1. Peter May and Beth Ebert CAWCR Bureau of Meteorology Australia
Verification issues
Peter May and Beth Ebert
CAWCR
Bureau of Meteorology
Australia

2. Observations
High resolution modelling increases demand for high resolution observations for verification
Observation error impacts verification results
Sharing of observations
Use of model analyses as "observations"
Challenging environments – polar regions, tropics, developing nations

3. Ensemble & high resolution NWP
Active area of verification research in recent years
How to evaluate high resolution ensembles?
More work needed in
Wind, moisture
Timing errors
High resolution observation datasets & associated uncertainty

4. Process verification Scientific / diagnostic verification methods
Often tailored
Frequently uses special datasets
What could be done routinely?
Processes of interest
Convection
Surface fluxes …

5. Seamless forecasts
Verification methods and strategies that apply across time scales, space scales
Verification methods that apply across variables (e.g., precipitation and streamflow)

6. Extremes Most important in terms of impact
Rare events – hard to collect robust sample size
Observations may have greater errors or may not exist (instrument destroyed by weather)
Many scores behave badly for rare events

7. Hazard impacts How to predict hazard impacts?
What observations can be used and how to obtain?
How to verify in the most meaningful way?
Whose job is it?

8. Warning verification More facets than ordinary verification
Lead time, onset & cessation, intensity level
Observations of the hazard

9. Environmental verification
Atmospheric composition & aerosols
Renewable (solar, wind, wave) energy
Water
Coastal processes
Vegetation state

10. Estimating forecast value
More important now than ever!
How to work with economists?
Collecting cost, losses and other information from other sectors

11. Communicating verification
Even sophisticated users struggle
Relevance to user
Presentation
Real-time and post real time