• Journal of the Korean Geographical Society
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• v.41 no.3 s.114
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• pp.361-372
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• 2006

The purpose of this paper is to analyze temporal trends and spatial distribution of frost occurrence days using 54 weather stations under the Korea Meteorological Administration during the recent 30years ($1971{\sim}2000$). The frost occurrence days in the middle inland area was more than in the coastal area, but the period of free-frost days in the coastal area was longer than that in the middle inland. In the southern and eastern coastal areas, the frost day was more than in the western coastal area. The distribution of the first frost day was similar to that of the last frost day. The first frost day in the coastal area appeared a month later than that in the middle inland. The last frost day in the coastal area appeared $20{\sim}25$ days later than that in the middle inland. At most of stations which the first frost day was getting delayed and the last frost day earlier, the frost occurrence days showed a decreasing trend. However, in some stations, the frost occurrence day was increasing. As the frost days in October, March and April at some stations showed an increasing trend, the damage due to the frost might be increased in some areas in South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.86-92
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• 2017

In this study, a model to classify frost occurrence and frost free day was developed using the digital weather forecast data provided by Korea Meteorological Administration (KMA). The minimum temperature, average wind speed, relative humidity, and dew point temperature were identified as the meteorological variables useful for classification frost occurrence and frost-free days. It was found that frost-occurrence date tended to have relatively low values of the minimum temperature, dew point temperature, and average wind speed. On the other hand, relatively humidity on frost-free days was higher than on frost-occurrence dates. Models based on machine learning methods including Artificial Neural Network (ANN), Random Forest(RF), Support Vector Machine(SVM) with those meteorological factors had >70% of accuracy. This results suggested that these models would be useful to predict the occurrence of frost using a digital weather forecast data.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.641-645
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• 2017

This study was conducted to compare three agro-climatic indices among 22 agro-climatic zones in Northeast China area. Meteorological data produced by NASA (MERRA-2) was used to calculate growing degree days (GDD), frost free period (FFP), and growth season length (GSL) at this study sites. The three indices did not differ among 6 years (2011-2016). However, they showed statistical spatial difference among agro-climatic zones. The GDD ranged between $531.7^{\circ}C{\cdot}day$ (zone 22) and $1650.6^{\circ}C{\cdot}day$ (zone 1). The range of the FFP was from 141.5 day (zone 22) to 241.7 day (zone 1). And the GSL showed spatial distribution between 125.1 day (zone 22) and 217.9 day (zone 1).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.14
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• pp.53-64
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• 1973

The studies reported herein were conducted to investigate the effect of thermal conditions in double-cropping of rice. The accumulated daily mean and minimum air temperatures, for the period of the last 30 years, were examined at the 10 different meteorogical stations which are located in the southern part of Korea. The results obtained could be summarized as follows: 1. The first cropping. a. It seemed to be free from any frost-damage of rice at the seeding stage at Yeosu, Pusan and Cheju. However, it was found that there were some dangers of frost damage for about 30 to 40 day at Iri, Chonju and Kwangju, for 18 to 28 days at Daeku and Ulsan, and for 4 to 14 days at Mokpo and Pohang, respectively. b. The early critical transplanting date seemed to be from middle to late-April in the first cropping. As compared with the ordinary lowland seedlings, the semi-protected and upland ones could be planted 5 and 10 days earlier, respectively. c. The early critical heading date was about late-June and there were some low-temperature damages for 8 to 25 days at young-ear formation stage of rice plant, depending upon location. d. The early critical ripening date (the early critical transplanting date of the 2nd cropping) was from late-July to early-August. It took about 32 to 39 days in ripening. There was a tendency of SS${\fallingdotseq}$SL$15^{\circ}C$ (${\theta}$15) and the minimum of $10^{\circ}C$ (${\theta}$10), the ten locations could be devided into two ripening groups of ${\theta}$15>${\theta}$10 and ${\theta}$15<${\theta}$10. c. The late critical ripening date was around October 9 at Iri, Chonju, Kwangju and Daeku and around October 28 at Mokpo, Yeosu, Pusan and eheju. Three to four days were more required for a complete ripening of rice, as compared with the above dates. d. There was an overlap of about 12 to 42 days between the first and second cropping when early-maturing varieties requiring an accumulated mean air temperature of $1, 550^{\circ}C$, from transplanting to heading, were grown. Therefore, some varieties which could head with an accumulated daily mean air temperature of 1, 000 to $1, 200^{\circ}C$, should be either developed or some new cultural technology be established in order to have a successful double cropping in rice.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.