• Journal of the Korean association of regional geographers
• /
• v.4 no.2
• /
• pp.151-164
• /
• 1998

I analyzed the correlation between El-Nino phenomenon and our country's temperature and precipitation laying the stress on the anomaly, and the result of this analysis is as follows: (1) The extraction of the occurrences of El-Nino at the place of sea surface around Nino.3 which was known as the sea area under observation for El-Nino reveals that there are 9 years (1969, 1970, 1973, 1977, 1987, 1992, 1995, 1998) when the temperature anomaly in January is more than 1.0 during the period of research years ($1969{\sim}1998$). (2) The tendency of change of sea surface temperature around Nino.3 and that of our country are about the same, but the anomaly of Pusan and Inchon was much greater than that of Jangki in the East Coast. (3) The anomaly of sea surface temperature around Nino.3 and that of the ground temperature showed the similar changing tendency, the temperature of our country has something to do with that of sea surface as the correlation of ground temperature with the temperature of sea surface showed 0.31. Anomaly warm winter has something to do with El-Nino because the temperature of our country was high when El-Nino phenomenon appeared. (4) As for the precipitation, we can see that it has generally increased after 1989 when the phenomenon of warm climate was intense than before that year. But as we study the change of anomaly, the precipitation has less correlation in comparison with the ground temperature. The precipitation in 1973, 1983 and 1987 which were El-Nino years was correlated with El-Nino. While the change of sea surface temperature has showed a tendency of plus(+)increase since 1990, the precipitation has showed a tendency of minus (-)decrease. Therefore it seems that the temperature of sea surface has little correlation with the amount of rainfall.

• Journal of the Korean earth science society
• /
• v.42 no.3
• /
• pp.264-277
• /
• 2021

This study analyzed the relationship between the total precipitable water vapor in the atmosphere and the moving speed of recent typhoons. This study used ground observation data of air temperature, precipitation, and wind speed from the Korea Meteorological Administration (KMA) as well as total rainfall data and Red-Green-Blue (RGB) composite images from the U.S. Meteorological and Satellite Research Institute and the KMA's Cheollian Satellite 2A (GEO-KOMPSAT-2A). Using the typhoon location and moving speed data provided by the KMA, we compared the moving speeds of typhoon Bavi, Maysak, and Haishen from 2020, typhoon Tapah from 2019, and typhoon Kong-rey from 2018 with the average typhoon speed by latitude. Tapah and Kong-rey moved at average speed with changing latitude, while Bavi and Maysak showed a significant decrease in moving speed between approximately 25°N and 30°N. This is because a water vapor band in the atmosphere in front of these two typhoons induced frontogenesis and prevented their movement. In other words, when the water vapor band generated by the low-level jet causes frontogenesis in front of the moving typhoon, the high pressure area located between the site of frontogenesis and the typhoon develops further, inducing as a blocking effect. Together with the tropical night phenomenon, this slows the typhoon. Bavi and Maysak were accompanied by copious atmospheric water vapor; consequently, a water vapor band along the low-level jet induced frontogenesis. Then, the downdraft of the high pressure between the frontogenesis and the typhoon caused the tropical night phenomenon. Finally, strong winds and heavy rains occurred in succession once the typhoon landed.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.4
• /
• pp.277-283
• /
• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.