The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.
Korean Journal of Agricultural and Forest Meteorology
/
v.12
no.1
/
pp.11-22
/
2010
According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.
Korean Journal of Agricultural and Forest Meteorology
/
v.17
no.3
/
pp.261-269
/
2015
The purpose of this research is to identify the significance of climate factors related to the significance of change of dry matter yield (DMY) of whole crop maize (WCM) by year through the exploratory data analysis. The data (124 varieties; n=993 in 7 provinces) was prepared after deletion and modification of the insufficient and repetitive data from the results (124 varieties; n=1027 in 7 provinces) of import adaptation experiment done by National Agricultural Cooperation Federation. WCM was classified into early-maturity (25 varieties, n=200), mid-maturity (40 varieties, n=409), late-maturity (27 varieties, n=234) and others (32 varieties, n=150) based on relative maturity and days to silking. For determining climate factors, 6 weather variables were generated using weather data. For detecting DMY and climate factors, SPSS21.0 was used for operating descriptive statistics and Shapiro-Wilk test. Mean DMY by year was classified into upper and lower groups, and a statistically significant difference in DMY was found between two groups (p<0.05). To find the reasons of significant difference between two groups, after statistics analysis of the climate variables, it was found that Seeding-Harvesting Accumulated Growing Degree Days (SHAGDD), Seeding-Harvesting Precipitation (SHP) and Seeding-Harvesting Hour of sunshine (SHH) were significantly different between two groups (p<0.05), whereas Seeding-Harvesting number of Days with Precipitation (SHDP) had no significant effects on DMY (p>0.05). These results indicate that the SHAGDD, SHP and SHH are related to DMY of WCM, but the comparison of R2 among three variables (SHAGDD, SHP and SHH) couldn't be obtained which is needed to be done by regression analysis as well as the prediction model of DMY in the future study.
Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.
Park, GwangSeob;Kim, Hyun-Cheol;Lee, Taehee;Son, Young Baek
Korean Journal of Remote Sensing
/
v.34
no.6_2
/
pp.1299-1310
/
2018
In this study, we analyzed distribution and movement trends using in-situ observations and particle tracking methods to understand the movement of the drift ice in the Arctic Ocean. The in-situ movement data of the drift ice in the Arctic Ocean used ITP (Ice-Tethered Profiler) provided by NOAA (National Oceanic and Atmospheric Administration) from 2009 to 2018, which was analyzed with the location and speed for each year. Particle tracking simulates the movement of the drift ice using daily current and wind data provided by HYCOM (Hybrid Coordinate Ocean Model) and ECMWF (European Centre for Medium-Range Weather Forecasts, 2009-2017). In order to simulate the movement of the drift ice throughout the Arctic Ocean, ITP data, a field observation data, were used as input to calculate the relationship between the current and wind and follow up the Lagrangian particle tracking. Particle tracking simulations were conducted with two experiments taking into account the effects of current and the combined effects of current and wind, most of which were reproduced in the same way as in-situ observations, given the effects of currents and winds. The movement of the drift ice in the Arctic Ocean was reproduced using a wind-imposed equation, which analyzed the movement of the drift ice in a particular year. In 2010, the Arctic Ocean Index (AOI) was a negative year, with particles clearly moving along the Beaufort Gyre, resulting in relatively large movements in Beaufort Sea. On the other hand, in 2017 AOI was a positive year, with most particles not affected by Gyre, resulting in relatively low speed and distance. Around the pole, the speed of the drift ice is lower in 2017 than 2010. From seasonal characteristics in 2010 and 2017, the movement of the drift ice increase in winter 2010 (0.22 m/s) and decrease to spring 2010 (0.16 m/s). In the case of 2017, the movement is increased in summer (0.22 m/s) and decreased to spring time (0.13 m/s). As a result, the particle tracking method will be appropriate to understand long-term drift ice movement trends by linking them with satellite data in place of limited field observations.
Myeong-Ju, Choi;Joong-Bae, Ahn;Young-Hyun, Kim;Min-Kyung, Jung;Kyo-Moon, Shim;Jina, Hur;Sera, Jo
Korean Journal of Agricultural and Forest Meteorology
/
v.24
no.4
/
pp.218-233
/
2022
The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.
In order to characterize the shear strength of the frozen sand for foundation design in cold region and prediction of adfreeze bond strength, many researchers developed test techniques and carried out many tests to analyze shear strength properties of the frozen sand for half a century. However, many studies for shear strength properties of the frozen sand have been carried out with limited circumstances, even though shear strength of the froze sand can be affected by various influence factors such as soil type, temperature conditions, and magnitude of normal stress. In this study, direct shear test equipment was used to analyze the shear strength characteristics of the frozen sand. Direct shear test equipment was designed for cold weather, and the direct shear tests were carried out inside of large-scaled low temperature chamber. Three soil types-two uniform sands and one well graded soil were used to analyze the shear strength of the frozen sand with three different temperature conditions and three different vertical confining pressures. In this research, a series of direct shear tests for shear strength of the frozen sand have been conducted to demonstrate the efficiency of effectiveness of the test equipment and low temperature chamber. This research also showed that shear strength of the froze sand increased with decreasing temperature condition, but the influence of vertical confining pressure was insignificant to the shear strength of the frozen sand.
Park, Kihyun;Min, Byung-Il;Kim, Sora;Kim, Jiyoon;Suh, Kyung-Suk
Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
/
v.18
no.2_spc
/
pp.261-273
/
2020
North Korea conducted the sixth underground nuclear test on September 3, 2017 at the Punggye-ri Nuclear Test Site (NTS). In contrast to the previous five nuclear tests, several induced earthquakes occurred around the NTS after the sixth nuclear test and this may have caused radioxenon leakages at the site. Considering these reported earthquakes, we performed atmospheric dispersion simulations on some radioxenon emission scenarios for this event using our Lagrangian Atmospheric Dose Assessment System (LADAS) model by employing the Unified Model (UM) based numerical weather prediction data produced by the Korea Meteorological Administration (KMA). To find out possible detection locations and times, we combined not only daily and weekly based delayed releases but also leakages after the reported earthquakes around the NTS to create emission scenarios. Our simulation results were generally in good agreement with the measured data of the Nuclear Safety and Security Commission and International Monitoring System (IMS) stations operated by the Comprehensive nuclear Test-Ban-Treaty Organization (CTBTO).
Journal of the Korean Association of Geographic Information Studies
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v.14
no.3
/
pp.203-222
/
2011
The characteristics of flood damages have been increasingly strengthened and take the form of unpredictable and unusual weather phenomena caused by climate change and climate anomalies. To prevent inundation damage caused by breach of hydraulic structure such as dam or levee, and trouble of drainage of inner basin, the prediction necessity of flood inundation area, flood risk analysis, and drawing flood risk maps have been on the rise, and the national flood risk maps have been produced. In this study, the quantitative flood vulnerability analysis was performed, which represents population living within flood-affected areas, types of economic activities, facilities affected by flood, in order to extend flood risk mapping from simple hazard concept into risk based idea. By applying it to Nakdong River basin, the flood vulnerability indices were estimated to draw flood risk maps subdivided into administrative districts. The result of this study can be applied to establish the disaster prevention measures and priority decision of disaster prevention project.
Data assimilation effect of mobile rawinsonde observation was evaluated using Unified Model (UM) with a Three-Dimensional Variational (3DVAR) data assimilation system during the intensive observation program of 2013 summer season (rainy season: 20 June-7 July 2013, heavy rain period: 8 July-30 July 2013). The analysis was performed by two sets of simulation experiments: (1) ConTroL experiment (CTL) with observation data provided by Korea Meteorological Administration (KMA) and (2) Observing System Experiment (OSE) including both KMA and mobile rawinsonde observation data. In the model verification during the rainy season, there were no distinctive differences for 500 hPa geopotential height, 850 hPa air temperature, and 300 hPa wind speed between CTL and OSE simulation due to data limitation (0000 and 1200 UTC only) at stationary rawinsonde stations. In contrast, precipitation verification using the hourly accumulated precipitation data of Automatic Synoptic Observation System (ASOS) showed that Equivalent Threat Score (ETS) of the OSE was improved by about 2% compared with that of the CTL. For cases having a positive effect of the OSE simulation, ETS of the OSE showed a significantly higher improvement (up to 41%) than that of the CTL. This estimation thus suggests that the use of mobile rawinsonde observation data using UM 3DVAR could be reasonable enough to assess the improvement of prediction accuracy.
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