The average ratio of the daily UV-B to total solar (75) irradiance at Busan (35.23$^{\circ}$N, 129.07$^{\circ}$E) in Korea is found as 0.11%. There is also a high exponential relationship between hourly UV-B and total solar irradiance: UV-B=exp (a$\times$(75-b))(R$^2$=0.93). The daily variation of total ozone is compared with the UV-B irradiance at Pohang (36.03$^{\circ}$N, 129.40$^{\circ}$E) in Korea using the Total Ozone Mapping Spectrometer (TOMS) data during the period of May to July in 2005. The total ozone (TO) has been maintained to a decreasing trend since 1979, which leading to a negative correlation with the ground-level UV-B irradiance doting the given period of cloudless day: UV-B=239.23-0.056 TO (R$^2$=0.52). The statistical predictions of daily total ozone are analyzed by using the data of the Brewer spectrophotometer and TOMS in East Asia including the Korean peninsula. The long-term monthly averages of total ozone using the multiplicative seasonal AutoRegressive Integrated Moving Average (ARIMA) model are used to predict the hourly mean UV-B irradiance by interpolating the daily mean total ozone far the predicting period. We also can predict the next day's total ozone by using regression models based on the present day's total ozone by TOMS and the next day's predicted maximum air temperature by the Meteorological Mesoscale Model 5 (MM5). These predicted and observed total ozone amounts are used to input data of the parameterization model (PM) of hourly UV-B irradiance. The PM of UV-B irradiance is based on the main parameters such as cloudiness, solar zenith angle, total ozone, opacity of aerosols, altitude, and surface albedo. The input data for the model requires daily total ozone, hourly amount and type of cloud, visibility and air pressure. To simplify cloud effects in the model, the constant cloud transmittance are used. For example, the correlation coefficient of the PM using these cloud transmissivities is shown high in more than 0.91 for cloudy days in Busan, and the relative mean bias error (RMBE) and the relative root mean square error (RRMSE) are less than 21% and 27%, respectively. In this study, the daily variations of calculated and predicted UV-B irradiance are presented in high correlation coefficients of more than 0.86 at each monitoring site of the Korean peninsula as well as East Asia. The RMBE is within 10% of the mean measured hourly irradiance, and the RRMSE is within 15% for hourly irradiance, respectively. Although errors are present in cloud amounts and total ozone, the results are still acceptable.
We studied basic ideas of a network based Gravity/Magnetic data processing server/client system which provides functions of data processing, forward modeling, inversion and data process on Data Base. This Java technology was used to provide facilities, socket communication and JDBC(Java Database Connectivity) technology to produce an effective and practical client application. The server computers are linked by network to process the MPI parallelized computing. This can provide useful devices of the geophysical process and modeling that usually require massive computing performance and time. Since this system can be accessed by lots of users, it can provides the consistent and confident results through the verified processing programs. This system also makes it possible to get results and outputs through internet when their local machines are connected to the network. It can help many users who want to omit the jobs of system administration and to process data during their field works.
This paper analyzed the characteristics of daily ozone variations over Kangreung and Wonju. It was found that the diurnal cycle of ozone over Wonju has a primary ozone peak in the afternoon and a minimum around sunrise, which is a typical diurnal ozone cycle observable in the urban area. However, the cycle over Kangreung shows a primary peak in the afternoon and secondary peak around 3 a.m. The amounts of ozone in the secondary peak is occasionally higher than that in the primary peak. This nocturnal ozone peak is frequently observed year-round, and the highest frequency and extent are observed in spring. The possible cause of this nocturnal ozone increase was investigated using meteorological parameters and the HYSPLIT trajectory model. It was found that the nocturnal ozone peak is highly correlated with strong wind speed, which has led to positive temperature anomaly. The trajectory model revealed that when the secondary peak occurred, the air was originated from the west and a sinking motion subsequently followed. These findings suggested that when the westerly wind is strongest in spring, the polluted airs from urban areas are transported to the upper boundary layer over Kangreung area. In the case of strong wind during the night, nocturnal ozone peaks were produced by active vertical mixing between lower boundary and upper boundary layers.
The temperature change patterns of climatic solar terms and their climatic fitness were analyzed. Harmonic analysis based on thirty-year(1981-2010) time-series data from sixty one weather stations across South Korea showed that the central peaks of the extreme heat had shifted toward start of autumn with increasing mean temperature. The overall climatic fitness of solar terms, such as major heat, frost descent, major snow, and major cold, was low, and it showed significant regional variations. The actual meteorological phenomenon representing each climatic solar term was observed much later than the day of the solar term at most weather stations. The number of observations, where an actual meteorological condition for each climatic solar term was recorded within ${\pm}1$ week from the day of that solar term, ranged only from 7.7% to 40.4% of the entire data. Study results also showed that the climatic fitness of major heat, frost descent, and major snow gradually changed in the east-west direction. Major cold, a solar term with higher climatic fitness, was influenced more strongly by latitude than longitude. Considering geographically uneven magnitude and trends in temperature changes, rearrangement and adjustment of time intervals between the solar terms may help us improve their applicability as realistic indicators of seasonal changes.
Park, Soon-Young;Yoo, Jung-Woo;Kang, Nam-Young;Lee, Soon-Hwan
Journal of Environmental Science International
/
v.26
no.5
/
pp.573-584
/
2017
In order to simulate a typhoon precisely, the satellite observation data has been assimilated using WRF (Weather Research and Forecasting model) three-Dimensional Variational (3DVAR) data assimilation system. The observation data used in 3DVAR was GPS Radio Occultation (GPS-RO) data which is loaded on Low-Earth Orbit (LEO) satellite. The refractivity of Earth is deduced by temperature, pressure, and water vapor. GPS-RO data can be obtained with this refractivity when the satellite passes the limb position with respect to its original orbit. In this paper, two typhoon cases were simulated to examine the characteristics of data assimilation. One had been occurred in the Western Pacific from 16 to 25 October, 2015, and the other had affected Korean Peninsula from 22 to 29 August, 2012. In the simulation results, the typhoon track between background (BGR) and assimilation (3DV) run were significantly different when the track appeared to be rapidly change. The surface wind speed showed large difference for the long forecasting time because the GPS-RO data contained much information in the upper level, and it took a time to impact on the surface wind. Along with the modified typhoon track, the differences in the horizontal distribution of accumulated rain rate was remarkable with the range of -600~500 mm. During 7 days, we estimated the characteristics between daily assimilated simulation (3DV) and initial time assimilation (3DV_7). Because 3DV_7 demonstrated the accurate track of typhoon and its meteorological variables, the differences in two experiments have found to be insignificant. Using observed rain rate data at 79 surface observatories, the statistical analysis has been carried on for the evaluation of quantitative improvement. Although all experiments showed underestimated rain amount because of low model resolution (27 km), the reduced Mean Bias and Root-Mean-Square Error were found to be 2.92 mm and 4.53 mm, respectively.
Journal of the Korean association of regional geographers
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v.22
no.4
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pp.856-874
/
2016
This study aims to figure out the weather and climate environment of Seoul area in S. Korea during 1623~1800, which has not been studied so far, by using daily records of weather conditions and meteorological phenomena in the Daily Records of Royal Secretariat of Joseon Dynasty(承政院日記) together with records of abnormal weather conditions and natural disasters in the Annals of the Joseon Dynasty(朝鮮王朝實錄). During 1500~1760 as a period of the Little Ice Age it was generally cold and dry, particularly cool summers of Seoul area. Changes in weather conditions and meteorological phenomena and climate changes appeared prominently at around 1650, 1710, 1770. The annual numbers of rain days and of snow days began to change largely in the 1640s. The rain(and snow) days reduced significantly in the 1710s~1650s, but increased sharply in the 1710s and later. The rain days in summer rapidly increased after the late 1710s, while the snow days greatly reduced after the mid 1770s. The cloudy days around the 1710s greatly reduced in summer, while slightly increased in winter. The hail days increased significantly in the late 1720s and lasted until the 1760s. The fog days began to reduce after 1770 to the fewer days than the climatic normals of 1981~2010. These times are overall consistent with findings of historical climatological cross-checking data and geophysical biological proxy data, accompanied by a trend of relatively enhanced colder and drier of Seoul area.
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.
Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS-DNB) data provides a much higher capability for observing and quantifying nighttime light (NTL) brightness in comparison with Defense Meteorological Satellite-Operational Linescan System (DMSP-OLS) data. In South Korea, there is little research on the detection of NTL brightness change using VIIRS-DNB data. This study analyzed the spatial distribution and change of NTL brightness between 2013 and 2016 using VIIRS-DNB data, and detected its spatial relation with possible influencing factors using regression models. The intra-year seasonality of NTL brightness in 2016 was also studied by analyzing the deviation and change clusters, as well as the influencing factors. Results are as follows: 1) The higher value of NTL brightness in 2013 and 2016 is concentrated in Seoul and its surrounding cities, which positively correlated with population density and residential areas, economic land use, and other factors; 2) There is a decreasing trend of NTL brightness from 2013 to 2016, which is obvious in Seoul, with the change of population density and area of industrial buildings as the main influencing factors; 3) Areas in Seoul, and some surrounding areas have high deviation of the intra-year NTL brightness, and 71% of the total areas have their highest NTL brightness in January, February, October, November and December; and 4) Change of NTL brightness between summer and winter demonstrated a significantly positive relation with snow cover area change, and a slightly and significantly negative relation with albedo change.
Kim, Dong-Gill;Chung, Suh-Yong;Melka, Yoseph;Negash, Mesele;Tolera, Motuma;Yimer, Fantaw;Belay, Teferra;Bekele, Tsegaye
Journal of Climate Change Research
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v.9
no.4
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pp.303-312
/
2018
In Ethiopia, climate change and deforestation are major issues hindering sustainable development. Local Ethiopian communities commonly perceive an increase in temperature and a decrease in rainfall. Meteorological data shows that rainfall has declined in southern Ethiopia, and spring droughts have occurred more frequently during the last 10-15 years. The frequently occurring droughts have seriously affected the agriculture-dominated Ethiopian economy. Forests can play an important role in coping with climate change. However, deforestation is alarmingly high in Ethiopia, and this is attributed mainly to agricultural expansion and fuel wood extraction. Deforestation has led to a decrease in various benefits from forest ecosystem services, and increased ecological and environmental problems including loss of biodiversity. To resolve the issues effectively, it is crucial to enhance climate change resilience through reforestation and various international collaborations are urgently needed. To continue collaboration activities for resolving these issues, it is first necessary to address fundamental questions on the nature of collaboration: does collaboration aim for a support-benefit or a mutual benefit situation; dividing the workload or sharing the workload; an advanced technology or an appropriate technology; and short-term and intensive or long-term and extensive?. Potential collaboration activities were identified by sectors: in the governmental sector, advancing governmental structure and policy, enhancing international collaborations and negotiations, and capacity building for forest restoration and management; in the research and education sector, identifying and filling gaps in forestry and climate change education, capacity building for reforestation and climate change resilience research, and developing bioenergy and feed stocks; and in the business and industry sector, supporting conservation based forestry businesses and industries, while promoting collaboration with the research and education sectors. It is envisaged that international collaboration for enhancing climate change resilience through reforestation will provide a strong platform for resolving climate change and deforestation issues, and achieving sustainable development in Ethiopia.
Journal of the Korean Association of Geographic Information Studies
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v.22
no.3
/
pp.65-81
/
2019
The twenty-four Solar Terms are Chinese traditional astronomical divisions that describe seasonal cycles of the year. Based on the analyses of meteorological data during 1979~2018, study results showed that the temperatures of the Solar Terms had increased in general in the Korean Peninsula. In North Korea, temperature increases were observed on 21 Solar Terms, and their seasonal mean temperatures were increased by $0.87^{\circ}C$, $1.19^{\circ}C$, $1.45^{\circ}C$, and $0.64^{\circ}C$ on average in spring, summer, fall, and winter, respectively. The duration of summer has lengthened due to the temperature rise in fall, and the magnitude of temperature change was greater in summer compared to winter. As for South Korea, increases in temperature were observed on 18 Solar Terms, and the temperature changes were more pronounced in fall and winter than spring and summer. The Great Snow temperature decreased more than any other Solar Terms during the study period, and this temperature change was observed both in North and South Koreas. The Great Cold, which represents the coldest day of the year, showed a significant temperature increase of $3.08^{\circ}C$, while the Slight Heat had a marginal temperature increase of $0.29^{\circ}C$. The hottest day and the first day of frost tended to come later than the Great Heat and the Frost's Decent. By contrast, the coldest day tended to occur later than the Great Cold in the study area. On average over the entire study period, the climatic fitness of the Great Heat and the Frost's Decent was higher in North Korea, and that of the Great Cold was higher in South Korea, respectively.
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