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Added Value Generated by Regional Climate Models
H. von Storch, F. FeserInstitute of Coastal Research, Helmholtz Zentrum Geesthacht, Germany
29 May 1 - June 2012 - 46th Congress of the Canadian Meteorological and Oceanographic Society (CMOS), Montreal
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
Climate = statistics of weather
The genesis of climate
Cs = f(Cl, Φs)
with
Cl = larger scale climate
Cs = smaller scale climate
Φs = physiographic detail at smaller scale
von Storch, H., 1999
“downscaling”
Model variance as a function of spatial scales. The rectangles show well and insufficiently resolved spatial scales of the global and regional model.
4
Pattern correlation coefficients for V at 500 hPa between the global reanalyses and the
RCM with standard forcing via the lateral boundaries and the
RCM with spectral nudging
09.-12.03.93
global
regional
Nudging of the large scales
5NCEP - RCM standard NCEP - RCM nudge
March 12, 1993, 0:00
Berliner Wetterkarte
RCM standard NCEP RCM nudge
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)
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 2
DWD/2NCEP and 2
DWD/2RCM
Determining mean spatial correlation patterns between
DWD, NCEP and RCM representations, for different
spatial scales.
9
Ratio of standard deviations of 2m temperature DWD-analysis / NCEP reanalysis [%], JJA 1992 – 1999, at the regional scale.
Added Value
Ratio of standard deviations of 2m temperatureDWD-analysis / regional simulation [%], JJA 1992 – 1999, at the regional scale.
10
Positive values show added value of the regional model.
95% significant deviations are marked by a *.
PCC
DWD and NCEP
PCC improvement/ deterioration
REMO Nudge
PCC improvement/ deterioration
REMO Standard
Pattern correlation coefficients [PCC, %]
Feser, MWR 2006
Improved presentation of effect of physiographic detail
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
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).
Added Value
Open Ocean: No value addedby dynamical downscaling
Coastal region:Added Valuein complexcoastal areas
Wind Speed 1998: Distribution
a) Open Ocean: buoy RARH b) Coast: Light Ship Channel
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
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
Density of North Atlanticpolar low genesis
Genesis in RCM simulation constrained by NCEP reanalsysis
Bracegirdle, T. J. and S. L. Gray, 2008 Zahn, M., and H. von Storch, 2008
Annual frequency of past North Atlantic polar lows
Zahn and von Storch, 2008
Set-up of multi-decadal simulation
NCEP/NCAR reanalysis 1/ CLM 2.4.6
Initialised: 1.1.1948 finishing: 28.2.2006
spectral nudging of scales > 700 km
σ=13
Projected changes in polar low frequency and vertical atmospheric stability
A2
C20
A1BB1
Zahn and von Storch, 2010
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)
North Pacific Polar Low on 7 March 1977(Chen et al., 2011)
NOAA-5 infrared satellite image at 09:58UTC 7th March 1977
Cavicchia and von Storch, 2011
Medicane of January 16, 1995
ECMWF analysis
CLM-COSMO, 10 km grid
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
Improved representation of forcing 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).
Red: buoy, yellow: radar, blue: wave model run with REMO winds
wave direction
significant wave height
[days]
[days]
Gerd Gayer, pers. comm., 2001
Annual mean winter high waters Cuxhavenred – reconstruction, black – observations
Interannual variability of mean water levels
(Weisse and Plüß 2006)
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)