a community statistical post-processing system thomas nipen and roland stull university of british...
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A community statisticalpost-processing system
Thomas Nipen and Roland StullUniversity of British Columbia
Motivation2
Post processingNWP modelData
assimilationNWP
products
Component approach3
Post processing
Data assimilation
NWP model (e.g. WRF)
NWPproducts
Microphysics
Radiation
Surface
Land-surface
Boundary layer
...
NWP model
Component approach4
Post processingNWP modelData
assimilation
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
NWPproducts
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Component approach
Goal Schemes
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Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Ensemble member selection
GoalSelect ensemble members
Schemes
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NWP ensemble
Climatology
Analogs1
1Delle Monache et al. (2011)
EnsembleInput data...
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Downscaling
GoalDownscale to output locations
Schemes
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Nearest neighbour
Linear interpolation
Spline interpolation
...
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Correction
GoalBias-correct the ensemble
Schemes
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Multivariate regression1
Kalman Filtering2
1Glahn&Lowry (1972)2Homleid (1995)
...
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Deterministic
GoalConvert to deterministic form
Schemes
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Ensemble mean
Ensemble median
Weighted average
Ensemble mean
...
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Uncertainty
GoalConvert to probabilistic form
Schemes
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Ensemble MOS1
Bayesian model averaging2
1Gneiting et al. (2005)2Raftery et al. (2005)
...
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Calibration
GoalRemove distributional bias
Schemes
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Quantile regression1
PIT-based2
1Bremnes (2004)2Nipen&Stull (2011)
...
Statistical model
Ensemble
Probabilistic
Deterministic
Uncertainty
Deterministic
Calibration
Updating
Updating
Downscaling
Selection Correction
Updating
GoalIncorporate recent observations
Schemes
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PIT-based1
1Nipen,West&Stull (2011)
Observations
...
Potential uses13
Research• Simplifies development
of new methods
• Offers facilities for comparing to existing methods
Operational
Potential uses14
SelectionAnalogs
DownscalingNearest N.
CorrectionKalman Filter
...
SelectionNWP ens.
DownscalingNearest N.
CorrectionRegression
...
Combination 1 Combination 2
Operational• Different combinations
yield different results
Research• Simplifies development
of new methods
• Offers facilities for comparing to existing methods
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Version 1.0
Available fall 2012• Implement all schemes
presented here
• Ability to contribute new schemes
• Input/output formats:• Flat files• NetCDF• GRIB
For more informationThomas Nipen ([email protected]) Roland Stull ([email protected])
http://weather.eos.ubc.ca
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