added value generated by regional climate models
DESCRIPTION
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. - PowerPoint PPT PresentationTRANSCRIPT
Added Value Generated by Regional Climate Models
H. von Storch, F. FeserInstitute of Coastal Research, Helmholtz Zentrum Geesthacht, Germany
22-26 January 2012 - 26th Conference on Hydrology, AMS 92nd Annual Meeting, New Orleans, USA
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.
standard formulation large-scale nudging
Similarity of zonal wind at 850 hPa between simulations and NCEP re-analyses
large scales
medium scales
Spectral nudging vs. standard formulation
Spectral nudging vs. standard formulation
Bea
te M
ülle
r, p
ers.
com
m.
DWD analysis
))
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 2DWD/2
NCEP and 2DWD/2
RCM
• Determining mean spatial correlation patterns between DWD, NCEP and RCM representations, for different spatial scales.
DWD-analysis/ NCEP reanalysis DWD-analysis / regional simulation
Ratio of standard deviations of 2m temperature
DJF 1992 – 1999, at the regional scale, %Feser, MWR 2006
Positive values show added value provided by the regional model.
95% significant deviations are marked by a *.
PCC
DWD and NCEP
PCC improvement/ deterioration
REMO Nudge
Pattern correlation coefficients
[PCC, %]
PCC improvement/ deterioration
REMO Standard
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
QuikSCAT: Added Value - BSS
Open Ocean: No value addedby dynamical downscaling
Coastal region:Added Valuein complexcoastal areas
Winterfeldt and Weisse, MWR 2009
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 polar 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 polar lows
PLS: Polar Low Season (Jul-Jun) 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
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
Brier Skill Score between JMA best track data and NCEP, CLM 0.5°, and CLM 0.165°
> 0 : CLM closer to best track
0 : CLM and NCEP equally close to best track
< 0 NCEP closer to best track
SLP
10m Wind Speed
Improved representation of forcing fields for impact models
• NCEP-driven multidecadal 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).
Coastdat Application
• Dynamical downscaling to obtain high-resolution (25-50 km grid; 1 hourly) description of weather stream.- use of NCEP re-analysis allows reconstruction of regional weather in past decades (1948-2010)- when global scenarios are used, regional scenarios with better description of space/time detail can be downscaled.
• Meteorological data are fed into dynamical models of weather-sensitive systems, such as ocean waves or long-range pollution. Integration area used in HZG reconstruction and
regional scenarios
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)
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)