Perturbation of Parametrized Tendencies and Surface Parameters in the Lokal-Modell Susanne Theis...
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Transcript of Perturbation of Parametrized Tendencies and Surface Parameters in the Lokal-Modell Susanne Theis...
Perturbation of Perturbation of Parametrized TendenciesParametrized Tendenciesand Surface Parametersand Surface Parameters
in the Lokal-Modellin the Lokal-Modell
Susanne Theis
Andreas Hense
Ulrich Damrath
Volker Renner
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
The LAM “Lokal-Modell“The LAM “Lokal-Modell“
• operational high-resolution model of the DWD
• nested within the GME
• horizontal gridsize: 7 km
• lead time: 48 hours
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Why are we looking into EPS?Why are we looking into EPS?
DMO of a
single simulation
noise-reduced forecast
and
probabilistic forecast
Development of a Postprocessing Method:
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Why are we looking into EPS?Why are we looking into EPS?
DMO of a
single simulation
noise-reduced forecast
and
probabilistic forecast
Development of a Postprocessing Method:
calibrationby an experimental ensemble
uncertainty inlateral boundary
conditions
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Aims of a LAM EPSAims of a LAM EPS
modeluncertainty uncertainty in
surface parameters
uncertainty inLAM output
?
uncertainty ininitial conditions
uncertainty inlateral boundary
conditions
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Selecting Certain Aspects Selecting Certain Aspects
modeluncertainty uncertainty in
surface parameters
uncertainty inLAM output
?
uncertainty ininitial conditions
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Perturbation of Roughness LengthPerturbation of Roughness Length
original perturbation
jhh
mm
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Perturbation of Roughness LengthPerturbation of Roughness Length
jj hhh
where jh = 0
STDV jh 0.05 h
E
and
Set-up of the ensemble (6 members):
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Case Study (July 4th, 1994)Case Study (July 4th, 1994)
mm/h
Ensemble Mean Standard Deviation
perturbation of roughness length (only)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
„„Stochastic Physics“: MethodStochastic Physics“: Method
Perturbation of parametrized tendencies:
dttetedtt
ete
t
t
t
t
00
;;)( )P() A(
Unperturbed simulation:
dttxtetetet
t
jjjj )(r)P( A(
0
;;);)(
Ensemble member:
(Buizza et al, 1999)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
„„Stochastic Physics“: NumericsStochastic Physics“: Numerics
Caveat: Stochastic differential equations need a different numerical scheme(Kloeden and Platen, 1999) -- we are still using the traditional scheme!
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Consistency with Surface RadiationConsistency with Surface Radiation
Perturbation of the temperature tendency should be consistent with the solar radiation flux at the surface:
z
Q
t
T
RAD
z
Q
z
Q
perturbationof tendency
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
„„Stochastic Physics“: Set-up No.1Stochastic Physics“: Set-up No.1
1.25 , 0.75 )(r; tx j
D = 5T = 4
x t
„low ampl.“
Set-up of the ensemble (10 members):
consistent perturbation of the solar radiation at the surface
+
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Roughness LengthRoughness Length
where jh = 0
STDV jh 0.05 h
E
and
jj hhh
Additionally, we keep the perturbation of the roughness length:
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Roughness Length: The BugRoughness Length: The Bug
where jh = 0
STDV jh 0.05 h
E
and
jj hhh
roughness length is too low (by a factor of 6)SORRY
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Case Study (July 10th, 2002)Case Study (July 10th, 2002)
mm/h
Ensemble Mean Standard Deviation
stochastic physics (low-amplitude)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Verification of Ensemble MeanVerification of Ensemble Mean
ENSMEANORIGINAL
stochastic physics (low-amplitude)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
„„Stochastic Physics“: Set-up No.2Stochastic Physics“: Set-up No.2
2.0 , 0.0 )(r; tx jD = 10T = 16
x t
„highamplitude“
Set-up of the ensemble (10 members):
consistent perturbation of the solar radiation at the surface
+
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Case Study (July 10th, 2002)Case Study (July 10th, 2002)
mm/h
Ensemble Mean Standard Deviation
stochastic physics (high-amplitude)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Verification of Ensemble MeanVerification of Ensemble Mean
ENSMEANORIGINAL
stochastic physics (high-amplitude)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Perturbation of Initial ConditionsPerturbation of Initial Conditions
Start of the LM-Simulations: 00 UTC
Initialize LM-simulation with the „wrong“ time of the nudged assimilation run:
Analysisof 01 UTC
Analysisof 00 UTC
Analysisof 23 UTC(prev.day)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Set-up of the EnsembleSet-up of the Ensemble
0.75,1.25 )(r; tx j
D = 5T = 4
x t
„low ampl.“
consistent perturbation of the solar radiation at the surface
+
Additionally, the parametrizedtendencies are perturbed:
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Set-up of the EnsembleSet-up of the Ensemble
Analysisof 01 UTC
Analysisof 00 UTC
Analysisof 23 UTC(prev.day)
3 simulations per analysis+ 1 unperturbed simulation
= 10 ensemble members
3 simulations3 simulations 3 simulations 3 simulations
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Case Study (July 10th, 2002)Case Study (July 10th, 2002)
mm/h
Ensemble Mean Standard Deviation
initial conditions &stochastic physics (low-amplitude)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
Verification of Ensemble MeanVerification of Ensemble Mean
ENSMEANORIGINAL
ínitial conditions & stochastic physics (low-amplitude)
OUTLINE
Introduction
Surface Parameters
Parametrized Tendencies
Initial Conditions
Conclusion
ConclusionConclusion
• the precipitation forecast is sensitive to the perturbation of roughness length, parametrized tendencies and initial conditions
• the sensitivity is largest on the scale of a few gridboxes in size
• the ensemble mean achieves better verification results than the unperturbed forecast (initial cond.!)