Atmospheric Chemistry and Physics www.atmos-chem-phys.net 1680-7316 1680-7324 7 21 2007 10.5194/acp-7-5659-2007 http://www.atmos-chem-phys.net/7/5659/2007/ http://www.atmos-chem-phys.net/7/5659/2007/acp-7-5659-2007.html http://www.atmos-chem-phys.net/7/5659/2007/acp-7-5659-2007.pdf 5659 5674 2007-11-15 Two adaptive radiative transfer schemes for numerical weather prediction models V. Venema victor.venema@uni-bonn.de A. Schomburg F. Ament C. Simmer Meteorologisches Institut, Universität Bonn, Auf dem Hügel 20, 53121 Bonn, Germany Meteo Schweiz, Numerical Models, Kraehbuehlstrasse 58, 8044 Zurich, Switzerland Radiative transfer calculations in atmospheric models are computationally expensive, even if based on simplifications such as the δ-two-stream approximation. In most weather prediction models these parameterisation schemes are therefore called infrequently, accepting additional model error due to the persistence assumption between calls. This paper presents two so-called adaptive parameterisation schemes for radiative transfer in a limited area model: A perturbation scheme that exploits temporal correlations and a local-search scheme that mainly takes advantage of spatial correlations. Utilising these correlations and with similar computational resources, the schemes are able to predict the surface net radiative fluxes more accurately than a scheme based on the persistence assumption. An important property of these adaptive schemes is that their accuracy does not decrease much in case of strong reductions in the number of calls to the δ-two-stream scheme. It is hypothesised that the core idea can also be employed in parameterisation schemes for other processes and in other dynamical models. Baldauf, M., Förstner, J., Klink, S., Reinhardt, T., Schraff, C., Seifert, A., and Stephan, K.: Kurze Beschreibung des Lokal-Modells Kürzestfrist LMK und seiner Datenbanken auf dem Datenserver des DWD, Stand 27.10.2006, DWD, Offenbach, Germany, 2006. Barker, H. W., Pincus, R., and Morcrette, J.-J.: The Monte Carlo independent column approximation: application within large-scale models, Proc. GCSS-ARM Workshop on the Representation of Cloud Systems in Large-Scale Models, Kananaskis, Alberta, Canada, 20–24 May, 2002. Buizza, R., Miller, M., and Palmer, T. N.: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system, Q. J. Roy. Meteor. Soc., 125, 2887–2908, 1999. Chevallier, F., Chéruy, F., Scott, N. A., and Chédin, A.: A neural network approach for a fast and accurate computation of a longwave radiative budget, J. Appl. Meteorol., 37, 1385–1397, 1998. Chevallier, F., Morcrette, J.-J., Chéruy, F., and Scott, N. A.: Use of a neural-networkbased long-wave radiative-transfer scheme in the ECMWF atmospheric model, Q. J. Roy. Meteor. Soc., 126, 761–776, 2000. Collins, W. D., Rasch, P. J., Boville, B. A., et al.: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Technical note, National Center for Atmospheric Research, Boulder, Colorado, http://www.ccsm.ucar.edu/models/atm-cam/, 2004. Davis, A. B., Marshak, A., Gerber, H., and Wiscombe, W. J.: Horizontal structure of marine boundary-layer clouds from cm- to km-scales, J. Geophys. Res., D104, 6123–6144, 1999. Gagnon, J. S., Lovejoy, S., and Schertzer, D.: Multifractal earth topography, Nonlin. Processes Geophys., 13, 541–570, 2006. Grabowski, W. W.: Coupling cloud processes with the large-scale dynamics using the Cloud-Resolving Convection Parameterization (CRCP), J. Atmos. Sci., 59, 978–997, 2001. Geleyn, J.-F., Fournier, R., Hello, G., and Pristov, N.: A new "bracketing" technique for a flexible and economical computation of thermal radiative fluxes, on the basis of the Net Exchange Rate (NER) formalism, WGNE Blue Book, 4-07, 2005. Green, J. S. A.: Division of radiative streams into internal transfer and cooling to space, Q. J. Roy. Meteor. Soc., 93, 371–372, 1967. Hofstadter, D. R.: Fluid concepts and creative analogies, Basic books, New York, 1995. Kessler, E.: On the distribution and continuity of water substance in atmospheric circulations, Meteorological Monographs, 10(32), p 84, 1969. King, M. D., Tsay, S. C., Platnick, S. E., Wang, M., Liou, K.-N.: Cloud retrieval algorithms for MODIS: Optical thickness, effective particle radius, and thermodynamic phase. Algorithm Theoretical Basis Document ATBD-MOD-05, NASA, Goddard Space Flight Center, Greenbelt, Maryland, 1997. Krasnopolski, V. M., Fox-Rabinovitz, M. S., and Chalikov, D. V.: New approach to calculation of atmospheric model physics: Accurate and fast neural network emulation of longwave radiation in a climate model, Mon. Weather Rev., 133, 1370–1383, 2005. Matsui, T., Leoncini, G., Pielke Sr., R. A., and Nair, U. S.: A new paradigm for parameterization in atmospheric models: application to the new Fu-Liou radiation code, Colorado State University, Dept. of Atmospheric Sci., paper no 747, 2004. Majewski, D., Lierman, D., Prohl, P., Ritter, B., Buchhold, M., Hanisch, T., Paul, G., Wergen, W., and Baumgardner, J.: The operational global icosahedral-hexagonal gridpoint model GME: Description and high-resolution tests, Mon. Weather Rev., 130, 319–338, 2002. Meteo France: Book 1, Chapter 21: The radiation parameterization, In The Meso-NH scientific documentation, http://mesonh.aero.obs-mip.fr/mesonh, 2002. Morcrette, J.-J.: On the effects of the temporal and spatial sampling of radiation fields on the ECMWF forecasts and analyses, Mon. Weather Rev., 128, 876–887, 2000. Nelder, J. A. and Mead, R.: A simplex method for function minimization, Comput. J., 7, 308–313, 1965. Niemela, S., Raisanen, P., and Savijarvi, H.: Comparison of surface radiative flux parameterizations – Part I: Longwave radiation, Atmos. Res., 58(1), 1–18, 2001a. Niemela, S., Raisanen, P., and Savijarvi, H.: Comparison of surface radiative flux parameterizations – Part II, Shortwave radiation, Atmos. Res., 58(2), 141–154, 2001b. Pincus, R., Barker, H. W., and Morcrette, J.-J.: A fast flexible approximate technique of computing radiative transfer for inhomogeneous clouds, J. Geophys. Res., 108(D13), 4376, doi:10.1209/2002JD003322, 2003. Pielke Sr., R. A., Matsui, T., Leoncini, G., Nobis, T., Nair, U. S., Lu, E., and Walko, R. L.: A new paradigm for parameterizations in numerical weather prediction and other atmospheric models, National Wea. Digest, 30, 93–99, 2005. Randall, D., Khairoutdinov, A. M., Arakawa, A., and Grabowski, W. W.: Breaking the cloud parameterization deadlock, Bull. Am. Meteorol. Soc., 84, 1547–1564, 2003a. Randall, D., Krueger, St., Bretherton, Ch., Curry, J., Duynkerke, P., Moncrieff, M., Ryan, B., Starr, D., Miller, M., Rossow, W., Tselioudis, G., and Wielicki B.: Confronting models with data: the GEWEX Cloud Systems Study, Bull. Am. Meteorol. Soc., 84(4), 455–469, 2003b. Reinhardt, T. and Seifert, A.: A three-category ice scheme for LMK, COSMO Newsletter, no. 6, July, 115–120, 2006. Ritter, B. and Geleyn, J.-F.: A Comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations, Mon. Weather Rev., 120, 303–325, 1992. Sass, B. H., Rontu, L., and Räisänen, P.: HIRLAM-2 radiation scheme: Documentation and tests, Rep. no. 16, SMHI, Norrköping, Sweden, 1994. Schättler, U., Doms, G., and Schraff, C.: Description of the nonhydrostatic regional model (LM). Part VII: user's guide, COSMO-Consortium for Small Scale Modelling, http://www.cosmo-model.org, 2005. Steppler, J., Doms, G., Schättler, U., Bitzer, H. W., Gassmann, A., Damrath, U., and Gregoric, G.: Meso-gamma scale forecasts using the nonhydrostatic model LM, Meteorol. Atmos. Phys., 82, 75–96, 2003. Theis, S.: Deriving probabilistic short-range forecasts from a deterministic high-resolution model, PhD thesis, University of Bonn, 2005. Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterisation in large-scale models, Mon. Weather Rev., 117, 1779–1799, 1989. Undén, P., Rontu, L., Järvinen, H., et al.: HIRLAM-5 scientific documentation, SMHI, Norrköping, Sweden, 2002. WCRP: Annual review of the World Climate Research Programme and report of the twenty-fifth session of the Joint Scientific Committee, http://www.wmo.ch/pages/prog/wcrp/pdf/jsc25report.pdf, Moscow, Russian Federation, 1–6 March, 2004.