• 대기
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• 제29권2호
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• pp.219-226
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• 2019

Generally, the weather forecast system has been run using prescribed ocean condition. As it is widely known that coupling between atmosphere and ocean process produces consistent initial condition at all-time scales to improve forecast skill, there are many trials on the application of data assimilation of coupled model. In this study, we implemented a weakly coupled data assimilation (short for WCDA) system in global NWP model with low horizontal resolution for coupled forecast with uncoupled initialization, following WCDA system at the Met Office. The experiment is carried out for a typhoon evolution forecast in 2017. Air-sea exchange process provides SST cooling and gives a substantial impact on tendency of central pressure changes in the decaying phase of the typhoon, except the underestimated central pressure. Coupled data assimilation is a challenging new area, requiring further work, but it would offer the potential for improving air-sea feedback process on NWP timescales and finally contributing forecast accuracy.

• Ocean and Polar Research
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• 제43권2호
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• pp.53-63
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• 2021

Changes in a marine environment have a broad socioeconomic implication on fisheries and their relevant industries so that there has been a growing demand for the medium-range (months to years) prediction of the marine environment Using a medium-range ocean prediction model (Ocean Mid-range prediction System, OMIDAS) for the northwest Pacific, this study attempted to assess seasonal difference in the mid-range predictability of the sea surface temperature (SST), focusing on the Korea seas characterized as a complex marine system. A three-month re-forecast experiment was conducted for each of the four seasons in 2016 starting from January, forced with Climate Forecast System version 2 (CFSv2) forecast data. The assessment using relative root-mean-square-error was taken for the last month SST of each experiment. Compared to the CFSv2, the OMIDAS revealed a better prediction skill for the Korea seas SST, particularly in the Yellow sea mainly due to a more realistic representation of the topography and current systems. Seasonally, the OMIDAS showed better predictability in the warm seasons (spring and summer) than in the cold seasons (fall and winter), suggesting seasonal dependency in predictability of the Korea seas. In addition, the mid-range predictability for the Korea seas significantly varies depending on regions: the predictability was higher in the East Sea than in the Yellow Sea. The improvement in the seasonal predictability for the Korea seas by OMIDAS highlights the importance of a regional ocean modeling system for a medium-range marine prediction.

• 한국해양학회지:바다
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• 제22권3호
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• pp.103-117
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• 2017

이 노트는 국립해양조사원이 5년(2012~2016년)간에 걸쳐 지역해(동해, 황 동중국해) 수치예측시스템을 구축하여 자동으로 끊임없이 운영하면서 확보한 기술들 중 다음 3가지를 담고 있다. (1) 끊임없이 3일 해양예측 자료를 생산하기 위한 전략, (2) 매일 특정시각에 외부 해양 기상자료(HYCOM, NOAA/NCEP GFS)를 안정적으로 내려 받는 방법과 (3) 해양예측시스템 운영자들이 휴대전화 단문 메시지 서비스(Short Message Service)를 이용하여 해양예측시스템 수행 시 발생하는 시스템 오류를 신속하게 파악할 수 있는 기능에 관하여 기술하였다. 이들 기본 기술과 운영시스템 구성의 기본 개념은 지역해와 연안 해양 수치예측시스템을 자동으로 운영하는 체계를 구축하는 데 있어서 유용하게 사용될 것이다.

• 대기
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• 제27권3호
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.645-648
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• 2005

The COMS(Communication, Ocean and Meteorological Satellite), a multi-mission geo-stationary satellite, is being developed by KARl. The first mission of the COMS is the meteorological image and data gathering for weather forecast by using a five channel meteorological imager. The second mission is the oceanographic image and data gathering for marine environment monitoring around Korean Peninsula by using an eight channel Geostationary Ocean Color Imager(GOCI). The third mission is newly developed Ka-Band communication payload certification test in space by providing communication service in Korean Peninsula and Manjurian area. There were many low Earth orbit satellites for ocean monitoring. However, there has never been any geostationary satellite for ocean monitoring. The COMS is going to be the first satellite for ocean monitoring mission on the geo-stationary orbit. The meteorological image and data obtained by the COMS will be distributed to end users in Asia-Pacific area and it will contribute to the improved weather forecast.

• 대기
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• 제26권4호
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• pp.599-615
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• 2016

This study investigates the accuracy of short-term ocean predictions during the development of ocean stratification for the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 5 (GloSea5) as well as the effect of atmosphere-ocean coupling on the predictions through a series of sensitive numerical experiments. Model performance is evaluated using the marine meteorological buoys at seas around the Korean peninsular (KP), Tropical Atmosphere Ocean project (TAO) buoys over the tropical Pacific ocean, and ARGO floats data over the western North Pacific for boreal winter (February) and spring (May). Sensitive experiments are conducted using an ocean-atmosphere coupled model (i.e., GloSea5) and an uncoupled ocean model (Nucleus for European Modelling of the Ocean, NEMO) and their results are compared. The verification results revealed an overall good performance for the SST predictions over the tropical Pacific ocean and near the Korean marginal seas, in which the Root Mean Square Errors (RMSE) were $0.31{\sim}0.45^{\circ}C$ and $0.74{\sim}1.11^{\circ}C$ respectively, except oceanic front regions with large spatial and temporal SST variations (the maximum error reached up to $3^{\circ}C$). The sensitive numerical experiments showed that GloSea5 outperformed NEMO over the tropical Pacific in terms of bias and RMSE analysis, while NEMO outperformed GloSea5 near the KP regions. These results suggest that the atmosphere-ocean coupling substantially influences the short-term ocean forecast over the tropical Pacific, while other factors such as atmospheric forcing and the accuracy of simulated local current are more important than the coupling effect for the KP regions being far from tropics during the development of ocean stratification.

• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.11-19
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• 2018

최근 GIS(Geographic Information System)을 중심으로 다양한 정보를 지도위에 제공하고 있으며, 대표적으로 국외의 경우 구글맵, 오픈스트리트맵, 빙맵 등이 있고, 국내의 경우 네이버지도, 다음지도, 브이월드맵 등이 GIS 기술의 한 부분인 WMS(Web Map Service)를 이용하여 서비스를 제공하고 있다. 본 논문에서는 현재 서비스되고 있는 벡터장 데이터 정보를 이용하여, 조류의 흐름도 와 스트림라인의 표출 방안 알고리즘 연구 및 사용자 편의성을 고려한 해양예측모델 데이터의 가시화 방안에 대해 연구를 수행하였다. 기존의 조류 흐름도 표출 및 스트림라인 표출 알고리즘과 제안하는 방식의 성능을 비교를 하여, 기존의 기술 보다 2배 이상 빠른 표출이 되는 것을 확인하였다.

• 한국해안·해양공학회논문집
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• 제30권2호
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• pp.84-94
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• 2018

해양파랑 예측에 있어 단일 수치모델의 불확실성을 보완하기 위하여 앙상블 기법을 적용한 지역 파랑예측시스템을 구축하였다. 기상청 전지구 대기 수치모델의 확률예측시스템에서 생산되는 24개 앙상블 해상풍을 입력자료로 이용, 87시간까지 파랑 예측자료를 생산하였으며, 기상청 계류부이 관측자료와 다양한 통계방법을 적용하여 검증을 수행하였다. 2일예측 이후의 앙상블 예측평균의 평균제곱근오차(RMSE)는 단일모델예측에 비하여 향상된 결과를 보였으며, 특히 3일예측의 경우 단일모델예측 대비 RMSE가 약 15% 정도 향상되었다. 이것은 앙상블 기법이 수치모델의 불확실성을 감소시켜 예측정확도 향상에 크게 기여한 것으로 보인다. ROC(Relative Operating Characteristic) 분석결과, 전체 예측시간에 대하여 ROC 영역이 모두 0.9 이상을 보여 확률예측 성능이 뛰어남을 보였으며, 앙상블 파랑예측 결과가 해상 확률예보에 유용하게 활용될 수 있을 것으로 판단된다.

• 한국해양학회지:바다
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• 제20권1호
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• pp.1-15
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• 2015

한반도 주변을 연구해역으로 하는 지역 해양순환예측시스템을 이용하여 관측기반의 분석 자료인 Operational Sea Surface Temperature and Sea Ice Analysis(OSTIA) 해수면 온도 자료의 동화를 통한 초기장 개선효과가 황해, 동중국해 그리고 동해의 해수면온도 예측결과에 미치는 영향을 조사하였다. 이를 위해서, 본 연구에서는 3차원 최적내삽법을 적용한 실험(Exp. DA)과 적용하지 않은 실험(Exp. NoDA)을 수행하여 각각의 실험결과를 관측자료와 비교 분석하였다. 2011년 9월 OSTIA 해수면 온도 자료와의 비교결과, Exp. NoDA는 24, 48, 72 예측시간에서 약 $1.5^{\circ}C$의 비교적 높은 Root Mean Square Error(RMSE)를 보였으나, Exp. DA에서는 모든 예측시간에서 $0.8^{\circ}C$ 이하의 상대적으로 낮은 RMSE가 나타났다. 특히, 초기 24시간 예측결과에서 RMSE는 $0.57^{\circ}C$를 보여 Exp. NoDA에 비해 예측성능이 크게 향상된 결과를 보였다. 해역별로는 황해와 동해에서 자료동화 적용 시, 60% 이상의 높은 RMSE 감소율이 나타났다. 기상청 8개 지점 연안 계류부이의 표층수온 자료를 이용하여 자료동화 효과를 계절적으로 살펴본 결과, 전반적으로 여름철을 제외한 모든 계절에서 자료동화 적용 후 70% 이상의 높은 RMSE 감소율을 보여 한반도 연안 표층수온의 단기 예측성이 향상됨을 확인하였다. 또한, 해수면 온도 자료의 동화로 인한 해양상층부의 수온구조 변화를 살펴보기 위해 동해를 대표해역으로 하여 Argo 수온 프로파일 자료와 실험결과를 비교하였다. 특히 연직 혼합이 강한 겨울철 해양 상층부(<100 m) 경우 Exp. DA의 RMSE가 Exp. NoDA에 비해 약 $1.5^{\circ}C$ 감소한 결과를 보여 해수면 온도의 자료동화 효과가 해양상층부의 수온 예측성 향상에 기여함을 확인하였다. 하지만, 겨울철 혼합층 아래에서는 Argo 관측 대비 수온 오차가 오히려 증가한 해역도 존재하여 해수면 온도 자료동화의 한계성도 나타났다.

• 대기
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• 제27권1호
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• pp.93-104
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• 2017

The effect of Advanced Microwave Sounding Unit-A (AMSU-A) observations on the short-range forecast in East Asia (EA) was investigated for the Northern Hemispheric (NH) summer and winter months, using the Forecast Sensitivity to Observations (FSO) method. For both periods, the contribution of radiosonde (TEMP) to the EA forecast was largest, followed by AIRCRAFT, AMSU-A, Infrared Atmospheric Sounding Interferometer (IASI), and the atmospheric motion vector of Communication, Ocean and Meteorological Satellite (COMS) or Multi-functional Transport Satellite (MTSAT). The contribution of AMSU-A sensor was largely originated from the NOAA 19, NOAA 18, and MetOp-A (NOAA 19 and 18) satellites in the NH summer (winter). The contribution of AMSU-A sensor on the MetOp-A (NOAA 18 and 19) satellites was large at 00 and 12 UTC (06 and 18 UTC) analysis times, which was associated with the scanning track of four satellites. The MetOp-A provided the radiance data over the Korea Peninsula in the morning (08:00~11:30 LST), which was important to the morning forecast. In the NH summer, the channel 5 observations on MetOp-A, NOAA 18, 19 along the seaside (along the ridge of the subtropical high) increased (decreased) the forecast error slightly (largely). In the NH winter, the channel 8 observations on NOAA 18 (NOAA 15 and MetOp-A) over the Eastern China (Tibetan Plateau) decreased (increased) the forecast error. The FSO provides useful information on the effect of each AMSU-A sensor on the EA forecasts, which leads guidance to better use of AMSU-A observations for EA regional numerical weather prediction.