1 / 26

Forecast Verification

muniya
Download Presentation

Forecast Verification

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. Forecast Verification Presenter: Neil Plummer National Climate Centre Lead Author: Scott Power Bureau of Meteorology Research Centre Acknowledgements A. Watkins, D. Jones, P. Reid, NCC

    2. Introduction Verification - what it is and why it is important? Terminology Potential problems Comparing various measures Assisting users of climate information

    3. What is verification? “check truth or correctness of” “process of determining the quality of forecasts” “objective analysis of degree to which a series of forecasts compares and contrasts with the equivalent observations of a given period”

    4. Why bother with verification? Scientific admin support is a new system better? assist with consensus forecasts Application of forecasts “how good are your forecasts?” “should I use them?” can be used to help estimate value

    5. Terminology can be confusing Verification is made a little tricky by the fact that everyday words are used to describe quantities with a precise statistical meaning. Common words include: accuracy skill reliability bias value hit rates, percent consistent, false alarm rate, ... all have special meanings in statistics

    6. Accuracy Average correspondence between forecasts and observations Measures mean absolute error, root mean square error

    7. Bias Correspondence between average forecast with average observation e.g. average forecast - average value of observation

    8. Skill Accuracy of forecasts relative to accuracy of forecasts using a reference method (e.g. guessing, persistence, climatology, damped persistence, …) Measures numerous!

    9. Reliability Degree of correspondence between the average observation, given a particular forecast, and that forecast taken over all forecasts e.g. suppose forecasts of : “10% or 30% or , …, or 70% or … chance of rain tomorrow” are routinely issued for many years if we go back through all of the forecasts issued a forecast of looking for occasions when forecast probability of 70% was issued, then we would expect to find rainfall on 70% of occasions if the forecast system is “reliable” this is often not the case

More Related