Executive Summary

APEC Climate Center (APCC) is a specialized institution of climate prediction based on Multi-Model Ensemble (MME) and one of their key responsibility is to improve fidelity of the operational long-range forecast in Korea, which is provided by Korea Meteorological Administration (KMA). KMA provides roughly two types of long-range forecast, one is monthly-rolling 3-month forecast and the other is weekly-rolling 1-month forecast. In order to produce the long-range forecast with high fidelity, an extensive understanding on the Korean climate variability as well as an appropriate interpretation on the predictions from climate prediction models is required. Therefore, this project aims to contribute the improvement of operational long-range forecast in Korea by covering the above mentioned two components.

The first subject of this project is the analysis on the climate factors in which affect Korean surface air temperature and precipitation variability based on the observational dataset. The El Niño-Southern Oscillation (ENSO) is the most prominent coupled ocean-atmosphere variability in the tropical Pacific and is recognized as a major source of climate variability in Korea. Due to the strong seasonal phase-locking feature of ENSO, the transition period of ENSO generally occurs during summer, and thus the teleconnection patterns should be susceptible to the different feature of ENSO evolution. Therefore, the summer climate variability over Korea that is associated with diverse features of ENSO evolution is investigated. Meanwhile, the winter season is the peak phase of ENSO, the ENSO-related tropical convection structures would be important for determining mid-latitude climate variability including Korea. Thus, the two distinct modes of convection variability over tropical Indo-Pacific and associated climate variability in Korea, especillay during January, are identified. The second research subject of the climate analysis based on the observational dataset is about the recent changes in the predictability of various climate predictors, which have been utilized in the operational long-range forecast. The predictability of climate predictors for the summer and winter temperature in Korea is examined. The long term changes of relation between the temperature and precipitation in Korea and its predictor and possible reason for relation change are also investigated.

Second, we conducted the analyses based on the operation climate models for producing optimal climate prediction information. The climatology, which is the reference value of operational long-range forecast, is updated every 10 years. Therefore, the climatology will be changed from the period of 1981-2010 to 1991-2020 in the next year (2021). Accordingly, it is required to identify the change of climate models’predictability in relation to the change of climatology period. It is also analyzed climate models’predictability of the Korean heat wave. Meanwhile, an expert seasonal prediction system for operational seasonal outlook (ESPreSSO) based on APCC MME has been developed and utilized in the operational long-range forecast. In this year, the ESPreSSO has been improved by applying new technology for flexible manage of EsPreSSO in the changes of model set and period of hindcast.

The third subject is about operating WMO Lead Center for Long Range Forecast (WMO LC-LRFMME). The WMO LC-LRFMME collected forecast data from global producing center and standardized forecast and hindcast data and displaying the Multi Model Ensemble (MME) results including deterministic and probabilistic method through the website. Also the WMO LC-LRFMME provided the seasonal forecast information to Regional Climate Outlook Forums (RCOF), Global Seasonal Climate Updates (GSCU) and KMA to a consensus on the state of the global and regional climate outlook. Meanwhile, The WMO LC-LRFMME’s seasonal forecast system improvements have been performed to provide customized seasonal prediction information and improve system management.

Finally, the research results of this project are direcly applied to the operational long-range forecast by engaging KMA’s operational works. We have been supported 1-month forecast every week based on the WMO sub-seasonal MME. In this regard, we are not only providing prediction results but also developing various prediction contents such as daily timeseries for supporting forecaster’s decision making. For supporting 3-month forecast, we have been provided integrated results every month by combining the forecast from the climate model, especially from APCC MME, and the influence of climate factors such as ENSO. We have been also participated in the monthly climate analysis discussion and provided the characteristic feature of the climate variability in Korea. Likewise, this project contributes to strengthen specificity of long-range forecast over Korea. We hope that this research results are acting for the cornerstone of improving Korean operational long-range forecast.