Munehiko Yamaguchi 　　　　　　　　　　　　　　　

　　　　　　　　　　　　　　　　　　　　　　　　　

　　 Typhoon Research Department,

Meteorological Research Institute of the Japan Meteorological Agency

9:00 – 12:00

2011.12.15 (Thr)

Topic No. 2

Initial Condition Sensitivity of Typhoon Track Prediction

in the Western North Pacific

Tropical Cyclone Ensemble Forecast

Nanjing, China

Performance of typhoon track predictions by NWP model

(Yamaguchi et al. 2009, MWR)

The accuracy of typhoon track predictions has improved steadily over the last few decades

Time series of 3-yr running mean of position errors by JMA’s Global Spectral Model from 1997 to 2007

The position error of 5-day forecasts in 2007 is smaller than that of 3-day forecasts in 1997.

Verification for individual casesPosi

tion

err

or

(km

)

Sample Number

Distance between Beijing and Shanghai

Position errors of 3-day predictions by JMA/GSM.

Verification period: 3 years from 2008 to 2010.

Some issues to be addressed

The accuracy of typhoon track forecasts has steadily improved.

Chan (2010, GPTC) Since Chan et al. (2002) paper, research on the physics of general TC motion has been almost non-existent, which suggests that most scientists are quite content with the current theories of TC motion.

Pre

sen

tIs

sues In reality, however, significant errors still exist and there are prediction cases

where the position error exceeds 1000 km at 3 days.

There are few studies focusing on the cause of prediction errors. (e.g. Carr and Elsberry 2000a, 2000b ） .

Ap

pro

ach

Obs.Data

assimilation NWP UserForecaster

Flow of typhoon forecasting

Various sources of prediction errorsAny approach to separate them to some extent?

Design of numerical experiments

JMA’s global spectral model (JMA/GSM) is run from the ECMWF’s initial conditions, which are available through the YOTC (Year of Tropical Convection) dataset, to distinguish TC track prediction errors attributed to initial conditions from those attributed to the NWP model.

Initial conditions are thought to be essential for accurate predictions in

cases where the prediction is significantly improved by replacing

the initial condition.

Meanwhile, hints for modifications of the NWP model will be given by cases where the replacement of the initial condition does not help improve the prediction

while the prediction by the other NWP system is accurate.

Black: Observed trackBlue: JMA’s model + JMA’s initial conditionGreen: ECMWF’s model + ECMWF’s initial conditionRed: JMA’s model + ECMWF initial condition

Results

Experiment period: 2009.07.22 to 2009.11.30 (4 months) Verified TCs: 16 TCs in the west Pac. over the 4 months

Forecast time (hours)

Posi

tion

erro

r (km

)

Num

ber o

f sam

ples

JM-JI: JMA’s model + JMA’s initial condition

EM-EI: EC’s model + EC’s initial condition

JM-EI:JMA’s model + EC’s initial condition

The difference between JM-JI and EM-EI is similar to that seen in the verification for TCs over 3 years (see figure on the right), that is, EM-EI is better than JM-JI by a lead time of one day.

Comparison with verification results over 3 years

Results

Replacing the original initial condition of JMA/GSM with the ECMWF analysis reduces the TC track prediction errors by 5 %, 11 %, 9 %, 11 % and 15 % at 1 to 5 days, respectively, and explains 20 %, 29 %, 29 %, 38 % and 68 % of the difference in the errors between JMA and ECMWF at 1 to 5 days, respectively.

Forecast time (hours)

Posi

tion

erro

r (km

)

Num

ber o

f sam

ples

Individual cases

There are prediction cases where the replacement of the initial condition significantly improves the track prediction.

Typhoon Dujuan initiated at 12 UTC 5th Sep. 2009

Typhoon Lupit initiated at 12 UTC 21st Oct. 2009

Black: Observed trackBlue: JMA’s model + JMA’s initial condition (JM-JI)Green: ECMWF’s model + ECMWF’s initial condition (EM-EI)Red: JMA’s model + ECMWF initial condition (JM-EI)Orange: JMA’s model + low wavenumber component (≤ T42) of ECMWF initial condition + high wavenumber component (≥ T42) of JMA initial condition (JM-EI2)

Error reduction at 3 day: 595 km to 122 km Error reduction at 3 day:

720 km to 280 km

Ensemble prediction for those cases

Typhoon Dujuan initiated at 12 UTC 5th Sep. 2009

Typhoon Lupit initiated at 12 UTC 21st Oct. 2009

Ensemble track prediction by the JMA Typhoon EPS (TEPS) that deals with initial condition uncertainties based on singular vectors.

TEPS captures the scenario of the observed track. It implies that TEPS is successful in expressing the uncertainties of TC

track predictions when they are sensitive to initial conditions.

Another individual cases

Typhoon Morakot initiated at 12 UTC 4th Aug. 2009

Typhoon Parma initiated at 12 UTC 30th Sep. 2009

There are prediction cases where the replacement of the initial condition does not help improve the prediction while the ECMWF’s prediction is accurate.

Black: Observed trackBlue: JMA’s model + JMA’s initial condition (JM-JI)Green: ECMWF’s model + ECMWF’s initial condition (EM-EI)Red: JMA’s model + ECMWF initial condition (JM-EI)

Ensemble prediction for those cases

TEPS cannot capture the observed track, either, implying need for modifications of JMA/GSM and/or dealing with model uncertainties in TEPS.

Typhoon Morakot initiated at 12 UTC 4th Aug. 2009

Typhoon Parma initiated at 12 UTC 30th Sep. 2009

Northward bias –Typhoon Conson (2010) -

Northward bias is not a problem only in JMA but also in other major NWP centers. It is noteworthy that such northward bias tends to appear in the east of Philippines.

JMA

CMC

ECMWF

UKMO

Northward bias –Typhoon Nanmadol (2011) -

JMA ECMWF

It would be of great importance to identify the cause of the bias and modify the NWP systems including EPSs for better deterministic and probabilistic forecasts.

CMC NCEP

Summary

1. The representation of the steering flow formed by the synoptic environment around the TCs is important for accurate TC track predictions as demonstrated by various previous studies (e.g. Chan and Gray 1982).

2. Ensemble prediction, which deals with initial condition uncertainties, is successful in expressing the uncertainties of TC track predictions when they are sensitive to initial conditions.

3. There are systematic errors in NWP models. The northward bias that tends to appear to the east of the Philippines would be common systematic errors among many NWP models.