• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.617-624
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• 2017

The production of cabbage, which is mainly cultivated in open field, varies greatly depending on weather conditions, and the price fluctuation is largely due to the presence of a substitute crop. Previous studies predicted the production of cabbage using actual weather data, but in this study, we predicted the wholesale price using unstructured agricultural meteorological data on the web. From January 2009 to October 2016, we collected documents including the cabbage on the portal site, and extracted keywords related to weather in the collected documents. We compared the forecast wholesale prices of simple models and unstructured agricultural weather models at the time of shipment. The simple model is AR model using only wholesale price, and the unstructured agricultural weather model is AR model using unstructured agricultural weather data additionally. As a result, the performance of unstructured agricultural weather model was has been found to be more accurate prediction ability.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.1
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• pp.57-67
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• 1998

A stochastic weather generator which simulate daily precipitation, maximum and minimum daily temperature, relative humidity was developed. The model parameters were estimated using stochastic characteristics analysis of historical data of 71 weather stations. Spatial variations of the parameters for the country were also analyzed. Model parameters of ungauged Sites were determined from parameters of adjacent weather stations using inverse distance method. The model was verified on Suwon and Ulsan weather stations and showed good agreement between simulated and observed data.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.4
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• pp.291-295
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• 1982

The biosphere of the earth is not only about to overpass the limit to meet the food demand of the world but also the stability of its food production has been also jeopardized by the disasters and pests, especially by the unpredictable weather disasters. In addition the agricultural and industrial pollution against biosphere aggravates the unstability of agricultural production and constitutes a threat in securing the food of the world. In Korea the yield level of crops has been greatly enhanced by the improved agrotechnologies and varietal improvement, but the yield variability due to unfavorable weather events and pests remained unchanged with the change in time. Among weather-related disasters the drought and flood damages has occurred most frequently and impacted most greatly on the agricultural production and its stability. During last decade (1970-l980) the rice production experienced the average annual loss of 0.544 million metric ton which was composed of 0.21 million M/T by climatic disaster, 0.21 million M/T by disease and 0.12 million M/T by insects, and the annual loss of upland crop production from climatic disasters amounted to 0.06 million metric tons. Especially in 1980, the global climatic disasters due to cold or hot temperature endangered the agricultural production all over the world and also the rice production of Korea recorded the unprecedented yield reduction of about 30 percent due to cool summer weather. Nowadays, the unusual weather conditions are prevaling throughout the world, and agro-meteologists predict that the unpredictable cool summer and drought will often attack the rice and other crops in 1980's. To meet the coming weather unstability and to secure the stable crop production, multilateral efforts should be rendered. Therefore, the Korea Society of Crop Science, which commemorates the 20th anniversary of its founding, prepared the symposium on Meteological Stress in Crop Production and its Countermeasures to discuss the decrease in agricultural production due to weather-related disasters and to devise the multilateral counter-measures against the unfavorable weather events.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.3
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• pp.107-112
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• 2008

"Jeung-Bo-San-Lim-Gyeong-Je" (meaning "Revised Forest Management") has been well recognized as the informative document that introduces scientific knowledge and experiences of Korean ancestors regarding weather and climate. The tradition of Gwan-Cheon-Mang-Gi(i.e., empirical forecasting of short-term weather phenomena based on the status of cloud or sky) has been continuously utilized as a civilian weather forecasting method and even for very short-term weather prediction by operational forecasters these days. This agricultural technology textbook, published during the Great King Youngjo in Chosun-Dynasty, may be regarded as a poorly written document from the modern standpoint. Nonetheless, this study demonstrates that by and large the empirical knowledge contained in the book is indeed science based although their applications are limited to several hours for local forecasts in agricultural practices and daily living. For example, the wisdom of keeping water at an optimum level in a paddy field after sowing to prevent young seedlings from late frost damages was not at all different from the present technique of vinyl covered seedling nursery.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• Journal of Bio-Environment Control
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• v.23 no.3
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• pp.192-198
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• 2014

To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

• Plant Resources
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• v.7 no.1
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• pp.36-38
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• 2004

Bacterial grain rot of rice caused by Burkholderia glumae was examined between weather condition and disease incidence. From 1998 to 2000, average disease incidence was 3.0 ％ without difference in survey regions. However, it was related closely to amount of rainfall that disease incidence higher in 1998 and 2000 to 3.0 ％ and 3.6 ％ respectively than 2.3 in 1999 relatively small volum of rainfall season.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.164-170
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• 2020

The weather conditions, such as temperature, precipitation, and sunshine duration, play one of the key roles in Agriculture. In particular, extreme weather events have crucial impacts on growth and yields of crops. This study estimates statistics of extreme weather events in 167 Si-gun over South Korea derived from high-resolution(30 and 270m) topo-climatology model for key three meteorological variables(temperature, precipitation and sunshine duration). It is shown that the characteristic of each extreme weather frequency in the topo-climatology model is in good agreement with observation from Korean Meteorological Administration's Automatic Surface Observing System. Moreover, it is possible to analyze the statistics of extreme weather more realistically because this data can cover the weather at not-observed regions. Hence, this data is expected to be used as baseline data for assessing vulnerability to extreme weather and politic decisions for damage reduction in agricultural sector.

• Korean Journal of Environmental Agriculture
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• v.41 no.1
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• pp.32-40
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• 2022

BACKGROUND: Climate-smart agriculture (CSA) has been proposed for sustainable agriculture and food security in an agricultural ecosystem disturbed by climate change. However, scientific approaches to local agricultural ecosystems to realize CSA are rare. This study attempted to evaluate the weather condition, rice production, and greenhouse gas emissions from the rice cultivation in Hwaseong-si, Gyeonggi-do to fulfill CSA of the rice cultivation. METHODS AND RESULTS: Over the past 3 years (2017~2019), Chucheong rice cultivar yield and methane emissions were analyzed from the rice field plot (37°13'15"N, 127° 02'22"E) in the Gyeonggi-do Agricultural Research and Extension Services located in Gisan-dong, Hwaseong-si, Gyeonggi-do. Methane samples were collected from three automated closed chambers installed in the plot. The weather data measured through automatic weather station located in near the plot were analyzed. CONCLUSION(S): The rice productivity was found to vary with weather environment in the agricultural ecosystem. And methane emissions are high in a favorable weather condition for rice growth. Therefore, it is necessary to minimize the trade-off between the greenhouse gas emission target for climate change mitigation and productivity improvement for CSA in a local rice cultivation.

• The Plant Pathology Journal
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• v.26 no.1
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• pp.37-48
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• 2010

This paper describes a web-based information system for plant disease forecast that was developed for crop growers in Gyeonggi-do, Korea. The system generates hourly or daily warnings at the spatial resolution of $240\;m{\times}240\;m$ based on weather data. The system consists of four components including weather data acquisition system, job process system, data storage system, and web service system. The spatial resolution of disease forecast is high enough to estimate daily or hourly infection risks of individual farms, so that farmers can use the forecast information practically in determining if and when fungicides are to be sprayed to control diseases. Currently, forecasting models for blast, sheath blight, and grain rot of rice, and scab and rust of pear are available for the system. As for the spatial interpolation of weather data, the interpolated temperature and relative humidity showed high accuracy as compared with the observed data at the same locations. However, the spatial interpolation of rainfall and leaf wetness events needs to be improved. For rice blast forecasting, 44.5% of infection warnings based on the observed weather data were correctly estimated when the disease forecast was made based on the interpolated weather data. The low accuracy in disease forecast based on the interpolated weather data was mainly due to the failure in estimating leaf wetness events.