• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.21-40
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• 2023

This study analyzed the cold air characteristics of the Nakdong Jeongmaek, which is advantageous for the formation of cold air that can flow into the city, in order to suggest the wind ventilation corridor plans, which have recently been increasing interest as a way to improve the urban thermal environment. In addition, based on the watershed analysis, specific cold-air watershed areas were established and management plans were suggested to expand the cold air function of the Nakdong Jeongmaek. As a result of the analysis of cold air in the Nakdong Jeongaek, cold air was strongly generated in the northern forest of the Jeongamek, and flowed into nearby cities along the valley topography. On average, the speed of cold air was high in cities located to the east of the Jeongmaek, while the height of cold air layer was high in cities located to the west. By synthesizing these cold air characteristics and watershed analysis results, the cold-air watershed area was classified into 8 zones, And the plans were proposed to preserve and strengthen the temperature reduction of the Jeongmaek by designating the zones as 'Conservation area of Cold-air', 'Management area of Cold-air', and 'Intensive management area of Cold-air'. In addition, in order to verify the temperature reduction of cold air, the effect of night temperature reduction effect was compared with the cold air analysis using weather observation data. As a result, the temperature reduction of cold air was confirmed because the night temperature reduction was large at the observation station with strong cold air characteristics. This study is expected to be used as basic data in establishing a systematic preservation and management plan to expand the cold air function of the Nakdong Jeongmaek.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• Journal of the Korean earth science society
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• v.37 no.1
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• pp.29-39
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• 2016

In this study, we estimated solar radiation by multiple regression analysis using sunshine duration and precipitation data, which are highly correlated to solar radiation. We found the regression equation using data obtained from GROM (Gangwon Regional Office of Metrology, station 105, 1980-2007) located in Gangneung, South Korea and validated the equation by applying data obtained from new GROM (newly relocated, station 104, 2009-2014) and data obtained from GWNU (Gangneung-Wonju National University, 2013-2014) located between stations 104 and 105. By using sunshine duration data alone, the estimation using data from station 104 resulted in a correlation coefficient of 0.96 and a standard error of $1.16MJm^{-2}$, which was similar to the previous results; the estimation using data from GWNU yielded better results with a correlation coefficient of 0.99 and a standard error of $0.57MJm^{-2}$. By using sunshine duration and precipitation data, the estimation (using data from station 104) yielded a correlation coefficient of 0.96 and a standard error of $0.99MJm^{-2}$, resulting in a lower standard error compared to what was obtained using sunshine duration data alone. The maximum solar radiation bias increased from -26.6% (March 2013) to -31.0% (February 2011) when both sunshine duration and precipitation data were incorporated into the estimation rather than when sunshine duration data alone was incorporated. This was attributed to the concentrated precipitation found during May and July-September, which resulted in negative coefficients of the estimating equation in other months. Therefore, the monthly average solar radiation should be estimated carefully when employing the monthly average precipitation for those places where precipitation is concentrated during summer, such as the Korean peninsula.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4323-4337
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• 1977

The study was to estimate the effect of the rise of water temperature in the warm water pool and to make contribution to the establishment of reducing to a damage of cool water as well as to the planning for warm water pool. This observation was performed in Wudu warm water pool located at Wudu-Dong of Chuncheon for two years from 1975 to 1976. The results were showed as follows; 1. The daily variation of water temperature was the least for inset (No.1; 0.6$^{\circ}C$) the second for middle overflow (No2: 3$^{\circ}C$, No.3; 2.3$^{\circ}C$) and another for outflet (No.4; 3.6$^{\circ}C$, No.5; 3.8$^{\circ}C$) And the highest reaching time of water temperature in each block was later about 1 hour than the time at which air temperature happend in the daytime. So, the variation of water temperature was sensitive to the variation of air temperature 2. The monthly variation of water temperature at each measuring point was plotted to be increased with increase in air temperature till August (Mean monthly rising degree; No.1; 1.15$^{\circ}C$, No.2; 1.7$^{\circ}C$, No.3; 1.73$^{\circ}C$, No.4; 2.08$^{\circ}C$, No.5; 2.0$^{\circ}C$), and expressed gradually descended influence upon water temperature after August. 3. The mean temperature of inflow folwed in warm Water pool was 7.5∼12.5$^{\circ}C$, and outflow temperature was described as 13.4∼22.5$^{\circ}C$ to be climbed. And So, the rising interval of water temperature was shown as 6.7∼10.4$^{\circ}C$. 4. The correlation between the rising of water temperature and the weather condition was found out highly significant. As the result, their correlation coefficents of water temperature depending on mean air temperature, ground temperature, wind velocity and relative humidity were to be 0.93, 0.90, - 0.83 and 0.71 respectively. But there was no confrimation of the correlation on the clouds, sunlight time, volume of evaporation, and heat capacity of horizontal place. 5. The water temperature of balance during the period of rice growing in Chuncheon district was shown as table 10, and the mean of whole period was calculated as about 23.7$^{\circ}C$. 6. The observed value of the outflow temperature passed through the warm water pool was higher than that of computed, the mean difference between two value was marked as 1.15$^{\circ}C$ for blockl, 1.18$^{\circ}C$ for block2, and 0.47$^{\circ}C$ for block3, respectivly. Therefore, the ratio on the rising degree between the observed and computed were shown as 53%, 44%, and 18%, mean 38% through each block warm water pool (referring item $\circled9$ of table 11,12, and 13). Accordingly, formula (4) in order to fit for each block warm water pool was transfromed as follow; {{{{ { theta }_{w } - { theta }_{ 0} =[1-exp LEFT { { 1-(1+2 varphi )} over {cp } CDOT { A} over { q} RIGHT } ] TIMES ( { theta }_{w } - { theta }_{ 0}) TIMES C }}}} Here, correction coefficinent was computed 1.38, and being substituted 1.38 for C in preceding formula, the expected water temperature will be calculated to be able to irrigate the rice paddy. As the result, we can apply the coefficient in order to plan and to construct a new warm water pool.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.183-193
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• 2020

This study was conducted to evaluate the effect of environment factors on the growth of autumn season cultivation of Kimchi cabbage using the big data in terms of public open data(weather, soil information, and growth of crop, etc.). The growth data and the environment data such as temperature, daylength, and rainfall from 2010 to 2019 were collected. As a result of composing the correlation matrix, the height and leaf number showed high correlation in growing degree days(GDDs) and daylength, and the yield showed negative correlation in growing degree days and the concentration of clay. GDDs and daylength explained about 89% and 84% of variation in height, respectively. These two environmental factors also explained about 85% and 79% of variation in leaf numbers, respectively. In contrast, the coefficient of determination was low for yield when GDDs and concentration of clay was used. The outcome of regional statistical analysis indicated that relationship between yield and sum of sand and silt were high in Haenam and Jindo areas. Hierarchical cluster analysis, which was performed to verify the association of yield, GDDs, and concentration of clay, showed that Haenam and Jindo were clustered together. Although GDDs and yield vary by year and region, and there are regions with similar concentration of clays, observation data are grouped as the result. These suggests that GDDs and soil texture are expected to be related to yield. The cluster analysis results can be used for further data analysis and agricultural policy establishment.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.

• Atmosphere
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• v.22 no.4
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• pp.489-497
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• 2012

Recently released a top secret document explicitly shows that the early development plan for an earth observation satellite in the USA has a hidden and more important purpose for a concept of 'free space' than the scientific purpose. At that time, the hidden and secret concept imbedded within the early space development plan prevail other national policies of the USA government for purpose of the national security. Under these circumstances, it is quite reasonable to accept a possibility that the meteorological satellites which play a key role in the every area of meteorology and climatology was also born for the hidden purposes. Even it is so, it is quite amazing that the first meteorological satellite is launched in the USA despite of the facts that the major users of the meteorological satellites were not very enthusiastic with the meteorological satellite and the program was not started as a formal meteorological satellite project. This was only possible because of the external socio-political impact caused by the successful launch of the Russian Sputnik satellite and a few key policy developers who favored the meteorological satellite program. It is also interesting to note that the beginning of the first Korean meteorological satellite program was initiated by a similar socio-political influence occurred by the launch of a North Korean satellite.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.132-142
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• 2010

Characteristics of meteorological elements were analyzed at Hwagae and Agyang where are the representative areas of Hadong green tea cultivation in Korea. An automatic weather monitoring system (AWS) and a simple data log were employed to measure meteorological data such as temperature, relative humidity, precipitation, and wind direction and speed for 2009. The annual average air temperature of Hwagae and Agyang was 14.5 and 14.2, respectively, showing the warmest month in August ($25.4^{\circ}C$ for Hwagae and $24.9^{\circ}C$ for Agyang) and the coldest month in January ($0.3^{\circ}C$ for Hwagae and $0.2^{\circ}C$ for Agyang). Annual average of daily temperature difference (= daily maximum temperature - daily minimum temperature) was $11.3^{\circ}C$ for Hwagae and $11.1^{\circ}C$ for Agyang. Hwagae and Agyang had 62.7% and 65.3% of the annual average relative humidity, respectively. Annual precipitation was 1387 mm for Hwagae and 1793 mm for Agyang of which were higher of 605mm for Hwagae and 835 mm for Agyang compared to that in 2008. Majority of precipitation occurred between May and August, attributing 77.6% for Hwagae and 76.6% for Agyang to the annual precipitation. The annual total sunshine duration was 2054.3 hrs in Hwagae with the longest monthly sunshine duration in May (235.1 hrs) and the shortest monthly sunshine duration in July (102.5 hrs). Dominant wind direction changed seasonally from northwesterly wind in fall and winter to southeasterly wind in spring and summer. The annual average wind speed was 1.5 m $s^{-1}$ with the highest monthly wind speed of 2.0 m $s^{-1}$ in December and the lowest monthly wind speed of 1.1 m $s^{-1}$ in February. It is expected that continuous observation and assessment of meteorological data will improve our understanding of optimal environmental conditions for green tea cultivation and be used for developing models of green tea cultivation in the Hadong area.