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Climate Services and Research

Enhancing Climate Prediction Services through Innovative Research and Technology

Climate Prediction

Operation of Climate Prediction Systems and Provision of Climate Information Services for the Asia-Pacific Region

Prediction Research & Development

Development of Innovative Technologies for Predicting Climate Extremes

Climate Change Analysis

Assessment of the reproducibility of extreme climate events on a decadal time scale and development of high-resolution downscaling technology to enhance the applicability of climate change analysis

Climate Model Testbed

Operation of the KMA Climate Prediction System Testbed and Establishment of a Verification Framework

Information System and Security

 

Climate Prediction

Goal

Provision of timely and reliable climate prediction

Strengthening climate information services for the Asia-Pacific region

Basic Functions

Operation of climate prediction systems and provision of climate information services for the Asia-Pacific region

Operation of online climate information services and response & analysis of user demands

Improvement of climate prediction and climate information service systems

Production, collection, distribution, and management of climate prediction data

Domestic and international cooperation in the field of climate

Main Research

The Climate Prediction Department (CDP) of the APEC Climate Center (APCC) has established a well-validated Multi-Model Ensemble (MME) prediction system through international collaboration with 16 leading operational climate centers and research institutes from 11 countries. This system provides global seasonal predictions for temperature and precipitation up to six months ahead, disseminated monthly to APEC member economies around the 15th of each month. In addition, APCC offers climate monitoring and verification information to increase the utilization of the APCC MME prediction information.

 

Since 2013, APCC has been operating the world’s first Boreal Summer Intraseasonal Oscillation (BSISO) prediction system in collaboration with the World Meteorological Organization (WMO), the Working Group on Numerical Experimentation (WGNE), and the Madden Julian Oscillation (MJO) Task Force. This system provides daily 2?3 week BSISO forecasts for Asia during May?October, predicting intraseasonal oscillations that influence the onset and characteristics of the Asian summer monsoon. To make these forecasts more user-friendly, APCC also offers probabilistic predictions of heavy rainfall events associated with BSISO.

 

Beyond climate prediction, APCC develops and operates online climate information service platform, Climate Information toolKit (CLIK). This platform aims to facilitate user-oriented access to climate data and predictions while expanding climate information services through research, development, and training workshops tailored to diverse user needs. CLIK enables users to produce user-defined MME prediction/verification and download digitized climate data in accessible formats, promoting effective utilization of APCC’s climate information.

 

APCC continues to enhance its prediction systems through foundational research and international cooperation projects. Efforts include improving forecast methodologies, and strengthening networks for climate knowledge sharing among APEC economies. These initiatives support the broader goal of providing reliable climate predictions while addressing key issues such as extreme climate.

※ MME (Multi-Model Ensemble): A method that integrates predictions from multiple models worldwide to improve accuracy by reducing systematic errors.

※ BSISO (Boreal Summer Intraseasonal Oscillation): A large-scale convective phenomenon occurring over the Indian Ocean every 15?60 days, gradually propagating eastward and northward, influencing Asian summer monsoon and atmospheric circulation.

※ CLIK(CLimate Information toolKit): An integrated online climate information service platform developed by APCC for producing, processing and accessing digitized climate prediction data efficiently.