• Magazine of the Korean Society of Agricultural Engineers
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• v.23 no.1
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• pp.25-36
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• 1981

• Proceedings of the Korean Society of Crop Science Conference
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• 1997.10a
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• pp.11-12
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• 1997

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.1-17
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• 2015

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.36-36
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• 2011

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2012.07a
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• pp.59-61
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• 2012

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.104-119
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• 2019

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.201-205
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• 2016

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.320-331
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• 2013

The National Center for AgroMeteorology (NCAM) has designed a risk management solution for individual farms threatened by the climate change and variability. The new service produces weather risk indices tailored to the crop species and phenology by using site-specific weather forecasts and analysis derived from digital products of the Korea Meteorological Administration (KMA). If the risk is high enough to cause any damage to the crops, agrometeorological warnings or watches are delivered to the growers' cellular phones with relevant countermeasures to help protect their crops against the potential damage. Core techniques such as scaling down of weather data to individual farm level and the crop specific risk assessment for operational service were developed and integrated into a cloud based service system. The system was employed and implemented in a rural catchment of 50 $km^2$ with diverse agricultural activities and 230 volunteer farmers are participating in this project to get the user-specific weather information from and to feed their evaluations back to NCAM. The experience obtained through this project will be useful in planning and developing the nation-wide early warning service in agricultural sector exposed to the climate and weather extremes under climate change and climate variability.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.55-70
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• 2001

It was unusual crop weather for 1998 and 1999 compared with normal in Korea. The consecutive days of the optimum ripening period for rice plant that had daily mean temperature 21~23$^{\circ}C$ for 40 days after flowering, increased with long anomalies in 1998~99. The air temperature during ripening period was much higher than the optimum temperature and lower sunshine hour than norm in the local adaptability tests of newly developed rice lines during those years. In response of rice cultivation to warming and cloudy weather during crop season, the yield shall be decreased. Most scientists agree that the rate of heating is accelerating and temperature change could become increasingly disruptive. Weather patterns should also become more erratic. Agrometeorologists could be analyzed yearly variations of temperature, sunshine hour and rainfall pattern focused on transient agroclimate change for last a decade. Rice agronomists could be established taking advantage of real time agricultural meteorology information system for fertilization, irrigation, pest control and harvest. Also they could be analyzed the characteristics of flowering response of the recommended and newly bred rice cultivars for suitable cropping plan such as cultural patterns and sowing or transplanting date. Rice breeders should be deeply considered introducing the characteristics of basic vegetative type of flowering response like Togil rices as prospective rice cultivars corresponding to global warming because of the rices needed higher temperature at ripening stage than japonica rices, photoperiod-sensitive and thermo-sensitive ecotypes.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.61-74
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• 2021

Agriculture is most closely related to weather, and the government pursues stable food production by weather research. However, abnormal weather conditions have occurred frequently around the world in recent years, and stable food production has been threatened. Among them, heavy snow in winter tends to increase in frequency and size, which causes serious damage to greenhouses. Therefore, it is imperative to build a system reflecting various demands to reduce the damage to agricultural facilities caused by heavy snow. A business model can realize this as a way of commercialization, however, no suitable model has been presented to date. Therefore, this study aims to design a representative business model that can establish a safety system by distributing a greenhouse disaster prevention warning system for heavy snow to farms.