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

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

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

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

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

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

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?

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

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

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

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