Wrap-up. Predicting atmospheric circulation DJF NAO Met Office operational seasonal forecasts with HadGEM3H N216L85O(0.25) with initial conditions from.

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Presentation transcript:

Wrap-up

Predicting atmospheric circulation DJF NAO Met Office operational seasonal forecasts with HadGEM3H N216L85O(0.25) with initial conditions from operational atmospheric analyses and NEMOVAR, 24 members, start date around the 1st of November (lagged method). Winter NAO correlation significant at the 98% confidence level. A. Scaife (Met Office)

Predicting atmospheric circulation DJF NAO seasonal forecasts using a multiple linear regression method (one-year-out crossvalidation) with the September sea-ice concentration over the Barents-Kara sea and the October snow cover over northern Siberia (one month lead time). J. García-Serrano (IPSL) r=0.79

Wrap-up LRF training  3 blocks: – Monitoring and verification Need of standarized verification of prob. consensus outlook Need of monitoring info for verification

Example verification seasonal forecasts from GCMs: RPSS

Reliability diagrams for the first 10 years of PRESAO (seasonal rainfall forecasts Jul-Sept) Over-forecasting in normal category Under-forecasting in below normal category Weak sharpness

Wrap-up LRF training  3 blocks: – Monitoring and verification Need of standarized verification of prob. consensus outlook Need of monitoring info for verification – Available information sources Models: different skill  Every model used has to be evaluated/verified Systematic approach to the sources of predictability  empirical algorithms – Methods, algorithms and projects Room for statistical algorithms/downscaling Need of updated info on relevant projects/initiatives

Way forward Joint LRF training (MedCOF, SEECOF, PRESANORD)? Once a year rotating N-S, E-W? Themes for the next LRF training session? Lectures/practical sessions?