• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.59-66
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• 2013

Among many factors, especially meteorological conditions can impact agricultural productivities. This study was conducted to analyze the relationships between crop yield and meteorological factors. We collected meteorological data (i.e., temperature and precipitation) from the Automated Weather System (AWS) of Korea Meteorological Administration (KMA) and the yield data of Chinese cabbage and Radish from local Nonghyup (NCAF:National Agricultural Cooperative Federation) and Farmers' Corporate Association. The agricultural data were classified into two groups. These groups are comprised of the farmers who produced a crop under 30 kg per $3.3m^2$ and over 30k g per $3.3m^2$ respectively. The daily meteorological data were calculated from the average value for ten days. Based on the regression analysis, we concluded that the yield of Chinese cabbage (Haenam) was related to average temperature, minimum temperature, precipitation, and number of days with precipitation, whereas that of Radish (Jeju) was related to average temperature, maximum temperature, and minimum temperature. The result suggests that these meteorological data can be used more effectively for the prediction of crop yield.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.69-82
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• 2023

Representative meteorological data of the rural water district, which is the spatial unit of the study, was produced using the grid-based national standard RCP scenario rainfall data provided by the Korea Meteorological Administration. The retrospective reproducibility of the climate model scenario data was analyzed, and the change in climate characteristics in the water district unit for the future period was presented. Finally the data characteristics and differences of each meteorological element according to various spatial resolution conversion and post-processing methods were examined. As a main result, overall, the distribution of average precipitation and R95p of the grid data, has reasonable reproducibility compared to the ASOS observation, but the maximum daily rainfall tends to be distributed low nationwide. The number of rainfall days tends to be higher than the station-based observation, and this is because the grid data is generally calculated using the area average concept of representative rainfall data for each grid. In addition, in the case of coastal regions, there is a problem that administrative districts of islands and rural water districts do not match. and In the case of water districts that include mountainous areas, such as Jeju, there was a large difference in the results depending on whether or not high rainfall in the mountainous areas was reflected. The results of this study are expected to be used as foundation for selecting data processing methods when constructing future meteorological data for rural water districts for future agricutural water management plans and climate change vulnerability assessments.

• 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.

• Atmosphere
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• v.22 no.3
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• pp.299-307
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• 2012

This study is aimed to validate errors for detected suspicious temperature data using various quality control procedures for 61 weather stations in the Republic of Korea. The quality control algorithms for temperature data consist of four main procedures (high-low extreme check, internal consistency check, temporal outlier check, and spatial outlier check). Errors of detected suspicious temperature data are judged by examining temperature data of nearby stations, surface weather charts, hourly temperature data, daily precipitation, and daily maximum wind direction. The number of detected errors in internal consistency check and spatial outlier check showed 4 days (3 stations) and 7 days (5 stations), respectively. Effective and objective methods for validation errors through this study will help to reduce manpower and time for conduct of quality management for temperature data.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.3
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of Environmental Science International
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• v.27 no.12
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• pp.1227-1239
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• 2018

In this study, daily precipitation data and daily average temperature data of meteorological observatories in Daegu, Busan, Daejeon, Seoul, Mokpo, and Gwangju cities inland and offshore were analyzed by using moving average method. Were compared. Overall, summarizing changes in precipitation and temperature over the 24 seasons, precipitation and temperature in all six stations increased compared to the past 1960s. In the case of precipitation, precipitation increased at the end of July and early August, whereas precipitation in April, September and early October decreased. In the case of temperature, especially in February, the temperature increased, and in Mokpo, the temperature from August to December showed a general decline. Changes in precipitation and temperature due to seasons in the 24 seasons affect agriculture and our everyday life, and further research is needed to determine how these changes will affect agricultural water supply, crop growth and daily life. The results of this study can be useful.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.7-9
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• 2004

The purpose of this study was to analyze the climatic water balance of the Korean peninsula using meteorological data and the evapotranspiration (ET) derived from NOAA/AVHRR. Quantifying water balance components is important to understand the basic hydrology. In this study, a simple method to estimate the ET was proposed based on a regression approach between NDVI and Morton's actual ET using NOAA/AVHRR data. The Morton's actual ET for land surface conditions was evaluated using a daily meteorological data from 77 weather stations, and the monthly averaged Morton's ETs for each land cover was compared with the monthly NDVIs during the year 2001. According to the climatic water balance analysis, water deficit and surplus distributed maps were created from spatial rainfall, soil moisture, and actual and potential ETs map. The results clearly showed that the temporal and spatial characteristics of dryness and wetness may be detected and mapped based on the wetness index.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.1
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• pp.3-9
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• 2005

The purpose of this study was to analyze the climatic water balance of the Korean peninsula using meteorological data and the evapotranspiration (ET) derived from NOAA/AVHRR, Quantifying water balance components is important to understand the basic hydrology, In this study, a simple method to estimate actual ET was proposed based on a regression approach between NDVI and Morton's actual ET using NOAA/AVHRR data, The Mortons actual ET for land surface conditions was evaluated using a daily meteorological data from 77 weather stations, and the monthly averaged Morton's ETs for each land cover was compared with the monthly NDVIs during the year 2001. According to the climatic water balance analysis, water deficit and surplus distributed maps were created from spatial rainfall, soil moisture, and actual and potential ETs map, The results clearly showed that the temporal and spatial characteristics of dryness and wetness may be detected and mapped based on the wetness index.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.68-76
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• 2006

A thermal time-based two-step phenological model was used to project flowering dates of Japanese cherry in South Korea from 1941 to 2100. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. Daily maximum and minimum temperature are used to calculate daily chill units until a pre-determined chilling requirement for rest release is met. After the projected rest release date, daily heat units (growing degree days) are accumulated until a pre-determined heating requirement for flowering is achieved. Model calculations using daily temperature data at 18 synoptic stations during 1955-2004 were compared with the observed blooming dates and resulted in 3.9 days mean absolute error, 5.1 days root mean squared error, and a correlation coefficient of 0.86. Considering that the phonology observation has never been fully standardized in Korea, this result seems reasonable. Gridded data sets of daily maximum and minimum temperature with a 270 m grid spacing were prepared for the climatological years 1941-1970 and 1971-2000 from observations at 56 synoptic stations by using a spatial interpolation scheme for correcting urban heat island effect as well as elevation effect. A 25km-resolution temperature data set covering the Korean Peninsula, prepared by the Meteorological Research Institute of Korea Meteorological Administration under the condition of Inter-governmental Panel on Climate Change-Special Report on Emission Scenarios A2, was converted to 270 m gridded data for the climatological years 2011-2040, 2041-2070 and 2071-2100. The model was run by the gridded daily maximum and minimum temperature data sets, each representing a climatological normal year for 1941-1970, 1971-2000, 2011-2040, 2041-2070, and 2071-2100. According to the model calculation, the spatially averaged flowering date for the 1971-2000 normal is shorter than that for 1941-1970 by 5.2 days. Compared with the current normal (1971-2000), flowering of Japanese cherry is expected to be earlier by 9, 21, and 29 days in the future normal years 2011-2040, 2041-2070, and 2071-2100, respectively. Southern coastal areas might experience springs with incomplete or even no Japanese cherry flowering caused by insufficient chilling for breaking bud dormancy.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.993-1001
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• 2015

Comparing to the other air pollutants like $SO_2$, CO, the number of exceedance of the ozone national ambient air quality standard(NAAQS) and the ozone warning increased recently in Busan. The purpose of this study is to find out the preliminary symptoms for high ozone days in Busan area. In order to find out the preliminary symptoms, the hourly ozone data at air quality monitoring stations and the hourly meterological parameters at Busan regional meteorological 2007 to 2013 were used for the analysis. Averaged daily max ozone concentration was the highest(0.055 ppm) at Noksan and Youngsuri in the ozone season from 2007 to 2013. The horizontal distributions of daily max. ozone including all stations in Busan at high ozone days(the day exceeding 0.1 ppm of ozone concentration at least one station) were classified from two to five clusters by hierarchial cluster analysis. The meteorological variables showing strong correlation with daily max. ozone were the daily mean dew point temperature, averaged total insolation, the daily mean relative humidity and the daily mean cloud amount. And the most frequent levels were $19-23^{\circ}C$ in dew point temperature, $21-24 MJ/m^2$ in total insolation on the day before, $2.6-3.0 MJ/m^2$ on the very day, 67-80% in relative humidity and 0-3 in cloud amount.