Theoretical and Applied Climatology

, Volume 130, Issue 3–4, pp 1175–1188 | Cite as

Sensitivity analysis of different parameterization schemes using RegCM4.3 for the Carpathian region

  • Ildikó Pieczka
  • Rita Pongrácz
  • Karolina Szabóné André
  • Fanni Dóra Kelemen
  • Judit Bartholy
Original Paper

Abstract

In order to quantify the impact of the use of different parameterization schemes on regional climate model outputs, hindcast experiments have been completed applying the Regional Climate Model version 4.3 (RegCM4.3) for the Carpathian region and its surroundings at 10-km horizontal resolution with three different cumulus convection schemes. Besides, the sensitivity of outputs for subgrid-scale processes is also studied by activating the subgrid Biosphere-Atmosphere Transfer Scheme (BATS) model within other RegCM experiments. Among the analyzed factors, RegCM is most sensitive to the applied convection scheme. The impact of closure assumption related to the used convective parameterization is secondary, while the use of subgridding has less influence on the outputs. RegCM4.3 results show improved performance over our previous model simulations but still have larger amplitude for annual precipitation cycle than the measurement-based reference data. Our validation results for temperature and precipitation suggest that for the selected region, the overall best performance is achieved when using the mixed Grell-Emanuel scheme together with Fritsch and Chappell closure.

References

  1. Anthes RA (1977) A cumulus parameterization scheme utilizing a one-dimensional cloud model. Mon Weather Rev 105(3):270–286CrossRefGoogle Scholar
  2. Arakawa A, Schubert WH (1974) Interaction of a cumulus cloud ensemble with the large scale environment. Part I J Atmos Sci 31:674–701CrossRefGoogle Scholar
  3. Arritt RW (2012) Interaction of convective parameterization and horizontal resolution in simulating precipitation over the CORDEX Central America domain. Presented at CLIVAR VAMOS Workshop on Modeling and Predicting Climate in the Americas, Petropolis, Brazil, 4–6 June 2012Google Scholar
  4. Berrisford P, Dee D, Poli P, Brugge R, Fielding K, Fuentes M, Kallberg P, Kobayashi S, Uppala S, Simmons A (2011) The ERA-Interim archive Version 2.0, ERA Report Series 1. 27p. ECMWF, UKGoogle Scholar
  5. Christensen JH, Kjellström E, Giorgi F, Lenderink G, Rummukainen M (2010) Weight assignment in regional climate models. Clim Res 44(2–3):179–194CrossRefGoogle Scholar
  6. Dash SK, Shekhar MS, Singh GP (2006) Simulation of Indian summer monsoon circulation and rainfall using RegCM3. Theor Appl Climatol 86(1–4):161–172CrossRefGoogle Scholar
  7. Davis N, Bowden J, Semazzi F, Xie L, Önol B (2009) Customization of RegCM3 regional climate model for eastern Africa and a tropical Indian Ocean domain. J Clim 22(13):3595–3616CrossRefGoogle Scholar
  8. Déqué M, Jones RG, Wild M, Giorgi F, Christensen JH, Hassell DC, Vidale PL, Rockel B, Jacob D, Kjellström E, De Castro M (2005) Global high resolution versus limited area model climate change projections over Europe: quantifying confidence level from PRUDENCE results. Clim Dynam 25(6):653–670CrossRefGoogle Scholar
  9. Dickinson RE, Henderson-Sellers A, Kennedy PJ (1993) Biosphere-atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model. NCAR Technical Note NCAR/TN-387 + STR. doi: 10.5065/D67W6959
  10. Elguindi N, Bi X, Giorgi F, Nagarajan B, Pal J, Solmon F, Rauscher S, Zakey A, Giuliani G (2011) Regional climatic model RegCM user manual version 4.3. 32p. ICTP, TriesteGoogle Scholar
  11. Elguindi N, Bi X, Giorgi F, Nagarajan B, Pal J, Solmon F, Rauscher S, Zakey A, O’Brien T, Nogherotto R, Giuliani G. (2014) Regional Climate Model RegCM User Manual Version 4.4. 34p. ICTP, TriesteGoogle Scholar
  12. Emanuel KA (1991) A scheme for representing cumulus convection in large-scale models. J Atmos Sci 48(21):2313–2335CrossRefGoogle Scholar
  13. Emanuel KA, Zivkovic-Rothman M (1999) Development and evaluation of a convection scheme for use in climate models. J Atmos Sci 56:1766–1782CrossRefGoogle Scholar
  14. Fox-Rabinovitz M, Cote J, Dugas B, Deque M, McGregor JL, Belochitski A (2008) Stretched-grid model Intercomparison project: decadal regional climate simulations with enhanced variable and uniform-resolution GCMs. Meteorog Atmos Phys 100(1–4):159–178CrossRefGoogle Scholar
  15. Fritsch JM, Chappell CF (1980) Numerical prediction of convectively driven mesoscale pressure systems. Part I: convective parameterization. J Atmos Sci 37:722–1733Google Scholar
  16. Giorgi F, Shields C (1999) Tests of precipitation parameterizations available in latest version of NCAR regional climate model (RegCM) over continental United States. J Geophys Res-Atmos 104(D6):6353–6375CrossRefGoogle Scholar
  17. Giorgi F, Marinucci MR, Bates GT, DeCanio G (1993) Development of a second generation regional climate model (RegCM2). Part II: convective processes and assimilation of lateral boundary conditions. Mon Weather Rev 121:2814–2832CrossRefGoogle Scholar
  18. Giorgi F, Francisco R, Pal J (2003) Effects of a subgrid-scale topography and land use scheme on the simulation of surface climate and hydrology. Part I: effects of temperature and water vapor disaggregation. J Hydrometeorol 4(2):317–333CrossRefGoogle Scholar
  19. Giorgi F, Coppola E, Solmon F, Mariotti L, Sylla MB, Bi X, Elguindi N, Diro GT, Nair V, Giuliani G, Turuncoglu UU, Cozzini S, Güttler I, O’Brien TA, Tawfik AB, Shalaby A, Zakey AS, Steiner AL, Stordal F, Sloan LC, Brankovic C (2012) RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim Res 52:7–29CrossRefGoogle Scholar
  20. Grell GA (1993) Prognostic evaluation of assumptions used by cumulus parameterizations. Mon Weather Rev 121(3):764–787CrossRefGoogle Scholar
  21. Grell GA, Dudhia J, Stauffer DR (1994) Description of the fifth generation Penn State/NCAR Mesoscale Model (MM5), Tech. Rep. TN-398 + STR. 121p. NCAR, BoulderGoogle Scholar
  22. Güttler I, Branković Č, Srnec L, Patarčić M (2014) The impact of boundary forcing on RegCM4. 2 surface energy budget. Clim Chang 125(1):67–78CrossRefGoogle Scholar
  23. Hamilton K, Ohfuchi W (2008) High-resolution numerical modeling of atmosphere and ocean. Springer, BerlinCrossRefGoogle Scholar
  24. Holtslag AAM, De Bruijn EIF, Pan HL (1990) A high resolution air mass transformation model for short-range weather forecasting. Mon Weather Rev 118(8):1561–1575CrossRefGoogle Scholar
  25. Jacob D, Bärring L, Christensen OB, Christensen JH, de Castro M, Deque M, Giorgi F, Hagemann S, Hirschi M, Jones R, Kjellström E, Lenderink G, Rockel B, Sánchez E, Schar C, Seneviratne S, Somot S, van Ulden A, van den Hurk B (2007) An inter-comparison of regional climate models for Europe: model performance in present-day climate. Clim Chang 81(1):31–52CrossRefGoogle Scholar
  26. Kiehl JT, Hack JJ, Bonan GB, Boville BA, Breigleb BP, Williamson D, Rasch P (1996) Description of the NCAR Community Climate Model (CCM3). Tech. Rep. NCAR/TN-420 + STR. NCAR, BoulderGoogle Scholar
  27. Kotlarski S, Keuler K, Christensen OB, Colette A, Déqué M, Gobiet A, Goergen K, Jacob D, Lüthi D, van Meijgaard E, Nikulin G, Schär C, Teichmann C, Vautard R, Warrach-Sagi K, Wulfmeyer V (2014) Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble. Geosci Model Dev 7:1297–1333CrossRefGoogle Scholar
  28. Lenderink G (2010) Exploring metrics of extreme daily precipitation in a large ensemble of regional climate model simulations. Clim Res 44(2):151–166CrossRefGoogle Scholar
  29. Liu YY, Parinussa RM, Dorigo WA, De Jeu RAM, Wagner W, van Dijk AIJM, McCabe MF, Evans JP (2011) Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrol Earth Syst Sc 15:425–436CrossRefGoogle Scholar
  30. Liu YY, Dorigo WA, Parinussa RM, de Jeu RAM, Wagner W, McCabe MF, Evans JP, van Dijk AIJM (2012) Trend-preserving blending of passive and active microwave soil moisture retrievals. Remote Sens Environ 123:280–297CrossRefGoogle Scholar
  31. Martínez-Castro D, da Rocha RP, Bezanilla-Morlot A, Alvarez-Escudero L, Reyes-Fernández JP, Silva-Vidal Y, Arritt RW (2006) Sensitivity studies of the RegCM3 simulation of summer precipitation, temperature and local wind field in the Caribbean region. Theor Appl Climatol 86(1–4):5–22CrossRefGoogle Scholar
  32. Peng J, Niesel J, Loew A, Zhang S, Wang J (2015) Evaluation of satellite and reanalysis soil moisture products over Southwest China using ground-based measurements. Remote Sens 7(11):15729–15747CrossRefGoogle Scholar
  33. Ploshay JJ, Lau NC (2010) Simulation of the diurnal cycle in tropical rainfall and circulation during boreal summer with a high-resolution GCM. Mon Weather Rev 138(9):3434–3453CrossRefGoogle Scholar
  34. Raju PVS, Bhatla R, Almazroui M, Assiri M (2015) Performance of convection schemes on the simulation of summer monsoon features over the South Asia CORDEX domain using RegCM-4.3. Int J Climatol 35(15):4695–4706CrossRefGoogle Scholar
  35. Rulfová Z, Kyselý J (2013) Disaggregating convective and stratiform precipitation from station weather data. Atmos Res 134:100–115CrossRefGoogle Scholar
  36. Rummukainen M (2010) State of the art with regional climate models. Wiley Interdiscip Rev Clim Chang 1(1):82–96CrossRefGoogle Scholar
  37. Ruti PM, Somot S, Giorgi F, et al. (2015) MED-CORDEX initiative for Mediterranean climate studies. B Am Meteorol Soc. doi:10.1175/BAMS-D-14-00176.1 Google Scholar
  38. Singh AP, Singh RP, Raju PVS, Bhatla R (2011) The impact of three different cumulus parameterization schemes on the Indian summer monsoon circulation. Int J Ocean Climate Syst 2(1):27–43CrossRefGoogle Scholar
  39. Sinha P, Mohanty UC, Kar SC, Dash SK, Kumari S (2013) Sensitivity of the GCM driven summer monsoon simulations to cumulus parameterization schemes in nested RegCM3. Theor Appl Climatol 112(1–2):285–306CrossRefGoogle Scholar
  40. Spinoni J, Szalai S, Szentimrey T, Lakatos M, Bihari Z, Nagy A, Németh Á, Kovács T, Mihic D, Dacic M, Petrovic P (2015) Climate of the Carpathian region in the period 1961–2010: climatologies and trends of 10 variables. Int J Climatol 35:1322–1341CrossRefGoogle Scholar
  41. Sundqvist H, Berge E, Kristjansson JE (1989) The effects of domain choice on summer precipitation simulation and sensitivity in a regional climate model. J Clim 11:2698–2712Google Scholar
  42. Szalai S, Auer I, Hiebl J, Milkovich J, Radim T, Stepanek P, Zahradnicek P, Bihari Z, Lakatos M, Szentimrey T, Limanowka D, Kilar P, Cheval S, Deak, Gy, Mihic D, Antolovic I, Mihajlovic V, Nejedlik P, Stastny P, Mikulova K, Nabyvanets I, Skyryk O, Krakovskaya S, Vogt J, Antofie T, Spinoni J (2013) Climate of the Greater Carpathian Region. Final Technical Report. www.carpatclim-eu.org
  43. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res-Atmos 106(D7):7183–7192CrossRefGoogle Scholar
  44. Torma C, Giorgi F (2014) Assessing the contribution of different factors in regional climate model projections using the factor separation method. Atmos Sci Lett 15:239–244Google Scholar
  45. Torma C, Bartholy J, Pongrácz R, Barcza Z, Coppola E, Giorgi F (2008) Adaptation and validation of the RegCM3 climate model for the Carpathian Basin. Időjárás 112(3–4):233–247Google Scholar
  46. Torma C, Coppola E, Giorgi F, Bartoly J, Pongracz R (2011) Validation of a high resolution version of the regional climate model RegCM3 over the Carpathian basin. J Hydrometeorol 12:84–100CrossRefGoogle Scholar
  47. Wagner W, Dorigo W, de Jeu R, Fernandez D, Benveniste J, Haas E, Ertl M (2012) Fusion of active and passive microwave observations to create an essential climate variable data record on soil moisture, ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (ISPRS annals), volume I-7. XXII ISPRS Congress, Melbourne, pp. 315–321Google Scholar
  48. Zanis P, Douvis C, Kapsomenakis I, Kioutsioukis I, Melas D, Pal JS (2009) A sensitivity study of the regional climate model (RegCM3) to the convective scheme with emphasis in central eastern and southeastern Europe. Theor Appl Climatol 97(3–4):327–337CrossRefGoogle Scholar
  49. Zhao M, Held IM, Lin SJ, Vecchi GA (2009) Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM. J Clim 22(24):6653–6678CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • Ildikó Pieczka
    • 1
  • Rita Pongrácz
    • 1
  • Karolina Szabóné André
    • 1
  • Fanni Dóra Kelemen
    • 1
    • 2
  • Judit Bartholy
    • 1
  1. 1.Department of MeteorologyEötvös Loránd UniversityBudapestHungary
  2. 2.Institute for Geophysics and MeteorologyUniversity of CologneCologneGermany

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