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The performance of the newly designed Pusan National University Coupled General Circulation Model (PNU CGCM) Ensemble Forecast System which produce 40 ensemble members for 12-month lead prediction is evaluated and analyzed in terms of boreal winter temperature over South Korea (S. Korea). The influence of ensemble size on prediction skill is examined with 40 ensemble members and the result shows that spreads of predictability are larger when the size of ensemble member is smaller. Moreover, it is suggested that more than 20 ensemble members are required for better prediction of statistically significant inter-annual variability of wintertime temperature over S.

Korea. As for the ensemble average (ENS), it shows superior forecast skill compared to each ensemble member and has significant temporal correlation with Automated Surface Observing System (ASOS) temperature at 99% confidence level. In addition to forecast skill for inter-annual variability of wintertime temperature over S. Korea, winter climatology around East Asia and synoptic characteristics of warm (above normal) and cold (below normal) winters are reasonably captured by PNU CGCM. For the categorical forecast with 3 � 3 contingency table, the deterministic forecast generally shows better performance than probabilistic forecast except for warm winter (hit rate of probabilistic forecast: 71%). It is also found that, in case of concentrated distribution of 40 ensemble members to one category out of the three, the probabilistic forecast tends to have relatively high predictability.

Meanwhile, in the case when the ensemble members distribute evenly throughout the categories, the predictability becomes lower in the probabilistic forecast.

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기사명 저자명 페이지 원문 목차
한반도 한파의 지역적 강화 메커니즘 = Local enhancement mechanism of cold surges over the Korean Peninsula 이혜영, 김주완, 박인규, 강현규, 류호선 p.383-392

통합모델을 이용한 토지피복변화와 도시 모수화 방안에 따른 지상 기온 모의성능 민감도 분석 = Sensitivity analysis of near surface air temperature to land cover change and urban parameterization scheme using unified model 홍선옥, 변재영, 박향숙, 이영곤, 김백조, 하종철 p.427-441

대규모 기후인자와 관련된 우리나라 봄철 산불위험도 변동 = Spring forest-fire variability over Korea associated with large-scale climate factors 정지윤, 우성호, 손락훈, 윤진호, 정지훈, 이석준, 이병두 p.457-467

PNU CGCM과 WRF를 이용한 남한 지역 기온 예측성 검증 = Predictability of temperature over South Korea in PNU CGCM and WRF hindcast 안중배, 심교문, 정명표, 정하규, 김영현, 김응섭 p.479-490

미래 기후 변화 시나리오에 따른 환북극의 변화 = Projection of circum-arctic features under climate change 이지연, 조미현, 고영대, 김백민, 정지훈 p.393-402

서울 서대문구 지상 미세먼지 관측 비교 = Comparison of ground-based particulate matter observations in the Seodaemun-gu district, Seoul 구자호, 이서영, 김민석, 박중희, 전수안, 노현석, 김준, 이윤곤 p.469-477

겉보기 열원 및 습기 흡원의 세 재분석 자료 비교와 몬순 지역별 분석 = Three reanalysis data comparison and monsoon regional analysis of apparent heat source and moisture sink 하경자, 김서경, 오효은, 문수연 p.415-425

변분에코추적법을 이용한 제주도 지역 여름철 강수계의 이동 특성 분석 = Characteristics of summer season precipitation motion over Jeju Island region using variational echo tracking 김권일, 이호우, 정성화, 류근수, 이규원 p.443-455

기상청 전지구예측시스템 자료에서의 2016~2017년 북반구 블로킹 예측성 분석 = Predictability of northern hemisphere blocking in the KMA GDAPS during 2016~2017 노준우, 조형오, 손석우, 백희정, 부경온, 이정경 p.403-414

항공기 온도 관측 자료의 편향 보정= Bias correction for aircraft temperature observation. pt1, Analysis of temperature bias characteristics by comparison with sonde observation . pt1, 존데와 비교를 통한 온도 편향 특성 분석 권희내, 강전호, 권인혁 p.357-367

20세기 이전 한국의 역사 기록에서 확인되는 황사 현상 = A study on the Asian dust phenomenon found in the historical records of Korea prior to the 20th century 전준혁 p.491-507

ICE-POP 2018기간 동계집중관측자료를 활용한 국지수치모델(LDAPS)의 행성경계층고도 검증 = Verification of planetary boundary layer height for local data assimilation and prediction system (LDAPS) using the winter season intensive observation data during ICE-POP 2018 인소라, 남형구, 이진화, 박창근, 심재관, 김백조 p.369-382

PNU CGCM 앙상블 예보 시스템의 겨울철 남한 기온 예측 성능 평가 = Evaluation of PNU CGCM ensemble forecast system for boreal winter temperature over South Korea 안중배, 이준리, 조세라 p.509-520

참고문헌 (48건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 Ahn, J.-B., and J. A. Lee, 2001: Numerical study on the role of sea-ice using ocean general circulation model. J. Korean Soc. Oceanogr., 6, 225-233 (in Korean with English abstract). 미소장
2 Comparative Study on the Seasonal Predictability Dependency of Boreal Winter 2m Temperature and Sea Surface Temperature on CGCM Initial Conditions 소장
3 Ahn, J.-B., and J. Lee, 2016: A new multi-model ensemble method using nonlinear genetic algorithm: An application to boreal winter surface air temperature and precipitation prediction. J. Geophys. Res. Atmos., 121, 9263-9277, doi:10.1002/2016JD025151. 미소장
4 Atmosphere 네이버 미소장
5 Alves, O., M. A. Balmaseda, D. Anderson, and T. Stockdale, 2004: Sensitivity of dynamical seasonal forecasts to ocean initial conditions. Quart. J. Roy. Meteor. Soc., 130, 647-667. 미소장
6 Balmaseda, M., and D. Anderson, 2009: Impact of initialization strategies and observations on seasonal forecast skill. Geophys. Res. Lett., 36, L01701. 미소장
7 The Land Surface Climatology of the NCAR Land Surface Model Coupled to the NCAR Community Climate Model 네이버 미소장
8 Branković, Č., T. N. Palmer, F. Molteni, S. Tibaldi, and U. Cubasch, 1990: Extended-range predictions with ECMWF models: Time-lagged ensemble forecasting. Quart. J. Roy. Meteor. Soc., 116, 867-912. 미소장
9 Chan, J. C. L., and C. Y. Li, 2004: The East Asia winter monsoon. Chang, C.P., Ed., East Asian Monsoon, World Scientific Publishing Co. Pet. Ltd., 54-106. 미소장
10 Chang, C.-P., Z. Wang, and H. Hendon, 2006: The Asian winter monsoon. Wang, B., Ed., The Asian Monsoon, Praxis Springer Berlin, 89-127. 미소장
11 The internal climate variability of HadCM3, a version of the Hadley Centre coupled model without flux adjustments 네이버 미소장
12 Guilyardi, E., and Coauthors, 2004: Representing El Niño in coupled ocean-atmosphere GCMs: the dominant role of the atmospheric component. J. Climate, 17, 4623-4629. 미소장
13 Performance Assessment of Weekly Ensemble Prediction Data at Seasonal Forecast System with High Resolution 소장
14 Variational Analysis Using Spatial Filters 네이버 미소장
15 An Elastic-Viscous-Plastic Model for Sea Ice Dynamics 네이버 미소장
16 Climate change. Dr. Cool. 네이버 미소장
17 Jeong, H. I., K. Ashok, B. G. Song, and Y. M. Min, 2008:Experimental 6-month Hindcast and forecast simulation using CCSM3. APCC 2008 Tech. Rep. APEC Climate Center, Korea. 미소장
18 Jhun, J.-G., and E.-J. Lee, 2004: A new East Asian Winter Monsoon Index and associated characteristics of the winter monsoon. J. Climate, 17, 711-726. 미소장
19 Jo, S., and J.-B. Ahn, 2014: Improvement of CGCM prediction for wet season precipitation over Maritime Continent using a bias correction method. Int. J. Climatol., 35, 3721-3732, doi:10.1002/joc.4232. 미소장
20 Jo, S., and J.-B. Ahn, 2017: Statistical forecast of early spring precipitation over South Korea using multiple linear regression. J. Climate Res., 12, 53-71, doi:10.14383/cri.2017.12.1.53 (in Korean with English abstract). 미소장
21 Jolliffe, I. T., and D. B. Stephenson, 2003: Forecast verification:a practitioner’s guide in atmospheric science. Wiley and Sons, 254 pp. 미소장
22 NCEP–DOE AMIP-II Reanalysis (R-2) 네이버 미소장
23 Kiehl, J. T., and P. R. Gent, 2004: The Community Climate System Model, Version 2. J. Climate, 17, 3666-3682. 미소장
24 Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, B. P. Briegleb, D. L. Williamson, and P. J. Rasch, 1996: Description of the NCAR community climate model (CCM3). NCAR Tech. Note. NCAR/TN-420+STR, 152 pp. 미소장
25 Kim, H.-J., and J.-B. Ahn, 2015: Improvement in Prediction of the Arctic Oscillation with a Realistic Ocean Initial Condition in a CGCM. J. Climate, 28, 8951-8967. 미소장
26 KMA, 2012: Construction of the abnormal climate probability forecast system using the joint seasonal forecast system between KMA and Met Office. Korean Meteorological Administration, Seoul, 97 pp. 미소장
27 KMA, 2018: 2017 abnormal climate report, Korean Meteorological Administration, 218 pp [Available online at http://www.climate.go.kr/home/cc_data/2018/2017_abnormal_climate_report.pdf.]. 미소장
28 Remote Sensing of Above-Ground Biomass 네이버 미소장
29 Verification and Comparison of Forecast Skill between Global Seasonal Forecasting System Version 5 and Unified Model during 2014 소장
30 Lim, E.-P., H. H. Hendon, S. Langford, and O. Alves, 2012: Improvements in POAMA2 for the prediction of major climate drivers and south eastern Australian rainfall. CAWCR Tech. Rep. No. 051, 23 pp [Available online at http://www.cawcr.gov.au/technicalreports/CTR_051.pdf.]. 미소장
31 Forecasting UK and European winters 네이버 미소장
32 MacLachlan, C., and Coauthors, 2015: Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Quart. J. Roy. Meteor. Soc., 141, 1072-1084. 미소장
33 Global Coupled General Circulation Models 네이버 미소장
34 Min, Y.-M., V. N. Kryjov, and S. M. Oh, 2014: Assessment of APCC multimodel ensemble prediction in seasonal climate forecasting: Retrospective (1983-2003) and real-time forecasts (2008-2013). J. Geophys. Res. Atmos., 119, 12132-12150, doi:10.1002/2014JD022230. 미소장
35 Molteni, F., and Coauthors, 2011: The new ECMWF seasonal forecast system (System 4). ECMWF Tech Memo 656, 51 pp [Available online at https://www.ecmwf.int/sites/default/files/elibrary/2011/11209-newecmwf-seasonal-forecast-system-system-4.pdf.]. 미소장
36 Comparison of projection skills of deterministic ensemble methods using pseudo-simulation data generated from multivariate Gaussian distribution 네이버 미소장
37 Pacanowski, R. C., and S. M. Griffies, 1999: MOM 3.0manual. Princeton, USA: NOAA/Geophysical Fluid Dynamics Laboratory 08542, 708 pp [Available online at https://www.gfdl.noaa.gov/wp-content/uploads/files/model_development/ocean/mom3_manual.pdf.]. 미소장
38 RDA, 2014: The Construction of Agrometeorological Information and Climate Modeling in Major Crop Production Area, Rural Development Administration, 138 pp [Available online at http://www.ndsl.kr/ndsl/search/detail/report/reportSearchResultDetail.do?cn=TRKO201400011432]. 미소장
39 RDA, 2018: Production of Dissemination of Agro-climate Information in Major Crop Production Areas. Rural Development Administration, 79 pp [Available online at http://www.ndsl.kr/ndsl/search/detail/report/reportSearchResultDetail.do?cn=TRKO201800043070]. 미소장
40 Saha, S., and Coauthors, 2014: The NCEP climate forecast system version 2. J. Climate, 27, 2185-2208, doi:10.1175/JCLI-D-12-00823.1. 미소장
41 Seong, M.-G., M.-S. Suh, and C. Kim, 2017: Intercomparison of Prediction Skills of Ensemble Methods Using Monthly Mean Temperature Simulated by CMIP5Models. Asia-Pac. J. Atmos. Sci., 53, 339-351, doi:10.1007/s13143-017-0039-y. 미소장
42 Sun, J., and J.-B. Ahn, 2015: Dynamical seasonal predictability of the arctic oscillation using a CGCM. Int. J. Climatol., 35, 1342-1353, doi:10.1002/joc.4060. 미소장
43 Takaya, Y., T. Yasuda, T. Ose, and T. Nakaegawa, 2010:Predictability of the mean location of typhoon formation in a seasonal prediction experiment with a coupled general circulation model. J. Meteor. Soc. Japan, 88, 799-812. doi:10.2151/jmsj.2010-502. 미소장
44 Taylor, K. E., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res.-Atmos., 106, 7183-7192. 미소장
45 How well do existing indices measure the strength of the East Asian winter monsoon? 네이버 미소장
46 STATISTICAL METHODS IN THE ATMOSPHERIC SCIENCES Second Edition 네이버 미소장
47 Williams, K. D., and Coauthors, 2015: The met office global coupled model 2.0 (GC2) configuration. Geosci. Model Dev., 8, 1509-1524, doi:10.5194/gmd-8-1509-2015. 미소장
48 Climatology and Interannual Variation of the East Asian Winter Monsoon: Results from the 1979–95 NCEP/NCAR Reanalysis 네이버 미소장

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