Prediction of extreme events at Subseasonal to Seasonal
Prediction of extreme events at Sub-seasonal to Seasonal lead times Frédéric Vitart, Laura Ferranti, Ivan Tsonevsky ECMWF Slide 1 S 2 S Extremes Workshop Dec 2016 - IRI -
INDEX 1. S 2 S database 2. MJO/Weather regimes in S 2 S database 3. Case studies: • 2010 Heat Wave over Russia • Tropical Cyclone PAM 4. Extreme Forecast products and Verification Slide 2 S 2 S Extremes Workshop Dec 2016 - IRI -
WWRP/WCRP Sub-seasonal to Seasonal (S 2 S) Prediction Project Sub-Projects Teleconnections (C. Stan and H. Lin) Madden-Julian Oscillation (D. Waliser and S. Woolnough) Monsoons (H. Hendon) Africa (A. Robertson and R. Graham) Extremes (F. Vitart) Verification and Products (C. Coelho) Research Issues • • • Slide 3 Predictability Teleconnection O-A Coupling Scale interactions Physical processes Modelling Issues • • • Initialisation Ensemble generation Resolution O-A Coupling Systematic errors Multi-model combination S 2 S Database S 2 S Extremes Workshop Dec 2016 - IRI - Needs & Applications Liaison with SERA (Working Group on Societal and Economic Research Applications)
S 2 S database Ø 3 -week behind real-time forecasts + re-forecasts (up to day 60) Ø Common grid (1. 5 x 1. 5 degree) Ø Data archived with a daily frequency (sub-daily for total precip/max and min 2 mtm) in GRIB 2 at ECMWF and CMA Ø About 80 parameters, including: § § § Slide 4 3 D fields (u/v/w/z/t/q) on 10 pressure levels (up to 10 h. Pa) Surface fluxes Sea Surface temperature Sea-ice cover (fraction) Snow depth/density/snow fall/snow albedo S 2 S Extremes Workshop Dec 2016 - IRI -
WWRP/WCRP S 2 S Database Timerange Resol. Ens. Size Freq. Hcsts ECMWF D 0 -46 T 639/319 L 91 51 2/week On the fly UKMO D 0 -60 N 216 L 85 4 daily NCEP D 0 -44 N 126 L 64 4 4/daily ECCC D 0 -32 0. 45 x 0. 45 L 40 21 weekly Bo. M D 0 -60 T 47 L 17 33 2/weekly Fix JMA D 0 -34 T 319 L 60 25 2/weekly Fix KMA D 0 -60 N 216 L 85 4 daily CMA D 0 -45 T 106 L 40 4 daily Fix 1886 -2014 CNRM D 0 -32 T 255 L 91 51 weekly Fix 1993 -2014 2/monthly 15 CNR-ISAC D 0 -32 0. 75 x 0. 56 L 54 40 weekly Fix 1981 -2010 6/month 1 HMCR D 0 -63 1. 1 x 1. 4 L 28 20 weekly Fix 1981 -2010 weekly 10 Slide 5 S 2 S Extremes Workshop Dec 2016 - IRI - Hcst length Hcst Freq Past 20 y Hcst Size 2/weekly 11 4/month 3 1999 -2010 4/daily 1 On the fly 1995 -2014 weekly 4 1981 -2013 6/month 33 1981 -2010 3/month 5 On the fly 1996 -2009 4/month 3 daily 4 On the fly 1993 -2015 Fix
Sub-seasonal prediction of extreme events § Prediction of large-scale, long lasting events (> 1 week): • Heat/cold waves • Droughts • Flooding § Prediction of statistics of small scale events, for example: • Tropical cyclones • Tornadoes Slide 6 S 2 S Extremes Workshop Dec 2016 - IRI -
Madden Julian Oscillation MJO PHASES Locations of large floods during 1985– 2010 MJO influences on large floods of the West Coast of North America From C. Zhang, BAMS 2013 Slide 7 S 2 S Extremes Workshop Dec 2016 - IRI -
Bivariate Correlation with ERA Interim – Ensemble Mean 1999 -2010 re-forecasts All Year Slide 8 S 2 S Extremes Workshop Dec 2016 - IRI - DJF 8
MJO Teleconnections (S 2 S re-forecasts) EI 0. 48 Z 500 Composites Phase 3 + 3 pentads NDJFM Bo. M 0. 15 CMA 0. 14 CNRM 0. 15 UKMO 0. 28 Slide 9 HMCR 0. 13 JMA 0. 22 S 2 S Extremes Workshop Dec 2016 - IRI - NCEP 0. 32 ECCC 0. 21 ISAC 0. 25 ECMWF 0. 31
Predicting skill associated with the Euro-Atlantic Regimes: NAO - NAO + Bom Blocking Bom Atlantic Ridge Bom Slide 10 S 2 S Extremes Workshop Dec 2016 - IRI - Bom October 29, 2014 10
Russian Heat Wave July-August 2010 § Worst heat wave on record over the past 33 years (Hoag, Nature 2014) § Estimated 55, 000 deaths § Wildfires, smoke, worst drought in nearly 40 years, and the loss of at least 9 million hectares of crops ERA interim 2 mtm anomalies 1 -7 August 2010 Slide 11 S 2 S Extremes Workshop Dec 2016 - IRI -
Russian Heat Wave 2010 ERA Interim Day 1 -7 Day 8 -14 Day 15 -21 1% 5% 4 July 1 August 15 August WEEK 1: time evolution of heat wave well predicted WEEK 2 and 3: Onset and decay predicted one week too late Slide 12 S 2 S Extremes Workshop Dec 2016 - IRI Timing of maximum well predicted
2 mtm anomalies over Russia – ECMWF reforecasts 1 -7 August 2010 1% 5% Lead time Slide 13 d 26 -32 d 22 -28 d 19 -25 d 15 -21 d 12 -18 d 8 -14 d 5 -11 S 2 S Extremes Workshop Dec 2016 - IRI - d 1 -7
2 mtm anomalies over Russia – S 2 S reforecasts 1 -7 August 2010 ECMWF (18 Jul) UKMO (17 Jul) BOM (16 Jul) NCEP(16 Jul) JMA(20 Jul) ECCC(21 Jul) HMCR(20 Jul) CNRM(15 Jul) ERA Interim Slide 14 S 2 S Extremes Workshop Dec 2016 - IRI -
2 mtm anomalies over Russia – S 2 S models reforecasts 1 -7 August 2010 July Slide 15 18 17 15 18 21 S 2 S Extremes Workshop Dec 2016 - IRI - 20 20 16 18 20
Tropical Cyclone PAM Case Study Formed Dissipated March 6, 2015 March 22, 2015 Hit Vanuatu islands on 13 March 2015 Most intense tropical cyclone of the south Pacific Ocean in terms of sustained winds and regarded as one of the worst natural disasters in the history of Vanuatu. Slide 16 S 2 S Extremes Workshop Dec 2016 - IRI -
March 2015 MJO Forecasts starting on 26 Feb 2015 Slide 17 S 2 S Extremes Workshop Dec 2016 - IRI -
Modulation of tropical cyclone density anomaly by MJO Phase 2 -3 MJO Phase 4 -5 OBS ECMWF NCEP JMA Bo. M Multi Slide 18 S 2 S Extremes Workshop Dec 2016 - IRI - MJO Phase 6 -7 MJO Phase 8 -1
Prediction from ECMWF Probability of a TC strike within 300 km 09 March 2015 Day 1 -7 23 February 2015 Day 15 -21 Slide 19 S 2 S Extremes Workshop Dec 2016 - IRI - 02 March 2015 Day 8 -14 16 February 2015 Day 22 -28
Tropical Cyclone Pam case study Multi-model prediction of TC strike probability anomalies- 9 -15 March 2015 (NCEP/ECMWF/Bo. M/JMA/CMA) 2015/02/19 day 19 -25 Slide 20 S 2 S Extremes Workshop Dec 2016 - IRI - 2015/02/26 day 12 -18
Impact of Resolution - Tropical cyclone PAM - 9 -15 March 2015 Probability of a TC strike within 300 km Day 12 -18 64 km 32 km 16 km 110 km+ SP Verification Slide 21 S 2 S Extremes Workshop Dec 2016 - IRI - Day 19 -25
Verification of extreme events in S 2 S database Main issues: § Rarity of extreme events in observations § Low number of ensemble members in most S 2 S re -forecasts § Low frequency of ensemble reforecasts in some S 2 S models § Short common re-forecast period 1999 -2010 S 2 S real-time forecasts are more suitable for verification of extreme events, but period covered is small (archived only from 1 st Jan 2015) Slide 22 S 2 S Extremes Workshop Dec 2016 - IRI -
Relative Operating Characteristics (ROC) score Decile Probabilities – May 2015 - April 2016 - NH ECMWF real-time forecasts Day 12 -18 Probability to be in lower decile Forecast Slide 23 S 2 S Extremes Workshop Dec 2016 - IRI - Probability to be in upper decile Persistence of previous week 23
2 m temp Cumulative Distribution Function ensemble predictions for 29 June - 5 July 2015 Climate 15 June 2015 (15 -21 d) Slide 24 18 June 2015 (12 -18 d) S 2 S Extremes Workshop Dec 2016 - IRI - 22 June 2015 (8 -14 d) 25 June 2015 (5 -11 d) Observed anomaly
2 m temp Extreme Forecast Index forecast range: 12 -18 days verifying 8 -14 August 2016 Ncep Ecmwf JMA Ukmo http: //www. ecmwf. int/en/research/projects/s 2 s/charts/s 2 s/ Slide 25 S 2 S Extremes Workshop Dec 2016 - IRI -
EFI skill assessment Preliminary results based on ECMWF system: Slide 26 S 2 S Extremes Workshop Dec 2016 - IRI -
Example of Attribution: March 2013 Cold wave over Europe 2 mtm anomalies ERA Interim ECMWF - strong MJOs ECMWF - Weak MJOs Slide 27 S 2 S Extremes Workshop Dec 2016 - IRI - NCEP - strong MJOs NCEP - Weak MJOs 27
Conclusions • The S 2 S database can be a useful resource for case studies, skill assessment and also attribution of extreme events • S 2 S models display skill to predict MJO up to 3 -4 weeks. However impact on NAO is weaker than in re-analysis and skill to predict European blocking (important for summer heat wave prediction) and NOA- (important with winter cold waves) is limited to 2 weeks. • Russian heat wave 2010: S 2 S model forecasts provided indications of an exceptional warm anomaly more than 10 days in advance. • Tropical cyclone PAM: High probabilities of TC strike 2 -3 weeks in advance, most likely because of the impact of the strongest MJO on record on TC activity • Preliminary verification of ECMWF model suggests some useful skill for decile and EFI extended-range prediction Slide 28 S 2 S Extremes Workshop Dec 2016 - IRI -
Regimes based on clustering of daily anomalies for 29 cold seasons (1980 -2008) 500 h. Pa geopotential • Obtain well-known Euro-Atlantic regime patterns ‘k means’ clustering applied to EOF pre-filtered data (retaining 80% of variance) m 2 s 2 Slide 29 S 2 S Extremes Workshop Dec 2016 - IRI - October 29, 2014 29
Heat Wave Prediction in ECMWF re-forecasts ERA Interim Monthly Forecast Day 12 -18 Slide 30 S 2 S Extremes Workshop Dec 2016 - IRI -
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