Ensemble Forecasting at RSMC La Réunion

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

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(2009-2010 season)

Available products from ensemble forecasts

Météo-France PEARP


ECMWF ensemble prediction system (EPS)


Other TIGGE products

– MOGREPS (UKMO) : cxml


Other TIGGE products (cxml)

– GEFS (NCEP) : cxml + wind and precipitation


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 2011 - 07UTC (Terra image – source : http://rapidfire.sci.gsfc.nasa.gov)

TC track forecasts

Illustration on the case of Bingiza: early prediction of impact zone

Bingiza, 2011-02-10 06UTCModerate Tropical Storm

TC track forecasts



TC track forecasts



PEARP

EPS

TC track forecasts



TC track forecasts


– Most of the models and ensembles indicate movement towards the South

– The spread of ensemble tracks is large

– BULLETIN : 2011-02-10 00UTC […] 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, 2011-02-12 12UTCTropical cyclone

TC track forecasts


Bingiza, 2011-02-12 12UTCTropical cyclone

TC track forecasts


TC track forecasts


– 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 allEPS

12/02 – 12UTC

TC track forecasts

LANDFALL AT MASAOLA ?

LANDFALL AT 02-14 AT 02UTC ?

REALISTIC TRACKS AT MEDIUM RANGE ?

REALISTIC TRACKS AT LONG RANGE ?

02-0918UTC

02-1018UTC

02-1118UTC

02-1218UTC

02-1318UTC

02-1006UTC

02-1106UTC

02-1206UTC

02-1306UTC

02-1406UTC

CENS EPS GEFS

MOGREPS PEARP Poor Man Ensemble

TC track forecasts

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-ensembleAll forecasts

TC track forecasts

Some other exemples :

– Cherono (Tropical storm 2011)

Multi-ensemble2011-03-17

TC track forecasts


– Yasi (TC, Australia 2011)

TC track forecasts


– Yasi (TC, Australia 2011)

TC intensity forecasts

Intensity forecasts: a difficult task!

Intensity&

Structure changeof 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)


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 Gelane (2010): a « rapid intensification ».

INT

EN

SIT

Y (

hP

a) Before

Rapid intensification


TC Gelane (2010) before rapid intensification (02/18 - 00UTC):

– 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 Gelane (2010) before rapid intensification (02/18 - 00UTC):

– Available ECMWF ensemble products :

Observation: 930hPa !!980


TC Gelane (2010)

INT

EN

SIT

Y (

hP

a)

Before Rapid filling


TC Gelane (2010) before rapid filling (02/19 - 12UTC):

– 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 Gelane (2010) before rapid filling (02/19 - 12UTC):

– Available ECMWF ensemble products :

Observation: 930hPa !!


Hurricane Irene (North Atlantic, 2011) : a « climatological » intensification.

Does the ensemble bring additional information with regard to the deterministic forecast?


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 ?


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 h Ech 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)














Website of RSMC La Réunion

Official RSMC forecastUncertainty 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


Official RSMC forecastUncertainty cone (derived from EPS)

Track forecasts from deterministic models

Bingiza, before landfall









Quantiles 25%, 50%, 75%, 90%:

~ a realistic extreme value

the median value

90%

50%

75%

25%


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

Documents

Ensemble Forecasting at RSMC La Réunion