• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Atmosphere
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• v.33 no.5
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• pp.531-548
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• 2023

We developed the Aviation Convective Index (ACI) for predicting deep convective area using the operational global Numerical Weather Prediction model of the Korea Meteorological Administration. Seasonally optimized ACI (ACI_SnOpt) was developed to consider seasonal variabilities on deep convections in Korea. Yearly optimized ACI (ACI_YrOpt) in Part 1 showed that seasonally averaged values of Area Under the ROC Curve (AUC) and True Skill Statistics (TSS) were decreased by 0.420% and 5.797%, respectively, due to the significant degradation in winter season. In Part 2, we developed new membership function (MF) and weight combination of input variables in the ACI algorithm, which were optimized in each season. Finally, the seasonally optimized ACI (ACI_SnOpt) showed better performance skills with the significant improvements in AUC and TSS by 0.983% and 25.641% respectively, compared with those from the ACI_YrOpt. To confirm the improvements in new algorithm, we also conducted two case studies in winter and spring with observed Convectively-Induced Turbulence (CIT) events from the aircraft data. In these cases, the ACI_SnOpt predicted a better spatial distribution and intensity of deep convection. Enhancements in the forecast fields from the ACI_YrOpt to ACI_SnOpt in the selected cases explained well the changes in overall performance skills of the probability of detection for both "yes" and "no" occurrences of deep convection during 1-yr period of the data. These results imply that the ACI forecast should be optimized seasonally to take into account the variabilities in the background conditions for deep convections in Korea.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.163-169
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• 2003

• Korean Journal of Fisheries and Aquatic Sciences
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• v.47 no.3
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• pp.264-273
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• 2014

To investigate species composition and seasonal variation of demersal organisms in the coastal waters off the Taean peninsula, otter trawl surveys were conducted from April 2010 to January 2011. A total of 75 species were collected, including 44 species of Pisces, 19 species of Crustacea, 6 species of Cephalopoda, 4 species of Gastropoda, and 1 species each of Bivalvia and Echinoidea. The dominant species in each season were Palaemon gravieri in spring, Charybdis bimaculata in summer, Loligo japonica in autumn, and Crangon hakodatei in winter. The number of species, individuals and biomass were highest in autumn and lowest in winter. The diversity index was highest in summer and lowest in winter. The dominance index was highest in winter and lowest in summer. The richness index was highest in autumn and lowest in winter. The evenness index was highest in summer and lowest in autumn. A cluster analysis showed that demersal organisms were divided into two groups; spring and winter organisms (Group 1) and summer and autumn organisms (Group 2). We detected a significant difference (P<0.05) between these groups, mainly owing to Platycephalus indicus, Repomucenus koreanus, and Paralichthys olivaceus within Pisces: Trachysalambria curvirostris, Metapenaeopsis dalei, P. gravieri, and C. hakodatei within Crustacea: and L. japonica within Cephalopoda.

• Fisheries and Aquatic Sciences
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• v.5 no.2
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• pp.114-121
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• 2002

A correction index of catchability (CIC) was derived using a 6 year research data set to examine the seasonal variation in catchability for the night time prawn fishery in Albatross Bay. CIC reflects the composite effect of the monthly variation in size selectivity, emergence­burying behaviour and population density variation of prawn populations. The values of CIC for four dominant species, Metapenaeus endeavouri, M. ensis, Penaeus semisulcatus and P. esculentus, were examined. The value of CIC for M. endeavouri varied substantially and was the highest in August. The values of CIC for M. ensis were high during November to March and the seasonality was weaker than that for M. endeavouri. The monthly variation in CIC for P. semisulcatus reflected the seasonal variation in population density, being high during November to February. These results suggest that the catch ability of P. esculentus is steady throughout the year but it varies greatly on a seasonal basis for M. endeavouri.

• Atmosphere
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• v.24 no.2
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• pp.235-243
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• 2014

Sources of aviation turbulence vary through the seasons, especially in the East Asia including Korean peninsula, associated primarily with the changes in the jet/front system and convective activities. For this reason, a seasonal Korean aviation Turbulence Guidance (KTG) system (seasonal-KTG) is developed in the present study by using pilot reports (PIREPs) and analysis data of the operational Unified Model (UM) of the Korea Meteorological Administration (KMA) for two years between June 2011 and May 2013. Twenty best diagnostics of aviation turbulence in each season are selected by the method of probability of detection (POD) using the PIREPs and UM data. After calculating a weighting value of each selected diagnostics using their area under curve (AUC), the 20 best diagnostics are combined with the weighting scores into a single ensemble-averaged index by season. Compared with the current operational-KTG system that is based on the diagnostics applying all seasons, the performances of the seasonal-KTG system are better in all seasons, except in fall.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.1
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• pp.31-37
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• 1988

This study, based on the monthly rainfall data, was carried out to determine the agricultural drought index which enables to describe the regional and seasonal drought characteristics of rice cropping system in Korea. The results obtained were summarized as follows ; 1.A new agricultural drought index (ADI) was evaluated seasonally according to the product of drought intensity and duration. This ADI is proposed as standard design criterion for irrigation planning. 2.The relationship between agricultural drought index and return periods was figured out. These diagrams could be used to estimate the seasonal drought severity of a certain year and to select design year corresponding to the specific drought frequency. 3.The regional drought characteristics were classified and those are useful to determine proper rice varieties and planting time and make drought counterplans. 4.Spring drought occurred once in 3 or 4 years and in a regional respect, rather frequently occurred in Seoul and Daegu areas than in Busan, Daejeon, Kwangju and Chuncheon areas. Summer drought occurred once in 5 years in Daegu and Busan areas and once in 7 or 8 years in other areas. 5.Sequential drought which gave severe drought damage of rice production occurred once in 20 years in Daegu area and in 10 years in Kwangju area.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.5
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• pp.571-578
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• 2018

Seasonal variability in algal community structure of the subtidal zone was examined at four study sites on the southeastern coast of Korea from February to November 2016. A total of 81 species of algae (8 green, 12 brown, and 61 red) were indentified. During the study period, the greatest number of species was observed at Sinamri (57 species) followed by Daesongri (50 species), Dongbaekri (47 species) and Gangyangri (42 species). Of the six functional seaweed forms, the coarsely-branched form was the most dominant, accounting for about 43% of the total species at Daesongri. The annual average biomass in wet weight varied from $700.59g/m^2$ at Sinamri to $1,712.45g/m^2$ at Daesongri. The parameters of seaweed community structures were as follows: dominance index (DI), 0.30-0.54; richness index (R), 4.92-7.05; evenness index (J'), 0.54-0.72; and diversity index (H'), 2.05-2.91.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1257-1264
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• 2018

This paper proposes Autoregressive Integrated Moving Average (ARIMA)-based forecasting algorithms using meteorological indices to predict seasonal peak load. First of all, this paper observes a seasonal pattern of the peak load that appears intensively in winter and summer, and generates ARIMA models to predict the peak load of summer and winter. In addition, this paper also proposes hybrid ARIMA-based models (ARIMA-Hybrid) using a discomfort index and a sensible temperature to enhance the conventional ARIMA model. To verify the proposed algorithm, both ARIMA and ARIMA-Hybrid models are developed based on peak load data obtained from 2006 to 2015 and their forecasting results are compared by using the peak load in 2016. The simulation result indicates that the proposed ARIMA-Hybrid models shows the relatively improved performance than the conventional ARIMA model.

• Korean Journal of Microbiology
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• v.27 no.4
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• pp.378-384
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• 1989

The numerical taxonomy of heterotrophic bacterial community in Lake Soyang was analysed. 95, 115, 88 and 75 strains which were isolated at each season from spring in 1987 to winter in 1988 were clustered by single matching coefficient. The diversity indices (H') were in the range of 0.511-1.684, and the community was most diverse in spring. THe seasonal variation of generic composition was significant. Of the domonant genera, Acinetobacter, Pseudomonas, and Flavobacterium were representative.