Highest Confidence Forecasts

• Model agreement– CMC=NAM=GFS

• Run-to-run changes (dMod/dt) very small• Models trending toward agreement

– Example:• OLD run: NAM=GFS but *not* CMC• NEW run: CMC trends toward WRF & GFS

• Models have current weather “in hand”• Parameterized processes not significant part of

feature

Lowest Confidence Forecasts

• Large model disagreement– ECMWF, WRF, GFS all have different

solutions

• Run-to-run changes (dMod/dt) large

• Don’t have current weather “in hand”

• Parameterized processes significant part of feature

When models disagree …..

• In a 12-36 hr. fcst, lean toward model/s that has “best” handle on current weather!

• Lean toward a model whose run-to-run change is small, especially if other models are trending toward it

• Lean away from a model if it is showing its bias!• Take consensus!

When models disagree …..

Rainfall forecast:Cape Canaveral, FL

Postpone a launch?

CMC

NAM

AVN

When models disagree …..

CMC

AVN

NAM

KJAX 141756Z 33008KT 1 1/2SM -RA BR OVC010 15/15 A3013 60086

Which model do you go with?

15Z RADAR

MODEL TREND: Single Model

Is the Trend a useful forecast technique?

MODEL TREND: Single Model

Is the Trend a useful forecast technique?

MODEL TREND: Single Model

Is trend any help at all in this case?

MODEL TREND: Single Model

LAGGED AVERAGE FORECAST- Average of each forecast valid at same time-“Poor man’s” Ensemble

MODEL TREND

Trending toward New York City?

MODEL TREND

Trend = Bust-o-matic

MODEL TREND

Interpreting Model Trends: What’s Legitimate ??

• Least significant if associated with “parameterized” situation

• 3-model run trend stronger signal than 2-model trend• Hierarchy of model run-to-run trends

– 24 ->12 hours most significant– 60-> 48 hours least significant

MODEL CONFIDENCE: Utilizing Trend & Agreement

MOST CONFIDENT!

MODEL CONFIDENCE: Utilizing Trend & Agreement

TRENDING TOWARD AGREEMENT

MODEL CONFIDENCE: Utilizing Trend & Agreement

TRENDING TOWARD AGREEMENT

MODEL CONFIDENCE: Utilizing Trend & Agreement

TRENDING TOWARD AGREEMENT

MODEL CONFIDENCE: Utilizing Trend & Agreement

TRENDING TOWARD AGREEMENT

MODEL CONFIDENCE: Utilizing Trend & Agreement

TRENDING TOWARD AGREEMENT

MODEL CONFIDENCE: Utilizing Trend & Agreement

What’s a forecaster to do? Suggestions???

MODEL CONFIDENCE: Utilizing Trend & Agreement

LEAST CONFIDENT!

ENSEMBLE FORECASTS

• What are ENSEMBLE FORECASTS?– Model’s initial conditions are perturbed– Variety of solutions occur– Ensembles on e-wall

ENSEMBLE FORECASTS

THESE ARE THE MEMBERS OF THE ENSEMBLE- Negative and Positive tweaks

ONE MODEL … MANY TWEAKS

ENSEMBLE FORECASTS

EACH MEMBER IS RUN OUT IN TIME- Provides “unique” solution

ENSEMBLE FORECASTS

ENSEMBLE MEAN IS “most likely” SOLUTION averaged over ALL cases

ENSEMBLE FORECASTS

HOW CONFIDENT ARE WE IN THE ENSEMBLE MEAN?

ENSEMBLE FORECASTS

IS THE ENSEMBLE MEAN more likely than the CLUSTERS?

ENSEMBLE FORECASTS

Which solution is LEAST likely?

MEM 1

MEM 2ENSEMBLE

MEAN

ENSEMBLE FORECASTS: Another Approach

THESE ARE DIFFERENT MODELS- WRF, GFS, NGM, MM5, EUR, MRF, UKM, CMC

MANY MODELS … MANY DIFFERENT “PHYSICS” & IC

ENSEMBLE FORECASTS

What’s the better approach?

MULTI-MODELCONSENSUS

ENSEMBLE FORECASTSMany “perturbations”, Many People

What’s the better approach?

Many “perturbations”, One YOU

ENSEMBLE FORECASTS

• Variance measures forecast reliability– Measures “robustness” of a model solution– How much confidence in model forecast

• Ensemble mean is “most accurate” averaged over all cases

• Member clustering can be useful

• TARGETING OBSERVATIONS

OPTMIZING MODEL OUTPUT

• MODEL AGREEMENT– Agreement of different models on same

solution = POWERFUL• Confidence high if models converge on solution• Confidence low if models diverge

• MODEL TREND– Run-to-run changes of a model

• Confidence higher if run-to-run changes are small• Confidence lower if run-to-run changes are large