• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.119-123
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• 2012

The duration of low temperature in winter season is one of the important agrometeorological characteristics in crop growing fields. This study was conducted to develop a method to estimate the duration of low-temperature with monthly meteorological data. Using daily meteorological data from 61 observation sites from 1981 to 2010, we analyzed the relationships between the averages of monthly temperature minima and the durations of low-temperature ranging from -15 to $5^{\circ}C$, The monthly mean of the January minimum air temperature was appropriate for theestimation of the durations of lowtemperature below $0^{\circ}C$. We tested a simple second order equation to predict durations of low-temperature. To apply the equation to various temperature ranges, we suggested two different equations for the estimation of coefficients a and b, which are dependent on the base temperatures from -15 to $0^{\circ}C$. Thevalidation of the equations using other daily meteorological datasets from 1971 to 2000 showed that they were appropriate for the range from -10 to $0^{\circ}C$, but underestimated at $-15^{\circ}C$.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.8 no.3
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• pp.243-250
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• 2003

The spatio-temporal distribution of zooplankton community was investigated in Kyeonggi Bay with monthly samples from February 2001 to December 2001 at 5 stations along a transect between Incheon coastal waters and Seongap-Do. Monthly mean abundance of total zooplankton ranged from 1,100(Feb.)∼404,200 indiv./㎥ (Aug.) and annual mean abundance of total zooplankton was 55,000 indiv./㎥. The spatial mean abundance of total zooplankton varied from 114,600 indiv./㎥ (Incheon coastal waters) to 16,500 indiv./㎥ (Seongab-Do). Zooplankton abundance was higher in the inner bay than in the outer bay. Noctiluca scintillans, Acartia hongi, Oithona davisae, Paracalanus crassirostris, Paracalanus indicus and Oikopluera spp. were dominant species in Kyeonggi Bay and they contributed 95％ of annual mean abundance of total zooplankton. Most of dominant species distributed widely in study area throughout the year, however seasonal abundance peak only happened in inner part of the Bay. This pattern suggests that the spatio-temporal distribution of zooplankton is affected by the variations of water temperature and phytoplankton standing stock.

• Atmosphere
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• v.28 no.2
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• pp.153-162
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• 2018

The statistical prediction model for wintertime surface air temperature, that is based on snow cover extent and Arctic sea ice concentration, is updated by considering $El-Ni{\tilde{n}}o$ Southern Oscillation (ENSO) and Quasi-Biennial Oscillation (QBO). These additional factors, representing leading modes of interannual variability in the troposphere and stratosphere, enhance the seasonal prediction over the Northern Hemispheric surface air temperature, even though their impacts are dependent on the predicted month and region. In particular, the prediction of Korean surface air temperature in midwinter is substantially improved. In December, ENSO improved about 10% of prediction skill compared without it. In January, ENSO and QBO jointly helped to enhance prediction skill up to 36%. These results suggest that wintertime surface air temperature in Korea can be better predicted by considering not only high-latitude surface conditions (i.e., Eurasian snow cover extent and Arctic sea ice concentration) but also equatorial sea surface temperature and stratospheric circulation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.1
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• pp.28-34
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• 2011

This study was carried out to estimate monthly mean of daily maximum and minimum temperature across North Korea at a 30 m grid spacing for a climatological normal year (1971-2000) and the 4 decadal averages (1971-1980, 1981-1990, 1991-2000, and 2001-2010). A geospatial climate interpolation method, which has been successfully used to produce the so-called 'High-Definition Digital Climate Maps' (HD-DCM), was used in conjunction with the 27 North Korean and 17 South Korean synoptic data. Correction modules including local effects of cold air drainage, thermal belt, ocean, solar irradiance and urban heat island were applied to adjust the synoptic temperature data in addition to the lapse rate correction. According to the final temperature estimates for a normal year, North Korean winter is expected colder than South Korean winter by $7^{\circ}C$ in average, while the spatial mean summer temperature is lower by $3^{\circ}C$ than that for South Korea. Warming trend in North Korea for the recent 40 years (1971-2010) was most remarkable in spring and fall, showing a 7.4% increase in the land area with 15 or higher daily maximum temperature for April.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.57-72
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• 2022

In this paper, we aimed to examine the flowering dates of cherry blossom and the peak dates of maple leaves in South Korea, by the combination of temperature observation data from ASOS (Automated Surface Observing System) and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate Resolution Imaging Spectroradiometer). The more recent years, the faster the flowering dates and the slower the peak dates. This is because of the impacts of climate change with the increase of air temperature in South Korea. By reflecting the climate change, our statistical models could reasonably predict the plant phenology with the CC (Correlation Coefficient) of 0.870 and the MAE (Mean Absolute Error) of 3.3 days for the flowering dates of cherry blossom, and the CC of 0.805 and the MAE of 3.8 for the peak dates of maple leaves. We could suppose a linear relationship between the plant phenology DOY (day of year) and the environmental factors like temperature and NDVI, which should be inspected in more detail. We found that the flowering date of cherry blossom was closely related to the monthly mean temperature of February and March, and the peak date of maple leaves was much associated with the accumulated temperature. Amore sophisticated future work will be required to examine the plant phenology using higher-resolution satellite images and additional meteorological variables like the diurnal temperature range sensitive to plant phenology. Using meteorological grid can help produce the spatially continuous raster maps for plant phenology.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.36 no.3
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• pp.306-316
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• 2003

We conducted a time-series analysis of temperature and salinity of sea water around Jeju Island, Korea. Monthly mean temperature and salinity was influenced by precipitation and weather conditions on Jeju as well as by oceanographic conditions of the open sea such as the Tsushima Warm Current and sea water in coastal areas. Salinity of Jeju coastal waters was the highest in April, and it was always over 34.00 psu with tiny fluctuation between December and June. Due to the effects of the Tsushima Warm Current, Jeju coastal waters maintained high salinity and stability. Low salinity and its large fluctuations during summer were closely associated with the China Coastal Water and precipitation in Jeju. The place of the lowest water temperature was the northeast coasts of Jeju (Gimneong, Hado, Jongdalri). In winter, as warmer water of the Tsushima Warm Current appeared in western area of Jeju dwindled flowing along the northern coasts of Jeju area and becoming cool, the lowest water temperature often appeared locally in Gimnyeong and its vicinitly in summer. The Tsushima Warm Current flows into the east entrance of Jeju Strait, but its influence is weak because of geometry and strong vertical mixing due to fast tidal currents.

• Journal of the Korean Society of Food Science and Nutrition
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• v.28 no.4
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• pp.942-947
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• 1999

This study was conducted to evaluate sanitary practices of employees in business & industry foodservice operations of Pusan and the Kyung Nam areas, and to suggest a guideline for an effective sanitation training program. The questionnaire was used in this study as a survey method. Questionnaire were administered to 246 employees. The results were as follows. 55.3% of employees have had regular(monthly) food sanitation education. The mean rating of food sanitary knowledge for all employees was 65.9/100. When the education level was higher and the age younger, the mean rating of was also higher. Among the ratio of correct answers for food sanitary knowledge areas, a equipment sanitation was the highest (80.5%), and time temperature was the lowest(45.3%). The mean rating of sanitary procedures for food storage was 4.80/5.00, pre preparation 4.04/5.00, personal hygiene 3.54/5.00, equipment sanitation 3.20/5.00, and food preparation 2.56/5.00. Employees regularly educated in food sanitation rated significantly higher for food preparation than those who were of irregulary educated. The higher mean rating group(over 66) for the food sanitary knowledge showed significantly higher rates in sanitary procedures(food preparation, equipment sanitation, and personal hygiene) than that of the lower group(below 65). The practice of personal hygiene was positively correlated (p<0.001) with sanitary concept and food preparation, among the food sanitary knowledge areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.252-261
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• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.27-36
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• 2006

The radiative convective equilibrium (RCE) temperature was calculated for the climate change study at King Sejong Station in West Antarctica. As a result of RCE model sensitivity test, the increases of surface albedo, solar zenith angle, and cloud optical thickness decrease surface temperature. On the other hand, the increases of carbon dioxide and cirrus cloud amount are caused by surface warming due to the greenhouse effect. According to the model calculation result, annual mean surface temperature shows a upward trend of 0.012oC/year during the period of 1958-2001. During the period of 1989∼2001, the trend of monthly mean surface temperature by model calculation is 0.01oC/month and the observation trend is 0.005oC/month.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.104-110
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• 2001

Ocean heat fluxes over a wide region are generally estimated by an aerodynamic bulk fromula. Though a remote sensing technique can be expected to estimated global heat flux, it is difficult to obtain air temperature and specific humidity at sea surface by a remote sensor. In this study present a new method with which to determine near-sea surface air temperature from in situ data. Also, These methods compared with other methods. A new method used a linear regression equation between sea surface temperature and air temperature of the buoys data. In this study new method is validated using observed monthly mean data at the Japan Meteorological Agency(JMA), National Data Buoy Center(NDBC) and Tropical Ocean-Global Atmosphere(TOGA)-Tropical Atmosphere Ocean(TAO) buoys. The result that bias and rmse are 0.28, 1.5$0^{\circ}C$ respectively. The correlation coefficient is 0.98. Also, to retrieve near-sea surface specific humidity(Q) from good nonlinear regression relationship between vapor pressure(Ea) of buoy data and air temperature, after obtained the third-order polynomial function, compared with that of estimated from SSM/I empirical equation by Schussel et al(1995). The result that bias and rmse are -1.42 and 1.75(g/kg).