubjectTerms | AERONET Aerosols Air pollution atmospheric chemistry chemical speciation data collection emissions MERRAero moderate resolution imaging spectroradiometer MODIS monitoring nitrates optical properties Particulate mater particulates retrospective studies satellites summer United States Environmental Protection Agency wavelengths Western United States winter |
Title | Evaluation of the surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States |
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