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Added Value Generated by Regional Climate Models

Feser, F., B. Rockel , H. von Storch, J. Winterfeldt, and M. Zahn, 2011: Regional climate models add value. Bull. Amer. Meteor. Soc. 92: 1181–1192. Added Value Generated by Regional Climate Models. H. von Storch, F. Feser Institute of Coastal Research, Helmholtz Zentrum Geesthacht , Germany.

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Added Value Generated by Regional Climate Models

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  1. Feser, F., B. Rockel, H. von Storch, J. Winterfeldt, and M. Zahn, 2011: Regional climate models add value. Bull. Amer. Meteor. Soc.92: 1181–1192 Added Value Generated by Regional Climate Models H. von Storch, F. Feser Institute of Coastal Research, Helmholtz ZentrumGeesthacht, Germany 29 May 1 - June 2012 - 46th Congress of the Canadian Meteorological and Oceanographic Society (CMOS), Montreal

  2. Climate = statisticsofweather The genesisofclimate Cs = f(Cl, Φs) with Cl = largerscaleclimate Cs = smallerscaleclimate Φs = physiographicdetailatsmallerscale  “downscaling” von Storch, H., 1999

  3. Model variance as a function of spatial scales. The rectangles show well and insufficiently resolved spatial scales of the global and regional model.

  4. 09.-12.03.93 Nudging of the large scales global Pattern correlation coefficients for V at 500 hPa between the global reanalyses and the RCM withstandard forcing via the lateral boundaries and the RCM with spectral nudging regional

  5. March 12, 1993, 0:00 RCM standard NCEP RCM nudge NCEP - RCM nudge Berliner Wetterkarte NCEP - RCM standard

  6. ) DWD analysis ) Beate Müller, pers. comm.

  7. Added value in reconstructions using spectral nudging Improved representation of • variability at medium scales. • effect of physiographic detail (coasts) • of sub-synoptic phenomena (polar lows, medicanes, typhoons) • forcing fields for impact models (ocean waves, storm surges)

  8. Improved presentation of variability at medium scales • NCEP-driven multidecadal simulation with RCM REMO • Employing spectral nudging (wind above 850 hPa, for scales > 800 km) • Usage of German Weather Service (DWD) regional analysis for a few years as reference to determine skill • Considering ratios 2DWD/2NCEP and 2DWD/2RCM • Determining mean spatial correlation patterns between DWD, NCEP and RCM representations, for different spatial scales.

  9. Added Value Ratio of standard deviations of 2m temperature DWD-analysis / NCEP reanalysis [%], JJA 1992 – 1999, at the regional scale. Ratio of standard deviations of 2m temperature DWD-analysis / regional simulation [%], JJA 1992 – 1999, at the regional scale.

  10. PCC improvement/ deterioration REMO Nudge PCC DWD and NCEP PCC improvement/ deterioration REMO Standard Pattern correlation coefficients [PCC, %] Positive values show added value of the regional model. 95% significant deviations are marked by a *. Feser, MWR 2006

  11. Improvedpresentationofeffectofphysiographicdetail • NCEP-driven multidecadal simulation with RCM REMO • Employing spectral nudging (wind above 850 hPa, for scales > 800 km) • Usage of Quikscat-windfields (Q) over sea. • Determining Brier Skill score B = 1 – (RCM-Q)2 / (NCEP-Q)2 for all marine grid boxes

  12. Added Value Open Ocean: No value added by dynamical downscaling Coastal region: Added Value in complex coastal areas Brier skill score using QuikSCAT level 2B12 as the “truth”, global reanalysis (NCEP reanalysis) as the reference forecast, and a regional model (SN-REMO) as forecast, Winterfeldt et al. (2010).

  13. Wind Speed 1998: Distribution b) Coast: Light Ship Channel a) Open Ocean: buoy RARH Percentile-percentile plots (qq-plots) of wind speed: The 99 dots represent the wind speed percentiles in steps of 1 percent. Winterfeldt and Weisse, MWR 2009

  14. Improved representation of sub-synoptic phenomena • NCEP-driven multidecadal simulation with RCM CLM • Employing spectral nudging (wind above 850 hPa, for scales > 800 km) • Simulation of sub-synoptic phenomena • Polar lows in the Northern North Atlantic • Polar lows in the North Pacific • Medicanes in the Mediterranean Sea • Typhoons in the West Pacific

  15. Densityof North Atlanticpolar lowgenesis Genesis in RCM simulationconstrainedby NCEP reanalsysis Bracegirdle, T. J. and S. L. Gray, 2008 Zahn, M., and H. von Storch, 2008

  16. Annual frequencyofpastNorth Atlantic polar lows Set-upof multi-decadalsimulation σ=13 NCEP/NCAR reanalysis 1/ CLM 2.4.6 Initialised: 1.1.1948 finishing: 28.2.2006 spectralnudgingofscales> 700 km Zahn and von Storch, 2008

  17. Projected changes in polar low frequency and vertical atmospheric stability Differences of the area and time-averaged ice-free SST and T500-hPa over the maritime northern North Atlantic as proxy for frequency of favorable polar low conditions (CMIP3/IPCC AR4) C20 B1 A1B A2 Zahn and von Storch, 2010

  18. MedicaneofJanuary 16, 1995 North Pacific Polar Low on 7 March 1977 (Chen et al., 2011) ECMWF analysis CLM-COSMO, 10 km grid NOAA-5 infrared satellite image at 09:58UTC 7th March 1977 Cavicchia and von Storch, 2011

  19. Brier Skill Score between JMA best track data and NCEP or CCLM Sea Level Pressure 10m Wind Speed > 0 : CLM closer to best track 0 : CLM and NCEP equally close to best track < 0 NCEP closer to best track Feser and von Storch, MWR 2008 b

  20. Improvedrepresentationofforcing fields for impact models • NCEP-driven multi-decadal simulation with RCM REMO • Employing spectral nudging (wind above 850 hPa, for scales > 800 km) • 1948-2010 simulation • Wind and air pressure used to drive models of sea level and circulation of marginal seas (not shown) for describing currents and sea level (North Sea “CoastDat”; not shown) • Wind used to drive models of the statistics of surface waves (ocean waves) in coastal seas (North Sea).

  21. Gerd Gayer, pers. comm., 2001 significant wave height [days] wave direction [days] Red: buoy,yellow: radar, blue: wave model run with REMO winds

  22. Interannual variability of mean water levels (Weisse and Plüß 2006) Annual mean winter high waters Cuxhavenred – reconstruction, black – observations

  23. Summary: Added value … • … in medium scales. Medium scales are determined by both the large scale dynamics and the regional physiographic details (Cs = f(Cl,Φs)) • More added value with large-scale constraint (spectral nudging) • Little improvement over driving large-scale fields for SLP, which is a large-scale variable, but significant improvement for structured fields like 2 m temp or coastal wind. • Dynamical downscaling works … - Large scales are hardly affected but smaller scales respond to regional physiographic detail. • Present analysis refers to reconstructions, where we can compare the results with a “truth”. For scenario simulations other approaches are needed (e.g., big brother-type)

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