Ensemble Forecasting at RSMC La Réunion WMO/WWRP Training, Nanjing, dec 2011 Matthieu Plu, Thierry Dupont, Sébastien Langlade, Nicole Girardot METEO-FRANCE RSMC La Réunion Laboratoire de l’Atmosphère et des Cyclones

Outline  Presentation of RSMC La Réunion  Available products from ensemble forecasts –Météo-France data –ECMWF data –TIGGE data  Track forecasts  Intensity forecasts  Wave forecasts  Storm surge  SWFDP RSMC La Réunion website

RSMC La Réunion  Since 1993, Météo-France La Réunion: WMO RSMC for tropical cyclones in the South-West Indian Ocean (SWIO)

RSMC La Réunion  Cyclone activity in the SWIO : –12% of the total worldwide cyclone activity –Impacts : many human losses every year (particularly in Madagascar), and significant economical impact in the richer countries (example : Dina 2002  95 M€ losses in La Réunion) –Severe winds and intense rainfall (La Réunion records), waves and storm surge (African coast and atolls)  Role of RSMC La Réunion for tropical cyclones : –Provide appropriate guidance information (analyses, forecasts) in real- time ; forecast term until 5 days –Climatology, database of TC –Training and R&D activities

RSMC La Réunion

 … but individual tracks are not so regular …

RSMC La Réunion  Equatorial waves (Kelvin waves, Rossby waves, Madden-Julian oscillation, …) modulate cyclone activity.  Mid-latitude events also play a significant role on cyclone dynamics (track and intensity) Density of occurrence of a mid-latitude Rossby-wave breakings at 200hPa during the rapid Intensification of a cyclone

RSMC La Réunion  Track error of deterministic models in the SWIO: Direct position error ( season)

Available products from ensemble forecasts  Météo-France PEARP

Available products from ensemble forecasts  ECMWF ensemble prediction system (EPS)

Available products from ensemble forecasts  Other TIGGE products –MOGREPS (UKMO) : cxml

Available products from ensemble forecasts  Other TIGGE products (cxml) –GEFS (NCEP) : cxml + wind and precipitation

Available products from ensemble forecasts  Other TIGGE products (cxml) –CENS (CMC) : cxml + wind and precipitation

TC track forecasts  General method for track prediction –Step 1 : Build the official RSMC track forecast –This step relies on deterministic models and on « consensus » of several models Ensemble tracks may help to eliminate from the consensus the outlying deterministic tracks

TC track forecasts  General method for track prediction –Step 2 : Writing the bulletin –Ensemble forecasts are used to : Provide some confidence of the forecast Give some possible alternative scenarios

TC track forecasts  Illustration on the case of Bingiza Tropical cyclone Bingiza 13 February UTC (Terra image – source :

TC track forecasts  Illustration on the case of Bingiza: early prediction of impact zone Bingiza, UTC Moderate Tropical Storm

TC track forecasts  Illustration on the case of Bingiza: early prediction of impact zone Bingiza, UTC Moderate Tropical Storm

TC track forecasts  Illustration on the case of Bingiza: early prediction of impact zone Bingiza, UTC Moderate Tropical Storm PEARP EPS

TC track forecasts  Illustration on the case of Bingiza: early prediction of impact zone Bingiza, UTC Moderate Tropical Storm

TC track forecasts  Illustration on the case of Bingiza: early prediction of impact zone –Most of the models and ensembles indicate movement towards the South –The spread of ensemble tracks is large –BULLETIN : UTC […] The track forecasts by numerical models are highly spread. There is some agreement that the storm movement may be somehow erratic during the next 48h. Then, some models suggest a track towards the South-West towards Madagascar, some others towards the South. The inhabitants of Mauritius, La Réunion and of Madagascar should follow the evolution of this system. –Not a precise warning

TC track forecasts  Illustration on the case of Bingiza: short-term prediction of landfall Bingiza, UTC Tropical cyclone

TC track forecasts  Illustration on the case of Bingiza: short-term prediction of landfall Bingiza, UTC Tropical cyclone

TC track forecasts  Illustration on the case of Bingiza: short-term prediction of landfall

TC track forecasts  Illustration on the case of Bingiza: short-term prediction of landfall –The ensembles confirm the RSMC track scenario –BULLETIN : 2011/02/12 06UTC […] Models indicate a direction towards the East coast of Madagascar and landfall between Masaola and Sainte Marie Island on Monday. The environmental conditions are favorable to intensification before landfall. The inhabitants of the East coast of Madagascar must follow with great attention the evolution of Bingiza. –48h before landfall, the forecast is: Precise: day of landfall given, location (~150km) Right: this forecast has been verified –Ensembles provided confidence in this forecast

TC track forecasts Subjective evaluation of ensemble systems to predict landfall: Position Timing Black: 0-24h Purple: 24h-48h Red: 48h-72h Orange: 72h-96h Yellow: 96h-120h Existence of the observed track in the ensemble tracks: as a majority as a minority not at all EPS 12/02 – 12UTC

TC track forecasts LANDFALL AT MASAOLA ? LANDFALL AT AT 02UTC ? REALISTIC TRACKS AT MEDIUM RANGE ? REALISTIC TRACKS AT LONG RANGE ? UTC UTC UTC UTC UTC UTC UTC UTC UTC UTC

CENSEPSGEFS MOGREPS PEARP Poor Man Ensemble TC track forecasts

 Conclusion on the case of Bingiza: –A difficult case for track forecast –At early stage, ensembles do not do better than deterministic models for predicting the impact areas –48h before landfall, ensembles provide precise and good information –At every stage, ensembles are useful to quantify the confidence of the forecast: early stage: low confidence 48h before landfall: high confidence Such information is conveyed in the RSMC bulletins.

Multi-ensemble All forecasts TC track forecasts  Some other exemples : –Cherono (Tropical storm 2011) Multi-ensemble

TC track forecasts  Some other exemples : –Yasi (TC, Australia 2011)

TC track forecasts  Some other exemples : –Yasi (TC, Australia 2011)

TC intensity forecasts  Intensity forecasts: a difficult task! Intensity & Structure change of the cyclone Davidson et al. (2008) Hanley et al. (2001) Gray (1979), Emanuel (1986) Montgomery (2008) Nguyen et al. (2006) Wang (2002) Schubert (1999) Initial structure External forcing - Atmosphere - Océan Internal dynamics Fujita (1952) Chan and Williams (1987) Ma et al. (2011) Leroux et al. (2012)

TC intensity forecasts  Intensity forecasts: a difficult task!  General forecasting method: –Interpretation of the internal structure and the environment (favorable/unfavorable) from model analyses and satellite images; –Deterministic models indicate a possible trend for the evolution of intensity; –Ensembles have not been used for intensity forecasts yet; –Exemples for « climatological » and « rapid » intensification.

TC intensity forecasts  TC Gelane (2010): a « rapid intensification ». INTENSITY (hPa) Before Rapid intensification

TC intensity forecasts  TC Gelane (2010) before rapid intensification (02/ UTC): –All deterministic models predict no intensification –RSMC bulletin: 12h-24h Strong Tropical Storm 36h-60h Moderate Tropical Storm 72h Tropical Depression –Verification : 12h-24h Tropical Cyclone 36h Intense Tropical Cyclone !!

TC intensity forecasts  TC Gelane (2010) before rapid intensification (02/ UTC): –Available ECMWF ensemble products : Observation: 930hPa !! 980

TC intensity forecasts  TC Gelane (2010) INTENSITY (hPa) Before Rapid filling

TC intensity forecasts  TC Gelane (2010) before rapid filling (02/ UTC): –All the deterministic models predicted Gelane to encounter strong vertical wind shear  rapid filling –The difference between the models when filling will occur, depending on the track forecast Deterministic models EPS strike probabilities STRONG SHEAR

TC intensity forecasts  TC Gelane (2010) before rapid filling (02/ UTC): –Available ECMWF ensemble products : Observation: 930hPa !!

TC intensity forecasts  Hurricane Irene (North Atlantic, 2011) : a « climatological » intensification.  Does the ensemble bring additional information with regard to the deterministic forecast?

TC intensity forecasts  Global models fail to represent correctly intensity evolutions,  Lagrangian EPSgrams do not bring useful information yet,  Some hope with resolution increase and with new products ?

TC intensity forecasts  Global models fail to represent correctly intensity evolutions,  Lagrangian EPSgrams do not bring useful information yet,  Some hope with resolution increase and with new products: Products in test (not operational)

High wave forecasts  Two ECMWF products are used: –EPSgrams –Probability maps

High wave forecasts  Two ECMWF products are used: –EPSgrams

High wave forecasts  Two ECMWF products are used: –Probability maps Ech 24 h Ech 48 hEch 72 h

Storm surge forecasts  Storm surge highly depends on : –Track –Intensity –Surface wind structure  R&D activities have begun to forecast storm surge: –Prediction of wind extensions (radius of maximum wind, other thresholds…), –Generate a « climatology » of storm surge in the SWIO from a surge model and a « climatology » of cyclones

SWFDP Website of RSMC La Réunion Purpose : –Provide guidance in real-time regarding tropical cyclones, and extreme wind and rainfall –A limited-access to the SWFDP and RA I national meteorological services –Available in two languages: French & English  Input data : –Aladin-Reunion forecast fields –For each cyclone, the official RSMC track forecast –Deterministic models (Météo-France, ECMWF, UKMO) –Forecast tracks from ensembles (PEArp, ECMWF EPS, NCEP, CMC, MOGREPS) and multi-ensemble –Fields (mslp, wind, rainfall) from ensembles (PEArp, ECMWF EPS, NCEP, CMC) and multi-ensemble

SWFDP Website of RSMC La Réunion  Permanent products: –Aladin-Réunion forecasts (00UTC and 12UTC, until 84h) –Probabilities and quantiles of strong winds and intense rainfall for 4 ensembles + multi-ensemble –mslp spaghettis forecasts (for cyclogenesis) for 4 ensembles + multi- ensemble  In case of a cyclone in the basin: –Official RSMC track forecast + uncertainty cone –Track forecasts from deterministic models –Tracks, live time, Strike probabilities, track for the 5 ensembles + multi- ensemble

SWFDP Website

2. Website of RSMC La Réunion Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Illustrations sur le cas de Bingiza (février 2011) Early detection of the cyclogenesis of Bingiza

Website of RSMC La Réunion Official RSMC forecast Uncertainty cone (derived from EPS) Track forecasts from deterministic models

SWFDP website of RSMC La Réunion  Regions where strong winds and heavy rainfall may occur are indicated in RSMC bulletins before landfall  More diagnoses are available in the SWFDP/RSMC La Réunion website  Probabilities of attaining a threshold : –Wind: 28kts, 48kts, 64kts, 90kts –Rainfall: 5mm/6h, 10mm/6h, 20mm/6h, 50mm/6h, 5mm/24h, 20mm/24h, 50mm/24h, 100mm/24h

Website of RSMC La Réunion Official RSMC forecast Uncertainty cone (derived from EPS) Track forecasts from deterministic models Bingiza, before landfall

Website of RSMC La Réunion Bingiza, before landfall

Website of RSMC La Réunion Bingiza, before landfall

Website of RSMC La Réunion Bingiza, before landfall

SWFDP website of RSMC La Réunion  Quantiles 25%, 50%, 75%, 90%: ~ a realistic extreme value the median value 90% 50% 75% 25%

SWFDP website of RSMC La Réunion the median value a realistic extreme value

Conclusion  Ensemble prediction products are now a major input at RSMC La Réunion, especially for: –Track prediction –Impacts: waves, rainfall, winds  Two main paths for using ensembles: –Confirm the RSMC scenario, or propose alternative scenarios –Convey some information about uncertainty in the bulletins  Future R&D activities: –Comparison of the ensemble track forecasts from different ensembles, and from multi-ensemble –Calibration of the ensemble forecasts for wind and precipitation –A major difficulty: verification and calibration of ensemble forecasts where the observations are sparse