Summary
A statistical-dynamical downscaling procedure for global climate simulations is described. The procedure is based on the assumption that any regional climate is associated with a specific frequency distribution of classified large-scale weather situations. The frequency distributions are derived from multi-year episodes of low resolution global climate simulations. Highly resolved regional distributions of wind and temperature are calculated with a regional model for each class of large-scale weather situation. They are statistically evaluated by weighting them with the according climate-specific frequency. The procedure is exemplarily applied to the Alpine region for a global climate simulation of the present January climate.
List of Symbols
Δλ west-east mesh size in geographic coordinates
Δϕ south-north mesh size in geographic coordinates
N number of large-scale weather classes
n number of regional-scale event classes
p pressure
P probability
Ø large-scale event
ϕ regional-scale event
q v specific humidity
θ potential temperature
u west-east wind component
v south-north wind component
Similar content being viewed by others
Abbreviations
- AGL:
-
above ground level
- LT:
-
local time
- UTC:
-
universal time coordinated
References
Boville, B. A., 1991: Sensitivity of simulated climate to model resolution.J. Climate 4, 469–485.
Boyle, J. S., 1993: Sensitivity of dynamical quantities to horizontal resolution for a climate simulation using the ECMWF (Cycle 33) Model.J. Climate 6, 796–815.
Cubasch, U., Hasselmann, K., Höck, H., Maier-Reimer, E., Mikolajewicz, U., Santer, B. D., Sausen, R., 1992: Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model.Climate Dyn.,8, 55–69.
Frey-Buness, A., 1993: Ein statistisch-dynamisches Verfahren zur Regionalisierung globaler Klimasimulationen. DLR-FB 93-47, obtainable from DLR, Zentrale Allgemeine Dienste, Versand, D-51140 Köln, ISSN 0939–2963.
Giorgi, F., Mearns, L. O., 1991: Approaches to the simulation of regional climate change: A review.Rev. of Geophys. 29, 191–216.
Grotch, S. L., MacCracken, M. C., 1991: The use of general circulation models to predict regional climatic change.J. Climate 4, 286–303.
Heimann, D., 1986: Estimation of regional surface-layer wind-field characteristics using a three-layer mesoscale model.Beitr. Phys. Atmosph. 59, 518–537.
Heimann, D., 1990: Three-dimensional modeling of synthetic cold fronts approaching the Alps.Meteorol. Atmos. Phys. 42, 197–219.
Heimann, D., 1992: Three-dimensional modeling of synthetic cold fronts interacting with northern Alpine foehn.Meteorol. Atoms. Phys. 48, 139–163.
Heimann, D., 1993: REWIH3D-1.0 Modell- und Programmbeschreibung. Report Nr. 3 des Instituts für Physik der Atmosphäre der Deutschen Forschungsanstalt für Luft- und Raumfahrt (DLR), ISSN 0943-4771.
Hewitson, B., 1994: Regional climates in the GISS general circulation model: surface air temperature.J. Climate 7, 283–303.
Lilly, D. K., Klemp, J. B., 1979: The effects of the terrain shape on nonlinear hydrostatic mountain waves.J. Fluid. Mech. 95, 241–261.
Manier, G., Dietzer, B., 1979: Untersuchung über den Einfluß der Topographie der Erdoberfläche auf den Zusammenhang zwischen den Häufigkeitsverteilungen von Bodenwind und geostrophischem Wind.Meteorol. Rdsch. 32, 35–44.
Marinucci, M. R., Giorgi, F., 1992: A 2 × CO2 climate change scenario over Europe generated using a limited area model nested in a general circulation model. 1. Present-day seasonal climate simulation.J. Geophys. Res. 97, 9989–10009.
Pielke, R. A., 1984:Mesoscale Meteorological Modeling. New York: Academic Press.
Physick, W. L., 1988: Review: Mesoscale modelling in complex terrain.Earth Science Reviews 12, 199–235.
Roeckner, E., Arpe, K. Bengtsson, L., Brinkop, S., Dümenil, L., Kirk, E., Lunkeit, F., Esch, M., Ponater, M., Rockel, B., Sausen, R., Schlese, U., Schubert, S., Windelband, M., 1992: Simulation of the present-day climate with the ECHAM model: Impact of model physics and resolution. Max-Planck-Institut für Meteorologie, Report No. 93, ISSN 0937–1060.
Schlesinger, M. E., Mitchell, J. F. B., 1987: Climate model simulations of the equilibrium climatic response to increased carbon dioxide.Rev. Geophys. 25, 760–798.
Stouffer, R. J., Manabe, S., Bryan, K., 1989: Interhemispheric asymmetry in climate response to a gradual increase of atmospheric CO2.Nature 342, 660–662.
Storch, H. von, Zorita, E., Cubasch, U., 1993: Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime.J. Climate 6, 1161–1171. ISSN 0937-1060.
Wanner, H., Furger, M., 1990: The Bise — Climatology of a regional wind north of the Alps.Meteorol. Atmos. Phys. 43, 105–115.
Wippermann, F., Groß, G., 1981: On the construction of orographically influenced wind roses for given distributions of the large-scale wind.Beitr. Phys. Atmos. 54, 492–501.
Zorita, E., Hughes, J. P., Lettemaier, D. P., Storch, H. von, 1993: Stochastic characterization of regional circulation pattern for climate model diagnosis and estimation of local precipitation. Max-Planck-Institut für Meteorologie, Report No. 109, ISSN 0937-1060.
Author information
Authors and Affiliations
Additional information
With 13 Figures
Rights and permissions
About this article
Cite this article
Frey-Buness, F., Heimann, D. & Sausen, R. A statistical-dynamical downscaling procedure for global climate simulations. Theor Appl Climatol 50, 117–131 (1995). https://doi.org/10.1007/BF00866111
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF00866111