연구보고서
- 저자
- 김유진 박사
- 작성일
- 2018.04.24
- 조회
- 525
- 요약
- 목차
The Korean Meteorological Administration (KMA) provides weekly and monthly operational long-range forecasts.
The former is a weekly-rolling 1-month leading forecast and the latter is a monthly-rolling leading three-month leading forecast.
Because the public needs for long-range forecast data is growing, especially in developed countries, such data can be used in socio-economic studies. Meanwhile, many operational long-range forecast institutes apply two methods to improve the accuracy of forecast: obtain more accurate climate dynamical forecast models; and/or to enhance statistical correction/prediction methods using observed data. Thus, many statistical tools and monitoring of real-time observations are used in the long-range forecast in addition to the dynamical models. This integrated method is a practical way to overcome limitations in the forecast skill of dynamical models.
The APEC Climate Center (APCC) has supported real-time operational long-range forecast through the Climate Prediction Department (CPD)/KMA.APCC scientists have participated in the monthly climate forecast meetings which are held at a middle day of every month in the CPD/KMA and they have made the APCC Multi-Model Ensemble (MME) forecast data available.
APCC scientists also have participated in the monthly climate analysis meetings which are held at the end of every month for improving the adaptation of the CPD/KMA to the climate forecast. In addition, because of the stable operation of the WMO Lead Centre for Long-Range Forecast MME (LC-LRFMME), APCC has provided the long-range forecast data by multi-model ensemble skill. CPD/KMA takes advantage of multiple sources for operational long-range forecast as well as its dynamical model, GloSea5.
The present work aims to systemize the several pre-existing collaborations between APCC and KMA, and to improve the efficiency of the operational long-range forecast system to achieve accurate long-range forecast in Korea. To achieve this goal, we have integrated the specific knowledge of climate forecast and the ability to interpret climate model data of the APCC scientists, with the know-how of the operational climate forecast of the CPD/KMA scientists.
Three methods to improve the forecast skill of the Korea climate are established in this work. Firstly, an operation of the WMO LC-LRFMME is accomplished to provide a multi-dynamical model ensemble forecast. A new MME forecast system for weekly scale is developed this year, APCC and KMA decide to hold clime forecast meetings regularly in weekly scale. Secondly, a climate analysis research using observed data is conducted to improve the knowledge of climate monitoring, such as about the teleconnection effect or the dynamical and statistical structure of the Korean summer precipitation, and about the cold days of Korean winter season. Lastly, characteristics of dynamical forecast models of the Korean climate are analyzed, and statistical tools that employ the characteristics of such dynamical models are established. Those operational data and analyzed data produced by APCC scientists are provided to CPD/KMA every week and month regularly through climate forecast/analysis meetings mentioned earlier.