No. 48

Spring 2017
Contents

Page

Launch of JM A’s Global Ensemble Prediction System for one-month prediction

1

El Niño Outlook (April ― October 2017)

3

JM A’s Seasonal Numerical Ensemble Prediction for Boreal Summer 2017

5

Warm Season Outlook for Summer 2017 in Japan

7

Summary of the 2016/2017 Asian Winter Monsoon

8

TCC contributions to Regional Climate Outlook Forums in Asia

14

TCC Experts Visit Indonesia

15

Launch of JMA’s Global Ensemble Prediction Systemfor one-month prediction
JMA replaced the previous One-month EPS (Ensemble
Prediction System) with the Global EPS (GEPS) on Thursday
23 March 2017 to produce prediction maps and gridded datasets for one-month predictions on the TCC website. The
GEPS is an integrated solution supporting JMA’s issuanceof typhoon information, one-week forecasts and one-monthforecasts. Major changes from the previous One-month EPS
and related performance are described below.

TL319 (55 km) to TL479 (40 km) from the initialtime up to 18 days ahead, whereas the resolution
from the 18th day on is the same as that of the previous system (i.e., TL319 (55 km)).
» The number of vertical layers has been increased
from 60 to 100, and the pressure of the top level has
been increased from 0.1 to 0.01 hPa.


1. Change in operational configuration of ensemble
members from initial dates
To support the provision of one-month prediction products on the TCC website every Thursday, the GEPS is run
once a week with 50 members composed of 13 members
each integrated from initial fields at 00 and 12 UTC every
Tuesday and Wednesday. Those of the previous
One-month EPS were composed of 25 members each integrated from initial fields at 12 UTC every Tuesday andWednesday. In terms of gridded dataset dissemination forone-month prediction, the 50 members will be composedof a 24-member set (Tuesday) and a 26-member set(Wednesday) as of Thursday 23 March 2017 based on thisoperational configuration change.

» Sea surface temperature perturbation has been introduced for production of boundary conditions.
3. Performance
In advance of the upgrade, a full set of hindcast experiments for the 32-year period from 1981 to 2012 was executed using the new system. Atmospheric initial conditions
for the experiments were taken from the Japanese 55-year
Reanalysis (JRA-55, Kobayashi et al. 2015), which is anadvanced dataset produced by JMA. Verification of thehindcast for the 30-year period from 1981 to 2010 indicates prediction skill enhancement. By way of example,
the forecast mean error of the weak Asian monsoon insummer became smaller than that of the previous
One-month EPS in terms of velocity potential at 200 hPa(Figure 1), and anomaly correlation coefficients of geopotential height at 500 hPa over the Northern Hemisphere forall seasons (Figure 2) show improvement under the new
system.

2. Major updates
Major changes in the new GEPS compared with the previous One-month EPS are as follows:

Atmospheric global circulation model (AGCM)» A low-resolution version of JMA’s Global Spectral
Model (GSM) launched in March 2016 (GSM1603)
is used with additional improvement of physicalprocesses.
» Horizontal resolution has been increased from

TCC News

Ensemble method» A combination of the Local Ensemble Transform
Kalman Filter (LETKF) method and the Singular
Vector (SV) methods has been introduced to produce initial perturbation as an alternative to the
Breeding Growing Mode (BGM) method.

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No. 48 | Spring 2017

(a) Previous One-month EPS(b) Global EPS (GEPS)

Figure 1 Climatological fields of velocity potential at 200 hPa (contours) and related mean error (shading) forsummer with (a) the previous One-month EPS and (b) the Global EPS (GEPS)
The contour interval is 2 × 106 m2/s.
Products for one-month forecasting are available on the
TCC website:
http://ds.data.jma.go.jp/tcc/tcc/products/model/index.html.
(Shiro Ishizaki, Climate Prediction Division)
References:
Kobayashi, S., Y. Ota, Y. Harada, A. Ebita, M. Moriya,
H. Onoda, K. Onogi, H. Kamahori, C. Kobayashi, H.
Endo, K. Miyaoka, and K. Takahashi, 2015: The JRA-55
reanalysis:
Generalspecifications
and
basic
characteristics. J. Meteor. Soc. Japan, 93, 5-48.

Figure 2 Differences in anomaly correlation coefficients for one-month mean geopotential height at
500 hPa
Positive values represent GEPS anomaly correlation
coefficients greater than those of the previous
One-month EPS. Higher values indicate more accurate
forecasts.

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No. 48 | Spring 2017

El Niño Outlook (May 2017 – November 2017)
There is a 50% probability that an El Niño event will
emerge by the beginning of boreal autumn. (Article based on
the El Niño outlook issued on 12 May 2017.)

the lower troposphere (trade winds) were near normal overthe central part. In summary, despite the recent persistenceof above-normal NINO.3 SSTs, no clear signs of El Niño
development were observed in April.
JMA's El Niño prediction model suggests that the
NINO.3 SST will be above or near normal during the prediction period (Figure 6). Based on this prediction and theobservations detailed above, there is a 70% likelihood thatthe five-month running mean NINO.3 SST in April will be+0.5°C or above. However, there is a probability of around
50% that this value will persist in boreal summer and beyond (Figure 7). In conclusion, there is a 50% probability
that an El Niño event will emerge by the beginning of boreal autumn.

El Niño/La Niña
The NINO.3 SST deviation was +0.6°C in April, having
remained at +0.5°C or more since February. SSTs in April
were above normal in much of the equatorial Pacific except near the date line, where below-normal values wereobserved (Figures 3 and 5(a)). Subsurface temperatures
were above normal in the western equatorial Pacific andbelow normal in the central part (Figures 4 and 5(b)). Atmospheric convective activity was below normal near thedate line over the equatorial Pacific, and easterly winds in

(a)

(a)

(b)

(b)

Figure 4 Monthly mean depth-longitude cross sectionsof (a) temperatures and (b) temperature anomalies inthe equatorial Indian and Pacific Ocean areas for April
2017
The contour intervals are 1˚C in (a) and 0.5˚C in (b). Thebase period for the normal is 1981 – 2010.

Figure 3 Monthly mean (a) sea surface temperatures(SSTs) and (b) SST anomalies in the Indian and Pacific
Ocean areas for April 2017
The contour intervals are 1˚C in (a) and 0.5˚C in (b). Thebase period for the normal is 1981 – 2010.

(a)

(b)

Figure 5 Time-longitude cross sections of (a) SST and (b) ocean heat content (OHC) anomalies along theequator in the Indian and Pacific Ocean areas
OHCs are defined here as vertical averaged temperatures in the top 300 m. The base period for the normal is 1981
– 2010.

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No. 48 | Spring 2017

Figure 6 Outlook of NINO.3 SST deviation produced by the El Niño prediction modelThis figure shows a time series of monthly NINO.3 SST deviations. The thick line with closed circles showsobserved SST deviations, and the boxes show the values produced for up to six months ahead by the El Niño
prediction model. Each box denotes the range into which the SST deviation is expected to fall with a probability of 70%.

Figure 7 ENSO forecast probabilities based on the El Niño prediction model
Red, yellow and blue bars indicate probabilities that the five-month running mean of the NINO.3 SST deviation from the latest sliding 30-year mean will be +0.5°C or above (El Niño), between +0.4 and -0.4°C (ENSO-neutral) and -0.5°C or below (La Niña), respectively. Regular text indicates past months, and bold text
indicates current and future months.
Western Pacific and Indian Ocean
The area-averaged SST in the tropical western Pacific(NINO.WEST) region was near normal in April. It is likelythat the values will remain near normal until boreal summer.
The area-averaged SST in the tropical Indian Ocean(IOBW) region was below normal in April. It is likely thatthe values will gradually approach the normal toward boreal summer.
(Ichiro Ishikawa, Climate Prediction Division)* The SST normal for the NINO.3 region (5°S – 5°N,
150°W – 90°W) is defined as a monthly average overthe latest sliding 30-year period (1986-2015 for thisyear).
* The SST normals for the NINO.WEST region (Eq. –15°N, 130°E – 150°E) and the IOBW region (20°S –20°N, 40°E – 100°E) are defined as linear extrapolations
with respect to the latest sliding 30-year period, in orderto remove the effects of significant long-term warming
trends observed in these regions.

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No. 48 | Spring 2017

JMA’s Seasonal Numerical Ensemble Prediction for Boreal Summer 2017
Based on JMA’s seasonal ensemble prediction system, sea
surface temperature (SST) anomalies are predicted to be
above normal in the equatorial Pacific during this boreal
summer, suggesting El Niño-like conditions. Active convection is predicted over the sea east of New Guinea, while inactive convection is predicted over the western Indian Ocean.
Precipitation is predicted to be above normal over and aroundthe Indochina Peninsula and the Philippines, reflecting anactive Southeast Asian Monsoon.

Figure 9 (b) shows predicted velocity potential (contours)
and related anomalies (shading) at the upper troposphere(200 hPa) for JJA. Negative (i.e., divergent) anomalies are
predicted over the sea east of New Guinea in association
with heavy precipitation. Conversely, positive (i.e., convergent) anomalies are predicted over the western Indian
Ocean.

(a)1.

Introduction
This article outlines JMA’s dynamical seasonal ensemble
prediction for boreal summer 2017 (June – August, referred
to as JJA), which was used as a basis for JMA’s operational
warm-season outlook issued on 24 May 2017. The outlook
is based on the seasonal ensemble prediction system of the
Coupled Atmosphere-ocean General Circulation Model(CGCM). See the column below for system details.
Section 2 outlines global SST anomaly predictions, andSection 3 describes the associated circulation field predictions for the tropics and sub-tropics. Finally, the circulation
fields predicted for the mid- and high latitudes of theNorthern Hemisphere are discussed in Section 4.

(b)

2.

SST anomalies (Figure 8)
Figure 8 shows predicted SSTs (contours) and related
anomalies (shading) for JJA. Above-normal anomalies are
predicted in the equatorial Pacific, suggesting El Niño-like
conditions. Conversely, below-normal anomalies are predicted in some parts of the southern Indian Ocean and the
Maritime Continent.

(c)

3. Prediction for the tropics and sub-tropics (Figure 9)
Figure 9 (a) shows predicted precipitation (contours) andrelated anomalies (shading) for JJA. Large above-normal
anomalies are predicted over the sea east of New Guinea inassociation with high SSTs exceeding 30°C. Above-normal
anomalies are also predicted over and around the Indochina
Peninsula and the Philippines, reflecting an active Southeast
Asian Monsoon. Meanwhile, below-normal anomalies are
predicted over the southeastern Indian Ocean in association
with low SSTs.

(d)

Figure 9 Predicted atmospheric fields from 60°N – 60°S
for June–August 2017 (ensemble mean of 51 members)(a) Precipitation (contours) and anomaly (shading). The
contour interval is 2 mm/day.
(b) Velocity potential at 200 hPa (contours) and anomaly(shading). The contour interval is 2 × 106 m2/s.
(c) Stream function at 200 hPa (contours) and anomaly(shading). The contour interval is 16 × 106 m2/s.
(d) Stream function at 850 hPa (contours) and anomaly(shading). The contour interval is 5 × 106 m2/s.

Figure 8 Predicted SSTs (contours) and SST anomalies(shading) for June–August 2017 (ensemble mean of 51
members)

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No. 48 | Spring 2017

(a)Figure 9 (c) shows predicted stream functions (contours)
and related anomalies (shading) at the upper troposphere(200 hPa) for JJA. Positive (i.e., anticyclonic) anomalies are
predicted over the northwestern Pacific in association withactive convection over the sea east of New Guinea. Suchanomalies are also predicted over China, the Indochina
Peninsula and the Philippines in association with an active
Southeast Asian Monsoon, suggesting a more dominant
Tibetan High than normal over these regions. Conversely,
negative (i.e., cyclonic) anomalies are predicted over West
Asia in association with inactive convection in the western
Indian Ocean.
Figure 9 (d) shows predicted stream functions (contours)
and related anomalies (shading) at the lower troposphere(850 hPa) for JJA. Negative (i.e., cyclonic) anomalies are
predicted over the sea north of the Philippines in association
with an active Southeast Asian Monsoon. Conversely,
equatorial symmetric anticyclonic anomalies are predicted
over the western Indian Ocean in association with inactive
convection.

(b)

4. Prediction for the mid- and high- latitudes of theNorthern Hemisphere
Figure 10 (a) shows predicted geopotential heights (contours) and related anomalies (shading) at 500 hPa for JJA.
Positive anomalies are predicted over most of the Northern
Hemisphere, reflecting high thickness caused by El Niño-like conditions and global warming trends.
Figure 10 (b) shows predicted sea level pressure (contours) and related anomalies (shading) for JJA. Positive
anomalies are predicted over the main islands of Japan,
suggesting a more dominant North Pacific High than normal. Conversely, negative anomalies are predicted over thesea north of the Philippines, suggesting active tropical cyclones in this region.

Figures 10 Predicted atmospheric fields from 20°N –90°N for June–August 2017 (ensemble mean of 51
members)(a) Geopotential height at 500hPa (contours) and anomaly(shading). The contour interval is 60 m.
(b) Sea level pressure (contours) and anomaly (shading).
The contour interval is 4hPa.

(Takashi Yamada, Climate Prediction Division)

JMA’s Seasonal Ensemble Prediction System
JMA operates a seasonal Ensemble Prediction System (EPS) using the Coupled atmosphere-ocean General Circulation
Model (CGCM) to make seasonal predictions beyond a one-month time range. The EPS produces perturbed initial conditions by means of a combination of the initial perturbation method and the lagged average forecasting (LAF) method.
The prediction is made using 51 members from the latest four initial dates (13 members are run every 5 days). Details of
the prediction system and verification maps based on 30-year hindcast experiments (1981–2010) are available at
http://ds.data.jma.go.jp/tcc/tcc/products/model/.

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No. 48 | Spring 2017

Warm Season Outlook for Summer 2017 in JapanJMA issued warm season outlook for the coming summer(June – August) over Japan in February and updated it on 24
May. This article outlines the update.

Mean Temperature

Tercile Probability (%)

Summer (June – August)

Below : Normal : Above

Precipitation

Tercile Probability (%)

1. Outlook summary (Figure 11) Seasonal mean temperatures are expected to be above
normal all over Japan.
 Seasonal precipitation amounts are expected to be
above normal on the Pacific side of western Japan andnear normal in other regions of the country.
2. Outlook backgroundFigure 12 summarizes expected large-scale oceanic/atmospheric characteristics for the coming summer. The
grounds for the outlook are given below.

(1) Outlook on oceanic conditions

Sea surface temperatures (SSTs) are expected to behigher than normal in the western tropical Pacific, especially east of New Guinea.
SST anomalies in the tropical Indian Ocean are expected to be relatively low.

Summer (June – August)

Below : Normal : Above(2) Outlook on atmospheric circulation fields










In response to the above SST anomaly patterns, convection is expected to be more active in the western
tropical Pacific with southerly shifting compared to theclimatology and less active in the tropical Indian
Ocean.
In association with inactive convection in the tropicalIndian Ocean, the Tibetan High is expected to be
weaker than normal, and its northeastward expansion(i.e., that extending into Japan) is also expected to be
weak. Accordingly, the subtropical jet stream, whichflows along the northern edge of the Tibetan High, is
expected to shift southward of its normal position.
In the pre-midsummer Baiu season, the north PacificHigh is expected to expand westward (i.e., to bestronger than normal over the sea south of Japan’s
main island) due to active and southerly shifted convection in the western tropical Pacific. Accordingly,
the Baiu front will be enhanced due to moist southerly
flows along the edge of the High, which could bringwet conditions to the Pacific side of western Japan andelsewhere.
In midsummer, sea level pressure anomalies are expected to be negative south of Japan in association
with active convection near the Philippines. Accordingly, the North Pacific High is expected to be stronger
than normal near the country’s main island (a phenomenon known as the Pacific-Japan (PJ) teleconnection pattern).
Overall temperatures in the troposphere are expected
to be higher than normal in association with the prevailing long-term trend. These tendencies are likely toincrease the chances of above-normal temperatures.
(Masayuki Hirai, Climate Prediction Division)

TCC News

Figure 11: Outlook for summer 2017 temperature (top)and precipitation (bottom) probability in Japan
Higher overall temperatures in the troposphere
180°

Subtropical Jet Stream

Climatological location• Shift southward from the EurasianEurasian Continent to areas near Japan

Climatological location
Climatological location

North Pacific High

Tibetan High• Weak northward expansion• Strong westward
expansion• Strong near the mainland
in midsummer
Convection• Active with southward shift
in the first-half of summer• Active near the Philippines in
midsummer

EQ.
More Inactive
convection

Colder SSTs

Warmer SSTs

Figure 12: Conceptual diagram showing expectedlarge-scale ocean/atmosphere characteristics for summer 20177

No. 48 | Spring 2017

Summary of the 2016/2017 Asian Winter Monsoon
This report summarizes the characteristics of the surface
climate and atmospheric/oceanographic considerations
related to the Asian winter monsoon for 2016/2017.

Figure 15 shows extreme climate events occurring between December 2016 and February 2017. In December,extremely high temperatures were seen in many parts ofMongolia, China, India, Sri Lanka and Pakistan, and extremely high precipitation amounts were observed aroundthe Korean Peninsula. In January, extremely high temperatures were seen over southern China and northern Myanmar, and extremely high precipitation amounts wereobserved from the southern Indochina Peninsula to northern Sumatra Island. In southern Thailand, more than 90
casualties due to heavy rain were reported in January(European Commission). Precipitation for January at
Songkhla in southern Thailand was 682 mm (776% of the1981 – 2010 normal) according to CLIMAT reports. In
February, extremely high temperatures were seen from thesouthern part of Eastern Siberia to the southeastern part ofCentral Siberia.
Although most of the season was warmer than normal,
cold-air outbreaks were recorded over many parts of East
Asia in mid-January and early February (Figure 16),
bringing heavy snowfall to the Sea of Japan side of western Japan.

Note: The Japanese 55-year Reanalysis (JRA-55; Kobayashi etal. 2015) atmospheric circulation data and COBE-SST (Ishii etal. 2005) sea surface temperature (SST) data were used for thisinvestigation. The outgoing longwave radiation (OLR) data referenced to infer tropical convective activity were originally provided by NOAA. The base period for the normal is 1981 – 2010.
The term “anomaly” as used in this report refers to deviationfrom the normal.
1. Surface climate conditions
Most Asian countries experienced warmer-than-normal
conditions throughout boreal winter 2016/2017 (Figure13). Three-month mean temperatures for December 2016
– February 2017 were ranked as very warm across large
areas of China, Southeast Asia and western India. Precipitation amounts during the season were above normal innortheastern China, Central Asia, Southeast Asia and Micronesia, and below normal in southwestern China andnorthern India (Figure 14).
(a) Dec. 2016 - Feb. 2017

Very warm
Very cold(b) Dec. 2016

Warm
Cold

Normal (+)
Normal (-)(d) Feb. 2017(c) Jan. 2017

Figure 13 (a) Three-month mean temperature anomalies for December 2016 – February 2017, and monthly
mean temperature anomalies for (b) December 2016, (c) January 2017 and (d) February 2017
Categories are defined by the three-month/monthly mean temperature anomaly against the normal divided by its
standard deviation and averaged in 5° × 5° grid boxes. The thresholds of each category are -1.28, -0.44, 0, +0.44
and +1.28. Standard deviations were calculated from 1981 - 2010 statistics. Areas over land without graphicalmarks are those where observation data are insufficient or where normal data are unavailable.

Dry
Wet

TCC News

Normal (-)
Normal (+)

Figure 14 Three-month total precipitation ratio for December 2016 – February 2017
Categories are defined by the three-month mean precipitation
ratio against the normal and averaged in 5° × 5° grid boxes. The
thresholds of each category are 70, 100 and 120%. Areas overland without graphical marks are those where observation data
are insufficient or where normal data are unavailable.

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No. 48 | Spring 2017

(a) Dec. 2016(c) Feb. 2017(b) Jan. 2017

Figure 15 Extreme climate events for (a) December 2016, (b) January 2017 and (c) February 2017
ΔT, SD and Rd indicate temperature anomaly, standard deviation and quintile, respectively.

(a) 10-16 Jan.

(b) 7-13 Feb.

Figure 16 Seven-day surface temperature anomalies for (a) 10 – 16 January and (b) 7 – 13 February 2017.
Both are based on SYNOP observation data.

2. Characteristic atmospheric circulation and oceanographic conditions

In the upper troposphere, clear large-scale divergent
anomalies were seen over Southeast Asia in association
with enhanced convective activity, and convergent anomalies were observed over the Indian Ocean and the Pacific(Figure 19 (a)). In the stream function field (Figure 19(b)), anticyclonic circulation anomalies were centeredover southeastern China.
In the lower troposphere, a pair of cyclonic circulation
anomalies was observed along the equator over the areafrom the eastern Indian Ocean to the Maritime Continent(Figure 19 (c)). In early January, a cyclonic circulation
system with enhanced convection brought heavy rain tosouthern Thailand (Figure 20).
An active convection phase of the Madden-Julian Oscillation (MJO) propagated eastward globally from thelatter half of January to February (Figure 21 (a)). Southern
Oscillation Index values remained near normal during
winter.

2.1 Conditions in the tropics
In winter 2016/2017, sea surface temperatures (SSTs)
along the equator were above normal in the western Pacific and below normal in the central – eastern Pacific(Figure 17). SSTs over the South China Sea to the seaseast of the Philippines were higher than normal.
Convective activity inferred from outgoing longwave
radiation (OLR) during the season was enhanced inSoutheast Asia and suppressed over the Indian Ocean andthe equatorial Pacific (Figure 18 (a)). In Southeast Asia,
where precipitation during this winter was generally categorized as above normal (Figure 14), enhanced convection
remained throughout the season, especially over the Indochina and Malay peninsulas in December (Figure 18(b)) and January (Figure 18 (c)).

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No. 48 | Spring 2017

Figure 17 Three-month mean sea surface temperature (SST) anomalies for December 2016 to February
2017
The contour interval is 0.5˚C.
(a) DJF 2016/2017(c) Jan. 2017(b) Dec. 2016(d) Feb. 2017

Figure 18 Outgoing longwave radiation (OLR) anomalies (a) averaged over the three months from December 2016 to February 2017, and for (b) December 2016, (c) January 2017 and (d) February 2017.
Blue and red shading indicates areas of enhanced and suppressed convective activity, respectively.

(a) Velocity Potential at 200 hPa(b) Stream Function at 200 hPa(c) Stream Function at 850 hPa

TCC News

Figure 19 Three-month mean (a) 200-hPa velocity
potential, (b) 200-hPa stream function, and (c)850-hPa stream function for December 2016 to
February 2017 (unit: 106 m2/s)(a) The contours indicate velocity potential at intervalsof 2 × 106 m2/s, and the shading shows velocity potential anomalies. D and C indicate the bottom and thepeak of velocity potential, corresponding to the centersof large-scale divergence and convergence, respectively. (b, c) The contours indicate stream function at intervals of (b) 10 and (c) 2.5 × 10 6 m2/s, and the shadingshows stream function anomalies. H and L denote thecenters of anticyclonic and cyclonic circulations, respectively.

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No. 48 | Spring 2017

(a) 850-hPa Stream Function and OLR
for 2 -8 Jan.

(b) Anomaly

Figure 20 (a) Seven-day mean 850-hPa stream function (contours) and outgoing longwave radiation (OLR;
shading) for 2 – 8 January 2017, and (b) related anomaly
The thin and thick contour intervals are 2.5 and 10 × 10 6 m2/s, respectively. Lower OLR values indicate enhanced
convective activity except in the mid- and high latitudes. The blue and red shading in (b) indicates areas of enhanced and suppressed convective activity, respectively. Arrows show wave activity fluxes indicating Rossby
wave packet propagation.

(b) OLR(a) χ200

Figure 21 Time-longitude cross section of seven-day running mean (a) 200-hPa velocity potential anomalies,and (b) outgoing longwave radiation (OLR) anomalies around the equator (5°S – 5°N) for October 2016 to
March 2017(a) The blue and red shading indicates areas of divergence and convergence anomalies, respectively. (b) The blue
and red shading indicates areas of enhanced and suppressed convective activity, respectively.

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2.2 Conditions in the extra-tropics and the Asian Winter Monsoon
In the 500-hPa height field in winter 2016/2017 (Figure
22 (a)), wave trains were seen along the subpolar jet
stream over the Eurasian Continent with positive anomalies in northern Europe and northern East Asia, and negative anomalies in Western Siberia and over the seas to theeast of Japan. In the sea level pressure field (Figure 23(a)), the Aleutian Low was centered to the west of its
normal position. The Siberian High was generally weaker
than normal, indicating that the Asian Winter Monsoon
was not as active as in normal winters.
Over East Asia, tropospheric temperatures were higher
than normal (Figure 24) due to the northward meanderingof the subpolar jet stream over northern East Asia (Figure
22 (a)) and the subtropical jet stream over southern China(Figure 19 (b)), causing warmer-than-normal winter conditions (Figure 13).
The subpolar jet stream meandered southward overWestern Siberia (Figure 22 (a)), where negative sea levelpressure anomalies were also centered (Figure 23 (a)).
This pattern brought southerly warm winds to Siberia andappears to have prohibited Siberian High development.
(a) DJF 2016/2017(b) Dec. 2016

Figure 25 shows that the intraseasonal variability of theSiberian High generally coincides with that of 500-hPa
height over Western Siberia. This weaker-than-normal
Siberian High was another factor behind the warm conditions seen in East Asia.
In the first half of winter, southerly wind anomalies
prevailed over southern China (Figure 26), where extreme
high temperatures were observed in December and January (Figure 15) in association with cyclonic circulation
anomalies around Southeast Asia and anticyclonic circulation anomalies to the east of Japan. Northerly cold air
flowed into the region less frequently than in normal winters, which contributed to the extreme high temperatures
observed over southern China.
As mentioned above, temperatures in mid-January andearly February over many parts of East Asia dropped significantly (Figure 16), and heavy snowfall was observedin Japan. During these periods, blocking highs developedaround the Bering Sea and migrated westward to Eastern
Siberia, and troughs deepened to the south of these highs(Figures 27 (a), (d)). In the sea level pressure fields (Figures 27 (b), (e)), the Siberian High extended to the eastern
coast of the Eurasian Continent and the Aleutian Low also
intensified, bringing strong cold-air flow into East Asia
(Figures 27 (c), (f)).
(Hiroshi Ohno, Climate Prediction Division)(c) Jan. 2017

TCC News(d) Feb. 2017

Figure 22 500-hPa height (a) averaged over the threemonths from December 2016 to February 2017, for (b)December 2016, (c) January 2017, and (d) February
2017
The contours indicate 500-hPa height at intervals of 60 m,
and the shading denotes anomalies. H and L indicate thepeak and bottom of 500-hPa height, respectively, and +(plus) and – (minus) show the peak and bottom of anomalies, respectively.

(a) DJF 2016/2017(b) Dec. 2016(c) Jan. 2017(d) Feb. 2017

12

Figure 23 Sea level pressure (a) averaged over
the three months from December 2016 to February 2017, for (b) December 2016, (c) January
2017 and (d) February 2017
The contours indicate sea level pressure at intervalsof 4 hPa, and the shading shows related anomalies.
H and L indicate the centers of high and low pressure systems, respectively, and + (plus) and – (minus) show the peak and bottom of sea level pressureanomalies, respectively.

No. 48 | Spring 2017

(m)

(hPa)

SLP

Z500

Figure 25 Intraseasonal variation of area-averaged sea level pressure anomalies aroundthe center of the Siberian High (40 – 60°N, 80 –120°E; black; left axis) and 500-hPa heightanomalies around Western Siberia (50 – 80°N,
50 – 90°E; red; right axis) from 16 November
2016 to 15 March 2017
Lines indicate five-day running means.

(m)Figure 24 Three-month mean anomalies of 300 –
850-hPa height difference for December 2016 to
February 2017
Positive values indicate higher-than-normal tropospheric temperatures.

Figure 26 850-hPa wind anomalies (arrows) and
850-hPa stream function anomalies (shading) for1 December 2016 to 10 January 2017
H and L denote the centers of anticyclonic and cyclonic circulation anomalies, respectively.
(106m2/s)(d) Z500 (7-13 Feb.)(a) Z500 (10-16 Jan.)(m)(e) SLP (7-13 Feb.)(b) SLP (10-16 Jan.)(hPa)(f) T850 (7-13 Feb.)(c) T850 (10-16 Jan.)

Figure 27 ((a), (d)) 500-hPa height, ((b), (e)) sea
level pressure and ((c), (f)) 850-hPa temperaturefor ((a) – (c)) 10 – 16 January and ((d) – (f)) 7 –13 February 2017
Contours indicate seven-day mean values at intervals of ((a), (d)) 60 m, ((b), (e)) 4 hPa and ((c), (f))
3°C, and shading denotes related anomalies.
(˚C)

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No. 48 | Spring 2017

References
Ishii, M., A. Shouji, S. Sugimoto and T. Matsumoto,2005: Objective Analyses of Sea-Surface Temperatureand Marine Meteorological Variables for the 20th Century
using ICOADS and the Kobe Collection. Int. J. Climatol.,
25, 865-879.

Kobayashi, S., Y. Ota, Y. Harada, A. Ebita, M. Moriya,
H. Onoda, K. Onogi, H. Kamahori, C. Kobayashi, H. Endo, K. Miyaoka, and K. Takahashi, 2015: The JRA-55
Reanalysis: General Specifications and Basic Characteristics. J. Meteorol. Soc. Japan, 93, 5 – 48.

TCC contributions to Regional Climate Outlook Forums in Asia
WMO Regional Climate Outlook Forums (RCOFs) bring
together national, regional and international climate experts on an operational basis to produce regional climate
outlooks based on input from participating NMHSs, regional institutions, Regional Climate Centers and global producers of climate predictions. By providing a platform forcountries with similar climatological characteristics todiscuss related matters, these forums ensure consistency
in terms of access to and interpretation of climate information. In spring 2016, TCC experts participated in two
RCOFs in Asia.
FOCRA II
The first RCOF was held at the 13th session of the Forum on Regional Climate Monitoring, Assessment andPrediction for Regional Association II (FOCRA II) in
Beijing, China, from 24 to 26 April. At the event, experts
from 16 countries/territories made presentations in sevensessions featuring talks by invited lecturers and other oralpresentations. TCC attendees gave two presentations outlining the details of the last winter monsoon and the outlook for this summer based on JMA’s seasonal Ensemble
Prediction System. The presentations contributed to discussions on a consensus outlook for the coming summer.

SASCOF-10
The second RCOF was the tenth session of the South
Asian Climate Outlook Forum (SASCOF-10) held in
Thimphu, Bhutan, from 24 to 26 April. This forum has
been held every year since 2010 to provide a consensus
outlook for South Asian monsoon season. The member
countries are Afghanistan, Bangladesh, Bhutan, India,
Maldives, Myanmar, Nepal, Pakistan and Sri Lanka. The
SASCOF consensus outlook is critically important inefforts by these nations to prevent disasters caused byextreme climate events such as heavy rainfall anddroughts. Experts from member countries share outlooks
for their own countries and engage in discussions withexperts from global centers to formulate a consensus
outlook. As a contribution to such activities, TCC dispatches experts annually to provide the latest South Asianmonsoon prediction based on JMA’s seasonal Ensemble
Prediction System (EPS) and to contribute to discussions
on the consensus outlook.
Two TCC experts participated in SASCOF-10 to provide predictions on oceanic and atmospheric conditions,
including probabilistic forecasting of monsoon rainfall inSouth Asia based on JMA’s seasonal EPS, and briefly
outlined the Center’s services. The prediction was consistent with those based on other models and supported adecision on the outlook for the 2017 summer monsoon
season.

Masayuki Hirai presents JMA’s seasonal forecast
at FOCRA II.

Takashi Yamada presents JMA’s seasonal forecast (top)and Yasushi Mochizuki presents TCC’s activities (bottom) at SASCOF-10.

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No. 48 | Spring 2017

Short note from a TCC expert – meeting with Bhutan
NMHS staff
As no TCC staff have yet had an opportunity to visit
Bhutan’s National Center for Hydrology and Meteorology(NCHM), TCC and NCHM representatives met cordiallyon the sidelines of SASCOF-10. The NCHM staff highlighted the current status of their operational climate activities, and possible future collaborative work was discussed. This was fruitful as a TCC focal point in clarifying how NCHM staff provide climate services to national
users and in understanding the current status of such services.

The RCOF provides valuable opportunities for TCC, in
its role as a Regional Climate Center, to interact directlywith users engaging in climate activities with TCC products and to collect related feedback. Such input contributes significantly to the improvement of TCC products
and activities.
TCC sincerely appreciates the contribution of the relevant NCHM representatives to these fruitful discussions.
(FOCRA II: Masayuki Hirai and Shingo Ito,
SASCOF-10: Takashi Yamada and Yasushi Mochizuki
Tokyo Climate Center)

TCC Experts Visit Indonesia
TCC arranges expert visits to NMHSs to support capacity building for climate services and facilitate the effective transfer of technical expertise on TCC products andtools.
As part of such efforts, two TCC experts visited theMeteorological, Climatological, and Geophysical Agency
of Indonesia (BMKG) from 21 to 23 March 2017 to holda training seminar on the generation of climate analysis
information with focus on statistical and dynamical relationships between primary modes of global-scale climate
variability and regional/local climates in the target country. The training was also intended to promote the effective use of TCC's Interactive Tool for Analysis of the
Climate System (iTacs). The visit was conducted as follow-up to the 2016 TCC Training Seminar (see TCC
News No. 46 and the TCC website for details), and provided a valuable platform for discussions on future collaboration between BMKG and TCC.
With the attendance of around 20 staff from regional
branches of BMKG and a dozen from its headquarters,
the TCC trainers began with a practice session for basic
iTacs operation. On the second day, presentations were

given on expertise and techniques necessary to identify
the statistical relationship between temperature and precipitation in Indonesia and primary modes of global climate variability, such as El Niño-Southern Oscillation(ENSO) and the Indian Ocean Dipole (IOD) Mode. The
trainers then outlined how to interpret statistical resultsfrom the viewpoint of climatological and meteorologicaldynamics. Using this background expertise and the TCC
analysis tool (available via the TCC website), the attendees worked hard to produce climate analysis information for their regions in Indonesia and gave presentations on their achievements. Another significant outcomeof the seminar was the advanced iTacs operation expertise gained by the attendees.
The visit provided outstanding opportunities for both
TCC and BMKG. The attendees deepened their understanding of primary modes and their expected impacts on
the regional climate of Indonesia, and TCC staff enjoyedfruitful discussions on future collaboration with BMKG.
TCC will continue to arrange expert visits to NMHSs in
Southeast Asia and elsewhere as necessary to assist with
operational climate services.
(Yoshinori Oikawa and Yasushi Mochizuki, Tokyo Climate Center)

You can also find the latest newsletter from Japan International Cooperation Agency (JICA).
JICA’s World (April 2017)https://www.jica.go.jp/english/publications/j-world/c8h0vm0000b2tu4r-att/1704.pdf
JICA’s World is the quarterly magazine published by JICA. It introduces various cooperation projects and partners alongwith the featured theme. The latest issue features “The Gaining Ground: The Bright Future of Asia and the Pacific”.
Tokyo Climate Center (TCC), Japan Meteorological Agency
Address: 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japan
TCC Website: http://ds.data.jma.go.jp/tcc/tcc/index.html

Any comments or inquiry on this newsletter and/or the TCC
website would be much appreciated. Please e-mail to
tcc@met.kishou.go.jp.
(Editors: Kiyotoshi Takahashi, Yasushi Mochizuki
and Atsushi Minami)

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No. 48 | Spring 2017