The Rossby Centre Regional Climate model RCA3: model description and performance

References

• Albrecht, B. A. 1981. Parameterization of trade-cumulus cloud amounts. J. Atmos. Sci. 38, 97–105.
   Web of Science ®Google Scholar
• Barker, H. W. 1996. A parameterization for computing grid-averaged solar fluxes for inhomogeneous marine boundary layer clouds. Part I: Methodology and Homogeneous Biases. J. Atmos. Sci. 53, 2289–2303.
   Web of Science ®Google Scholar
• Barker, H. W., Wielicici, B. A. and Parker, L. 1996. A parameterization for computing grid-averaged solar fluxes for inhomogeneous marine boundary layer clouds. Part H: Validation using satellite data. J. Atmos. Sci. 53, 2304–23216.
   Web of Science ®Google Scholar
• Barker, H. W. and Wielicki, B. A. 1997. Parameterizing grid-averaged longwave fluxes for inhomogeneous marine boundary layer clouds. J. Atmos. Sci. 54, 2785–2798.
   Web of Science ®Google Scholar
• Barrett, A. I., Hogan, R. J. and O’Connor, E. J. 2009. Evaluating fore-casts of the evolution of the cloudy boundary layer using diurnal composites of radar and lidar observations. Geophys. Res. Lett. 36, L17811, 10.1029/2009GL038919.
   Google Scholar
• Betts, A. K., Ball, J. H., Barr, A. G., Black, T. A., McCaughey, J. H. and co-authors 2006. Assessing land-surface-atmosphere coupling in the ERA-40 reanalysis with boreal forest data. Agric. Forest MeteoroL140, 365-382.
   Google Scholar
• Brasseur, O. 2001. Development and application of a physical approach to estimating wind gusts, Monthly Weather Rev. 129, 5–25.
   Web of Science ®Google Scholar
• Bringfelt, B., Räisänen, J., Gollvilc, S., Lindstriim, G., Graham, L. P. and co-authors. 2001. The land surface treatment for the Rossby Centre re-gional atmosphere climate model — version 2, Reports of Meteorology and Climatology 98, SMHI, SE-601 76 Norrkoping, Sweden.
   Google Scholar
• Brinkop, S. and Roecicner, E. 1995. Sensitivity of a general circulation model to parameterizations of cloud-turbulence interactions in the atmospheric boundary layer. Tellus 47A, 197–220.
   Google Scholar
• Brunetti, M., Buffoni, L., Mangianti, F., Maugeri, M. and Nanni, T. 2004. Temperature, precipitation and extreme events during the last century in Italy. Global Planet. Change 40, 141–149.
   Web of Science ®Google Scholar
• Cahalan, R. F., Ridgeway, W., Wiscombe, W. J., Bell, T. L. and Snider, J. B. 1994. The albedo of fractal clouds. J. Atmos. Sci.51, 2434-2455.
   Google Scholar
• Choudhury, B. J. and Monteith, J. L. 1988. A four-layer model for the heat budget of homogeneous land surfaces. Q. J. R. MeteoroL Soc. 114, 373-398.
   Google Scholar
• Clapp, R. B. and Hornberger, G. M. 1978. Empirical equations for some soil hydraulic properties. Water Resources Res. 14, 601–604.
   Web of Science ®Google Scholar
• Cuijpers, J. W. M. and Duynkerke, P. G. 1993. Large eddy simulations of trade wind with cumulus clouds. J. Atmos. Sci. 50, 3894-3908.
   Google Scholar
• Cuxart, J., Bougeault, P. and Redelsperger, J.-L. 2000. A turbulence scheme allowing for mesoscale and large-eddy simulations. Q. J. R. MeteoroL Soc. 126, 1–30.
   Web of Science ®Google Scholar
• Davies, H. C. 1976. A lateral boundary formulation for multi-level pre-diction models. Q. J. R. MeteoroL Soc. 102, 405–418.
   Web of Science ®Google Scholar
• Deardorff, J. W. 1978. Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. J. Geophys. Res. 83, 1889–1903.
   Web of Science ®Google Scholar
• Douville, H., Royer, J.-F. and Mahfouf, J.-F. 1995. A new snow param-eterization for the Meteo-France climate model. Part I: Validation in stand-alone experiments. Clim. Dyn. 12, 21–35.
   Web of Science ®Google Scholar
• Doscher, R., Wyser, K., Meier, H. E. M., Qian, M. and Redler, R. 2009. Quantifying Arctic contributions to climate predictabil-ity in a regional coupled ocean-ice-atmosphere model. Clim. Dyn. 34, 10.1007/s00382-009-0567-y.
   Google Scholar
• Drusch, M., Vasiljevic, D. and Viterbo, P. 2004. ECMWF’s global snow analysis: assessment and revision based on satellite observations. J. Appl. Meteor 43, 1282–1294.
   Google Scholar
• FAO-UNESCO (ed.), 1981. Soil Map of the World, Volume 5. UNESCO-Paris, Europe.
   Google Scholar
• Frei, C., Christensen, J., Deque, M., Jacob, D. and Vidale, P. 2003. Daily precipitation statistics in regional climate models: evaluation and in-tercomparison for the European Alps. J. Geophys. Res. 108, 4124–4142.
   Web of Science ®Google Scholar
• Gilgen, H. and Ohmura, A. 1999. The Global Energy Balance Archive (GEBA). Bull. Am. MeteoroL Soc. 80, 831–850.
   Web of Science ®Google Scholar
• Graham, L. P. 2002. A simple runoff routing routine for the Rossby Centre Regional Climate Model. In: Proceedings from the)0(II Nordic Hydrological Conference (ed. Killingtveit, A.). Roros, Norway, 4-7 August, 573-580.
   Google Scholar
• Hagemann, S., Botzet, M., Diimenil, L. and Machenhauer, B. 1999. Derivation of global GCM boundary conditions from 1 km land use satellite data. Tech. Rep. 289, Max-Planck-Institute for Meteorology, Hamburg, Germany.
   Google Scholar
• Hagemann S., Machenhauer B., Jones R., Christensen O. B., Deque M. and co-authors. 2004. Evaluation of water and energy budgets in regional climate models applied over Europe. Clim. Dyn. 23. 547-567.
   Google Scholar
• Häggmark, L., Ivarsson, K.-I., Gollvilc, S. and Olofsson, P.-0. 2000. Mesan, an operational mesoscale analysis system. Tellus 52A, 2–20.
   Google Scholar
• Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D. and co-authors. 2008. European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. J. Geophys. Res. 113, D20119, 10.1029/2008JDO10201.
   Google Scholar
• He, Y., Monahan, A. H., Jones, C. G., Dai, A., Biner, S. and co-authors. 2010. Probability distributions of land surface wind speeds over North America, J. Geophys. Res. 115, D04103, 10.1029/2008JDO10708.
   Google Scholar
• Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, New York.
   Google Scholar
• Illingworth, A. J., Hogan, R. J., O’Connor, E. J., Bouniol, D., Brooks, M. E. and co-authors. 2007. Cloudnet — continuous evaluation of cloud profiles in seven operational models using ground-based observations. Bull. Am. MeteoroL Soc. 88, 883-898.
   Google Scholar
• Iwashima, T. and Yamamoto, R. 1993. A statistical analysis of the ex-treme events: long term trend of heavy daily precipitation, J. Meteor Soc. Jpn. 71, 637–640.
   Web of Science ®Google Scholar
• Jaeger, E. B., Stockli, R. and Seneviratne, S. I. 2009. Analysis of planetary boundary layer fluxes and land-atmosphere coupling in the regional climate model CLM. J. Geophys. Res. 114, D17106, 10.1029/2008JD011658.
   Web of Science ®Google Scholar
• Jarvis, P. G. 1976. The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Philos. Trans. R. Soc. Lond. B273, 593–610.
   Web of Science ®Google Scholar
• Jones, C. G. and Sanchez, E. 2002. The representation of shallow cu-mulus convection and associated cloud fields in the Rossby Cen-tre atmospheric model, HIRLAIVI Newsletter 41, SMHI, SE-601 76 Norrkoping, Sweden.
   Google Scholar
• Jones, C. G., Samuelsson, P. and Kjellström, E. 2011. Regional climate modelling at Rossby Centre. Preface to the RCA3 special issue in Tellus63A, 1-3.
   Google Scholar
• Jones, C., Willa, U., Ullerstig, A. and Hansson, U. 2004. The Rossby Centre regional atmospheric climate model part I: model climatology and performance for the present climate over Europe. Ambio 33(4-5), 199–210.
   Web of Science ®Google Scholar
• Kain, J. S. 2004. The Kain—Fritsch convective parameterization: an up-date. J. Appl. Meteorl. 43, 170–181.
   Web of Science ®Google Scholar
• Kain, J. S. and Fritsch, J. M. 1990. A one-dimensional entrain-ing/detraining plume model and its application in convective param-eterization. J. Atmos. Sci. 47, 2784–2802.
   Web of Science ®Google Scholar
• Kain, J. S. and Fritsch, J. M. 1993. Convective parameterizations for mesoscale models: The Kain—Fritsch scheme. In: The Representation of Cumulus Convection in Numerical Models (eds. Emanuel, K. A. and Raymond, D. J.). American Meteorological Society Monograph, Boston, USA, 246 pp.
   Google Scholar
• Källen, E. (ed.). 1996. HIRLAM Documentation Manual. System 2.5. Available on request from SMHI, SE-60176 Norrkoping, Sweden.
   Google Scholar
• Karl, T. R. and Knight, R. W. 1998. Secular trends of precipitation amount, frequency, and intensity in the United States. Bull. Am. Me-teorl. Soc. 79, 231–241.
   Web of Science ®Google Scholar
• Kjellstrom E., Barring L., Gollvilc S., Hansson U., Jones C. and co-authors. 2005. A 140-year simulation of European climate with the new version of the Rossby Centre regional atmospheric climate model (RCA3). Report in Meteorology and Climatology 108, SMHI, SE-60176 Norrkoping, Sweden,54 pp.
   Google Scholar
• Kjellstrom, E., Barring, L., Jacob, D., Jones, R., Lenderink, G. and co-authors. 2007. Variability in daily maximum and minimum tem-peratures: recent and future changes over Europe. Clim. Change 81, 249-265, 10.1007/s10584-006-9220-5.
   Google Scholar
• Koster, R. D. and Suarez, M. J. 1992. A comparative analysis of two land-surface heterogeneity representations. J. Climate 5, 1379–1390.
   Web of Science ®Google Scholar
• Lawrence D. M. and Slater A. G. 2008. Incorporating organic soil into a global climate model. Clim. Dyn. 30, 145–160.
   Web of Science ®Google Scholar
• Lenderinlc, G. and de Rooy, W. 2000. A robust mixing length formulation for a TKE-1 turbulence scheme, HIRLAIVI Newsletter 36, KNMI, The Netherlands, 25-29.
   Google Scholar
• Lenderinlc, G. and Holtslag, A. A. M. 2004. An updated length-scale formulation for turbulent mixing in clear and cloudy boundary layers. Q. J. R. Meteorol. Soc. 130, 3405–3427.
   Web of Science ®Google Scholar
• Lind, P. and Kjellstrom, E. 2009. Water budget in the Baltic Sea drainage basin: evaluation of simulated fluxes in a regional climate model. Boreal Environ. Res. 14, 56–67.
   Web of Science ®Google Scholar
• Lindstrom, G. and Gardelin, M. 1999. A simple snow parameterization scheme intended for the RCA model based on the HBV runoff model. SWECLIM Newsletter 6, SMHI, Sweden,16-20.
   Google Scholar
• Lindstrom, G., Johansson, B., Persson, M., Gardelin, M. and Bergstrom, S. 1997. Development and test of the distributed HBV-96 hydrological model. J. HydroL 201, 272–288.
   Web of Science ®Google Scholar
• Liou, K.-N. 1992. Radiation and Cloud Processes in the Atmosphere: Theory, Observation, and Modeling. Oxford University Press, Oxford, UK.
   Google Scholar
• Ljungemyr, P., Gustafsson, N. and Omstedt, A. 1996. Parameteriza-tion of lake thermodynamics in a high-resolution weather forecasting model. Tellus 48A, 608–621.
   Google Scholar
• Lopez-Moreno, J. I. and Beniston, M. 2009. Daily intensity precip-itation for the 21st century: seasonal changes over an Atlantic-Mediterranean gradient in the Pyrenean mountains. Theor AppL Cli-matol. 95, 375–384.
   Web of Science ®Google Scholar
• Louis, J. F., Tiedtke, M. and Geleyn, J. F. 1982. A short history of the PBL parameterization at ECMWF. In: Workshop on Boundary Layer Parameterization, European Centre for Medium-Range Weather Fore-casts Reading, UK,59-79.
   Google Scholar
• Lucas-Picher, P., Caya, D., de Elia, R. and Laprise, R. 2008. Investigation of regional climate models’ internal variability with a ten-member ensemble of ten-year simulations over a large domain. Clim. Dyn. 31, 927–940. 10.1007/s00382-008-0384-8
   Web of Science ®Google Scholar
• Markovic, M., Jones, C. G., Wingera, K. and Paquinb, D. 2009. The surface radiation budget over North America: gridded data assess-ment and evaluation of regional climate models. Int. J. ClimatoL 29, 2226–2240.
   Web of Science ®Google Scholar
• Masson V., Champeaux J. L., Chauvin F., Meriguet C. and Lacaze R. 2003. A global database of land surface parameters at lkm res-olution for use in meteorological and climate models. J. Climate 16.1261–1282.
   Web of Science ®Google Scholar
• McCumber, M. C. and Pielke, R. A. 1981. Simulation of the effects of surface fluxes of heat and moisture in a mesoscale numerical model 1. Soil layer. J. Geophys. Res. 86, 9929–9938.
   Web of Science ®Google Scholar
• Milton, S. and Wilson, C. 1996. The impact of parameterized subgrid-scale orographic forcing on systematic errors in a global NWP model. Mon. Wea. Rev. 124, 2023–2045.
   Web of Science ®Google Scholar
• Mitchell, T. D. and Jones, P. D. 2005. An improved method of con-structing a database of monthly climate observations and associated high-resolution grids. Int. J. ClimatoL 25, 693–712.
   Web of Science ®Google Scholar
• Nikulin, G., Kjellström, E., Hansson, U., Strandberg, G. and Ullerstig, A. 2011. Evaluation and future projections of temperature, precipitation and wind extremes over europe in an ensemble of regional climate simulations. Tellus 63A, 41–55.
   Google Scholar
• Noilhan, J. and Planton, S. 1989. A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev. 117, 536–549.
   Web of Science ®Google Scholar
• Nordstrom, M. 2005. Estimation of gusty winds in RCA. Master thesis, Department of Earth Sciences, Uppsala University. ISSN 1650-6553 Nr 101.42 pp.
   Google Scholar
• O’Dell, C. W., Wentz, F. J. and Bennartz, R. 2008. Cloud liq-uid water path from satellite-based passive microwave observa-tions: a new climatology over the global oceans. J. Clim. 21, 1721–1739.
   Web of Science ®Google Scholar
• Raab, B. and Vedin, H., Eds., 1995. Climate, Lakes and Rivers. National Atlas of Sweden, Vol. 14. SNA Publishing, Box 45029 SE-10430 Stockholm, Sweden, 176 pp.
   Google Scholar
• Räisdnen, J., Hansson, U., Ullerstig, A., Doscher, R., Graham, L. P. and co-authors. 2003. GCM driven simulations of recent and future climate with the Rossby Centre coupled atmosphere - Baltic Sea regional climate model RCAO, Reports Meteorology and Climatology 101, SMHI, SE-601 76 Norrkoping, Sweden.
   Google Scholar
• Räisdnen, P., Rummukainen, M. and Räisdnen, J. 2000. Modification of the HIRLAM radiation scheme for use in the Rossby Centre regional atmospheric climate model, Reports Meteorology and Climatology 49, Department of Meteorology, University of Helsinki, Finland.
   Google Scholar
• Rasch, P. J. and Kristjánsson, J. E. 1998. A comparison of the CCM3 model climate using diagnosed and predicted condensate parameter-izations. J. Climate 11, 1587–1614.
   Web of Science ®Google Scholar
• Roebeling, R. A. and van Meijgaard, E. 2009. Evaluation of the daylight cycle of model predicted cloud amount and condensed water path over Europe with observations from MSG-SEVIRI. J. Climate 22, 1749–1766. 10.1175/2008JCLI2391.1.
   Web of Science ®Google Scholar
• Rubel, F. and Hantel, M. 2001. BALTEX 1/6-degree daily precipitation climatology. MeteoroL Atmos. Phys. 77. 155–166.
   Web of Science ®Google Scholar
• Rummukainen, M. 2010. State-of-the-art with regional climate models. WIREs Climate Change 1, 82–96, 10.1002/wcc.008.
   Web of Science ®Google Scholar
• Samuelsson R, Gollvik S. and Ullerstig A. 2006. The land-surface scheme of the Rossby Centre regional atmospheric climate model (RCA3). Report in Meteorology 122. SMHI, SE-60176 Norrkoping, Sweden,25 pp.
   Google Scholar
• Sass B. H., Rontu L., Savijärvi H. and Räisdnen P. 1994. HIRLAM-2 Radiation scheme: documentation and tests. Hirlam Technical Report No. 16, SMHI, SE-60176 Norrkiiping, Sweden,43 pp.
   Google Scholar
• Savijärvi H. 1990. A fast radiation scheme for mesoscale model and short-range forecast models. J. AppL Met. 29. 437–447.
   Google Scholar
• Schwarb, M., Daly, C., Frei, C. and Schär, C. 2001. Mean seasonal precipitation throughout the European Alps, 1971-1990. Hydrologic Atlas of Switzerland, National Hydrologic Service, Bern.
   Google Scholar
• Sellers, P. J., Dickinson, R. E., Randall, D. A., Betts, A. K., Hall, F. G. and co-authors. 1997. Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science 275, 502-509, 10.1126/science.275.5299.502.
   Google Scholar
• Shuttleworth, W. J. and Wallace, J. S. 1985. Evaporation from sparse crops-an energy combination theory. Q. J. R. MeteoroL Soc. 111, 839–855.
   Web of Science ®Google Scholar
• Simmons, A. J. and Burridge, D. M. 1981. An energy and angular-momentum conserving finite-difference scheme and hybrid vertical coordinates. Mon. Wea. Rev. 109, 758–766.
   Web of Science ®Google Scholar
• Slingo, A. and Schrecker, H. M. 1982. On the shortwave radiative properties of stratiform water clouds. Q. J. R. MeteoroL Soc. 108, 407–426.
   Web of Science ®Google Scholar
• Smith S. A., Doyle, J. D., Brown, A. R., Webster, S. 2006. Sensitivity of resolved mountain drag to model resolution for MAP case-studies. Q. J. R. Meteorol. Soc. 132, 1467–1487.
   Web of Science ®Google Scholar
• Stephens, G. L. and Webster, P. J. 1979. Sensitivity of radiative forcing to variable cloud and moisture. J. Atmos. Sci. 36, 1542–1556.
   Web of Science ®Google Scholar
• Tiedtke, M. 1996. An extension of cloud-radiation parameterization in the ECMWF model: the representation of subgrid-scale variations of optical depth. Mon. Wea. Rev. 124, 745–750.
   Web of Science ®Google Scholar
• Unden, R, Rontu, L., Järvinen, H., Lynch, P., Calvo, J. and co-authors. 2002. HIRLAM-5 scientific documentation. HIRLAM Report, SMHI, SE-601 76 Norrkiiping, Sweden, 144 p.
   Google Scholar
• Ungersböck, M., Rubel, E, Fuchs, T. and Rudolf, B. 2001. Bias correc-tion of global daily rain gauge measurements. Phys. Chem. Earth (B) 26,411–414.
   Web of Science ®Google Scholar
• Uppala, S. M., Milberg, P. W., Simmons, A. J., Andrae, U., da Costa Bechtold, V. and co-authors. 2005. The ERA-40 Re-analysis. Q. J. R. MeteoroL Soc. 131, 2961-3012.
   Google Scholar
• Van Den Hurk, B. J. J. M., Viterbo, P., Beljaars, A. C. M. and Betts, A. K. 2000. Offline validation of the ERA40 surface scheme. Technical Memorandum 295, ECMWF, 42 pp.
   Google Scholar
• Van Der Linden, P. and Mitchell, J. F. B. (eds) 2009. ENSEMBLES: Climate Change and its Impacts: Summary of Research and Results from the ENSEMBLES Project. Met Office Hadley Centre, Fitzroy Road, Exeter EX1 3PB, UK,160 pp.
   Google Scholar
• Viterbo, P., Beljaars, A. and Teixeira, J. 1999. The representation of soil moisture freezing and its impact on the stable boundary layer. Q. J. R. MeteoroL Soc. 125, 2401–2426.
   Web of Science ®Google Scholar
• Wallace, J. S., Roberts, J. M. and Sivakumar, M. V. K. 1990. The estimation of transpiration from sparse dryland millet using stom-atal conductance and vegetation area indices. Agric. For. Met. 51, 35–49.
   Web of Science ®Google Scholar
• Willen, U. 2008. Preliminary use of CM-SAF cloud and radiation products for evaluation of regional climate simulations. Reports Meteorology and Climatology 131, SMHI, SE-601 76 Norrkoping, Sweden.
   Google Scholar
• Willmott, C. J. and Matsuura, K. 1995. Smart interpolation of annu-ally averaged air temperature in the United States. J. AppL Met. 34, 2577–2586.
   Google Scholar
• Wyser, K., Rontu, L. and Savijärvi, H. 1999. Introducing the effective radius into a fast radiation scheme of a mesoscale model. Contr. Atmos. Phys. 72, 205–218.
   Google Scholar