• Korean Journal of Environment and Ecology
• /
• v.29 no.3
• /
• pp.344-352
• /
• 2015

This study aims to identify the difference in the starting time of the dawn chorus of different species of birds and related environmental conditions. For this study, the bird songs were recorded every 2 hours a day starting from 2 hours before sunrise for a whole spring season (from April to June, 2014) in Korea. The recorded sounds were analyzed to find the starting time of each species' song by sonogram pattern using a sound analyzing program (Adobe Audition CC). To analyze the relationship between the environmental conditions and the time of the birdsong of each species, we collected the data of environmental conditions: daily precipitation, Julian date, time of sunrise and moonrise, temperature data and twilight time from the Korea Meteorological Office. As a result of this study, it was found that there are several statistical correlation between the starting time of the birdsong and environmental conditions (every environmental condition except daily precipitation and time of moonrise). Also, the difference of the starting time among each species were identified. The species were divided into 3 groups (early, mid and late) by their wake-up time. Ring-necked pheasant and yellow-throated bunting were categorized as 'Early' group and all woodpeckers were categorized as'Late' group. This study is significant as it first presented a classification of wild birds in Korea by the starting time of their dawn chorus. However, further studies are required to identify why each species to do their dawn singing at different times.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.2B
• /
• pp.155-163
• /
• 2011

In this study, a soil moisture estimation model was developed using a decision tree model, an artificial neural networks (ANN) model, remotely sensed data, and ground network data of daily precipitation, soil moisture and surface temperature. Soil moisture data of the Yongdam dam basin (5 sites) were used for model validation. Satellite remote sensing data and geographical data and meteorological data were used in the classification and regression tree (CART) model for data classification and the ANNs model was applied for clustered data to estimate soil moisture. Soil moisture data of Jucheon, Bugui, Sangjeon, Ahncheon sites were used for training and the correlation coefficient between soil moisture estimates and observations was between 0.92 to 0.96, root mean square error was between 1.00 to 1.88%, and mean absolute error was between 0.75 to 1.45%. Cheoncheon2 site was used for validation. Test statistics showed that the correlation coefficient, the root mean square error, the mean absolute error were 0.91, 3.19%, and 2.72% respectively. Results demonstrated that the developed soil moisture model using CART and ANN was able to apply for the estimation of soil moisture distribution.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.415-423
• /
• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• Journal of the Korean earth science society
• /
• v.40 no.6
• /
• pp.613-623
• /
• 2019

Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.1 no.1
• /
• pp.72-80
• /
• 1999

The study was conducted to establish the safe cropping season for direct- seeding on flooded paddy by the analysis of meteorological data(l973~1992, 20 years) from Korea Meteorological Administration. The critical date for early seeding(CDES) at direct- seeding culture on flooded paddy was decided by the appearance date of daily mean air temperature(DMAT) of 15$^{\circ}C$. The optimum heading date(OHD) was the first day when 22$^{\circ}C$ of daily mean air temperature could be kept for 40 days of ripening period after heading, and the critical date of late heading for safe ripening(CDHR) was the last day when 19$^{\circ}C$ of daily mean air temperature could be kept for 40 days after heading. The optimum seeding date(OSD) and the critical date for late seeding(CDLS) could be decided by the accumulated temperature from OHD and CDHR to the appearance dates of necessary temperatures for early, intermediate, and intermediately late maturing varieties. This results can be used for the determination of the safe cropping season of direct-seeding on flooded paddy in each agroclimatic zone. For instance, the OSD appearance date for early maturing variety in Suwon region appeared to be May 11~20 and the CDLS appearance date was May 31~June 7.

• Journal of the Korean association of regional geographers
• /
• v.1 no.1
• /
• pp.45-60
• /
• 1995

The purpose of this study is to classify the Korean precipitation regions on the basis of the characteristics of extratropical cyclonic precipitation. From now on, extratropical cyclone is called cyclone in short. By using factor analysis and Ward method in cluster analysis, precipitation regions on the basis of the characteristics of cyclonic precipitation are classified The principal data used in this study are daily precipitation records obtained from 60 weather stations of the Korea Meteorological Service during the ten years($1981{\sim}1990$), and weather charts published by the Japan Meteorological Agency. The results obtained in this study are summarized as follows: (1) In the factor analysis using 43 variables which have relation to the extratropical cyclonic precipitations, They are seven factors whose eigenvalues are above 1.0. This explains 86 percent of total amount. The first factor explains the characteristics of precipitation in the middle-west area and its contribution degree has the highest 10.9 percent. (2) According to the cluster analysis method of Ward, extratropical cyclonic precipitation regions are classified seven macro regions(such as Kyungki and North Youngseo, Youngdong and Ullungdo, Hoseo and South Youngseo, Honam and Northwest Chejudo, Southeast Chejudo, North Youngnam, and South Youngnam), 22 meso regions. (3) The characteristics of precipitation regions have relations to the path of cyclone, the direction of air inflow and the strike of mountain ranges. As the conclusion, the Central China Low brings much precipitation in the southern coast and southern area of Korea as moving to the northeastward. The North China Low moves eastward and brings much precipitation in the western area of the Taeback mountain ranges. The probability of extratropical cyclonic precipitation is the lowest in the inland of Yeongnam and the eastern coastal areas which belong to the rain shadow region. Namely, The seasonal and spatial characteristics of precipitation are closely associated with the path of cyclone and the direction of air inflow according to its passage, and the strike of mountain ranges.

• Journal of Korea Water Resources Association
• /
• v.41 no.2
• /
• pp.212-228
• /
• 2008

Five representative reference evapotranspiration(RET) equations were selected, and these equations were compared with pan evaporation by correlation analysis. Pan coefficients were also estimated. Furthermore, five selected RET equations were compared to find the similarity among those at the 21 meteorological stations located in South Korea. Five RET equations selected from 4 different category were Penman(combination approach), FAO Penman-Monteith(FAO P-M) (single source approach), Makkink and Priestley-Taylor (radiation approach) and Hargreaves(temperature approach) equations. In this study, the geographical and topographical conditions were considered for the selection of study stations. The daily meteorological data measured from 1970 at an interval of 5 years were applied in this study. The evapotranspiration estimates obtained by applying evapotranspiration equations were evaluated with numerical and graphical methods. The correlation coefficients between pan evaporation and RET in study stations were above 0.9 indicating very high correlation; however, the slopes of the individual regression lines show the values greater or less than 1.0. Hargreaves equation(temperature approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 12 study stations, which are located near to seashore except Daegu station. On the other hand, Priestley-Taylor equation(radiation approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 8 study stations, which are located in inland.

• Journal of Environmental Impact Assessment
• /
• v.19 no.2
• /
• pp.169-177
• /
• 2010

One of the most obvious climatic manifestations of urbanization in Korea is a trend towards higher air temperature. The trends of long-term annual temperature generally well describe the warming of urban areas. The increase of air temperature in urban area has been observed to the present since the meteorological observations in Korea began. The objective of this study is to explore the actual increase and the regional long-term trends of air temperature attributed to urbanization in the Korean Peninsula. Therefore, temperatures of the selected urban areas were compared with that of the surrounding rural areas, with the results varying by the application of the estimates of each region. The second objective is to separate the long-term trend of surface air temperature of global warming from urbanization and to find the actual temperature increase from urbanization in Korean peninsula. For the data analysis, daily air temperatures observed by the Korea Meteorological Administration (KMA) during between from 1961 and 2005 were used at five rural sites and cities. The re-analyzed surface air temperatures by the National Centers for Environmental Prediction (NCEP) was also carried out to compare the result from the observed air temperature in the Korean climate domain. In this study, the urban areas in Korea showed high increase rate of air temperature with $0.4^{\circ}C$ per decade during past 50 year period, while rural sites as Chupungryung with the $0.2^{\circ}C$ decadal increase rate. The analyses reflect that the urban area shows the high rate of temperature increase with $1.39^{\circ}C$ of regression value at the urban area, Seoul, and $0.43^{\circ}C$ at the rural site, Chupungnyeong during the period of 30 years. The temperature increas due to the urbanization only showed the increase range between $0.44^{\circ}C$ and $0.86^{\circ}C$, and the observed decrease in diurnal temperature range at five urban areas during the 30 years period.

• The Journal of Engineering Geology
• /
• v.22 no.4
• /
• pp.387-398
• /
• 2012

Korean agricultural areas that employ water curtain cultivation (WCC) have recently suffered extensive groundwater shortages due to an increase in the number of facilities. The primary focus of this study is to measure the daily groundwater use and discharge rates in the Cheongweon and Chungju pilot areas, while the second focus is to estimate the total amount of groundwater used in WCC areas nationwide in Korea. Taking into consideration several factors, including motor type, outflow abilities of wells, records of daily minimum temperatures below $0^{\circ}C$, and the number of running wells according to weather variations, we estimated that $53,138m^3/ha$ of groundwater had been used in the 4-hectare Cheongweon pilot area during the winter period of late 2011 through early 2012. On a prorated areal basis, we can calculate that the total groundwater used nationwide was 0.57 billion $m^3$ in WCC areas of $10,746m^2$. This value is equivalent to 33.7% of the total agricultural groundwater use (1.69 billion $m^3$) in Korea. During 9-22 February 2012, the daily water discharge rate in the 4-ha Cheongweon pilot area ranged from 2,079 to $2,628m^3$, averaging $2,341m^3$. Combining this value with meteorological records for 94 days with a daily minimum temperature below $0^{\circ}C$ results in an estimated groundwater volume of $54,990m^3/ha$ for the pilot area during the 2011-2012 winter period. The total amount of groundwater used nationwide in WCC areas would then be 0.59 billion $m^3$, equivalent to 34.9% of the total agricultural groundwater use in Korea. In the Chungju area, the groundwater discharge rate was estimated to be less than 805 $m^3$/ha. This value, combined with weather data for 108 days with a daily minimum temperature below $0^{\circ}C$ in this area, can be applied to infer that the total groundwater volume used in WCC areas nationwide is no more than 55% of the total agricultural groundwater use in Korea.

• Korean Journal of Remote Sensing
• /
• v.33 no.2
• /
• pp.135-147
• /
• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.