Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Soo-Ock Kim"'
Publikováno v:
Atmosphere, Vol 12, Iss 7, p 846 (2021)
Spring frosts damage crops that have weakened freezing resistance after germination. We developed a machine learning (ML)-based frost-classification model and optimized it for orchard farming environments. First, logistic regression, decision tree, r
Externí odkaz:
https://doaj.org/article/2dac0056ac0d492abdbed2119350cc7a
Autor:
Soo-ock Kim, Jin I. Yun
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 18:135-142
Autor:
Soo-ock Kim, Jin I. Yun
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 18:55-63
Autor:
Jin I. Yun, Soo-ock Kim
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 17:281-289
College of Life Sciences, Kyung Hee University, Yongin 17104, Korea(Received October 13, 2015; Revised November 1, 2015; Accepted November 2, 2015)ABSTRACTInformation on sunshine duration and solar radiation are indispensable to the understanding of
Publikováno v:
Asia-Pacific Journal of Atmospheric Sciences. 51:197-203
A drought index with respect to the spatio-temporal scale was developed in response to the demand from the agricultural sector in South Korea. The new drought index was calculated based on the soil water balance between the supply and demand of water
Publikováno v:
Asia-Pacific Journal of Atmospheric Sciences. 51:239-247
When the midday temperature distribution in a mountainous region was estimated using data from a nearby weather station, the correction of elevation difference based on temperature lapse caused a large error. An empirical approach reflecting the effe
Autor:
Jin I. Yun, Soo-ock, Kim
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 16:297-303
The effect of solar irradiance has been used to estimate daily maximum temperature, which make it possible to reduce the error inherent to lapse-rate based elevation difference correction in mountainous terrain. Still, recent observations indicated t
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 15:320-331
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
Autor:
Jin I. Yun, Soo-ock, Kim
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 15:291-297
Automated weather stations were installed at 9 locations with, three different elevations, (i.e., 50m, 100m, and 300m a.s.l.) with different slope and aspect in a small watershed (50km 2 area). Air temperature at 1500 LST and solar radiation accumula
Publikováno v:
Korean Journal of Agricultural and Forest Meteorology. 15:76-84
An adequate downscaling of the official forecasts of Korea Meteorological Administration (KMA) is a prerequisite to improving the value and utility of agrometeorological information in rural areas, where complex terrain and small farms constitute maj