• Atmosphere
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• v.18 no.4
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• pp.475-483
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• 2008

The hourly precipitation data from 1973 to 2007 observed at 60 weather stations over Korea are used to characterize the diurnal and semidiurnal cycles of total precipitation amount, intensity and frequency and examine their spatial patterns and interannual variations. The results show that the diurnal cycle peaks in the morning (03-09LST) and the semidiurnal cycle peaks in the late afternoon (16-20LST). It is found that the spatial variations of the peak phase of diurnal or semidiurnal cycle relative to their corresponding seasonal mean cycle are considerably small (large) for total precipitation amount and intensity (frequency, respectively) in both winter and summer seasons. Also, the diurnal phase variations for individual years relative to the seasonal mean precipitation show the significant interannual variability with dominant periods of 2-5 years for all three elements of precipitation and the slightly decreasing trend in total precipitation amount and intensity. To compare the relative contributions of frequency and intensity to the diurnal and semidiurnal cycles (and their sum) of total precipitation amount, the percentage variance of each cycle of precipitation amount explained by frequency is estimated. The fractional variance accounted for by precipitation intensity is greater than that of frequency for these three cycles. All above analyses suggest that intensity plays a more important role than frequency in the diurnal variations of total precipitation amount.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1247-1250
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• 2004

The amount of precipitation during El Nino over Korea increases in Summer and Winter. However, it decreases in Fall, and exhibits not much change in Spring. Especially, the amount of precipitation during September of El Nino year is much less than that of the September of non-El Nino year. The amount of precipitation during El Nino year of October and November shows similar amount of precipitation during non-El Nino year of the same period. The reason for decreasing precipitation in September is related to the weakening of the 2nd rainy season during the development of El Nino over East Asia including Korea. Insufficiency of fall precipitation during El Nino year influences drought in Spring for next year.

• Atmosphere
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• v.33 no.4
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• pp.367-385
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• 2023

The variabilities of precipitation and particulate matters (i.e., PM₁₀ and PM_2.5) and the scavenging efficiency of PMs by precipitation were quantified using long-term measurements in Seoul, Korea. The 21 years (2001~2021) measurements of precipitation and PM₁₀ mass concentrations, and the 7 years (2015~2021) of PM_2.5 mass concentrations were used. Statistical analysis was performed for each period (i.e., year, season, and month) to identify the long-term variabilities of PMs and precipitation. PM₁₀ and PM_2.5 decreased annually and the decreasing rate of PM₁₀ was greater than PM_2.5. The precipitation intensity did not show notable variation, whereas the annual precipitation amount showed a decreasing trend. The summer precipitation amount contributed 61.10% to the annual precipitation amount. The scavenging efficiency by precipitation was analyzed based on precipitation events separated by 2-hour time intervals between hourly precipitation data for 7 years. The scavenging efficiencies of PM₁₀ and PM_2.5 were quantified as a function of precipitation characteristics (i.e., precipitation intensity, amount, and duration). The calculated average scavenging efficiency of PM₁₀ (PM_2.5) was 39.59% (35.51%). PM₁₀ and PM_2.5 were not always simultaneously scavenged due to precipitation events. Precipitation events that simultaneously scavenged PM₁₀ and PM_2.5 contributed 42.24% of all events, with average scavenging efficiency of 42.93% and 43.39%. The precipitation characteristics (i.e., precipitation intensity, precipitation amount, and precipitation duration) quantified in these events were 2.42 mm hr^-1, 15.44 mm, and 5.51 hours. This result corresponds to 145% (349%; 224%) of precipitation intensity (amount; duration) for the precipitation events that do not simultaneously scavenge PM₁₀ and PM_2.5.

• Journal of Korea Water Resources Association
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• v.52 no.6
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• pp.421-427
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• 2019

The amount of exploitable groundwater amount in Korea has been determined by multiplying the 10-year frequency low precipitation by the recharge rate. In practice, however, the interpretation of the frequency analysis of precipitation is omitted, and the value obtained by multiplying the average recharge rate by the minimum precipitation in the recent 10 years is used as the recharge amount. Therefore, the contradiction arises that the amount of precipitation to be applied is determined according to the period selection rather than the actual low precipitation by the 10-year frequency analysis. In this study, we proposed a method for estimating the exploitable groundwater amount using the recharge amount considering the moving averaged 10-year minimum precipitation and the size of precipitation. This method was applied to the Uiwang, Gwacheon and Seongnam areas and the exploitable groundwater amount was calculated and compared with the results obtained by conventional methods. As a result, it has been confirmed that if the 10-year minimum precipitation is selected in the period including the extreme drought, the problem of underestimating the exploitable groundwater amount can be overcome by using the moving average minimum precipitation.

• Atmosphere
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• v.22 no.1
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• pp.57-71
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• 2012

Influences of orographic and ocean effect, which depend on the detailed geographic characteristics, upon winter time (December-February) precipitation in the Yeongdong region are investigated. Most of precipitation events in the Yeongdong region during the wintertime are associated with moist northeasterly (coming from the northeast direction) winds and also the spatial distribution of precipitation shows a great difference between Mountain area (Daegwallyeong) and Coastal area (Gangneung). The linear correlation coefficient between the meteorological variables obtained from NCEP/NCAR Reanalysis Data and precipitation amount for each precipitation type is calculated. Mountain type precipitation is dominated by northeasterly wind speed of the low level (1000 hPa and 925 hPa) and characterized with more precipitation in mountain area than coastal area. However, Coastal type precipitation is affected by temperature difference between ocean and atmosphere, and characterized with more precipitation in coastal area than mountain area. The results are summarized as follows; In the case of mountain type precipitation, the correlation coefficient between wind speed at 1000 hPa (925 hPa) and precipitation amount at Daegwallyeong is 0.60 (0.61). The correlation is statistical significant at 1% level. In the case of coastal type precipitation, the correlation coefficient of temperature difference between ocean and 925 hPa (850 hPa) over the East sea area and precipitation amount at Gangneung is 0.33 (0.34). As for the mountain type precipitation, a detailed analysis was conducted in order to verify the relationship between precipitation amount at Daegwallyeong and low level wind speed data from wind profiler in Gangneung and Buoy in the East Sea. The results also show the similar behavior. This result indicates that mountain type precipitation in the Yeongdong region is closely related with easterly wind speed. Thus, the statistical analysis of the few selected meteorological variables can be a good indicator to estimate the precipitation totals in the Yeongdong region in winter time.

• Journal of Environmental Science International
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• v.26 no.3
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• pp.289-302
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• 2017

During the research period, error analysis of the amount of daily precipitation was performed with data obtained from 2DVD, Parsivel, and AWS, and from the results, 79 days were selected as research days. According to the results of a synoptic meteorological analysis, these days were classified into 'LP type, CF type, HE type, and TY type'. The dates showing the maximum daily precipitation amount and precipitation intensity were 'HE type and CF type', which were found to be attributed to atmospheric instability causing strong ascending flow, and leading to strong precipitation events. Of the 79 days, most days were found to be of the LP type. On July 27, 2011 the daily precipitation amount in the Korean Peninsula reached over 80 mm (HE type). The leading edge of the Northern Pacific high pressure was located over the Korean Peninsula with unstable atmospheric conditions and inflow of air with high temperature and high humidity caused ascending flow, 120 mm/h with an average precipitation intensity of over 9.57 mm/h. Considering these characteristics, precipitation in these sample dates could be classified into the convective rain type. The results of a precipitation scale distribution analysis showed that most precipitation were between 0.4-5.0 mm, and 'Rain' size precipitation was observed in most areas. On July 9, 2011, the daily precipitation amount was recorded to be over 80 mm (CF type) at the rainy season front (Jangma front) spreading across the middle Korean Peninsular. Inflow of air with high temperature and high humidity created unstable atmospheric conditions under which strong ascending air currents formed and led to convective rain type precipitation.

• Atmosphere
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• v.19 no.2
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• pp.199-211
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• 2009

In this paper, we examine the multiple change-point and change pattern in the 54 years (1954-2007) time series of the annual and the heavy precipitation characteristics (amount, days and intensity) averaged over South Korea. A Bayesian approach is used for detecting of mean and/or variance changes in a sequence of independent univariate normal observations. Using non-informative priors for the parameters, the Bayesian model selection is performed by the posterior probability through the intrinsic Bayes factor of Berger and Pericchi (1996). To investigate the significance of the changes in the precipitation characteristics between before and after the change-point, the posterior probability and 90% highest posterior density credible intervals are examined. The results showed that no significant changes have occurred in the annual precipitation characteristics (amount, days and intensity) and the heavy precipitation intensity. On the other hand, a statistically significant single change has occurred around 1996 or 1997 in the heavy precipitation days and amount. The heavy precipitation amount and days have increased after the change-point but no changes in the variances.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.875-885
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• 2012

In this study, the total precipitation amount in Jeju Island was estimated with the simulated precipitation for ungauged stations missing precipitation data using the spatial precipitation analysis. The missing data were generated through the modified multiple linear regression in this study, and the analysis of spatial precipitation was conducted with the PRISM(Parameter-elevation Regression on Independent Slope Model). The generated data with modified multiple linear regression model have similar pattern with original data. Thus, the model in this study shows good applicability to estimate the missing data. The difference of annual average precipitation between Case 1 (original data) and Case 2 (modified data) appears very small ratio which is about 1.5%. However, the difference of annual average precipitation according to elevation shows the large ratio up to 37.4%. As the results, the method of estimating missing data in this study would be useful to calculate the total precipitation amount at the low station density area and the places with the high spatial variation of precipitation.

• Atmosphere
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• v.18 no.2
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• pp.111-120
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• 2008

This study presents a change-point in the 30 years (1976-2005) time series of the annual and the heavy precipitation characteristics (amount, days and intensity) averaged over South Korea using Bayesian approach. The criterion for the heavy precipitation used in this study is 80 mm/day. Using non-informative priors, the exact Bayes estimators of parameters and unknown change-point are obtained. Also, the posterior probability and 90% highest posterior density credible intervals for the mean differences between before and after the change-point are examined. The results show that a single change-point in the precipitation intensity and the heavy precipitation characteristics has occurred around 1996. As the results, the precipitation intensity and heavy precipitation characteristics have clearly increased after the change-point. However, the annual precipitation amount and days show a statistically insignificant single change-point model. These results are consistent with earlier works based on a simple linear regression model.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.3
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• pp.1-11
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• 2011

The temporal variability of spring (March, April, May) monthly precipitation, precipitation effectiveness, monthly maximum precipitation, monthly precipitation of different durations, and the precipitation days over several threshold (i.e. 0, 10, 20, 30, 40, and 50 mm/day) of 59 weather stations between 1973 and 2009 were analyzed. Also to analyze the regional characteristics of temporal variability, 59 weather stations were classified by elevations, latitudes, longitudes, river basins, inland or shore (east sea, south sea, west sea) area and the level of urbanization. Results demonstrated that trends of variables increase in April and decrease in May except precipitation day. Overall trend of precipitation amount and precipitation effectiveness is same but precipitation effectiveness of several sites decrease despite the trend of precipitation amount increases which may be caused by the air temperature increase. Therefore more effective water supply strategy is essential for Spring season. Regional characteristics of Spring precipitation variability can be summarized that increase trend during May become stronger with the increase of latitude and elevation which is similar to that of Summer season. The temporal variability of variables showed different behaviors according to river basins, inland or shore (east sea, south sea, west sea) area and the level of urbanization.