• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.368-368
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• 2022

The Soil and Water Assessment Tool (SWAT) has been widely used to simulate the long-term hydrological conditions of a catchment. Two output variables, outflow and sediment yield have been widely investigated in the field of water resources management, especially in determining the conditions of ungauged subbasins. The presence of missing data in weather input data can cause poor representation of the climate conditions in a catchment especially for large or mountainous catchments. Therefore, in this study, a custom module was developed and evaluated to determine the efficiency of utilizing basic spatial interpolation methods in the estimation of weather input data. The module has been written in Python language and can be considered as a pre-processing module prior to using the SWAT model. The results of this study suggests that the utilization of the proposed pre-processing module can improve the simulation results for both outflow and sediment yield in a catchment, even in the presence of missing data.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.103-114
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• 2017

Radiation energy budget was analyzed using observation data from the Weather Information Service Engine (WISE) energy flux tower on the Seoul metropolitan area. Among observation data from the 13 energy flux towers, we used meteorological variables, radiation data (upward and downward short wave, upward and downward long wave, net short wave, net long wave and net radiation), albedo and emissivity for 15 months from July 2016 to September 2017. Although Gajwa (205) and Ttuksumm (216) sites located in urban, the albedo was relatively high due to the surround environment by glass wall buildings and the Han river around the sites. And Bucheon (209) site located in the suburb represented generally low emissivity. As a result, the albedo decreased and the emissivity increased in the city center. In the Seoul metropolitan area, the net radiation energy is $73.9W/m^2$ that the radiation budget of the surface is absorbed into the atmosphere. According to WISE observation data, it can be seen that observation at each sites are influenced by the surrounding environment.

• The Plant Pathology Journal
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• v.39 no.6
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• pp.548-565
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• 2023

Armillaria root disease affects forests around the world. It occurs in many habitats and causes losses in the infested stands. Weather conditions are important factors for growth and development of Armillaria species. Yet, the relation between occurrence of damage caused by Armillaria disease and weather variables are still poorly understood. Thus, we used generalized linear mixed models to determine the relationship between weather conditions of current and previous year (temperature, precipitation and their deviation from long-term averages, air humidity and soil temperature) and the incidence of Armillaria-induced damage in young (up to 20 years old) and older (over 20 years old) coniferous stands in selected forest districts across Poland. We used unique data, gathered over the course of 23 years (1987-2009) on tree damage incidence from Armillaria root disease and meteorological parameters from the 24-year period (1986-2009) to reflect the dynamics of damage occurrence and weather conditions. Weather parameters were better predictors of damage caused by Armillaria disease in younger stands than in older ones. The strongest predictor was soil temperature, especially that of the previous year growing season and the current year spring. We found that temperature and precipitation of different seasons in previous year had more pronounced effect on the young stand area affected by Armillaria. Each stand's age class was characterized by a different set of meteorological parameters that explained the area of disease occurrence. Moreover, forest district was included in all models and thus, was an important variable in explaining the stand area affected by Armillaria.

• Atmosphere
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• v.26 no.4
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• pp.495-508
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• 2016

In order to determine the prediction possibility of heavy rainfall, a variety of analyses was conducted by using three-dimensional data obtained from Korea Local Analysis and Prediction System (KLAPS) re-analysis data. Strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Heavy rainfall occurred in the cloud system with a thick convective clouds. The moisture convergence, temperature and potential temperature advection showed increase into the heavy rainfall occurrence area. The distribution of integrated liquid water content tended to decrease as rainfall increased and was characterized by accelerated convective instability along with increased buoyant energy. In addition, changes were noted in the various characteristics of instability indices such as K-index (KI), Showalter Stability Index (SSI), and lifted index (LI). The meteorological variables used in the analysis showed clear increases or decreases according to the changes in rainfall amount. These rapid changes as well as the meteorological variables changes are attributed to the surrounding and meteorological conditions. Thus, we verified that heavy rainfall can be predicted according to such increase, decrease, or changes. This study focused on quantitative values and change characteristics of diagnostic variables calculated by using numerical models rather than by focusing on synoptic analysis at the time of the heavy rainfall occurrence, thereby utilizing them as prognostic variables in the study of the predictability of heavy rainfall. These results can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of such precipitation. In the analysis of various case studies of heavy rainfall in the future, our study result can be utilized to show the development of the prediction of severe weather.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.527-536
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• 2012

In this paper we analyze the effect of circular variables such as wind direction, time and month on the ozone level. In particular, we examined the effect of wind direction by exploratory data analysis methods and provide the correlation and regression analyzes in the cases including all circular explanatory variables. In the analysis, we convert time and month variables to circular variables and analyze the effect of these variables on regression analysis; in addition, we also consider circular-circular regression. We used weather condition and air pollution data collected from Dongdaemoon district of Seoul in 2007.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.625-634
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• 2016

Three leading agencies under different ministries - Korea Meteorological Administration (KMA) in the ministry of Environment, Han river control office in the Ministry of Land, Infrastructure and Transport (MOLIT) and Weather Group of ROK Air Force in the Ministry of National Defense (MND) - have been operated radars in the purpose of observing weather, hydrology and military operational weather in Korea. Eight S-band dual-pol. radars have been newly installed or replaced by these ministries over different places by 2015. However each ministry has different aims of operating radars, observation strategies, data processing algorithms, etc. Due to the differences, there is a wide level of accuracy on observed radar data as well as the composite images made of the cross governmental radar measurement. Gaining fairly high level of accuracy on radar data obtained by different agencies has been shared as a great concern by the ministries. Thus, "an agreement of harmonizing weather and hydrological radar products" was made by the three ministries in 2010. Particularly, this is very important to produce better rainfall estimation using the cross governmental radar measurement. Weather Radar Center(WRC) in KMA has been developed an empirical method using measurements observed by Yongin testbed radar. This study is aiming to examine the efficiency of the empirical method to improve the accuracies of radar rainfalls estimated from cross governmental dual-pol. radar measurements. As a result, the radar rainfalls of three radars (Baengnyeongdo, Biseulsan, and, Sobaeksan Radar) were shown improvement in accuracy (1-NE) up to 70% using data from May to October in 2015. Also, the range of the accuracies in radar rainfall estimation, which were from 30% to 60% before adjusting polarimetric variables, were decreased from 65% to 70% after adjusting polarimetric variables.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.230-236
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• 2024

This study aimed to analyze the environmental factors affecting tomato growth by examining the correlation between weather and growth environment sensor data from P Smart Farm located in Gwangseok-myeon, Nonsan-si, Chungcheongnam-do. Key environmental variables such as the temperature, humidity, sunlight hours, solar radiation, and daily light integral (DLI) significantly affect tomato growth. The optimal temperature and DLI conditions play crucial roles in enhancing tomato growth and the photosynthetic efficiency. In this study, we developed a model to correct and predict the time-series variations in internal environmental sensor data using external weather sensor data. A linear regression analysis model was employed to estimate the external temperature variations and internal DLI values of P Smart Farm. Then, regression equations were derived based on these data. The analysis verified that the estimated variations in external temperature and internal DLI are explained effectively by the regression models. In this research, we analyzed and monitored smart-farm growth environment data based on weather sensor data. Thereby, we obtained an optimized model for the temperature and light conditions crucial for tomato growth. Additionally, the study emphasizes the importance of sensor-based data analysis in dynamically adjusting the tomato growth environment according to the variations in weather and growth conditions. The observations of this study indicate that analytical solutions using public weather data can provide data-driven operational experiences and productivity improvements for small- and medium-sized facility farms that cannot afford expensive sensors.

• Atmosphere
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• v.21 no.2
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• pp.197-208
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• 2011

The objective of this study is to describe the short-range forecast system of the Korea Air Force (KAF) and to verificate its performace in 2009 summer. The KAF weather prediction model system, based on the Weather Research and Forecasting (WRF) model (i.e., the KAF-WRF), is configured with a parent domain overs East Asia and two nested domains with the finest horizontal grid size of 2 km. Each domain covers the Korean peninsula and South Korea, respectively. The model is integrated for 84 hour 4 times a day with the initial and boundary conditions from National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data. A quantitative verification system is constructed for the East Asia and Korean peninsula domains. Verification variables for the East Asia domain are 500 hPa temperature, wind and geopotential height fields, and the skill score is calculated using the difference between the analysis data from the NCEP GFS model and the forecast data of the KAF-WRF model results. Accuracy of precipitation for the Korean penisula domain is examined using the contingency table that is made of the KAF-WRF model results and the KMA (Korea Meteorological Administraion) AWS (Automatic Weather Station) data. Using the verification system, the operational model and parallel model with updated version of the WRF model and improved physics process are quantitatively evaluated for the 2009 summer. Over the East Aisa region, the parallel experimental model shows the better performance than the operation model. Errors of the experimental model in 500 hPa geopotential height near the Tibetan plateau are smaller than errors in the operational model. Over the Korean peninsula, verification of precipitation prediction skills shows that the performance of the operational model is better than that of the experimental one in simulating light precipitation. However, performance of experimental one is generally better than that of operational one, in prediction.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.41-51
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• 1999

This study was conducted to investigate the effects of local climatic conditions on the annual increment of Korean white pine planted in Gapyung and Yaungdong. For this, stand variables such as mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique which makes use of empirical relationships between the topography and the weather in study sites was applied to produce normal estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine. Then, the yearly climatic variables from 1990 to 1997 for each study site were derived from the spatial interpolation procedures based on inverse- distance weighting of the observed deviation from the climatic normals at the nearest 11 standard weather stations. From these estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc., which affect the tree growth, were computed on yearly base for each locality. The deviations of measured annual increments from the expected annual increments for 8 years based on yield table of Korean white pine were then correlated with and regressed on the yearly weather variables to examine effects of local climatic conditions on the growth. Gapyung area provides better conditions for the growth of Korean white pine in the early stage than Youngdong area. This indicates that the conditions such as low temperature, high relative humidity, and large amount of precipitation provide favor environment for the early growth of Korean white pine. A ccording to the correlation and regression an analysis using local climatic conditions and annual increments, the growth pattern of Gapyung area corresponds to this tendency. However, it was found that the relationship between annual increments and local climatic conditions in Youngdong area shows different tendency from Gapyung. These results mean that the yearly growth pattern could not sufficiently be explained by climatic conditions with high variance in yearly weather variables. In addition, the poor growth in Youngdong area might not only be affected by climatic conditions, but also by other environmental factors such as site quality.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.153-153
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• 2017