• 한국수산과학회지
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• 제25권6호
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• pp.457-473
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• 1992

양향성 대륙붕에서 1차 파동방정식은 양 해안경계에서의 바람응력과, 대륙붕폭에 걸친 바람응력의 회전효과를 갖는다. 황해에서 바람응력 회전효과는 대륙붕파를 발생시키는 힘으로서 무시될 수 있다. 켈빈파는 대륙붕파보다 약화될 때까지의 거리가 매우 크기 때문에 황해 북쪽만(별)을 거의 약화되지 않고 통과할 수 있다. 파동특성을 따라 적분하는 수치방법은 반대방향으로 전파되는 파동을 수용하기 위해 조절되었다. 보다 실제와 가까운 해안선을 사용한 결과, 모델재생이 해류에서는 개선되었으나 해수면에서는 거의 개선되지 않았다. 이것은 해수면을 주로 결정하는 켈빈파가 해저지형의 변화에 영향을 극히 적게 받음을 의미한다 보다 개선된 해수면 재생을 위해서는 동지나 해에서 황해로 전파되는 켈빈파의 에너지를 알 필요가 있다. 해안을 따른 순풍류와 골을 따른 역풍류의 기본구조는 계절풍에 의해 발생하는 황해의 계절순환을 뒷받침한다.

• 대기
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• 제30권2호
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

• 대기
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• 제26권1호
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• pp.203-214
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• 2016

This study explores the 6-month lead prediction skill of stratospheric temperature and circulations in the Global Seasonal forecasting model version 5 (GloSea5) hindcast experiment over the period of 1996~2009. Both the tropical and extratropical circulations are considered by analyzing the Quasi-Biennial Oscillation (QBO) and Northern Hemisphere Polar Vortex (NHPV). Their prediction skills are quantitatively evaluated by computing the Anomaly Correlation Coefficient (ACC) and Mean Squared Skill Score (MSSS), and compared with those of El Nino-Southern Oscillation (ENSO) and Arctic Oscillation (AO). Stratospheric temperature is generally better predicted than tropospheric temperature. Such improved prediction skill, however, rapidly disappears in a month, and a reliable prediction skill is observed only in the tropics, indicating a higher prediction skill in the tropics than in the extratropics. Consistent with this finding, QBO is well predicted more than 6 months in advance. Its prediction skill is significant in all seasons although a relatively low prediction skill appears in the spring when QBO phase transition often takes place. This seasonality is qualitatively similar to the spring barrier of ENSO prediction skill. In contrast, NHPV exhibits no prediction skill beyond one month as in AO prediction skill. In terms of MSSS, both QBO and NHPV are better predicted than their counterparts in the troposphere, i.e., ENSO and AO, indicating that the GloSea5 has a higher prediction skill in the stratosphere than in the troposphere.

• 대기
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• 제29권3호
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• pp.295-309
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• 2019

Due to frequent occurrence of abnormal weather, the need to improve the accuracy of subseasonal prediction has increased. Here we analyze the performance of weekly predictions out to 6 weeks by GloSea5 climate model. The performance in circulation field from January 1991 to December 2010 is first analyzed at each grid point using the 500-hPa geopotential height. The anomaly correlation coefficient and mean-square skill score, calculated each week against the ECWMF ERA-Interim reanalysis data, illustrate better prediction skills regionally in the tropics and over the ocean and seasonally during winter. Secondly, we evaluate the predictability of 7 major teleconnection patterns in the Northern Hemisphere: North Atlantic Oscillation (NAO), East Atlantic (EA), East Atlantic/Western Russia (EAWR), Scandinavia (SCAND), Polar/Eurasia (PE), West Pacific (WP), Pacific-North American (PNA). Skillful predictability of the patterns turns out to be approximately 1~2 weeks. During summer, the EAWR and SCAND, which exhibit a wave pattern propagating over Eurasia, show a considerably lower skill than the other 5 patterns, while in winter, the WP and PNA, occurring in the Pacific region, maintain the skill up to 2 weeks. To account for the model's bias in reproducing the teleconnection patterns, we measure the similarity between the teleconnection patterns obtained in each lead time. In January, the model's teleconnection pattern remains similar until lead time 3, while a sharp decrease of similarity can be seen from lead time 2 in July.

• 대기
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• 제31권2호
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• pp.215-227
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• 2021

The necessity of the prediction on the Seasonal-to-Subseasonal (S2S) timescale continues to rise. It led a series of studies on the S2S prediction models, including the Global Seasonal Forecasting System Version 5 (GloSea5) of the Korea Meteorological Administration. By extending previous studies, the present study documents sea surface temperature (SST) prediction skill around the Korean peninsula in the GloSea5 hindcast over the period of 1991~2010. The overall SST prediction skill is about a week except for the regions where SST is not well captured at the initialized date. This limited prediction skill is partly due to the model mean biases which vary substantially from season to season. When such biases are systematically removed on daily and seasonal time scales the SST prediction skill is improved to 15 days. This improvement is mostly due to the reduced error associated with internal SST variability during model integrations. This result suggests that SST around the Korean peninsula can be reliably predicted with appropriate post-processing.

• 한국지구과학회지
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• 제42권6호
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• pp.605-622
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• 2021

Seasonal forecasting has numerous socioeconomic benefits because it can be used for disaster mitigation. Therefore, it is necessary to diagnose and improve the seasonal forecast model. Moreover, the model performance is partly related to the ocean model. This study evaluated the hindcast performance in the upper ocean of the Global Seasonal Forecasting System version 5-Global Couple Configuration 2 (GloSea5-GC2) using a multivariable integrated evaluation method. The normalized potential temperature, salinity, zonal and meridional currents, and sea surface height anomalies were evaluated. Model performance was affected by the target month and was found to be better in the Pacific than in the Atlantic. An increase in lead time led to a decrease in overall model performance, along with decreases in interannual variability, pattern similarity, and root mean square vector deviation. Improving the performance for ocean currents is a more critical than enhancing the performance for other evaluated variables. The tropical Pacific showed the best accuracy in the surface layer, but a spring predictability barrier was present. At the depth of 301 m, the north Pacific and tropical Atlantic exhibited the best and worst accuracies, respectively. These findings provide fundamental evidence for the ocean forecasting performance of GloSea5.

• 대기
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• 제32권2호
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• pp.149-162
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• 2022

This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation for the period of 1991~2016. Additionally, we evaluated the prediction skill of those variables depending on the combination of the initial dates in the sub-seasonal scale for the dust source region affecting South Korea. The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) from GloSea5-ADAM were compared to that from Synoptic observation and European Centre for medium range weather forecasts reanalysis v5, respectively, based on Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC) as evaluation criteria. In general, the Asian dust and meteorological variables in the source region showed high ACC in the prediction scale within one month. For all variables, the use of the initial dates closest to the prediction month led to the best performances based on MBE, RMSE, and ACC, and the performances could be improved by adjusting the number of ensembles considering the combination of the initial date. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions.

• 대기
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• 제34권2호
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• pp.97-106
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• 2024

The seasonal forecast skill of tropical cyclones (TCs) in the Northern Hemisphere from the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 6 (GloSea6) hindcast has been verified for the period 1993 to 2016. The operational climate prediction system at KMA was upgraded from GloSea5 to GloSea6 in 2022, therefore further validation was warranted for the seasonal predictability and variability of this new system for TC forecasts. In this study, we examine the frequency, track density, duration, and strength of TCs in the North Indian Ocean, the western North Pacific, the eastern North Pacific, and the North Atlantic against the best track data. This methodology follows a previous study covering the period 1996 to 2009 published in 2020. GloSea6 indicates a higher frequency of TC generation compared to observations in the western North Pacific and the eastern North Pacific, suggesting the possibility of more TC generation than GloSea5. Additionally, GloSea6 exhibits better interannual variability of TC frequency, which shows relatively good correlation with observations in the North Atlantic and the western North Pacific. Regarding TC intensity, GloSea6 still underestimates the minimum surface pressures and maximum wind speeds from TCs, as is common among most climate models due to lower horizontal resolutions. However, GloSea6 is likely capable of simulating slightly stronger TCs than GloSea5, partly attributed to more frequent 6-hourly outputs compared to the previous daily outputs.

• 한국해안·해양공학회논문집
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• 제36권2호
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• pp.61-69
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• 2024

해상풍력 단지 개발 시 파랑은 구조물 설계 하중 결정과 단지 배치 등에 있어서 필수적으로 고려되어야 한다. 그러나 해상풍력 개발지역으로 간주되고 있는 왕등도 인근 해역에 대한 파랑 후측 연구는 부족한 실정이다. 본 연구에서는 MIKE 21 모델을 이용하여 2021년 1년간 왕등도 중심의 서남해 파랑 후측을 통해 왕등도 인근 파랑 특성을 분석하였다. 파랑 후측 결과 상왕등도 부이와 부안 부이에서 유의파고에 대한 RMSE가 0.177, 0.225 Pearson 상관계수는 0.971, 0.970으로 높은 재현성을 보여주었다. 모델의 검증 후 왕등도 인근 해역에 대한 파랑 특성을 분석한 결과 계절에 따라 파랑이 크게 달라지는 경향을 보였다. 최대 유의파고 발생 시 위치별로 큰 차이를 보였으며 이는 해상풍력 구조물의 설계 하중 결정에 있어 중요한 영향을 미칠 것으로 예상된다.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 춘계학술대회 초록집
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• pp.164.1-164.1
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• 2011

Previously, many researchers assessed nearshore wave energy in two ways. The first is a simulation with respect to the offshore wave time series to validate the wave buoy data and the wave model results, and the other is to simulate the representative waves of typical seasonal wave conditions. The former requires enormous computational time and effort. The latter yields inspection on the patterns for the spatial and temporal distribution of nearshore wave energy but tends to underestimates the amount of wave energy in the nearshore region owing to the correlation between the significant wave height and wave period. $\ddot{O}$zger et al. (2004) derived the stochastic wave energy formulation by introducing a correction factor explicitly in terms of the covariance of the wave energy and significant wave height. In this study, a correction factor was applied for the assessment of nearshore wave energy obtained by numerical simulation of wave transformation with respect to representative waves.