• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.169-177
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• 1999

There is some limitations for ship to gather weather and sea state information. To make up for this weakness, land organizations can gather the wider variety of information, evaluate the navigational safety on a ship, and supply this information to the ship. In this study, the involuntary speed loss are calculated using the real-time information on weather and considering the increase of resistance induced by wave, and the navigational safety in a seaway is evaluated. The used model for computer simulation is Lpp 93m frigate class ship. The feasibility study is made of using simulation results in actual operation.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1031-1041
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• 2018

ANFIS-based methodology for improving GloSea5 ensemble weather forecast is developed and evaluated in this study. The proposed method consists of two steps: pre & post processing. For ensemble prediction of GloSea5, weights are assigned to the ensemble members based on Optimal Weighting Method (OWM) in the pre-processing. Then, the bias of the results of pre-processed is corrected based on Model Output Statistics (MOS) method in the post-processing. The watershed of the Chungju multi-purpose dam in South Korea is selected as a study area. The results of evaluation indicated that the pre-processing step (CASE1), the post-processing step (CASE2), pre & post processing step (CASE3) results were significantly improved than the original GloSea5 bias correction (BC_GS5). Correction performance is better the order of CASE3, CASE1, CASE2. Also, the accuracy of pre-processing was improved during the season with high variability of precipitation. The post-processing step reduced the error that could not be smoothed by pre-processing step. It could be concluded that this methodology improved the ability of GloSea5 ensemble weather forecast by using ANFIS, especially, for the summer season with high variability of precipitation when applied both pre- and post-processing steps.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.489-498
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• 2023

Advancements in hardware performance and computing technology have facilitated the progress of climate prediction models to address climate change. The Korea Meteorological Administration employs the GloSea6 model with supercomputer technology for operational use. Various universities and research institutions utilize the Low-GloSea6 model, a low-resolution coupled model, on small to medium-scale servers for weather research. This paper presents an analysis using Intel VTune Profiler on Low-GloSea6 to facilitate smooth weather research on small to medium-scale servers. The tri_sor_dp_dp function of the atmospheric model, taking 1125.987 seconds of CPU time, is identified as a hotspot. Nonlinear regression models, a machine learning technique, are applied and compared to existing functions conducting numerical operations. The K-Nearest Neighbors regression model exhibits superior performance with MAE of 1.3637e-08 and SMAPE of 123.2707%. Additionally, the Light Gradient Boosting Machine regression model demonstrates the best performance with an RMSE of 2.8453e-08. Therefore, it is confirmed that applying a nonlinear regression model to the tri_sor_dp_dp function during the execution of Low-GloSea6 could be a viable alternative.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.4
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• pp.94-100
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• 2006

The purpose of this case study is to determine the possibility of Numerical Forecasting of sea fog at West Sea in spring time. For practical method of analyzing the data collected from 24th to 26th March 2003, Numerical Weather Prediction model MM5(Mesoscale Model Version 5) and synoptic field study using synoptic chart, upper level chart, and sea surface temperature were employed. The results of synoptic field analysis summarized that sea fog at West sea in spring is intensified by the inflow of the warm flow from west or southwest, low sea surface temperature to increase the temperature difference between air and sea surface, and inversion layer to disturb the disperse. It appears that the possibility of sea fog forecasting by MM5, in view of the result that the MM5 output is similar to the synoptic fields analysis.

• Water for future
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• v.21 no.4
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• pp.389-397
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• 1988

For determination of the design wves at the seven selected sites in the South Sea, a method of hindcasting the past annual largest significant waves from the records of both the wind speed at the nearby weather stations and the weather charts of typhoons are utilized. The design significant waves in deep water are determined through the extremal probability analysis for three major wave directions(SW, S, SE) at each site from the annual extremal series of wave heights. Design significant wave heights with the return period of 100 years ranged between 4.6m and 8.8m with the wave period ranging between 8.2 seconds and 12.9 seconds. Through the analysis of weather maps, both the fetches for the wind directions SW-SE along the South Coast and the relationship between the wind speed at sea and the wind speed at the nearby land weather stations for seasonal winds are determined. The wind speed at sea are found to be 0.8-0.9 times the wind speed at the land stations for $U_1$>15m/s. The ratio of the duration-averaged wind speed to the maximum wind speed varies between 0.7-0.9 as a negative exponential function for the duration ranging 2< t< 13 hours.

• Atmosphere
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• v.31 no.4
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• pp.433-443
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• 2021

The wind speed and wind direction in Yeongdong are one of the crucial meteorological factors for forecasting snowfall in this area. To improve the snowfall forecast in Yeongdong region, Yeongdong Extreme Snowfall-Windstorm Experiment, YES-WEX was designed. We examined the wind field variation simulated with Local Data Assimilation and Prediction System (LDAPS) using observed wind field during YES-WEX period. The simulated wind speed was overestimated over the East Sea and especially 2 to 4 times in the coastal line. The vertical wind in Yeongdong region, which is a crucial factor in the snowfall forecast, was not well simulated at the low level (850 hPa~1000 hPa) until 12 hours before the forecast. The snowfall distribution was also not accurately simulated. Three hours after the snowfall on the East Sea coast was observed, the snowfall was simulated. To improve the forecast accuracy of snowfall in Yeongdong region, it is important to understand the weather conditions using the observed and simulated data. In the future, data in the northern part of the East Sea and the mountain slope of Taebaek observed from the meteorological aircraft, ship, and drone would help in understanding the snowfall phenomenon and improving forecasts.

• Atmosphere
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• v.25 no.1
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• pp.51-66
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• 2015

This study was conducted to perform various sensitivity experiments using WRF (Weather Research and Forecasting) model in order to determine the effects of terrains of the Korean Peninsula and the land-sea thermal contrast on the formation and development of the convergent cloud band for the cases of 1 February 2012. The sensitivity experiments consist of the following five ones: CNTL experiment (control experiment), and TMBT experiment, BDMT experiment and ALL experiment that set the terrain altitude of Taeback Mountains and Northern mountain complex as zero, respectively, and the altitude of the above-mentioned two mountains as zero, and LANDSEA experiment that set to change the Korean Peninsula into sea in order to find out the land-sea thermal contrast effect. These experiment results showed that a cold air current stemming from the Siberian high pressure met the group of northern mountains with high topography altitude and was separated into two air currents. These two separated air currents met each other again on the Middle and Northern East Sea, downstream of the group of northern mountains and converged finally, creating the convergent cloud band. And these experiments suggested that the convergent cloud band located on the Middle and Northern East Sea, and the cloud band lying on the southern East sea to the coastal waters of the Japanese Island facing the East Sea, were generated and developed by different dynamical mechanisms. Also it was found that the topography of Taeback Mountains created a warm air advection region due to temperature rise by adiabatic compression near the coastal waters of Yeongdong Region, downstream of the mountains. In conclusion, these experiment results clearly showed that the most essential factor having an effect on the generation and development of the convergent cloud band was the topography effect of the northern mountain complex, and that the land-sea thermal contrast effect was insignificant.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.409-431
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• 2014

In this study, the characteristics in the simulation of high-resolution coastal weather, i.e. sea surface wind (SSW) and significant wave height (SWH), were studied in a southeastern coastal region of Korea using the WRF and SWAN models. This analyses was performed based on the effects of various input factors in the WRF and SWAN model during M-Case (moderate days with average 1.8 m SWH and $8.4ms^{-1}$ SSW) and R-Case (rough days with average 3.4 m SWH and $13.0ms^{-1}$ SSW) according to the strength of SSW and SWH. The effects of topography (TP), land cover (LC), and sea surface temperature (SST) for the simulation of SSW with the WRF model were somewhat high on v-component winds along the coastline and the adjacent sea of a more detailed grid simulation (333 m) during R-Case. The LC effect was apparent in all grid simulations during both cases regardless of the strength of SSW, whereas the TP effect had shown a difference (decrease or increase) of wind speed according to the strength of SSW (M-Case or R-Case). In addition, the effects of monthly mean currents (CR) and deepwater design waves (DW) for the simulation of SWH with the SWAN model predicted good agreement with observed SWH during R-Case compared to the M-Case. For example, the effects of CR and DW contributed to the increase of SWH during R-Case regardless of grid resolution, whereas the differences (decrease or increase) of SWH occurred according to each effect (CR or DW) during M-Case.

• Journal of the korean society of oceanography
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• v.39 no.4
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• pp.212-221
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• 2004

Concentrations of suspended particulate matters (SPM) and their distribution patterns were monitored three times in the East China Sea during the winter season in 1998 and 1999. SPM concentrations showed significant temporal variations controlled by the atmospheric conditions and sea states. In coastal area, SPM values were about 10-20 mg/l in fair weather conditions, but exceeded 100mg/l during the storm periods. Turbid waters were distributed widespread in the continental shelf of the East China Sea and the coastal area of the Korean Peninsula, and these two areas were connected along a NE-SW direction. The distribution patterns of turbid waters were interpreted as representing the transport behavior of suspended matter. Although the primary source of inner shelf mud deposits of Korea seems to be the Korean Peninsula, contribution from the East China Sea to the coastal area of Korea increases especially during the winter season.

• Atmosphere
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• v.29 no.4
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• pp.451-461
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• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.