Winter 2010

No. 19Contents

Improvements in JMA’s Ensemble Prediction System for LongLong-range Forecasting1

Highlights of the Global Climate for 20096

Summary of Japan’s Climate in 20097

TCC Activity Report for 20098

Training Seminar on Climate Analysis using ReRe-analysis Data

9

Improvements in JMA’s Ensemble Prediction System
for Long-range Forecasting
JMA will replace its Ensemble Prediction System (EPS) for
operational long-range forecasting in February 2010. The
main updates are outlined below.
Introduction of a coupled ocean-atmosphere generalcirculation model (CGCM) instead of the atmosphericgeneral circulation model (AGCM) used to date
● Change in ensemble techniques and EPS operation● Provision of new grid point value (GPV) products
The specifications of the current and new EPSs areshown in Table 1(the next page). Forecast performance will
be improved, especially with longer lead times and over thetropical region, in association with these updates. As in thepast, the date of issuance for long-range forecasts is the25th of the month or earlier.
●

1. Change from AGCM to CGCM
The long-range forecasting model will be changed froman AGCM (two-tiered method) to a CGCM (one-tiered
method) (Figure1) and unified with the El Niño prediction
model in February 2010.
.
The CGCM consists of an AGCM and an ocean generalcirculation model (OGCM), and can represent air-sea interactions more appropriately than the AGCM, which has aspectral triangular 95 (TL95) horizontal resolution(equivalent to a Gaussian grid of nearly 180 km) and 40
unevenly spaced hybrid levels in the vertical resolution.
The model top is at the 0.4 hPa level. It is a low-resolution
version of JMA’s operational AGCM for short- and medium-range forecasting. The OGCM is the MeteorologicalResearch Institute Community Ocean Model (MRI.COM).

Figure. 1 Improvement of JMA’s long-range forecast modelTokyo Climate Center1

No. 19 | Winter 2010

Table 1 Specifications of the current and new EPSs for long-range forecasting in JMA

Atmospheric general circulation model (AGCM)
Horizontal resolution
Vertical layers
Ocean general circulation
model (OGCM)
Horizontal resolution
Vertical layers
Initial conditions
Atmosphere
Ocean
Land surface
Sea surface temperature(SST)
Sea ice distribution
CO2 concentration
Perturbation method

Ensemble size
Time integration range

Current system (until Jan. 2010)
New system (from Feb. 2010)
V0703C
JMA/MRI-CGCM
JMA-GSM (based on the JMA/MRI Unified Model)
TL95 (about 1.875º, Gaussian grid 180 km)
40 (model top: 0.4 hPa)
*1
MRI.COM---

1.0 deg in longitude, 0.3 – 1.0 deg in latitude(75ºS – 75ºN)
50
*2

JCDAS
(JMA Climate Data Assimilation System)*3
MOVE/MRI.COM-G--(Ocean Data Assimilation)
Climatology
Two-tiered method; combination of perOne-tiered method with flux adjustment
sisted anomaly and prediction using the El
Niño prediction model
Climatology
Constant
Trend
Singular Vector (SV) method
Combination of Breeding of Growing Modes(BGM) and Lagged Average Forecast (LAF)
methods
51
51 (9 BGM & 5-day LAF)
4 months or more, up to 7 months
7 months
JMA Global Analysis

System details can be found at:*
1 http://ds.data.jma.go.jp/tcc/tcc/products/elnino/jmamri_cgcm_doc.html*
2 http://jra.kishou.go.jp/JRA-25/index_en.html*
3 http://ds.data.jma.go.jp/tcc/tcc/products/elnino/move_mricom_doc.html

1997). Oceanic initial perturbations are estimated throughthe ocean data assimilation system (MOVE/MRI.COM-G)
forced by the surface heat and momentum flux associatedwith the atmospheric initial perturbation fields. The 51member ensemble is generated using prediction resultsfrom six different initial dates (Figure 2).

2. Changes in ensemble technique and EPS operation
The new EPS for long-range forecasting is run every fivedays with nine members, and initial perturbations are estimated for both the atmosphere and the ocean. Atmosphericinitial perturbations are obtained using the Breeding ofGrowing Modes (BGM) method (Toth and Kalnay, 1993,

Current system

51 members

51-member ensemble
from 1 initial date

Target month
Initial dateOldestInitial date

1st month

2nd month…

LatestInitial date

5 days10 days
15 days
20 days
25 daysTokyo Climate Center

New System
51-member ensemble
from different 6 initialdates

9 members
9951 members
9
9
6

2

Figure 2 Schema of aggregation for
the ensemble members in the current
and new systems

No. 19 | Winter 2010

will also be updated. GPV products (shown in Table 2) areavailable only to National Meteorological and Hydrological
Service (NMHS) users through the Global Producing Centre of Long Range Forecasts (GPC) page on the TCC website.

3. Provision of new GPV products
TCC will start providing monthly GPV data from individual ensemble members in addition to ensemble mean
data. The GPV data of hindcast experiments by the CGCM

Table 2 Specifications of GPV products from EPS for long-range forecasting
Parameters
Ensemble mean*1
Individual ensemble members

U200, V200, Z500, U850, V850, T850, mean sea level pressure, precipitation,
2-m temperature, SST
Z100, Z200, U200, V200, T200, Z300, Z500, U500, V500, T500, Z850, U850, V850,
T850, RH850, Q850, mean sea level pressure, precipitation, 2-m temperature, SST

Temporal resolution

1-month mean (ensemble mean & individual ensemble members)
3-month mean (ensemble mean)

Spatial coverage and resolution

Global, 2.5º × 2.5º

Lead time

Between about 0.5 and 5.5 months

Issuance timing

No later than the 25th of each month

Data format

GRIB2*2

Data for calibration

Model normals based on hindcast experiments*1 Including standard deviation with the exception of SST*2 Details can be found at http://www.wmo.ch/pages/prog/www/WMOCodes/GRIB.html

Reanalysis/JMA Climate Data Assimilation System; Onogi
et al., 2007), COBE-SST (Centennial in-situ ObservationBased Estimates of variability of SST and marine meteorological variables; Ishii et al., 2005) and GPCP (Global Precipitation Climatology Project; Adler et al., 2003). The
verification results based on hindcast experiments areshown here.

4. Improvements in forecast performance
Results from hindcast experiments (Table 3) using the
CGCM show that its introduction improves long-range
forecast performance, especially with longer lead times andover the tropical region, compared to the AGCM. The data
used for verification are JRA-25/JCDAS (Japanese 25-year

Table 3 Specifications of hindcast experiments for long-range forecasting

Current system

New system

Model

V0703C (AGCM)

JMA/MRI-CGCM

Target period

All months from 1984 to 2005; 22 years

All months from 1979 to 2008; 30 years

Time integration range

7 months

7 months

Ensemble size (method)

11 (SV)10 (5 BGM & 15-day LAF)
*1

JRA-25 /JCDAS

Atmosphere
Initialconditions

Ocean
Land surface---

MOVE/MRI.COM-G

Climatology

System details can be found at:
1 http://jra.kishou.go.jp/JRA-25/index_en.html*

Tokyo Climate Center3

No. 19 | Winter 2010

Figure 3 shows anomaly correlation coefficients (ACC)of three-month mean SSTs. The CGCM has a high level offorecast skill for tropical SSTs over most of the Indian
Ocean and the western tropical Pacific in addition to the
ENSO-related region. In particular, improvements in forecast skill for SSTs are significant over the northern tropicalIndian Ocean and the western tropical Pacific compared tothat of the AGCM.

month mean stream function at 850 hPa (upper) and geopotential height at 500 hPa (lower) between the CGCM andthe AGCM. The CGCM also improves the forecast skill fortropical circulation. The level of skill for both fields is improved, especially over the western tropical Pacific.
Figure 6 shows a comparison of relative operating characteristics (ROC) areas in tercile (three-class) probability
forecasts (all tercile) for three-month mean surface temperature and precipitation over the tropical region with a
one-month lead time. The CGCM improves the level ofprobabilistic skill for the tercile probability forecasts, especially over the tropical region. Tercile probability forecasts
for three-month mean surface temperature and precipitation
are made available on the TCC website, and are generatedusing the Model Output Statistics (MOS) technique basedon hindcast experiments.

Figure 4 shows a comparison of ACCs for three-monthmean precipitation between the CGCM and the AGCM.
Corresponding to the high forecast skill for tropical SSTs,
the level of skill for tropical precipitation is also improved.
This is partially due to the fact that a realistic relationshipbetween SST and precipitation is reproduced in the CGCM
through its physically reasonable air-sea interaction processes, which were not represented in the AGCM.
Figure 5 shows a comparison of ACCs for the three-(Takayuki Tokuhiro, Climate Prediction Division)

Figure 3 Anomaly correlation coefficients (ACCs) of three-monthmean SSTa) ACCs with a four-month lead time
for Jun. – Aug. in the CGCMb) Time series of ACCs (average for
12 initial months) over the northern
Indian Ocean (left) and the tropicalwestern Pacific (right). Orange bars
represent CGCM ACCs, while blue
ones show those of the AGCM. The
target years used for verification are
1984 – 2005.

Figure 4 ACCs of three-monthmean precipitationa) As per Fig. 3a), but for CGCM
(left) and AGCM (right)b)As per Fig. 3b), but over the Indian
monsoon area (left) and the northwestern Pacific monsoon area (right)

Tokyo Climate Center4

No. 19 | Winter 2010

Figure 5 As per Fig. 4a)but for ACCs of stream function at
the 850-hPa level (upper) and geopotential height at the 500-hPa level(lower)Figure 6 Relative Operating Characteristics (ROC) areas in tercile probability forecasts (all tercile) for three-monthmean surface temperature (left) and precipitation (right) over the tropical region with a one-month lead time.
The red and blue lines represent ROC areas with the CGCM and the AGCM, respectively. A value of 50% in the ROC areais the climatological score. The target years used for verification are 1979 – 2008 for the CGCM and 1984 – 2005 for the
AGCM.

References

Toth, Z. and E. Kalnay, 1993: Ensemble forecasting at NMC: The
Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Jageneration of perturbations. Bull. Amer. Meteor. Soc., 74,
nowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gru2317-2330.
ber, J. Susskind, P. Arkin, E. Nelkin, 2003: The Version 2
Toth, Z. and E. Kalnay, 1997: Ensemble forecasting at NCEP and
Global Precipitation Climatology Project (GPCP) Monthly
the breeding method. Mon. Wea. Rev., 125, 3297-3319.
Precipitation Analysis (1979-Present). J. Hydrometeor., 4,
Usui, N., S. Ishizaki, Y. Fujii, H. Tsujino, T. Yasuda and M.
1147-1167.
Kamachi, 2006: Meteorological Research Institute Multivariate
Ocean Variational Estimation (MOVE) System: Some early
Ishii, M., A. Shouji, S. Sugimoto and T. Matsumoto, 2005: Objecresults. Adv. Space Res., 37, 806-822.
tive Analyses of Sea-Surface Temperature and Marine Meteorological Variables for the 20th Century using ICOADS and the
Kobe Collection. Int. J. Climatol., 25, 865-879.
Onogi, K., J. Tsutsui, H. Koide, M. Sakamoto, S. Kobayashi, H.
Hatsushika, T. Matsumoto, N. Yamazaki, H. Kamahori, K.
Takahashi, S. Kadokura, K. Wada, K. Kato, R. Oyama, T. Ose,N. Mannoji and R. Taira, 2007: The JRA-25 Reanalysis. J.
Meteor. Soc. Japan, 85, 369-432.

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No. 19 | Winter 2010

Highlight of the Global Climate for 2009
Annual mean temperatures were above normal in mostareas of the world except in central Siberia and from Canada to the USA (Figure 7). Extremely high temperatures
were frequently observed around low latitudes from 30°S to
30°N, while extremely low temperatures were observed
around the central USA in October and December, around
China in November and from western Siberia to eastern
China in December.
Annual precipitation amounts were above normal ineastern Siberia, from the Philippines to western Indonesia
and from Europe to northern Africa, while they were below
normal on the Arabian Peninsula, in southern South America and from central to southern Australia (Figure 8). Extremely heavy precipitation amounts were frequently observed in northern Europe, while extremely light precipitation amounts were observed frequently in northern Argentina.
Major extreme climatic events and weather-related disasters in 2009 are as listed below (see also Figure 9):(1) Low temperatures from western Siberia to eastern China(Dec.)(2) Low temperatures around China (Nov.)(3) Heavy precipitation from eastern Mongolia to northern

Japan (Dec.)(4) High temperatures from China to the Middle East (Feb. –Oct.)(5) Typhoons and torrential rains in the Philippines (May,
Sep. – Oct.)(6) High temperatures from Micronesia to Indonesia (Apr. –Dec.)(7) Torrential rains in southern India (Sep. – Oct.)(8) Heavy precipitation in northern Europe (Jul.)(9) Heavy precipitation from the Aral Sea to northern Africa(Sep.)(10) Torrential rains in southern Africa (Mar.)(11) High temperatures around Madagascar (Jan. – Feb.,
May – Dec.)(12) Low temperatures around the central USA (Oct., Dec.)(13) High temperatures from Central America to northern
South America (May – Dec.)(14) Light precipitation around northern Argentina (Jan.,
Mar. – Apr.)(15) Heat waves and bushfires in southeastern Australia (Jan.
– Feb.)

Figure 7 Annual mean temperature anomalies for 2009
Categories are defined by the annual mean temperature anomaly
against the normal divided by its standard deviation and averaged
in 5° × 5° grid boxes. The thresholds of the categories are -1.28σ,-0.44σ, 0, +0.44σ and +1.28σ, as shown in the legend. The normal values and standard deviations are calculated from 1971 –2000 statistics. Land areas without marks represent regions whereobservation data are insufficient or normal data are unavailable.

Figure 8 Annual total precipitation amount ratios for 2009
Categories are defined by the annual precipitation ratio to thenormal averaged in 5° × 5° grid boxes. The thresholds of the categories are 70%, 100% and 120%, as shown in the legend. Land
areas without marks represent regions where observation data are
insufficient or normal data are unavailable.

(8)(8) WetWet Jul.
Jul.

(1)(1) Cold
Cold Dec.
Dec.

(Takafumi Umeda, Climate Prediction Division)(2)(2) Cold
Cold Nov.
Nov.

(4)(4) Warm
Warm Feb.
Feb. –– Oct.
Oct.

(3)
(3) WetWet Dec.
Dec.
(12)(12) Cold
Cold Oct.,
Oct., Dec.
Dec.
(13)
(13) Warm
Warm
May
May –– Dec.
Dec.

(5)
(5) Typhoons,Typhoons, torrential
torrential rains
rains
May,
May, Sep.
Sep. –– Oct.
Oct.
(9)(9) WetWet Sep.
Sep.

(6)(6) Warm
Warm Apr.
Apr. –– Dec.
Dec.
(7)(7) Torrential
Torrential rains
rains
Sep.
Sep. –– Oct.
Oct.

(10)
(10) Torrential
Torrential rains
rains
Mar.
Mar.

(15)
(15) Heat
Heat waves,waves, bushfires
bushfiresJan.
Jan. –– Feb.
Feb.

(11)
(11) Warm
Warm
Jan.
Jan. –– Feb.,
Feb., MayMay –– Dec.
Dec.

(14)
(14) Dry
Dry Jan.,Jan., Mar.
Mar. –– Apr.
Apr.

Figure 9 Extreme events and weather-related disasters in 2009
Major extreme climatic events and weather-related disasters occurring during the year are indicated schematically.

Tokyo Climate Center

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No. 1９ | Winter 2009

Summary of Japan’s Climate in 2009
● Above-normal annual mean temperature nationwide● Light snowfall on the Sea of Japan side
● Light precipitation in western Japan and on the Sea of Japan side of eastern Japan from April to June
● Repeated and localized heavy rainfall in July and August● Short sunshine duration in northern, eastern and westernJapan in July and August● Below-normal incidences of typhoon formation, approachand landfall in Japan(1) Annual temperature, precipitation and sunshine
duration (Figure 10)
The average surface temperature over Japan (averaged
over 17 observatories confirmed as being relatively unaffected by urbanization) in 2009 was 0.56°C above normal(based on the 1971 – 2000 average), and was the seventh
highest since 1898. Area-averaged annual mean temperature anomalies were +0.6°C in northern Japan, +0.7°C ineastern Japan, +0.6°C in western Japan and +0.5°C in Okinawa/Amami. Annual precipitation amounts were significantly above normal on the Pacific side of northern Japan,
while they were below normal on the Pacific side of western Japan and in Okinawa/Amami and near normal in otherareas. Annual sunshine durations were below normal innorthern and eastern Japan and on the Sea of Japan side ofwestern Japan. Meanwhile, they were above normal in Okinawa/Amami and near normal on the Pacific side of western Japan.
(2) Seasonal climate features (Figure 11)
As the winter monsoon was much weaker than usual,seasonal mean temperature was above normal nationwide.
In particular, they were significantly high in northern andeastern Japan and in Okinawa/Amami. Snowfall amounts
were also significantly below normal on the Sea of Japanside. Cyclones periodically passed near mainland Japan,
causing above-normal precipitation amounts on the Pacificside. Anticyclones covered the area around Okinawa/
Amami, where seasonal sunshine durations and precipitation amounts were significantly above and below normal,(Noriaki Watanabe, Climate Prediction Division)

Figure 11 Time series of five-day running mean temperature
anomalies for subdivisions
The normal is the 1971 – 2000 average.

Figure 10 Annual climate anomalies/ratios over Japan in
2009

Tokyo Climate Center

respectively.
In spring, seasonal mean temperatures were above normal in northern, eastern and western Japan. In the latter,seasonal precipitation amounts and sunshine durations weresignificantly below and above normal, respectively, due tothe limited influence of cyclones and fronts. In Okinawa/
Amami, cloudy or rainy weather was dominant in Marchand April, but sunny weather was dominant in May.
Cloudy or rainy weather was dominant in mainland Japan during the summer. As a result, seasonal sunshine durations were below normal over northern, eastern and westernJapan, while seasonal precipitation amounts were above
normal in northern Japan and on the Sea of Japan side ofwestern Japan. In the second half of July and the first halfof August, cyclones, fronts and typhoons brought localized
heavy rain to many parts of Japan. Seasonal mean temperatures were above normal in Okinawa/Amami due to hot
weather dominant in July and August.
In autumn, seasonal mean temperatures were near normal in northern and eastern Japan, and temperatures varied
widely. In Okinawa/Amami, seasonal mean temperatures
were significantly above normal, and particularly hot
weather was dominant in the first half of autumn. In September, monthly precipitation amounts were significantly
below normal nationwide. In contrast, they were significantly above normal for western Japan in November due tothe frequent passage of cyclones and fronts around thecountry. In October, Typhoon Melor (0918) made landfall
on mainland Japan, bringing heavy rainfall and strong
winds.
In the first half of December, temperatures were above
normal nationwide and heavy precipitation was brought to
the Pacific side of the country by migratory cyclones. In
contrast, a strong cold surge brought heavy snowfall to the
Sea of Japan side and resulted in low temperatures all overJapan in the second half of the month. Monthly snowfall
amounts were above normal on the Sea of Japan side ofeastern Japan for the first time in four years.

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No. 19 | Winter 2010

TCC Activity Report for 2009
The Tokyo Climate Center (TCC) of the Japan Meteorological
Agency (JMA) has prepared the Activity Report of the Tokyo
Climate Center for 2009, detailing the climate-related activities of TCC in 2009 and its plans for 2010.

diagnosis referred to as ITACS, which stands for Interactive
Tool for Analysis of the Climate System. ITACS enables
users not only to monitor current climate status but also to
analyze the complicated system that lies behind climaticconditions. The system is now available on the TCC website, which is intended for use by National Meteorologicaland Hydrological Services (NMHSs) and related research
institutes. For more details, including information on how
to apply, refer to http://jra.kishou.go.jp/itacs-info/tcc/
conditions.html.

1. Designation of TCC as an RCC in RA II
TCC was formally designated as one of the first Regional
Climate Centers (RCCs) in Regional Association II (Asia)
together with the China Meteorological Administration’s
Beijing Climate Center (BCC) at the 61st session of the
WMO’s Executive Council held in Geneva, Switzerland,
from 3 to 12 June 2009. TCC and BCC started their operational climate-related activities as RCCs on 1 July. As aresult of close cooperation between the two centers, theRegional Climate Center Network in RA II website has
been launched at http://www.rccra2.org/detail/index.htm.
Ms. K. Hayashi, Head of TCC, gave a presentation titled“Activity of Regional Climate Centers in Asia” at theWorld Climate Conference-3 (WCC-3) held in Geneva
from 31 August to 4 September 2009, introducing climaterelated activities embarked upon by TCC and BCC andfuture plans being formulated by the RCCs in RA II. The
presentation file is available on the WCC-3 website at
http://www.wcc3.org/wcc3docs/pdf/I3_Hayashi.pdf.

4. Long-range forecasting (monthly, seasonal, longerrange forecasts issued and disseminated based on model
simulations or statistical methods)
JMA improved its one-month ensemble prediction system in March 2008 (see TCC News No. 12 for details).
Accordingly, GPV products for one-month forecasts were
upgraded in April 2009 with the change of data format from
GRIB1 to GRIB2 and the provision of new products (daily
GPV data for individual ensemble members and hindcast
data) on the TCC website.
5. Training activities
TCC held the Training Seminar on Climate Analysis using Reanalysis Data from December 1 to 4 2009 with 11
invited participants from Asian and Pacific countries(Bangladesh, Indonesia, Laos, Malaysia, Mongolia, Pakistan, Papua New Guinea, the Philippines, Sri Lanka, Thailand and Vietnam). The attendees deepened their knowledge and grasp of practical techniques for climate analysis,in particular learning how to use ITACS through lecturesand hands-on exercises (see Article 5).
JMA has run 3-month courses in meteorology for NMHS
experts since 1973 as part of the training initiatives provided by the Japan International Cooperation Agency(JICA). The 2009 course was held from September to December with an emphasis on the operational use of numerical weather prediction, satellite meteorology and climate
information. In the climate information session, staff members from the Climate Prediction Division gave lectures on
climate system monitoring, long-range forecasting, El Niño
outlook and global warming projection to four participantsfrom Bhutan, Cambodia, Myanmar and Mongolia.

2. TCC website
TCC operates a website providing climate-related operational data and products as well as presentation materials
used in meetings and training events(http://ds.data.jma.go.jp/tcc/tcc/index.htm).
The Center renewed its El Niño Monitoring and Outlook
page (http://ds.data.jma.go.jp/tcc/tcc/products/elnino/index.html) and began providing SST monitoring and prediction information in newly defined SST monitoring regions called IOBW (covering the tropical Indian Ocean)and NINO.WEST through the website. On the renewed
page, SST deviation diagnosis and six-month outlooks for
IOBW and NINO.WEST are available.
The following content has been added to the TCC website:a) Madden-Julian Oscillation (MJO) information
http://ds.data.jma.go.jp/tcc/tcc/products/clisys/mjo/moni_mjo.htmlb) Monthly and annual anomalies of JMA's global surface
temperature data averaged in 5° x 5° grid boxes http://
ds.data.jma.go.jp/tcc/tcc/products/gwp/temp/ann_wld.html

6. Future plans
In February 2010, JMA will introduce a coupled oceanatmosphere general circulation model (CGCM) for operational seasonal forecasts, which is expected to improve prediction skill, especially in subtropical areas. GPC (Global
Producing Center) Tokyo will start providing products generated using the CGCM (see Article 1).
However, TCC recognizes that it is necessary to provide
tools and guidance for the handling and interpretation ofthese products from GPC. In order to facilitate their utilization, TCC plans to hold a training seminar on seasonal prediction in the coming autumn or winter. Furthermore, guidance materials on using the products will be made available
on the TCC website, which will help NMHSs generate theirown forecast products to meet user requirements. The Center also plans to develop new tools for prediction products
within a few years.
(Kumi Hayashi, Climate Prediction Division)c) Gridded global sea surface temperature data sets (COBESST) from 1891 onward http://ds.data.jma.go.jp/tcc/tcc/
products/elnino/cobesst/cobe-sst.htmld) Statistical relationships (atmospheric circulations regressed on El Niño monitoring indices) (renewed content)
http://ds.data.jma.go.jp/tcc/tcc/products/clisys/newoceanindex/explanation.html
3. Climate information services (monitoring, climate
reviews, etc.)
TCC provides a number of regular reports, such as
Monthly Report of Worldwide Extreme Climate Events,
Monthly Highlights on Climate System, El Niño Outlook,
Global Average Surface Temperature Anomaly and Annual
Report on Climate System.
JMA has developed a useful web-based tool for climate

Tokyo Climate Center

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No. 19 | Winter 2010

Training Seminar on Climate Analysis using Re-analysis Data
sis through lectures and exercises using the web-based Interactive Tools for Analysis of the Climate System(ITACS). Developed by JMA, this set of tools enables users
not only to monitor current climate conditions but also to
analyze the characteristics and factors that lie behind suchconditions and extreme climatic events. After a series oflectures and two days of practical exercise using ITACS,
each participant gave a presentation on the exercise results
focusing on climatic events of their interest. The seminarprovided a good opportunity for the participants to deepen
their knowledge of climate analysis.

The Training Seminar on Climate Analysis using Reanalysis Data was held at JMA Headquarters in Tokyo from
1 to 4 December, 2009, as part of the capacity-building
activities of the Tokyo Climate Center – one of the Regional Climate Centers in RA II of the World Meteorological Organization (WMO). The purpose of the seminar was
to assist NMHSs in enhancing their operational climatic
analysis performance. The seminar was attended by 11 participants from 11 countries engaged in operational longrange forecasting at NMHSs in East and Southeast Asia andthe Pacific region (Bangladesh, Indonesia, Laos, Malaysia,
Mongolia, Pakistan, Papua New Guinea, the Philippines,
Sri Lanka, Thailand and Vietnam). The participants learned
about the purpose and practical techniques of climate analy-(Kumi Hayashi, Climate Prediction Division)

Any comments or inquiries on this newsletter and/or the
Tokyo Climate Center (TCC), Climate Prediction Division, JMA
TCC website would be much appreciated. Please e-mail to: Address: 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japantcc@climar.kishou.go.jp
TCC website: http://ds.data.jma.go.jp/tcc/tcc/index.html(Chief Editor: Kumi Hayashi)Tokyo Climate Center

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No. 19 | Winter 2010