• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Journal of the Korean earth science society
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• v.33 no.2
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• pp.139-147
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• 2012

Mongolia's solar-meteorological resources map has been developed using satellite data and reanalysis data. Solar radiation was calculated using solar radiation model, in which the input data were satellite data from SRTM, TERA, AQUA, AURA and MTSAT-1R satellites and the reanalysis data from NCEP/NCAR. The calculated results are validated by the DSWRF (Downward Short-Wave Radiation Flux) from NCEP/NCAR reanalysis. Mongolia is composed of mountainous region in the western area and desert or semi-arid region in middle and southern parts of the country. South-central area comprises inside the continent with a clear day and less rainfall, and irradiation is higher than other regions on the same latitude. The western mountain region is reached a lot of solar energy due to high elevation but the area is covered with snow (high albedo) throughout the year. The snow cover is a cause of false detection from the cloud detection algorithm of satellite data. Eventually clearness index and solar radiation are underestimated. And southern region has high total precipitable water and aerosol optical depth, but high solar radiation reaches the surface as it is located on the relatively lower latitude. When calculated solar radiation is validated by DSWRF from NCEP/NCAR reanalysis, monthly mean solar radiation is 547.59 MJ which is approximately 2.89 MJ higher than DSWRF. The correlation coefficient between calculation and reanalysis data is 0.99 and the RMSE (Root Mean Square Error) is 6.17 MJ. It turned out to be highest correlation (r=0.94) in October, and lowest correlation (r=0.62) in March considering the error of cloud detection with melting and yellow sand.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• Korean Journal of Environment and Ecology
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• v.33 no.6
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• pp.636-644
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• 2019

The purpose of this study was to investigate the callings of nocturnal birds using bioacoustic recording technology to identify species and to analyze the ecological characteristics of each species. Three sites - Seoraksan National Park, National Institute of Ecology, and Mudeungsan National Park - were investigated. The investigation period was from the middle of April 2018 to early March 2019 for Seoraksan national park, from late February of 2018 to the middle of February 2019 for the National Institute of Ecology, and from the middle of February 2018 to the end of August 2018 for Mudeungsan National Park. The main research results are as follows. Firstly, nocturnal bird species identified by the survey included Caprimulgus indicus, Otus sunia, Zoothera aurea, Bubo bubo, and Strix uralensis, 5 species in total. Secondly, the breeding call period of each species was from early May to early August for C. indicus, from early April to the end of September for O. sunia, from early March to early October for Z. aurea, from late September to early February for B. bubo, and from mid-January to early March for S. uralensis. Thirdly, the mating call rhythm was between 16:00 and 10:00 on the following day for all the observed species in the three regions, and the peak time zone was from 20:00 to 06:00 on the following day. Fourthly, there was no correlation between the cumulative call frequency and the precipitation for each species. Fifthly, the mean temperature during the period when the specific calls of nocturnal birds were detected was -4.00 ℃ for S. uralensis, 2.58 ℃ for B. bubo, 13.66 ℃ for Z. aurea, 19.50 ℃ for O. sunia, and 20.77 ℃ for C. indicus. The ANOVA results showed that there was a significant difference in mean temperature for the calling by species and that the mean temperature was S. uralensis, B. bubo, Z. aurea, and O. sunia-C. indicus, in the ascending order, for 4 groups in total. The period of the specific mating calls confirmed by the study is a period in which the frequency of calls was the highest among the periods when the specific calls were detected. Since it is associated with the known mating period of each species, the period of the high frequency of calls confirmed by the bioacoustic monitoring can be regarded as the mating season. This study is meaningful in that it is the early research that has used the bioacoustic recording technology to identify species and ecological characteristics of species of nocturnal birds in Korea.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.4
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• pp.214-226
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• 2013

To understand the changing patterns in phytoplankton communities, we conducted 12 surveys along the Nakdong River, its estuary, and adjacent coastal areas between January 2011 and October 2012 (during the period of barrage construction and sediment dredging). Monthly precipitation ranged from 0 to 502 mm during the survey period, and salinity ranged between 0.1 psu and 0.3 psu in the Nakdong River, regardless of the depth, indicating no seawater influence, while salinity showed large seasonal fluctuations in the estuarine and coastal station, ranging from 0.1 psu to 34.8 psu. A total of 402 phytoplankton species were identified, 178 species from the river and 331 species from the estuary and coastal areas. Phytoplankton standing crop increased in 2012 compared to that in 2011, and was found to be highest in the river, followed by the estuary and coastal areas. Among the top 20 species in frequency of occurrence and dominance, Stephanodiscus spp., Aulacoseira granulata, and Aulacoseira granulata var. angustissima and Pseudo-nitzschia spp. were important species along the river-estuary-coastal areas. Diatoms were the major taxonomic group inhabiting the Nakdong river-estuary-coastal areas. A comparison of seasonal dominant phytoplankton species revealed a slight decrease over the years, from 13 species in 2011 to 10 species in 2012. However, no significant difference was found in the diversity of phytoplankton species between the two survey years, although lightly greater diversity was observed in the coastal areas than in the river and estuary. Cluster analysis with community composition data revealed that the community structure varied significantly in 2011 depending on the time of survey, while in 2012, it hardly showed any variation and was simpler. An increase in the phytoplankton standing crop, fewer dominant species, and simpler community structure in 2012 compared to those in 2011 are probably due to the rapid environmental changes along the Nakdong River. To investigate these ecological relationships, it is necessary to conduct further studies focusing on integrated analyses of biocenosis, including phytoplankton with respect to the changes in nutrient distribution, variation of freshwater discharge, and effect area of freshwater in the Nakdong estuary and adjacent coastal areas.

• Atmosphere
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• v.24 no.3
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• pp.303-315
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• 2014

Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.