The CPC Consolidation Forecast

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The CPC Consolidation Forecast. David Unger Dan Collins, Ed O’ Lenic, Huug van den Dool NOAA/NWS/NCEP/Climate Prediction Center. Overview. A regression procedure designed for ensembles. Derive a relationship between the BEST member of an N-member ensemble and the observation:

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### The CPC Consolidation Forecast

David Unger

Dan Collins, Ed O’ Lenic,

Huug van den Dool

NOAA/NWS/NCEP/Climate Prediction Center

Overview
• A regression procedure designed for ensembles.

Derive a relationship between the BEST member of an N-member ensemble and the observation:

Y = a0 + a1fb + ε

Ensemble Regression
• Weights represent the probability of a given member being the best.
• If weights are known, coefficients can be calculated from the ensemble set.

(No need to explicitly identify the best member)

April Data  June-August Mean SST’s

A series of forecasts

K = The fraction of the original model spread

Multi Model Consolidation
• At least 25 years of “hindcast” data
• Standardize each model (means and standard deviations)
• Remove trend from models and observations
• Weight the various models
• Perform regression
• Add trends onto the results
Nino 3.4 Consolidation
• CFS, CCA, CA, MKV

(Statistical and Dynamic models mixed)

• Lead -2 and Lead -1 are a mix of observations and the one and two-month forecast from the CFS
U.S. Temperature and Precipitation Consolidation
• CFS
• Canonical Correlation Analysis (CCA)
• Screening Multiple Linear Regression(SMLR)
• OCN - Trends.
Performance

CRPSS

RPSS - 3

HSS

Bias (C)

% Cover

CCA+SMLR

CFS

CFS+CCA+SMLR, Wts.

All – Equal Wts.

Official

Future Work
• Add more tools and models
• Improve weighting method
• Trends are too strong
• Improve method of mixing statistical and dynamical tools
Recursive Regression
• Y = a0 + a1fi

a+= (1-α) a+ αStats(F,Y)

Stats(F,Y) represents error statistic based on the most recent case

α = .05

a+= .95a + .05 Stats(F,Y)

SST Consolidation
• CFS – 42 members (29%)
• Constructed Analog

(CA) – 12 members (18%)

• CCA – 1 member (17%)
• MKV – 1 member (36%)