• Atmosphere
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• v.26 no.4
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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.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.226-231
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• 2003

A coupling system of MM5 and POM using Stampi with different kinds of parallel computer is proposed and comparative numerical simulations of mesoscale wind induced by topography around East Sea/Sea of Japan are carried out. The results are as follows： 1) Strong horizontal conversion is induced by high mountain Pekdoo at its leeside. 2) The conversion winds at lee of high mountain are not clear in monthly and yearly mean NCEP-reanalysis because of coarse resolution of 1.86 degree by 1.86 degree. But Wind conversion is well simulated at atmosphere and ocean coupling system. And the conversion area of lee side of mountain is also agreed well with observed data of NSCAT launched in satellite ADEOS. 3) The surface ocean current is well correspondent with wind direction, induced by high mountains. And small different wind field information lead the different of particle distribution in numerical experiments of particle distribution on ocean surface.

• Atmosphere
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• v.29 no.2
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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 Science Journal
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• v.41 no.1
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• pp.1-10
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• 2006

Total sea surface temperature (SST) in a coupled GCM is diagnosed by separating the variability into signal variance and noise variance. The signal and the noise is calculated from multi-decadal simulations from the COLA anomaly coupled GCM and the interactive ensemble model by assuming both simulations have a similar signal variance. The interactive ensemble model is a new coupling strategy that is designed to increase signal to noise ratio by using an ensemble of atmospheric realizations coupled to a single ocean model. The procedure for separating the signal and the noise variability presented here does not rely on any ad hoc temporal or spatial filter. Based on these simulations, we find that the signal versus the noise of SST variability in the North Pacific is significantly different from that in the equatorial Pacific. The noise SST variability explains the majority of the total variability in the North Pacific, whereas the signal dominates in the deep tropics. It is also found that the spatial characteristics of the signal and the noise are also distinct in the North Pacific and equatorial Pacific.

• Atmosphere
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• v.23 no.2
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• pp.205-220
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• 2013

Upper ocean response to typhoon Ewiniar (0603) and its impact on the following typhoon Bilis (0604) are investigated using observational data and numerical experiments. Data used in this study are obtained from the Ieodo Ocean Research Station (IORS), ARGO, and satellite. Numerical simulations are conducted using 3-dimensional Princeton Ocean Model. Results show that when Ewiniar passes over the western North Pacific, unique oceanic responses are found at two places, One is in East China Sea near Taiwan and another is in the vicinity of IORS. The latter are characterized by a strong sea surface cooling (SSC), $6^{\circ}C$ and $11^{\circ}C$ in simulation and observation, under the condition of typhoon with a fast translation speed (8m $s^{-1}$) and lowering intensity (970 hPa). The record-breaking strong SSC is caused by the Yellow Sea Bottom Cold Water, which produces a strong vertical temperature gradient within a shallow depth of Yellow Sea. The former are also characterized by a strong SSC, $7.5^{\circ}C$ in simulation, with a additional cooling of $4.5^{\circ}C$ after a storm's passage mainly due to enhanced and maintained upwelling process by the resonance coupling of storm translation speed and the gravest mode internal wave phase speed. The numerical simulation reveals that the Ewiniar produced a unfavorable upper-ocean thermal condition, which eventually inhibited the intensification of the following typhoon Bilis. Statistics show that 9% of the typhoons in western North Pacific are influenced by cold wakes produced by a proceeding typhoon. These overall results demonstrate that upper ocean response to a typhoon even after the passage is also important factor to be considered for an accurate intensity prediction of a following typhoon with similar track.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.3 no.1
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• pp.16-24
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• 1998

In this study, Ocean General Circulation Model (OGCM) has been developed as a counterpart of Atmospheric General Circulation (AGCM) for the study of coupled ocean-atmosphere climate system. The oceanic responses to given atmospheric boundary conditions have been investigated using the OGCM. In an integration carried out over 100 simulated years with climatological monthly mean data (EXP 1), most parts of the model reached a quasi-equilibrium climate reproducing many of the observed large-scale oceanic features remarkably well. Some observed narrow currents, however, such as North Equatorial Counter Current, were inevitably distorted due to the model's relatively coarse resolution. The seasonal changes in sea ice cover over the southern oceans around Antarctica were also simulated. In an experiment (EXP 2) under boundary condition of 10-year monthly data (1982-1991) from NCEP/NCAR Reanalysis Project model properly reproduced major oceanic changes during the period, including El Ni$\tilde{n}$os of 1982-1983 and 1986-87. During the ENSO periods, the experiment showed eastward expansion of warm surface waters and a negative vertical velocity anomalies along' the equator in response to expansion of westerly current velocity anomalies as westerly wind anomalies propagated eastward. Simulated anomalous distribution and the time behavior in response to El Ni$\tilde{n}$o events is consistent with that of the observations. These experiments showed that the model has an ability to reproduce major mean and anomalous oceanic features and can be effectively used for the study of ocean-atmosphere coupling system.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1229-1238
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• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.

• Journal of the Korean Society for information Management
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• v.37 no.1
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• pp.153-177
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• 2020

In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.

• Journal of the Korean earth science society
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• v.43 no.6
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• pp.691-711
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• 2022

The state-of-the-art Earth system model as a virtual Earth is required for studies of current and future climate change or climate crises. This complex numerical model can account for almost all human activities and natural phenomena affecting the atmosphere of Earth. The Unified Model (UM) from the United Kingdom Meteorological Office (UK Met Office) is among the best Earth system models as a scientific tool for studying the atmosphere. However, owing to the expansive numerical integration cost and substantial output size required to maintain the UM, individual research groups have had to rely only on supercomputers. The limitations of computer resources, especially the computer environment being blocked from outside network connections, reduce the efficiency and effectiveness of conducting research using the model, as well as improving the component codes. Therefore, this study has presented detailed guidance for installing a new version of the UM on high-performance parallel computers (Linux clusters) owned by individual researchers, which would help researchers to easily work with the UM. The numerical integration performance of the UM on Linux clusters was also evaluated for two different model resolutions, namely N96L85 (1.875° ×1.25° with 85 vertical levels up to 85 km) and N48L70 (3.75° ×2.5° with 70 vertical levels up to 80 km). The one-month integration times using 256 cores for the AMIP and CMIP simulations of N96L85 resolution were 169 and 205 min, respectively. The one-month integration time for an N48L70 AMIP run using 252 cores was 33 min. Simulated results on 2-m surface temperature and precipitation intensity were compared with ERA5 re-analysis data. The spatial distributions of the simulated results were qualitatively compared to those of ERA5 in terms of spatial distribution, despite the quantitative differences caused by different resolutions and atmosphere-ocean coupling. In conclusion, this study has confirmed that UM can be successfully installed and used in high-performance Linux clusters.