The Full Picture

an El Niño and La Niña/climate monitoring system and a long-

range forecast system. Through this project, the El Niño prediction

and a dynamic long-range forecast system has been operating since

1999. Since then, several improvement projects have been carried

out such as a global sea surface temperature forecast model and a

long-range forecast model development. Currently, the systems

operationally carry out monitoring and prediction of global climate,

including El Niño and La Niña, and predicted information and

products are being provided to the WMO and used for WMO press

releases for the El Niño/La Niña Update.

Based on statistical methods, KMA started to issue a monthly

long-range forecast in 1973, a cold and warm seasonal three-month

long-range forecast from 1984, and four seasonal forecasts from

1991. The dynamic long-range forecast system has been operating

since September 1999 using a global long-range forecast model,

Global Data Assimilation and Prediction System (GDAPS

T106L21), which was developed through aforementioned projects.

Currently KMA produces three types of dynamic long-range fore-

casts: one-month, three-month, and six-month forecast. The

one-month forecasts are issued three times a month, consisting of

temperature, precipitation and air pressure patterns for the next

30 days. The three-month forecasts, which are produced on a

monthly basis, consist of temperature and precipitation trends

including special seasonal events such as Asian dust, Typhoon and

Changma (rainy season over Korea) for the next three months. The

six-month forecast is issued twice a year (May and November).

Those results and activities are presented and discussed at the Joint

Meeting on Seasonal Prediction of the East Asian Monsoon, in

which the East Asian countries participate.

The effort to improve climate prediction techniques

was also realized in the establishment of the APEC

Climate Center (APCC), which was set up in Busan,

the Republic of Korea in November 2005, with a view

to enhancing the capacity of monitoring and predict-

ing unusual weather and climate changes in the

Asia-Pacific region. The basic principle in the opera-

tion of APCC is to share optimized and high-cost

climate information and products with the participat-

ing organizations from APEC member economies. The

APCC tries to realize the APEC vision of regional pros-

perity through the enhancement of economic

opportunities, the reduction of economic loss, and the

protection of life and property by responding effec-

tively to natural disasters and mitigating economic

losses in the case of extreme climate events. The APCC

contributes to the enhancement the socio-economic

well-being of APEC member economies by utilizing

up-to-date scientific knowledge and applying innova-

tive climate prediction techniques. APCC, which was

also registered as a modelling and data processing

centre for the Global Earth Observation System of

Systems (GEOSS), has processed and disseminated

operational climate prediction information and prod-

ucts based on the multi-model ensemble (MME)

technique to all member economies APCC carries out

sensitivity studies of various individual models and the

APCC-MME system to surface boundary forcing. In

this connection, a statistical downscaling using MME

products is developed and implemented for the esti-

mation of rainfall over the Korean peninsula and other

regions. Examinations of predictability of specific

phenomena, such as the El Niño-Southern Oscillation

(ENSO), Pacific/North American pattern (PNA), trop-

ical cyclone activity, intra-seasonal variations of

monsoon prediction, Asian dust, and extreme climate

events are also being carried out.

With the above experiences in the area of climate

monitoring and prediction, KMA has recently served

as one of nine WMO Global Producing Centres (GPCs)

for long-range forecasts (LRF) since November 2006.

Recently, KMA began to distribute long-range forecast

data to other GPCs and WMO member countries

through the website.

The further development of

advanced prediction schemes for long-range forecasts

is now a current task of KMA. KMA is operationally

using the MME techniques, which has been proved to

be a leading-edge technology to make up for the

systematic errors of each single model. A comparison

of single model results and multi-model ensemble

prediction indicates that MME results are superior to

the individual models. With recognition of this expe-

rience, KMA will also work as a collector of global LRF

data provided by other GPCs. Such prediction data will

be standardized and disseminated to other GPCs and

Regional Climate Centers (RCCs).

The provision and sharing of technical information

and techniques about MME is important for users to

pursue LRF MME predictions. In this connection, KMA

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Single model vs. multi-model ensemble

MME techniques, which has been proved to be a leading-edge technology in

compensating for the systematic errors of each single model. Here, single model

results are compared with multi-model ensemble predictions

Source: Won-Tae Yun, Florida State University (FSU) Multi Model Superensemble

Prediction system, The Second Regional Climate Modeling Workshop for the Greater

Horn of Africa, DMC Nairobi, Kenya, February 2004

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