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EUCLIPSE Toulouse meeting April 2012. Process-level evaluation at selected grid-points: Constraining a system of interacting parameterizations through multiple parameter evaluation at Cabauw. Roel Neggers. Process-level evaluation. - PowerPoint PPT Presentation
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EUCLIPSE Toulouse meeting April 2012
Roel Neggers
Process-level evaluation at selected grid-Process-level evaluation at selected grid-points:points:
Constraining a system of interacting Constraining a system of interacting parameterizations through multiple parameterizations through multiple
parameter evaluation at Cabauwparameter evaluation at Cabauw
Process-level evaluation
We have built good experience at (idealized) single-case level (e.g. We have built good experience at (idealized) single-case level (e.g. GCSS), and can demonstrate successes in model improvement.GCSS), and can demonstrate successes in model improvement.
However, possible shortcomings:However, possible shortcomings:
* Cases might not represent actual climate; parameterizations might * Cases might not represent actual climate; parameterizations might get tuned to rare situationsget tuned to rare situations
* Cases might not represent those situations that are most * Cases might not represent those situations that are most troublesome in GCMs;troublesome in GCMs;
* The use of relevant observational data has been somewhat limited.* The use of relevant observational data has been somewhat limited.
These arguments motivate a move towards more comprehensive, These arguments motivate a move towards more comprehensive, statistically significant approach in model evaluation, in statistically significant approach in model evaluation, in combination with a more efficient use of observational datasets.combination with a more efficient use of observational datasets.
The “testbed” idea
1) SCM and GCM evaluation for long periods of time at permanent 1) SCM and GCM evaluation for long periods of time at permanent meteorological sites (e.g. ARM, CloudNet)meteorological sites (e.g. ARM, CloudNet)
Emphasis: fast physics (boundary-layer, soil)Emphasis: fast physics (boundary-layer, soil)
2) Use a 2) Use a multiple-parameter approachmultiple-parameter approach in the evaluation in the evaluation (“CloudNet+”)(“CloudNet+”)
Constrain the system of interacting parameterizations at multiple Constrain the system of interacting parameterizations at multiple points with key measurementspoints with key measurements
Goals:Goals: * Try and identify compensating errors in interaction between low * Try and identify compensating errors in interaction between low
clouds & radiative transfer (e.g. too bright – too few)clouds & radiative transfer (e.g. too bright – too few)
* Trace their impact through the coupled BL – soil system * Trace their impact through the coupled BL – soil system (heat & moisture budgets)(heat & moisture budgets)
Neggers et al, BAMS, in press, 2012
Short example
The motivation: problems with a new BL scheme in IFSThe motivation: problems with a new BL scheme in IFS
Too little cloud cover at noonToo little cloud cover at noon
Associated 2m T warm bias over landAssociated 2m T warm bias over land
Can long-term SCM evaluation at Cabauw provide some insight?Can long-term SCM evaluation at Cabauw provide some insight?
1. less PBL clouds
2. larger SW down
3. larger H
4. low level warming
SW
Hypothesis
Long-term SCM evaluation at Cabauw (2007-2010)
Obs vs Model scatterplots of monthly meansObs vs Model scatterplots of monthly means RACMO SCMRACMO SCM: : Control (red) and new (blue) schemeControl (red) and new (blue) scheme RACMO 3D in forecast mode (grey)RACMO 3D in forecast mode (grey)
8-point check
Expanding to multiple independently-measured parameters that reflect the Expanding to multiple independently-measured parameters that reflect the impact mechanism as illustrated beforeimpact mechanism as illustrated before
Model performance – Taylor diagram
Reproduction of observed pattern in variation of monthly-meanReproduction of observed pattern in variation of monthly-mean
Correlation between model differences
Tracing impacts
Following degrading correlations in coupled BL – soil systemFollowing degrading correlations in coupled BL – soil system
Zooming in
Identifying regimes
Cabauw cloud-scenes on 8 days with biggest model differenceCabauw cloud-scenes on 8 days with biggest model difference
Conditional sampling
Make a list of shallow cu daysMake a list of shallow cu days
Criterion:Criterion:1.1. positive surface buoyancy fluxpositive surface buoyancy flux2.2. LCL below BL topLCL below BL top3.3. Total cloud cover < 50%Total cloud cover < 50%
Evaluation against LES
New set of 4 parameters New set of 4 parameters reflecting cloud vertical reflecting cloud vertical structure in the boundary-structure in the boundary-layerlayer
LES (x) vs SCM (y), daily valuesLES (x) vs SCM (y), daily values
Evaluated for the time-range Evaluated for the time-range 10-14 UTC to capture diurnal 10-14 UTC to capture diurnal variationvariation
One month of DALES (June 2008)One month of DALES (June 2008)
zzbasebase
cfcfmaxmax
zzcf maxcf max
overlap ratiooverlap ratio
controlcontrol newnew
Bar-chart
Monthly-mean bias for June 2008Monthly-mean bias for June 2008
Impact of including a new cloud overlap function
Multi-year bias for 2007-2010Multi-year bias for 2007-2010Green: including SGS overlap for cumuliform clouds Green: including SGS overlap for cumuliform clouds (Neggers et al, JGR, 2011)(Neggers et al, JGR, 2011)
Conclusions
Multiple parameter evaluation was performed against multi-year Multiple parameter evaluation was performed against multi-year Cabauw dataCabauw data
RACMO physics was subjected to a 12-point check reflecting the cloud RACMO physics was subjected to a 12-point check reflecting the cloud structure, radiative budget and heat budget of coupled boundary-structure, radiative budget and heat budget of coupled boundary-layer soil systemlayer soil system
This revealed the existence of a compensating error between the This revealed the existence of a compensating error between the representation of cloud vertical structure and cloud overlap in the representation of cloud vertical structure and cloud overlap in the cumuliform boundary layercumuliform boundary layer