Light Scattering Reviews, Volume 11 pp 67-115

Part of the Springer Praxis Books book series (PRAXIS) | Cite as

Community Radiative Transfer Model for Air Quality Studies

Chapter

Abstract

This chapter presented the latest Community Radiative Transfer Model (CRTM), which is applicable for passive microwave, infrared and visible sensors. The CRTM has been used in operational radiance assimilations in support of weather forecasting and in the generation of satellite products. In the paper we discussed the CRTM applications to assimilate aerosol optical depths derived from satellite measurements. The assimilation improved the analysis of aerosol mass concentrations, and enhanced the forecast skill for aerosol mass concentrations. We also introduced a retrieval algorithm and a retrieval product of carbon monoxide by using satellite measurements.

References

  1. Alvarado MJ, Wang C, Prinn RG (2009) Formation of ozone and growth of aerosols in young smoke plumes from biomass burning: 2. Three-dimensional Eulerian studies. J Geophys Res 114:D09307. doi:10.1029/2008JD011186 Google Scholar
  2. Anderson DC, Loughner CP, Weinheimer A, Diskin G, Canty TP, Salawitch RJ, Worden H, Fried A, Mikoviny T, Wisthaler A, Dickerson RR (2014) Measured and modeled CO and NOy in DISCOVER-AQ: an evaluation of emissions and chemistry over the eastern US. Atmos Environ 96:78–87CrossRefGoogle Scholar
  3. Baldridge AM, Hook SJC, Grove I, Rivera G (2009) The ASTER spectral library version 2.0. Remote Sens Environ 113:711–715. doi:10.1016/j.rse.2008.11.007 CrossRefGoogle Scholar
  4. Benedetti A et al (2009) Aerosol analysis and forecast in the European centre for medium-range weather forecasts integrated forecast system: 2. Data assimilation. J Geophys Res 114:D13205. doi:10.1029/2008JD011115 CrossRefGoogle Scholar
  5. Benedetti A, Reid JS, Colarco PR (2011) International cooperative for aerosol prediction (ICAP) workshop on aerosol forecast verification. Bull Am Meteor Soc 92:ES48–ES53. doi:10.1175/BAMS-D-11-00105.1
  6. Bian H, Chin M, Kawa SR, Yu H, Diehl T (2010) Multi-scale carbon monoxide and aerosol correlations from MOPITT and MODIS satellite measurements and GOCART model: implication for their emissions and atmospheric evolutions. J Geophys Res 115:D07302. doi:10.1029/2009JD012781 CrossRefGoogle Scholar
  7. Binkowski FS, Roselle SJ (2003) Models-3 community multiscale air quality (CMAQ) model aerosol component, 1 model description. J Geophys Res 108:4183. doi:10.1029/2001JD001409 CrossRefGoogle Scholar
  8. Boukabara S, Weng F, Liu Q (2007) Passive microwave remote sensing of extreme weather events using NOAA-18 AMSUA and MHS. IEEE Geosci Remote Sens 45:2228–2246CrossRefGoogle Scholar
  9. Buchard V, da Silva A, Colarco P, Darmenov A, Govindaraju R, Spurr R (2014) Using OMI aerosol index and aerosol absorption optical depth to evaluate the NASA MERRA aerosol reanalysis. Atmos Chem Phys Discuss 14:32177–32231CrossRefGoogle Scholar
  10. Byun DW, Schere KL (2006) Review of the governing equations, computational algorithms, and other components of the Models-3 community multiscale air quality (CMAQ) modeling system. Appl Mech Rev 59:51–77CrossRefGoogle Scholar
  11. Byun DW, Hanna A, Coats CJ, Hwang D (1995a) Models-3 air quality model prototype science and computational concept development. Transactions of air & waste management association specialty conference on regional photochemical measurement and modeling studies, San Diego, CA, pp 197–212, 8–12 Nov 1993Google Scholar
  12. Byun DW, Coats CJ, Hwang D, Fine S, Odman T, Hanna A, Galluppi KJ (1995b) Prototyping and implementation of multiscale air quality models for high performance computing. Mission earth symposium, Phoenix, AZ, pp 527–532, 9–13 Apr 1993Google Scholar
  13. Byun DW, Dabdub D, Fine S, Hanna AF, Mathur R, Odman MT, Russell A, Segall EJ, Seinfeld JH, Steenkiste P, Young J (1996) Emerging air quality modeling technologies for high performance computing and communication environments. In: Gryning SE, Schiermeier F (eds) Air pollution modeling and its application XI, pp 491–502Google Scholar
  14. Byun DW, Ching JKS, Novak J, Young J (1998) Development and implementation of the EPA models-3 initial operating version: community multi-scale air quality (CMAQ) model: twenty-second NATO/CCMS international technical meeting on air pollution modelling and its application. In: Gryning SE, Chaumerliac N (eds) Air pollution modeling and its application XII. Plenum Publishing Corporation, Berlin, pp 357–368Google Scholar
  15. Cao C, Xiong J, Blonski S, Liu Q, Uprety S, Shao X, Bai Y, Weng F (2013) Suomi NPP VIIRS sensor data record verification, validation, and long-term performance monitoring. J Geophys Res Atmos 118 (2013) doi:10.1002/2013JD020418
  16. Chai T, Kim H-C, Lee P, Tong D, Pan L, Tang Y, Huang J, McQueen J, Tsidulko M, Stajner I (2013) Evaluation of the United States National Air Quality Forecast Capability experimental real-time predictions in 2010 using air quality system ozone and NO2 measurements. Geosci Model Dev 6:1831–1850. doi:10.5194/gmd-6-1831-2013
  17. Chen Y, Weng F, Han Y, Liu Q (2008) Validation of the community radiative transfer model (CRTM) by using cloudsat data. J Geophys Res 113:D00A03. doi:10.1029/2007JD009561
  18. Chen Y, Han Y, Weng F (2012) Comparison of two transmittance algorithms in the community radiative transfer model: application to AVHRR. J Geophys Res 117:D06206. doi:10.1029/2011JD016656 Google Scholar
  19. Chin M, Savoie DL, Huebert BJ, Bandy AR, Thornton DC, Bates TS, Quinn PK, Saltzman ES, De Bruyn WJ (2000) Atmospheric sulfur cycle in the global model GOCART: Comparison with field observations and regional budgets. J Geophys Res 105:24689–24712CrossRefGoogle Scholar
  20. Chin M, Ginoux P, Kinne S, Torres O, Holben BN, Duncan BN, Martin RV, Logan JA, Higurashi A, Nakajima T (2002) Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sunphotometer measurements. J Atmos Sci 59:461–483CrossRefGoogle Scholar
  21. Chin M, Ginoux P, Lucchesi R, Huebert B, Weber R, Anderson T, Masonis S, Blomquist B, Bandy A, Thornton D (2003) A global aerosol model forecast for the ACE-Asia field experiment. J Geophys Res 108:8654. doi:10.1029/2003JD003642 CrossRefGoogle Scholar
  22. Chin M, Chu DA, Levy R, Remer LA, Kaufman YJ, Holben BN, Eck T, Ginoux P (2004) Aerosol distribution in the northern hemisphere during ACE-Asia: results from global model, satellite observations, and sunphotometer measurements. J Geophy Res 109:D23S90. doi:10.1029/2004JD004829
  23. Chin M, Diehl T, Ginoux P, Malm W (2007) Intercontinental transport of pollution and dust aerosols: implications for regional air quality. Atmos Chem Phys 7:5501–5517CrossRefGoogle Scholar
  24. Chin M, Diehl T, Dubovik O, Eck TF, Holben BN, Sinyuk A, Streets DG (2009) Light absorption by pollution, dust and biomass burning aerosols: a global model study and evaluation with AERONET data. Ann Geophys 27:3439–3464CrossRefGoogle Scholar
  25. Ching JKS, Byun DW, Hanna A, Odman T, Mathur R, Jang C, McHenry J, Galluppi K (1995) Design requirements for multiscale air quality models. Mission earth symposium, Phoenix, AZ, pp 532–538, 9–13 Apr 1995Google Scholar
  26. Clough SA, Shephard MW, Mlawer EJ, Delamere JS, Iacono MJ, Cady-Pereira K, Boukabara S, Brown PD (2005) Atmospheric radiative transfer modeling: a summary of the AER codes. J Quant Spectrosc Radiat Transf 91:233–244. doi:10.1016/j.jqsrt.2004.05.058 CrossRefGoogle Scholar
  27. Coats CJ, Hanna AH, Hwang D, Byun DW (1995) Model engineering concepts for air quality models in an integrated environmental modeling system. Transactions of air & waste management association specialty conference on regional photochemical measurement and modeling studies, San Deigo, CA, pp 213–223, 8–12 Nov 1993Google Scholar
  28. Colarco P, da Silva A, Chin M, Diehl T (2010) Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. J Geophy Res 115:D14207. doi:10.1029/2009JD012820 CrossRefGoogle Scholar
  29. Collins WD, Rasch PJ, Eaton BE, Khattatov BV, Lamarque J-F (2001) Simulating aerosols using a chemical transport model with assimilation of satellite aerosol retrievals: Methodology for INDOEX. J Geophys Res 106:7313–7336. doi:10.1029/2000JD900507 CrossRefGoogle Scholar
  30. Cooke WF, Liousse C, Cachier H, Feichter J (1999) Construction of a 1o x 1o fossil fuel emission data set for carbonaceous aerosol and implementation and radiative impact in the ECHAM4 model. J Geophys Res 104:22137–22162CrossRefGoogle Scholar
  31. Courtier P, Thépaut J-N, Hollingsworth J (1994) A strategy for operational implementation of 4D-Var, using an incremental approach. Q J R Meteorol Soc 120:1367–1387. doi:10.1002/qj.49712051912 CrossRefGoogle Scholar
  32. d’Almeida GA (1991) Atmospheric aerosols, A. Deepak Publishing, HamptonGoogle Scholar
  33. Darmenov A, da Silva AM (2013) The quick fire emissions dataset (QFED)—documentation of versions 2.1, 2.2 and 2.4, NASA technical report series on global modeling and data assimilation. NASA TM-2013-104606, vol 32, pp 1–183Google Scholar
  34. Davidson PM, Seaman N, Schere K, Wayland RA, Hayes JL, Carey KF (2004) National air quality forecasting capability: first steps toward implementation. In: Proceedings of sixth conference on atmospheric chemistry, American Meteorological Society, Seattle, WA (Paper J2.10)Google Scholar
  35. Ding S, Yang P, Weng F, Liu Q, Han Y, van Delst P, Li J, Baum B (2011) Validation of the community radiative transfer model. J Q S Spectrosc Radiat Transf 112:1050–1064Google Scholar
  36. Djalalova IL, Monache D, Wilczak J (2015) PM2.5 analog forecast and Kalman filter post-processing for the community multiscale air quality (CMAQ) model. Atm Envir 108:76–87CrossRefGoogle Scholar
  37. Draxler RR, Ginoux P, Stein AF (2010) An empirically derived emission algorithm for wind blown dust. J Geophys Res 115. doi:10.1029/2009JD013167
  38. Duncan BN, Martin RV, Staudt AC, Yevich R, Logan JA (2003) Interannual and seasonal variability of biomass burning emissions constrained by satellite observations. J Geophys Res 108:4100. doi:10.1029/2002JD002378 CrossRefGoogle Scholar
  39. Eder B, Kang D, Trivikrama Rao S, Mathur R, Yu S, Otte T, Schere K, Wayland R, Jackson S, Davidson P, McQueen J, Bridgers G (2010) Using national air quality forecast guidance to develop local air quality index forecasts. Bull Am Meteor Soc 91:313–326. doi:10.1175/2009BAMS2734.1
  40. Evans KF, Stephens GL (1991) A new polarized atmospheric radiative transfer model. J Quant Spectrosc Radiat Transfer 46:413–423CrossRefGoogle Scholar
  41. Fischer J, Grassl H (1984) Radiative transfer in an atmospheric-ocean system: an azimuthally depedent matrix operator approach. Appl Opt 23:1032–1039CrossRefGoogle Scholar
  42. Gambacorta A, Barnet C, Wolf W, King T, Maddy E, Strow L, Xiong X, Nalli N, Goldberg M (2014) An experiment using high resolution NPP CrIS measurements for atmospheric trace gases: carbon monoxide retrievals impact study. IEEE Geosci Remote Sens Lett 11:1639–1643CrossRefGoogle Scholar
  43. Ginoux P, Chin M, Tegen I, Prospero J, Holben B, Dubovik O, Lin S-J (2001) Sources and global distributions of dust aerosols simulated with the GOCART model. J Geophys Res 106:20255–20273CrossRefGoogle Scholar
  44. Ginoux P, Prospero J, Torres O, Chin M (2004) Long-term simulation of dust distribution with the GOCART model: correlation with the North Atlantic oscillation, environ. Model Softw 19:113–128Google Scholar
  45. Goldberg M, Qu L, McMillin Y, Wolf W, Zhou L, Divakarla M (2003) Airs near-real-time products and algorithms in support of operational weather prediction. IEEE Trans Geosci Remote Sens 41:379–389CrossRefGoogle Scholar
  46. Guenther AC, Hewitt N, Erickson D, Fall R, Geron C, Graedel T, Harley P, Graedel L, Lerdau M, McKay WA, Pierce T, Scholes B, Steinbrecher R, Tallamraju R, Taylor J, Zimmerman P (1995) A global model of natural volatile organic compound emissions. J Geophys Res 100:8873–8892CrossRefGoogle Scholar
  47. Hale GM, Querry MR (1973) Optical constants of water in the 200-nm to 200-mm wavelength region. Appl Opt 12:555–563CrossRefGoogle Scholar
  48. Han Y, van Delst P, Liu Q, Weng F, Yan B, Treadon R, Derber J (2006) Community radiative transfer model (CRTM)—Version 1. NOAA NESDIS Technical Report 122Google Scholar
  49. Han Y, Weng F, Liu Q, van Delst P (2007a) A fast radiative transfer model for SSMIS upper atmosphere sounding channel. J Geophys Res 112:D11121. doi:10.1029/2006JD008208 CrossRefGoogle Scholar
  50. Han Y, Weng F, Liu Q, van Delst P (2007b) A fast radiative transfer model for SSMIS upper atmosphere sounding channel. J Geophys Res 112:D11121. doi:10.1029/2006JD008208 CrossRefGoogle Scholar
  51. Hansen JE, Travis LD (1974) Light scattering in planetary atmospheres. Space Sci Rev 16(1973):527–610CrossRefGoogle Scholar
  52. Heidinger AK, Christopher O, Bennartz R, Greenwald T (2006) The successive-order-of-interaction radiative transfer model. Part I: model development. J Appl Meteorol 45:1388–1402CrossRefGoogle Scholar
  53. Hess M, Koepke P, Schult I (1998) Optical properties of aerosols and clouds: the software package OPAC. Bull Am Met Soc 79:831–844CrossRefGoogle Scholar
  54. Hu YX, Wielicki B, Lin B, Gibson G, Tsay SC, Stamnes K, Wong T (2000) δ-Fit: a fast and accurate treatment of particle scattering phase functions with weighted singular-value decomposition least-squares fitting. JQSRT 65:681–690CrossRefGoogle Scholar
  55. Ignatov A, Sapper J, Laszlo I, Nalli N, Kidwell K (2004) Operational aerosol observations (AEROBS) from AVHRR/3 on board NOAA-KLM satellites. J Atmos Oceanic Technol 21(2004):3–26. doi:10.1175/1520-0426021<0003:OAOAFO>2.0.CO;2 CrossRefGoogle Scholar
  56. Janjic ZI (2003) A nonhydrostatic model based on a new approach. Meteorol Atmos Phys 82:271–285. doi:10.1007/s00703-001-0587-6 CrossRefGoogle Scholar
  57. Kim D, Chin M, Bian H, Tan Q, Brown ME, Zheng T, You R, Diehl T, Ginoux P, Kucsera T (2013) The effect of the dynamic surface bareness to dust source function, emission, and distribution. J Geophys Res 118:1–16. doi:10.1029/2012JD017907 Google Scholar
  58. Kopp TJ, Thomas W, Heidinger AK, Botambekov D, Frey RA, Hutchison KD, Iisager BD, Brueske K, Reed B (2014) The VIIRS cloud mask: progress in the first year of S-NPP toward a common cloud detection scheme. J Geophys Res Atmos 119:2441–2456. doi:10.1002/2013JD020458 CrossRefGoogle Scholar
  59. Koren I, Kaufman YJ, Washington R, Todd MC, Rudich Y, Vanderlei Martins J, Resenfeld D (2006) The Bodele depressions: a single spot in the Sahara that provides most of the mineral dust to the Amazon forecast. Environ Res Lett 1:014005 (5pp). doi:10.1088/1748-9326/1/1/014005
  60. Larrabee Strow L, Hannon SE, De Souza-Machado S, Motteler HE, Tobin E (2003) An overview of the AIRS radiative transfer model. IEEE Trans Geosci Remote Sens 41:303–313Google Scholar
  61. Lee P, Liu Y (2014) Preliminary evaluation of a regional atmospheric chemical data assimilation system environmental surveillance. Int J Environ Res Public Health 11:12795–12816CrossRefGoogle Scholar
  62. Liang S, Zhong B, Fang H (2006) Improved estimation of aerosol optical depth from MODIS imagery over land surfaces. Remote Sens Environ 104:416–425CrossRefGoogle Scholar
  63. Liang X-M, Ignatov A, Kihai Y (2009) Implementation of the community radiative transfer model in advanced clear-sky processor for oceans and validation against nighttime AVHRR radiances. J Geophys Res 114:D06112. doi:10.1029/2008JD010960 CrossRefGoogle Scholar
  64. Liou KN (2002) An introduction to atmospheric radiation, 2nd edn. Academic Press, San DiegoGoogle Scholar
  65. Liss PS, Merlivat L (1986) Air-sea gas exchange rates: introduction and synthesis. In: Buat-Menard P (ed) The role of air-sea exchange in geochemical cycling. Reidel, Hinghan, MA, pp 113–127Google Scholar
  66. Liu G (2008) A database of microwave single-scattering properties for nonspherical ice particles. Bull Am Meteor Soc. 89:1563–1570. doi:10.1175/2008BAMS2486.1 CrossRefGoogle Scholar
  67. Liu Q, Boukabara S (2014) Community radiation transfer model (CRTM) applications in supporting the Suomi national polar-orbiting partnership (SNPP) mission validation and verification. Remote Sen Environ 140:744–754CrossRefGoogle Scholar
  68. Liu Q, Ruprecht E (1996) A radiative transfer model: matrix operator method. Appl Opt 35:4229–4237CrossRefGoogle Scholar
  69. Liu Q, Simmer C (1996) Polarization and intensity in microwave radiative transfer model. Contrib Atmos Phys 69:535–545Google Scholar
  70. Liu Q, Weng F (2006) Advanced doubling-adding method for radiative transfer in planetary atmospheres. J Atmos Sci 63:3459–3465CrossRefGoogle Scholar
  71. Liu Q, Weng F (2009) Recent stratospheric temperature observed from satellite measurements. SOLA 5:53–56. doi:10.2151/sola.2009-014 CrossRefGoogle Scholar
  72. Liu Q, Weng F (2013) Using advanced matrix operator (AMOM) in community radiative transfer. IEEE JSTAR 6:1211–1212. doi:10.1109/JSTARS.2013.2247026 Google Scholar
  73. Liu Q, Xiao S (2014) Effects of spectral resolution and signal-to-noise ratio of hyperspectral sensors on retrieving atmospheric parameters. Opt Lett 39:60–63CrossRefGoogle Scholar
  74. Liu Z, Vaughan M, Winker D, Kittaka C, Getzewich B, Kuehn R, Omar A, Powell K, Trepte C, Hostetler C (2009a) The CALIPSO lidar cloud and aerosol discrimination: version 2 algorithm and initial assessment of performance. J Atmos Oceanic Technol 26:1198–1213CrossRefGoogle Scholar
  75. Liu X, Zhou DK, Larar AM, Smith WL, Schluessel P, Newman SM, Taylor JP, Wu W (2009b) Retrieval of atmospheric profiles and cloud properties from IASI spectra using super-channels. Atmos Chem Phys 9:9121–9142. doi:10.5194/acp-9-9121-2009 CrossRefGoogle Scholar
  76. Liu Z, Liu Q, Lin HC, Schwartz CS, Lee YH, Wang T (2011a) Three-dimensional variational assimilation of MODIS aerosol optical depth: implementation and application to a dust storm over East Asia. J Geophys Res 116:D23206. doi:10.1029/2011JD016159 Google Scholar
  77. Liu Q, Weng F, English S (2011b) An improved fast microwave water emissivity model. IEEE TGRS 49:1238–1250Google Scholar
  78. Liu Q, Li C, Xue Y (2013) Sensor-based clear and cloud radiance calculations in the community radiative transfer model. Appl Opt 52:4981–4990CrossRefGoogle Scholar
  79. Liu H, Remer LA, Huang J, Huang H-C, Kondragunta S, Laszlo I, Oo M, Jackson JM (2014) Preliminary evaluation of S-NPP VIIRS aerosol optical thickness. J Geophys Res Atmos 119(2014):3942–3962. doi:10.1002/2013JD020360 CrossRefGoogle Scholar
  80. Lu S, Huang H-C, Hou Y-T, Tang Y, McQueen J, da Silva A, Chin M, Joseph E, Stockwell W (2010) Development of NCEP global aerosol forecasting system: an overview and its application for improving weather and air quality forecasts. In: NATO science for peace and security series: air pollution modelling and its application vol XX, pp 451–454. doi:10.1007/978-90-481-3812-8, 2010
  81. Lu S, da Silva A, Chin M, Wang J, Moorthi S, Juang H, Chuang HY, Tang Y, Jones L, Iredell M, McQueen J (2013) The NEMS GFS aerosol component: NCEP’s global aerosol forecast system, NCEP Office Note 472. Available at: http://www.lib.ncep.noaa.gov/ncepofficenotes/files/on472.pdf, Washington D.C., 26 pp
  82. Lu S, Iredell M, Wang J, Moorthi S, McQueen J, Chuang H-Y, Hou Y-T, Juang H, Yang W, da Silva A, Chin M (2013) The NEMS GFS aerosol component: NCEP’s global aerosol forecast system, NCEP Office Note 472, 26 pp. Available at: http://www.lib.ncep.noaa.gov/ncepofficenotes/files/on472.pdf, Washington D.C.
  83. McMillin LM, Crone JJ, Goldberg MD, Kleespies TJ (1995) Atmospheric transmittance of an absorbing gas. 4. OPTRAN: a computationally fast and accurate transmittance model for absorbing gases with fixed and variable mixing ratios at variable viewing angles. Appl Opt 34:6269–6274CrossRefGoogle Scholar
  84. Mishchenko MI, Lacis AA, Travis LD (1994) Errors induced by the neglect of polarization in radiance calculations for Rayleigh-scattering atmospheres. J Quant Spectrosc Radiat Transfer 51:491–510CrossRefGoogle Scholar
  85. Mishchenko MI, Travis LD, Lacis AA (2006) Multiple scattering of light by particles. University Press, CambridgeGoogle Scholar
  86. Olivier JG, Bouwman AF, van der Maas CW, Berdowski JJ (1994) Emission database for global atmospheric research (Edgar). Environ Monit Assess 31:93–106. doi:10.1007/BF00547184 CrossRefGoogle Scholar
  87. Otte TL, Pouliot G, Pleim JE, Young JO, Schere KL, Wong DC, Lee PCS, Tsidulko M, McQueen JT, Davidson P, Mathur R, Chuang HY, DiMego G, Seaman NL (2005) Linking the eta model with the community multiscale air quality (CMAQ) modeling system to build a national air quality forecasting system. Weather Forecast 20:367–384CrossRefGoogle Scholar
  88. Pan L, Tong D, Lee P, Kim H-C, Chai T (2014) Assessment of NOx and O3 forecasting performances in the U.S. national air quality forecasting capability before and after the 2012 major emissions updates. Atmos Envir 95:610–619. doi:10.1016/j.atmosenv.2014.06.020
  89. Plass GN, Kattawar W, Catchings FE (1973) Matrix operator theory of radiative transfer, 1: rayleigh scattering. Appl Opt 12:314–329CrossRefGoogle Scholar
  90. Pommier M, Law KS, Clerbaux C, Turquety S, Hurtmans D, Hadji-Lazaro J, Coheur P-F, Schlager H, Ancellet G, Paris J-D, Nédélec P, Diskin GS, Podolske JR, Holloway JS, Bernath P (2010) IASI carbon monoxide validation over the Arctic during POLARCAT spring and summer campaigns. Atmos Chem Phys 10:10655–10678. doi:10.5194/acp-10-10655-2010 CrossRefGoogle Scholar
  91. Potter P, Ramankutty N, Bennett EM, Donner SD (2010) Characterizing the spatial patterns of global fertilizer application and manure production. Earth Interact 14:1–22. doi:10.1175/2009EI288.1 CrossRefGoogle Scholar
  92. Reid JS, Benedetti A, Colarco PR, Hansen JA (2011) International operational aerosol observability workshop. Bull Am Meteor Soc 92:ES21–ES24. doi: 10.1175/2010BAMS3183.1
  93. Remer LA et al (2005) The MODIS aerosol algorithm, products, and validation. J Atmos Sci 62:947–973. doi:10.1175/JAS3385.1 CrossRefGoogle Scholar
  94. Rolph GD, Draxler RR, Stein AF, Taylor A, Ruminski MG, Kondragunta S, Zeng J, Huang H, Manikin G, McQueen JT, Davidson PM (2009) Description and verification of the NOAA smoke forecasting system: the 2007 fire season. Weather Forecast 24:361–378Google Scholar
  95. Rosenkranz PW (2001) Retrieval of temperature and moisture profiles from AMSU-A and AMSU-B measurements. IEEE Trans Geosci Remote Sens 39:2429–2435CrossRefGoogle Scholar
  96. Sarwar G, Luecken D, Yarwood G, Whitten G, Carter B (2008) Impact of an updated carbon bond mechanism on air qual-ity using the community multiscale air quality modeling system: preliminary assessment. J Appl Meteorol Clim 47:3–14CrossRefGoogle Scholar
  97. Saunders RW, Matricardi M, Brunel P (1999) An improved fast radiative transfer model for assimilation of satellite radiance observations. Quart J R Meteorol Soc 125:1407–1425CrossRefGoogle Scholar
  98. Saunders R, Brunel P, von Engeln A, Bormann N, Strow L, Hannon S, Heilliette S, Liu X, Miskolczi F, Han Y, Masiello G, Moncet JL, Uymin G, Sherlock V, Turner DS (2007) A comparison of radiative transfer models for simulating AIRS radiances. J Geophys Res 112:D01S90. doi:10.1029/2006JD007088
  99. Schmetz J, Raschke E (1981) An approximate computation of infrared radiative fluxes in a cloudy atmosphere. Pure appl Geophys 119:248–258CrossRefGoogle Scholar
  100. Seinfeld JH, Pandis SN (2006) Atmospheric chemistry and physics—from air pollution to climate change, 2nd edn. Wiley, New YorkGoogle Scholar
  101. Sessions WR, Reid JS, Benedetti A, Colarco PR, da Silva A, Lu S, Sekiyama T, Tanaka TY, Baldasano JM, Basart S, Brooks ME, Eck TF, Iredell M, Hansen JA, Jorba OC, Juang H-M, Lynch P, Morcrette J-J, Moorthi S, Mulcahy J, Pradhan Y, Razinger M, Sampson CB, Wang J, Westphal DL (2015) Development towards a global operational aerosol consensus: basic climatological characteristics of the international cooperative for aerosol prediction multi-model ensemble (ICAP-MME). Atmos Chem Phys 15:355–362. doi:10.5194/acp-15-335-2015 Google Scholar
  102. Stamnes K, Tsay S-C, Wiscombe W, Jayaweera K (1988) Numerically stable algorithm for discrete ordinate method radiative transfer in multiple scattering and emitting layered media. Appl Opt 27:2502–2529CrossRefGoogle Scholar
  103. Susskind J, Barnet CD, Blaisdell J (2003) Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Trans Geosci Remote Sens 41:390–409CrossRefGoogle Scholar
  104. Sutton MA, Mason KE, Sheppard LJ, Sverdrup H, Haeuber R, Hicks WK (eds) (2014) Nitrogen deposition, critical loads and biodiversity. Springer, New YorkGoogle Scholar
  105. Van de Hulst HC (1963) A new look at multiple scattering, Technical Report. Goddard Institute for Space Studies, NASA, New YorkGoogle Scholar
  106. Van Delst P, Wu X (2000) A high resolution infrared sea surface emissivity database for satellite applications.In: Technical proceedings of eleventh international ATOVS study conference, Budapest, Hungary, pp 407–411, 20–26 SeptGoogle Scholar
  107. Vogel R, Liu Q, Han Y, Weng F (2011) Evaluating a satellite-derived global infrared land surface emissivity data set for use in radiative transfer modeling. J Geophys Res 116:D08105. doi:10.1029/2010JD014679 Google Scholar
  108. Weng F, Liu Q (2003) Satellite data assimilation in numerical weather prediction models, part I: forward radiative transfer and jocobian modeling in cloudy atmospheres. J Atmos Sci 60:2633–2646CrossRefGoogle Scholar
  109. Weng F, Yan B, Grody NC (2001) A microwave land emissivity model. J Geophys Res 106:20,115–20,123Google Scholar
  110. Wiscombe WJ (1980) Improved Mie scattering algorithms. Appl Opt 19:1505–1509CrossRefGoogle Scholar
  111. Wiscombe WJ, The Delta-M Method (1957) Rapid yet accurate radiative flux calculations for strongly asymmetric phase function. J Atmos Sci 34:1408–1422Google Scholar
  112. Wu W-S, Purser RJ, Parrish DF (2002) Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon Weather Rev 130:2905–2916CrossRefGoogle Scholar
  113. Wu X, Liu Q, Zeng J, Grotenhuis M, Qian H, Caponi M, Flynn L, Jaross G, Sen B, Buss R et al (2014) Evaluation of the sensor data record from the nadir instruments of the ozone mapping profiler suite (OMPS). J Geophys Res-ATMOS 119:6170–6180Google Scholar
  114. Yan B, Weng F, Meng H (2008) Retrieval of snow surface microwave emissivity from the advanced microwave sounding unit. J Geophys Res 113:D19206. doi:10.1029/2007JD009559 CrossRefGoogle Scholar
  115. Yang P, Wei HL, Huang HL, Baum BA, Hu YX, Kattawar GW, Mishchenko MI (2005) Fu, Scattering and absorption property database for nonspherical ice particles in the near- through far-infrared spectral region. Appl Opt 44:5512–5523CrossRefGoogle Scholar
  116. Yang K, Simon A, Ge CC, Wang J, Dickerson RR (2014) Advancing measurements of tropospheric NO2 from space: New algorithm and first global results from OMPS. Geophys Res Lett 41(2014):4777–4786. doi:10.1002/2014GL060136 Google Scholar
  117. Zhang X, Kondragunta X, Ram J, Schmidt C, Huang H-C (2011) Near-real-time global biomass burning emissions products from geostationary satellite constellation. J Geophys Res 117:D14201. doi:10.1029/2012JD017459 Google Scholar
  118. Zhou L, Goldberg M, Barnet C, Cheng Z, Sun F, Wolf W, King T, Liu X, Sun H, Divakarla M (2008) Regression of surface spectral emissivity from hyperspectral instruments. IEEE Trans Geosci Remote Sens 46:328–333CrossRefGoogle Scholar
  119. Zhou DK, Larar AM, Liu X, Smith WL, Larrabee Strow L, Yang P, Schlüssel P, Calbet X (2011) Global land surface emissivity retrieved from satellite ultraspectral IR measurements. IEEE Trans Geosci Remote Sens 49:1277–1290. doi:10.1109/TGRS.2010.2051036 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Center for Satellite Applications and ResearchNational Oceanic and Atmospheric AdministrationCollege ParkUSA
  2. 2.Atmospheric Sciences Research CenterState University of New YorkAlbanyUSA

Personalised recommendations