310 likes | 398 Views
Highest Confidence Forecasts. Model agreement NGM=WRF=AVN Run-to-run changes (dMod/dt) very small Models trending toward agreement Example: OLD run: WRF=AVN but *not* NGM NEW run: NGM trends toward WRF & AVN Models have current weather “in hand”
E N D
Highest Confidence Forecasts • Model agreement • NGM=WRF=AVN • Run-to-run changes (dMod/dt) very small • Models trending toward agreement • Example: • OLD run: WRF=AVN but *not* NGM • NEW run: NGM trends toward WRF & AVN • Models have current weather “in hand” • Parameterized processes not significant part of feature
Lowest Confidence Forecasts • Large model disagreement • NGM, WRF, AVN 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 ….. AVN Rainfall forecast: Cape Canaveral, FL Postpone a launch? ETA NGM
When models disagree ….. AVN 15Z RADAR ETA Which model do you go with? NGM KJAX 141756Z 33008KT 1 1/2SM -RA BR OVC010 15/15 A3013 60086
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 can cause problems…look for at least 3 consecutive runs of the 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
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 MEM 1 ENSEMBLE MEAN MEM 2 Which solution is LEAST likely?
ENSEMBLE FORECASTS: Another Approach THESE ARE DIFFERENT MODELS - ETA, AVN, NGM, MM5, EUR, MRF, UKM, CMC MANY MODELS … MANY DIFFERENT “PHYSICS” & IC
ENSEMBLE FORECASTS MULTI-MODEL CONSENSUS What’s the better approach?
ENSEMBLE FORECASTS Many “perturbations”, Many People Many “perturbations”, One YOU What’s the better approach?