Seamless prediction systems prove potential for skillful Arctic - PowerPoint PPT Presentation

Seamless prediction systems prove potential for skillful Arctic sea-ice forecasts far beyond weather time scales IUP Seminar Bremen, May 4 th , 2018 Lorenzo Zampieri Alfred Wegener Institute

Outlook Predictability and ensemble forecasting Research Motivation The S2S Prediction Project Verification metrics Predictive skills Dynamical models vs Climatology

Predictability and Ensemble Forecasting

A simple set of equations… !" !# = −&" + &( !" !# = −") + *" − ( !) !# = "( − +) Lo Lorenz, E. N. (1963) De Dete termi rministic no nonp nper eriodic fl flow.

…with an interesting solution J. J. Sl Sling ngo an and T. T. Palmer (2011)

Ensemble Forecasting J. J. Sl Sling ngo an and T. T. Palmer (2011)

Research Motivations

Im Images from the YOPP PP Pr Promotional Video

Im Images from the YOPP PP Pr Promotional Video

S2S Sub-seasonal to Seasonal Prediction Project

The S2S timescale Im Image from the S2S Pr Promotional Video

The S2S Database • Coupled models from operational weather forecast centers UK Met Office KMA Météo France ECMWF CMA NCEP • Ensemble forecasts • Dynamical sea ice components • Assimilated sea surface temperature and sea-ice concentration • Long temporal coverage (25 years)

Verification Metrics

The sea-ice edge position Sea-ice edge Observation Sea-ice edge Model Integrated Ice Edge Error IIEE = " + $

The Spatial Probability Score Ensemble sea-ice forecasts Probabilistic verification metric required Spatial Probability Score (' ( − ' * ) , -% !"! = $ % Spatial Probability Skill Score !"! !"!! = . − !"! /012

Ensemble Forecasting J. J. Sl Sling ngo an and T. T. Palmer (2011)

Methods Summary UKMO CMA ECMWF MF Verification against KMA NCEP satellite observations Ensemble S2S through the SPS sea-ice forecasts Forecast SPS compared with the climatological CSPS Assessment of the Evaluation of the forecast forecast errors predictive skills and biases

Skills of S2S forecast systems 1 1 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.75 0.5 ● ● ● ● SPS [10 6 ฀ km 2 ] ● ● ● ● ● ● ● ● ● ● SPSS ● ● 0.5 ● ● 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 �0.5 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ECMWF CMA (out of range) UKMO MF KMA ECMWF Pres. NCEP Climatology �� 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60 Lead Time [Days] Lead Time [Days] Results averaged over 12 years of hindcasts (1999-2010)

Forecasting the 2007 minimum ECMWF UKMO KMA Day 30 - 2007.09.15 Day 30 - 2007.09.15 Day 30 - 2007.09.15 NCEP CMA MF Day 30 - 2007.09.15 Day 30 - 2007.09.15 Day 30 - 2007.09.13 ECMWF Pres. Climatology Day 30 - 2007.09.16 2007.09.16 Sea Ice Probability 15% sic OSI-SAF

The CSPS seasonal cycle 100 100 1 0 0 80 20 80 20 0.75 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● CSPS [10 6 ฀ km 2 ] ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 60 40 60 40 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● AEE [%] ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ME [%] ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● O [%] U [%] ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.5 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 40 60 40 60 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.25 20 80 20 80 100 100 0 0 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Jan 01 Apr 01 Jul 01 Oct 01 Jan 01 Jan 01 Apr 01 Jul 01 Oct 01 Jan 01 Jan 01 Apr 01 Jul 01 Oct 01 Jan 01 Time Time Time Skills of the climatological forecasts based on the previous 10 years of observations 15/09/2007 forecast is based on: 15/09/1996, 15/09/1997, … , 15/09/2006