Response in extremes of daily precipitation and wind from a downscaled multi-model ensemble of anthropogenic global climate change scenarios

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Haugen, Jan Erik ; Iversen, Trond (2008)

Time-slices of eight global climate model (GCM) response simulations of the IPCC IS92a, CMIP2, SRES A2, B2 and A1B greenhouse gas scenarios have been downscaled using the HIRHAM atmospheric regional climate model (RCM). The area covers Central and Northern Europe, adjacent sea-areas and Greenland. The GCM data were provided from the Max Planck Institute, Germany (MPI), the Hadley Centre, U.K. (HC), the Bjerknes Centre, Norway (BCCR) and University of Oslo, Norway (UiO). The resulting ensemble covers a range of future climate realizations from different global models, different greenhouse gas scenarios and natural climate variability. In order to present trends in statistical parameters including extreme events and their return periods, the downscaled response data are combined as an ensemble of equally valid possible realizations. The combined statistics is obtained after adjustments accounting for (i) different set-ups of the respective GCMs in producing the control climate and (ii) the variable range of time between the control and scenario periods. We find that annual extreme events of daily precipitation and wind speed in the control climate become more frequent in the scenario period over large areas in Northern Europe. The variability in the regional result appears sensitive to the phase of the Scandinavian pattern.
  • References (42)
    42 references, page 1 of 5

    Ådlandsvik, B. 2008. Marine downscaling of a future climate scenario for the North Sea. Tellus 60A, doi:10.1111/j.1600-0870.2008.00311.x.

    Allen, M. R., Stott, P. A., Mitchell, J. F. B., Schnur, R. and Delworth, T. L. 2000. Quantifying the uncertainty in forecasts of anthropogenic climate change. Nature 407(Oct. 5), 617-620.

    Benestad, R. E. 2005. Climate change scenarios for Northern Europe from multi-model IPCC AR4 climate simulations. Geophys. Res. Lett. 32, L17704, doi:10.1029/2005GL023401.

    Bjørge, D., Haugen, J. E. and Nordeng, T. E. 2000. Future climate in Norway. DNMI Research Rep. 103, 41 pp. Norwegian Meteorological Institute, P. O. Box 43 Blindern, N-0313 Oslo, Norway, ISSN 0332- 9879.

    Boer, G. J. 1994. Predictability regimes in atmospheric flow. Mon. Wea. Rev. 122, 2285-2295.

    Barnston, A. G. and Livezey, B. E. 1987. Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon. Wea. Rev 115, 1083-1126.

    Castro, C. L., Pielke, Sr., R. A. and Leoncini, G. 2005. Dynamical downscaling: Assessment of value retained and added using the Regional Atmospheric Modeling System (RAMS). J. Geophys. Res. 110, D05108, doi:10.1029/2004JD004721.

    Christensen, J. H., Machenhauer, B., Jones, R. G., Scha¨r, C., Ruti, P. M. and co-authors. 1997. Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions. Clim. Dyn. 13, 489-506.

    Christensen, O. B. and Christensen, J. H. 1998. Very high-resolution climate simulations over Scandinavia. Present Climate. J. Climate 11(12), 3204-3229.

    Christensen, J. H., Ra¨isa¨nen, J., Iversen, T., Bjørge, D., Christensen, O. B. and co-authors. 2001. A synthesis of regional climate change simulations - A Scandinavian perspective. Geophys. Res. Lett. 28, 1003-1006.

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