Climate Dynamics

, Volume 40, Issue 9–10, pp 2515–2533 | Cite as

Evaluation of regional climate simulations for air quality modelling purposes

  • Laurent Menut
  • Om P. Tripathi
  • Augustin Colette
  • Robert Vautard
  • Emmanouil Flaounas
  • Bertrand Bessagnet


In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional “climate modeling” source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.


Climate change Regional modelling Air quality 



This study is carried out in the framework of the COordinated Regional Downscaling EXperiment (CORDEX). The evaluation is also part of the French National project SALUTAIR whose aim is to provide future regional air quality scenario simulations, in the framework of the PRIMEQUAL program. All simulations were done on the CEA CCRT computers.


  1. Amann M, Bertok I, Cofala J, Gyarfas F, Heyes C, Klimont Z, Schopp W, Winiwater W (2005) Clean air for Europe (CAFE) program final report. International Institute for Applied Systems Analysis, Laxenburg, AustriaGoogle Scholar
  2. Appel K, Roselle S, Gilliam R, Pleim J (2010) Sensitivity of the community multiscale air quality (CMAQ) model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers. Geosci Model Dev 3:169–188CrossRefGoogle Scholar
  3. Beniston M, Stephenson DB, Christensen OB, Ferro CAT, Frei C, Goyette S, Halsnaes K, Holt T, Jylha K, Koffi B, Palutikof J, Schoell R, Semmler T, Woth K (2007) Future extreme events in European climate: an exploration of regional climate model projections. Clim Change 81(1):71–95CrossRefGoogle Scholar
  4. Carvalho A, Monteiro A, Solman S, Miranda A, Borrego C (2010) Climate-driven changes in air quality over Europe by the end of the 21st century with special reference to Portugal. Environ Sci Policy 13:445–458CrossRefGoogle Scholar
  5. Cattiaux J, Quesada B, Arakelian A, Codron F, Vautard R, Yiou P (2011) North-Atlantic dynamics and European temperature extremes in the IPSL model: sensitivity to atmospheric resolution. Clim Dyn (this issue)Google Scholar
  6. Cha DH, Jin CS, Lee DK, Kuo YH (2011) Impact of intermittent spectral nudging on regional climate simulation using weather research and forecasting model. J Geophys Res 116:D10,103CrossRefGoogle Scholar
  7. Chen F, Dudhia J (2001) Coupling an advanced land-surface/hydrology model with the penn state NCARMM5 modeling system. part i: model implementation and sensitivity. Mon Weather Rev 129:569–585CrossRefGoogle Scholar
  8. Christensen J, Carter T, Rummukainen M, Amanatidis G (2007) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Change 81:1–6CrossRefGoogle Scholar
  9. Colette A, Favez O, Meleux F, Chiappini L, Haeffelin M, Morille Y, Malherbe L, Papin A, Bessagnet B, Menut L, Leoz E, Rouil L (2011a) Assessing in near real time the impact of the April 2010 Eyjafjallajokull ash plume on air quality. Atmos Environ 45:1217–1221CrossRefGoogle Scholar
  10. Colette A, Granier C, Hodnebrog O, Jakobs H, Maurizi A, Nyiri A, Bessagnet B, D Angiola A, D Isidoro M, Gauss M, Meleux F, Memmesheimer M, Mieville A, Rouil L, Russo F, Solberg S, Stordal F, Tampieri F (2011b) Air quality trends in Europe over the past decade: a first multi-model assessment. Atmos Chem Phys Discuss 11:19,029–19,087CrossRefGoogle Scholar
  11. Crétat J, Pohl B, Richard Y, Drobinski P (2011) Uncertainties in simulating regional climate of Souterhn Africa: sensitivity to physical parameteirzations using WRF. Clim Dyn 1–22. doi: 10.1007/s00382-011-1055-8
  12. Cuvelier C, Thunis P, Vautard R, Amann M, Bessagnet B, Bedogni M, Berkowicz R, Brandt J, Brocheton F, Builtjes P, Carnavale C, Coppalle A, Denby B, Douros J, Graf A, Hellmuth O, Hodzic A, Honore C, Jonson J, Kerschbaumer A, de Leeuw F, Minguzzi E, Moussiopoulos N, Pertot C, Peuch VH, Pirovano G, Rouil L, Sauter F, Schaap M, Stern R, Tarrason L, Vignati E, Volta M, White L, Wind P, Zuber A (2007) CityDelta: a model intercomparison study to explore the impact of emission reductions in European cities in 2010. Atmos Environ 41(1):189–207CrossRefGoogle Scholar
  13. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Holm EV, Isaksen L, Kallberg P, Kohler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thepaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597. doi: 10.1002/qj.828.
  14. Fichefet T, Morales-Maqueda A (1999) Modelling the influence of snow accumulation and snow-ice formation on the seasonal cycle of the Antarctic sea-ice cover. Clim Dyn 15(4):251–268CrossRefGoogle Scholar
  15. Flaounas E, Bastin S, Janicot S (2011) Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF. Clim Dyn 1–23. doi: 10.1007/s00382-010-0785-3
  16. Grell GA, Devenyi D (2002) A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys Res Lett 29(14):1693. doi: 10.1029/2002GL015311 CrossRefGoogle Scholar
  17. Haylock MR, Hofstra N, Tank AMGK, Klok EJ, Jones PD, New M (2008) A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. J Geophys Res Atmos 113(D20). doi: 10.1029/2008JD010201
  18. Heikkila U, Sandvik A, Sorteberg A (2010) Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model. Clim Dyn 1–14. doi: 10.1007/s00382-010-0928-6
  19. Hogrefe C, Rao S, Kasibhatla P, Kallos G, Tremback C, Hao W, Olerud D, Xiu A, McHenry J, Alapaty K (2001) Evaluating the performance of regional-scale photochemical modeling systems: part I—meteorological predictions. Atmos Environ 35:4159–4174CrossRefGoogle Scholar
  20. Hogrefe C, Hao W, Zalewsky E, Ku J, Lynn B, Rosenzweig C, Schultz M, Rast S, Newchurch M, Wang L, Kinney P, Sistla G (2011) An analysis of long-term, regional-scale ozone simulations over the North-Eastern United States: variability and trends. Atmos Chem Phys 11:567–582CrossRefGoogle Scholar
  21. Hong SY, Dudhia J, Chen S (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–120CrossRefGoogle Scholar
  22. Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341. doi: 10.1175/MWR3199.1 CrossRefGoogle Scholar
  23. Hourdin F, Musat I, Bony S, Braconnot P, Codron F, Dufresne J, Fairhead L, Filiberti M, Friedlingstein P, Grandpeix J, Krinner G, Levan P, Li Z, Lott F (2006) The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Clim Dyn 27:787–813CrossRefGoogle Scholar
  24. Hourdin F, Foujols M, Codron F, Guemas V, Dufresne J, Bony S, Denvil S, Guez L, Lott F, Gattahs J, Braconnot P, Marti O, Meurdesoif Y (2011a) From LMDZ4 to LMDZ5: impact of the atmospheric model grid configuration on the climate and sensitivity of IPSL climate model. Clim Dyn (this special issue)Google Scholar
  25. Hourdin F, Grandpeix JY, Rio C, Bony S, Jam A, Cheruy F, Rochetin N, Fairhead L, Idelkadi A, Musat I, Dufresne JL, Lefebvre MP, Lahellec A, Guichard F, Lafore JP, Couvreux F, Roehrig R (2011b) LMDZ5 New physics : impact on the climatology and sensitivity of the IPSL climate model of a refundation of the boundary layer/convection/cloud parameterization. Clim Dyn (this special issue)Google Scholar
  26. IPCC (2007) Climate change 2007—the physical science basis, contribution of working group I to the fourth assessment report of the IPCC. IPCC Geneva, p 981Google Scholar
  27. Isaksen ISA, Granier C, Myhre G, Berntsen TK, Dalsøren SB, Gauss M, Klimont Z, Benestad R, Bousquet P, Collins W, Cox T, Eyring V, Fowler D, Fuzzi S, Jöckel P, Laj P, Lohmann U, Maione M, Monks P, Prevot ASH et al (2009) Atmospheric composition change: climate-chemistry interactions. Atmos Environ 43(33):5138–5192Google Scholar
  28. Jacob D, Barring L, Christensen OB, Christensen JH, de Castro M, Deque M, Giorgi F, Hagemann S, Hirschi M, Jones R, Kjellstrom E, Lenderink G, Rockel B, Sanchez E, Schar C, Seneviratne SI, Somot S, van Ulden A, van den Hurk B (2007) An intercomparison of regional climate models for Europe: model performance in present-day climate. Clim Change. doi: 10.1007/s10584-006-9213-4
  29. Kain J (2004) The Kain-Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181CrossRefGoogle Scholar
  30. Kjellstrom E, Nikulin G, Strandberg G, Ullerstig A (2011) 21st century changes in the European climate: uncertainties derived from an ensemble of regional climate model simulations. Tellus 63A:24–40Google Scholar
  31. Krinner G, Viovy N, de Noblet-Ducoudre N, Ogee J, Polcher J, Friedlingstein P, Ciais P, Sitch S, Prentice I (2005) A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. J Glob Biogeochem Cycle 19. doi: 10.1029/2003GB002199
  32. Leibensperger EM, Mickley LJ, Jacob DJ, Chen WT, Seinfeld JH, Nenes A, Adams PJ, Streets DG, Kumar N, Rind D (2011) Climatic effects of 1950–2050 changes in US anthropogenic aerosols—Part 1: aerosol trends and radiative forcing. Atmos Chem Phys Discuss 11(8):24,085–24,125.
  33. Madec G, Delecluse P, Imbard M, Levy C (1997) Ocean general circulation model reference manual, 3. LODYC, Technical Report, p 91Google Scholar
  34. Marti O, Braconnot P, Dufresne J, Bellier J, Benshila R, Bony S, Brockmann P, Cadule P, Caubel A, Codron F, de Noblet N, Denvil S, Fairhead L, Fichefet T, Foujols MA, Friedlingstein P, Goosse H, Grandpeix JY, Guilyardi E, Hourdin F, Idelkadi A, Kageyama M, Krinner G, Levy C, Madec G, Mignot J, Musat I, Swingedouw D, Talandier C (2010) Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution. Clim Dyn 34(1):1–26. doi: 10.1007/s00382-009-0640-6 CrossRefGoogle Scholar
  35. de Meij A, Gzella A, Cuvelier C, Thunis P, Bessagnet B, Vinuesa J, Menut L, H K (2009) The impact of MM5 and WRF meteorology over complex terrain on CHIMERE model calculations. Atmos Chem Phys 9:6611–6632CrossRefGoogle Scholar
  36. Meinke I, Geyer B, Feser F, von Storch H (2006) The impact of spectral nudging on cloud simulation with a regional atmospheric model. J Atmos Ocean Tehcnol 23:815–824CrossRefGoogle Scholar
  37. Meleux F, Solmon F, Giorgi F (2007) Increase in European summer ozone amounts due to climate change. Atmos Environ 41:7577–7587CrossRefGoogle Scholar
  38. Menut L (2008) Sensitivity of hourly Saharan dust emissions to NCEP and ECMWF modelled wind speed. J Geophys Res Atmos 113:D16,201. doi: 10.1029/2007JD009522 CrossRefGoogle Scholar
  39. Menut L, Bessagnet B (2010) Atmospheric composition forecasting in Europe. Ann Geophys 28:61–74CrossRefGoogle Scholar
  40. Miguez-Macho G, Stenchikov GL, Robock A (2004) Spectral nudging to eliminate the effects of domain position and geometry in regional climate model simulations. J Geophys Res 109:D13,104CrossRefGoogle Scholar
  41. Mlawer EJ, Taubman S, Brown P, Iacono M, Clough S (1997) Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated k-model for the longwave. J Geophys Res 102:16,663–16,682CrossRefGoogle Scholar
  42. Nikulin G, Kjellstrom E, Hansson U, Jones C, Strandberg G, Ullerstig A (2011) Evaluation and future projections of temperature, precipitation and wind extremes over Europe in an ensemble of regional climate simulations. Tellus 63A:41–55Google Scholar
  43. Pierce T, Hogrefe C, Rao ST, Porter S, Ku JY (2010) Dynamic evaluation of a regional air quality model: assessing the emission-induced weekly ozone cycle. Atmos Environ 44:3583–3596. doi: 10.1016/j.atmosenv.2010.05.046 CrossRefGoogle Scholar
  44. Pirovano G, Coll I, Bedogni M, Alessandrini S, Costa M, Gabusi V, Lasry F, Menut L, Vautard R (2007) On the influence of meteorological input on photochemical modelling of a severe episode over a coastal area. Atmos Environ 41:6445–6464CrossRefGoogle Scholar
  45. Rouil L, Honore C, Vautard R, Beekmann M, Bessagnet B, Malherbe L, Meleux F, Dufour A, Elichegaray C, Flaud J, Menut L, Martin D, Peuch A, Peuch V, Poisson N (2009) PREV’AIR : an operational forecasting and mapping system for air quality in Europe. BAMS 90:73–83. doi: 10.1175/2008BAMS2390.1 CrossRefGoogle Scholar
  46. Sanchez-Gomez E, Somot S, Deque M (2009) Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961–2000. Clim Dyn T33:723–736CrossRefGoogle Scholar
  47. Seaman N (2000) Meteorological modeling for air-quality assessments. Atmos Environ 34(12-14):2231–2259. doi: 10.1016/S1352-2310(99)00466-5 CrossRefGoogle Scholar
  48. Separovic L, de Elia R, Laprise R (2011) Impact of spectral nudging and domain size in studies of RCM response to parameter modification. Clim Dyn 1–19.
  49. Shindell D, Lamarque J-F, Unger N, Koch D, Faluvegi G, Bauer S, Ammann M, Cofala J, Teich H (2008) Climate forcing and air quality change due to regional emissions reductions by economic sector. Atmos Chem Phys 8:7101–7113CrossRefGoogle Scholar
  50. Shindell DT, Faluvegi G, Walsh M, Anenberg SC, Dingenen RV, Muller NZ, Austin J, Koch D, Milly G (2011) Climate, health, agricultural and economic impacts of tighter vehicle emission standards. Nat Clim Change. doi: 10.1038/NCLIMATE1006
  51. Smyth S, Yin D, Roth H, Jiang W, Moran M, Crevier LP (2006) The impact of GEM and MM5 meteorology on CMAQ air quality modeling results in eastern Canada and the northeastern United States. J Appl Meteorol 45:1525–1541. doi: 10.1175/JAM2420.1 CrossRefGoogle Scholar
  52. Uppala S, Simmons A, Dee D, Kallberg P, Thepaut JN (2008) Atmospheric reanalyses and climate variations. In: Bronnimann S, Luterbacher J, Ewen T, Diaz HF, Stolarski RS, Neu U (eds) Climate variability and extremes during the past 100 years, Springer, Advances in Global Change Research, vol 33, pp 103–117. doi: 10.1007/978-1-4020-6766-2_6
  53. Valari M, Chatignoux E, Menut L (2011) Using a chemistry transport model to account for the spatial variability of exposure-concentrations in epidemiologic air pollution studies. J Air Waste Manag Assoc 61:164–179CrossRefGoogle Scholar
  54. Vautard R, Szopa S, Beekmann M, Menut L, Hauglustaine DA, Rouil L, Roemer M (2006) Are decadal anthropogenic emission reductions in Europe consistent with surface ozone observations? Geophys Res Lett 33:L13,810. doi: 10.1029/2006GL026080 Google Scholar
  55. Vautard R, Cattiaux J, Yiou P, Thepaut JN, Ciais P (2010) Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nat Geosci 3:756–761CrossRefGoogle Scholar
  56. Vautard R, Moran MD, Solazzo E, Gilliam RC, Matthias V, Bianconi R, Chemel C, Ferreira J, Geyer B, Hansen AB, Jericevic A, Prank M, Segers A, Silver JD, Werhahn J, Wolke R, Rao ST, Galmarini S (2012) Evaluation of the meteorological forcing used for the air quality model evaluation international initiative (AQMEII) air quality simulations. Atmos Environ 53:15–37Google Scholar
  57. Von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Weather Rev 128:3664–3673CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Laurent Menut
    • 1
  • Om P. Tripathi
    • 1
    • 2
  • Augustin Colette
    • 3
  • Robert Vautard
    • 4
  • Emmanouil Flaounas
    • 1
  • Bertrand Bessagnet
    • 3
  1. 1.Institut P.-S. Laplace, Laboratoire de Météorologie Dynamique, CNRS UMR 8539, Ecole PolytechniquePalaiseauFrance
  2. 2.Department of Atmospheric SciencesUniversity of ArizonaTucsonUSA
  3. 3.INERIS, Institut National de l’Environnement Industriel et des Risques, Parc technologique ALATAVerneuil en HalatteFrance
  4. 4.Laboratoire des Sciences du Climat et de l’Environnement, IPSL/CEAGif sur YvetteFrance

Personalised recommendations