1. JMA Seasonal Prediction of South Asian Climate for OND 2017
Takuya Komori
Tokyo Climate Center (TCC)
Japan Meteorological Agency (JMA)

2. Contents Outline of JMA Seasonal Ensemble Prediction System
Current oceanic condition
JMA’s seasonal numerical ensemble prediction
Probabilistic Forecast
Summary

3. Contents Outline of JMA Seasonal Ensemble Prediction System
Current oceanic condition
JMA’s seasonal numerical ensemble prediction
Probabilistic Forecast
Summary

4. Specification of Seasonal EPS
Model
JMA/MRI-CGCM2
Resolution
[Atmosphere] H: TL159 (~110 km), V: L60 (up to 0.1hPa)
[Ocean] H:1.0ºlon.,0.3–0.5ºlat. (with Tri-polar grid), V: L52+BBL
Forecast range
7 months
Initial conditions
[Atmosphere] JRA-55 (JMA Climate Data Assimilation System)
[Ocean] MOVE/MRI.COM-G2 (Ocean Data Assimilation)
[Land] JRA-55 land analysis
Boundary conditions
SST: Predicted, Sea ice: Sea-ice model
Ensemble method
Combination of Breeding of Growing Modes (BGM) and
Lagged Average Forecast (LAF)
Ensemble size
51 (13 BGMs & 4 initial days with 5-day LAF)
Freq. of model product creation
Once a month (around 20th of every month)
In this presentation,
Initial month: Sep 2017
Forecast period: OND 2017
Baseline: average

5. Prediction Skill for El Niño forecast
Hindcast experiments for 30 years (1981 – 2010)
NINO.3 150W-90W, 5S-5N

6. Prediction Skill of JMA Seasonal EPS
Bias-corrected Anomaly Correlation for OND (Initial month: September)
Hindcast experiments for 30 years (1981 – 2010)
SST
Precipitation
2m Temperature
Relatively low prediction skill should be considered in South Asia

7. Prediction Skill of JMA Seasonal EPS Area-averaged precipitation for OND (Initial month: September)
Hindcast experiments for 30 years (1981 – 2010)
South Asia
Precipitation Anomaly
[mm/day]
South
Asia
CI2 DL
60E
90E
115E
140E
170E
170W 5N 5S
10N
20N
30N
CI2
r=0.75 DL
r=0.73
South Asia
r=0.30
[mm/day]
forecast
[mm/day]
ANALYSIS
ANALYSIS
ANALYSIS

8. Contents Outline of JMA Seasonal Ensemble Prediction System
Current oceanic condition
JMA’s seasonal numerical ensemble prediction
Probabilistic Forecast
Summary

9. Monthly Mean SST Anomalies (Aug 2017)
Pacific
SSTs are above normal in the western equatorial Pacific, but below normal in the central and eastern equatorial Pacific.
Indian Ocean
SSTs are above normal in the southwestern Indian Ocean, but below normal in the southeastern Indian Ocean. Namely, it’s a positive IOD like distribution.

10. SST Indices -0.2 oC +0.81 oC +0.11 oC El Niño Neutral La Niña NINO.3
SST indices are defined as deviations from the climatological mean based on a sliding 30-year period, removing long-term trend.
August 2017
NINO.3
-0.2 oC
+0.81 oC
NINO.WEST
IOBW
+0.11 oC
2006
2017
El Niño
Neutral
La Niña

11. Contents Outline of JMA Seasonal Ensemble Prediction System
Current oceanic condition
JMA’s seasonal numerical ensemble prediction
Probabilistic Forecast
Summary

12. SST and OHC for ONDJF 2017-2018 Initial date: 8th Sep 2017
Ensemble mean
Time-longitude cross section along the EQ (September-March)
SST anomalies
Ocean Heat Content anomalies
Indian Ocean
Pacific
Atlantic
Indian Ocean
Pacific
Atlantic
[oC]
[oC]
SSTs for ONDJF2017
For subsurface water, a cold Kelvin wave is predicted to move eastward from the boreal autumn to winter. 
It is likely that La Niña like SST conditions will persist from the boreal autumn to winter.
A positive IOD like OHC condition is predicted to end around December in the Indian Ocean.
anomaly
[oC]

13. Predicted area-averaged SSTs for ONDJF 2017 Initial date: 8th Sep 2017
IOBW
NINO.WEST
NINO.3
ONDJF
ONDJF
ONDJF
Red dots indicate observed values, and yellow boxes indicate predictions. Each box denotes the range where the value will be included with the probability of 70%.
IOBW is predicted to be near normal.
NINO.WEST is predicted to be near or above normal.
NINO.3 is predicted to be near or below normal.
Prediction Skill for ONDJF (Anomaly Correlation, hindcast)
IOBW
NINO.WEST
NINO.3
ACC=0.87
ACC=0.70
ACC=0.88

14. Velocity potential at 200hPa
Precipitation and 200hPa Velocity Potential for OND Initial date: 8th Sep 2017
Ensemble mean
Precipitation
Velocity potential at 200hPa D C
Anomaly (shaded)
[mm/day]
[106 m2/s]
Anomaly (shaded)
Positive anomalies (Heavy rainfall) are predicted over the Philippines and South China Seas in association with warm SST conditions.
Negative anomalies (Light rainfall) are predicted over the equatorial central Pacific Ocean in association with La Niña like conditions.
Negative (Divergence) anomalies are predicted over the Philippines in association with the heavy rainfall around the Philippines. Over the western Indian Ocean, the forecast uncertainty is relatively large.
Positive (Convergence) anomalies are predicted over the equatorial Pacific Ocean in association with La Niña like conditions.

15. Precipitation over South Asia for OND 2017 Initial date: 8th Sep 2017
Ensemble mean
Anomaly (shaded)
[mm/day]
Precipitation is predicted to be near or above normal in South Asia.

16. Temperature over South Asia for OND 2017 Initial date: 8th Sep 2017
Ensemble mean
Anomaly (shaded)
[oC]
Temperature is predicted to be slightly above normal in most part of South Asia.

17. Histograms of Area-averaged Precipitation Anomalies for OND 2017 Initial date: 8th Sep 2017
51 ensemble members
RAIN (South Asia)
60E-90E, 10N-30N
RAIN (CI2 Region)
115E-140E, 10N-20N
RAIN (DL)
170E-170W, 5S-5N
Dry
Wet
Dry
Wet
Dry
Wet
Near or above normal
(Large ensemble spread)
Above normal
Below normal
(Small ensemble spread)
La Niña
Prediction Skill (Anomaly Correlation, hindcast)
ACC=0.30
ACC=0.75
ACC=0.73

18. Predicted Dipole Mode Index (DMI) for ONDJF 2017 Initial date: 8th Sep 2017
DMI = SST(50-70E,10S-10N) - SST(90-110E,10S-0)
51 ensemble members
OND
DJF
DMI is predicted to be neutral or slightly positive.
DMI is predicted to be neutral.
Low prediction Skill
Prediction Skill for OND and DJF (Anomaly Correlation, hindcast)
OND
ACC=0.75
DJF
ACC=0.17

19. Contents Outline of JMA Seasonal Ensemble Prediction System
Current oceanic condition
JMA’s seasonal numerical ensemble prediction
Probabilistic Forecast
Summary

20. Probability (%) of Most Likely Category for OND 2017 Initial date: 8th Sep 2017
Temperature
Precipitation
Most likely category for temperature :
above normal in most part of South Asia.
Most likely category for precipitation :
near or above normal in most part of South Asia.
Relatively low prediction skill should be considered.
Model Output Statistics (MOS) technique based on the 30 years hindcast is used.
Masked grids denote insufficient prediction skill (ROC area score < 0.5).

21. EUROSIP Forecast for OND 2017 Initial Month: Sep 2017
baseline
A most likely category of temperature is above normal in South Asia.
La Niña like conditions are predicted.
At last, I would like to introduce the public products of EUROSIP multi-model ensemble seasonal forecast.
These products are made under the leadership of ECMWF in collaboration with some major seasonal prediction centers.
JMA joined a member of EUROSIP public products since March 2017.
As you can see, JMA single model forecast I mentioned are well consistent with EUROSIP multi-model ensemble forecast.
El Niño like conditions, above normal temperature and near normal precipitation are expected.
JMA joined a member of EUROSIP public products since March 2017.
A most likely category of precipitation is near or above normal in South Asia.
Copyright © European Centre for Medium-Range Weather Forecasts
EUROSIP public products are referenceable in the following website.

22. Summary JMA Seasonal Ensemble Prediction System predicts as follows:
(Outlook for Oceanic conditions)
It is likely that La Niña like SST conditions will persist through boreal winter.
It is likely that the Indian Ocean SST (IOBW) will be near normal until boreal winter
(Outlook for Temperature in South Asia)
Above normal in most part of South Asia.
(Outlook for Precipitation in South Asia)
Area-averaged precipitation of South Asia is expected to be near or above normal from October to December 2017.
　More plots are available at:

23. Backup Slides

24. EUROSIP Forecast for OND 2017 Initial Month: Sep 2017
baseline
A most likely category of MSLP is below normal in South Asia.
La Niña like conditions are predicted.
At last, I would like to introduce the public products of EUROSIP multi-model ensemble seasonal forecast.
These products are made under the leadership of ECMWF in collaboration with some major seasonal prediction centers.
JMA joined a member of EUROSIP public products since March 2017.
As you can see, JMA single model forecast I mentioned are well consistent with EUROSIP multi-model ensemble forecast.
El Niño like conditions, above normal temperature and near normal precipitation are expected.
JMA joined a member of EUROSIP public products since March 2017.
A most likely category of SST is near or above normal in South Asia.
Copyright © European Centre for Medium-Range Weather Forecasts
EUROSIP public products are referenceable in the following website.

25. 850hPa wind and SLP for OND 2017 Initial date: 8 Sep 2017
Ensemble mean
850hPa wind anomaly
SLP
Cyclonic circulation anomalies extending over the 10N-20N latitudinal band from Africa to the Philippine Sea are predicted.
Negative anomalies extending over the Arabian Sea, South Asia, the South China Sea and the Sea south of Japan are widely predicted.
変更無しです。
left: 850-hPa stream function (106 m2/s) and wind vector anomalies (m/s); right: sea level pressure (hPa)

26. Prediction Skill for Seasonal forecast
Hindcast experiments for 30 years (1981 – 2010)
2m Temperature
(Northern Hemisphere)
Precipitation
(Tropics)