• Ocean and Polar Research
• /
• v.24 no.1
• /
• pp.19-31
• /
• 2002

Precipitation variability around King Sejong Station related with E1 $Ni\~{n}o$/Southern Oscillation (ENSO) is evaluated using the gauge-based monthly data of its neighboring stations. Though three Ant-arctic Stations of King Sejong (Korea), Frei (Chile), and Artigas (Uruguay) are all closely located within 10 km, their precipitation data show mostly insignificant positive or rather negative correlations among them in the annual, seasonal and monthly precipitation. This result indicates that there are locally large variations in the distribution of precipitation around King Sejong Station. The monthly data of Frei Station for 31 years (1970-2000) are analyzed for examining the ENSO signal in precipitation because of its longer precipitation record compared to other two stations. From the analysis of seasonal precipitation, it is seen that there is a tendency of less precipitation than the average during E1 $Ni\~{n}o$ events. This dryness is more distinct in fall to spring seasons, in which the precipitation decreases down to about 30% of seasonal mean precipitation. However, the precipitation signal related with La $Ni\~{n}a$ events is not significant. From the analysis of monthly precipitation, it is found that there is a strong negative correlation during 1980s and in the late 1990s, and a weak positive correlation in the early 1990s between normalized monthly precipitation at Frei Station and Sea Surface Temperature (SST) anomalies in the $Ni\~{n}o$ 3.4 region. However, this relation may be not applied over the region around King Sejong Station, but at only one station, Frei.

• Atmosphere
• /
• v.28 no.2
• /
• pp.175-185
• /
• 2018

Characteristics of precipitation response to enhanced aerosols have been investigated during the severe haze events observed in Korea for 2011 to 2016. All 6-years haze events are classified into long-range transported haze (LH: 31%), urban haze (UH: 28%), and yellow sand (YS: 18%) in order. Long-range transported one is mainly discussed in this study. Interestingly, both LH (68%) and YS (87%) appear to be more frequently accompanied with precipitation than UH (48%). We also found out the different timing of precipitation for LH and YS, respectively. The variations of precipitation frequency for the LH event tend to coincide with aerosol variations specifically in terms of temporal covariation, which is in contrast with YS. Increased aerosol loadings following precipitation for the YS event seems to be primarily controlled by large scale synoptic forcing. Meanwhile, aerosols for the LH event may be closely associated with precipitation longevity through changes in cloud microphysics such that enhanced aerosols can increase smaller cloud droplets and further extend light precipitation at weaker rate. Notably, precipitation persisted longer than operational weather forecast not considering detailed aerosol-cloud interactions, but the timescale was limited within a day. This result demonstrates active interactions between aerosols and meteorology such as probable modifications of cloud microphysics and precipitation, synoptic-induced dust transport, and precipitation-scavenging in Korea. Understanding of aerosol potential effect on precipitation will contribute to improving the performance of numerical weather model especially in terms of precipitation timing and location.

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

• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.200-204
• /
• 2012

In engineering hydrology, an estimation of precipitation loss is one of the most important issues for successful modeling to forecast flooding or evaluate water resources for both surface and subsurface flows in a watershed. An accurate estimation of precipitation loss is required for successful implementation of rainfall-runoff models. Precipitation loss or hydrological abstraction may be defined as the portion of the precipitation that does not contribute to the direct runoff. It may consist of several loss elements or abstractions of precipitation such as infiltration, depression storage, evaporation or evapotranspiration, and interception. A composite loss rate model that combines four loss rates over time is derived as a lumped form of a continuous time function for a storm event. The composite loss rate model developed is an exponential model similar to Horton's infiltration model, but its parameters have different meanings. In this model, the initial loss rate is related to antecedent precipitation amounts prior to a storm event, and the decay factor of the loss rate is a composite decay of four losses.

• Journal of Environmental Science International
• /
• v.27 no.12
• /
• pp.1227-1239
• /
• 2018

In this study, daily precipitation data and daily average temperature data of meteorological observatories in Daegu, Busan, Daejeon, Seoul, Mokpo, and Gwangju cities inland and offshore were analyzed by using moving average method. Were compared. Overall, summarizing changes in precipitation and temperature over the 24 seasons, precipitation and temperature in all six stations increased compared to the past 1960s. In the case of precipitation, precipitation increased at the end of July and early August, whereas precipitation in April, September and early October decreased. In the case of temperature, especially in February, the temperature increased, and in Mokpo, the temperature from August to December showed a general decline. Changes in precipitation and temperature due to seasons in the 24 seasons affect agriculture and our everyday life, and further research is needed to determine how these changes will affect agricultural water supply, crop growth and daily life. The results of this study can be useful.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.379-379
• /
• 2020

The influence of drought has increased due to global warming. In addition, forest fires have occurred more frequently due to droughts and resulted in property losses and casualty. In this study, the effects of drought on Goseong-Sokcho Forest Fire in 2019 were analyzed using high-resolution synthetic precipitation data. In order to determine the severity of drought, the average, 20%tile and 80%ile values were calculated using the synthetic precipitation data of the past 30 years and compared with the current climatology. We have investigated the multi-year accumulated precipitation data to determine the persistence of drought. In Goseong-Sokcho forest fire case, the two-year cumulative synthetic precipitation data shows a similar value to the climate, but the three-year cumulative synthetic precipitation data was close to the 20%ile lines of the climate value. It may expose that the shortage of precipitation in 2017 had persisted until 2019, despite abundant precipitation during the summer in 2018. Therefore, Goseong-Sokcho forest fire might be spread more rapidly by drought which has been persisted since 2017.

• Journal of Korean Society on Water Environment
• /
• v.24 no.6
• /
• pp.725-740
• /
• 2008

In this study a multi-site daily precipitation generator which generates the precipitation with similar spatial correlation, and at the same time, with conserving statistical properties of the observed data is developed. The proposed generator is intended to be a tool for down-scaling the data obtained from GCMs or RCMs into local scales. The occurrences of precipitation are simultaneously modeled in multi-sites by 2-parameter first-order Markov chain using random variables of spatially correlated while temporally independent, and then, the amount of precipitation is simulated by 3-parameter mixed exponential probability density function that resolves the issue of maintaining intermittence of precipitation field. This approach is applied to the Nakdong river basin and the observed data are daily precipitation data of 19 locations. The results show that spatial correlations of precipitation series are relatively well simulated and statistical properties of observed precipitation series are simulated properly.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.180-180
• /
• 2023

To improve global risk management, understanding the characteristics and distribution of precipitation is crucial. However, obtaining spatially and temporally resolved climatic data remains challenging due to sparse gauge observations and limited data availability, despite the use of satellite and reanalysis products. To address this challenge, merging available precipitation products has been introduced to generate spatially and temporally reliable data by taking advantage of the strength of the individual products. However, most of the existing studies utilize all the available products without considering the varying performances of each dataset in different regions. Comprehensively considering the relative contributions of each parent dataset is necessary since their contributions may vary significantly and utilizing all the available datasets for data merging may lead to significant data redundancy issues. Hence, for this study, we introduce a site-specific precipitation merging method that utilizes the Quadruple Collocation (QC) approach, which acknowledges the existence of error-cross correlation between the parent datasets, to create a high-resolution global daily precipitation data from 2001-2020. The performance of multiple gridded precipitation products are first evaluated per region to determine the best combination of quadruplets to be utilized in estimating the error variances through the QC approach and computation of merging weights. The merged precipitation is then computed by adding the precipitation from each dataset in the quadruplet multiplied by each respective merging weight. Our results show that our approach holds promise for generating reliable global precipitation data for data-scarce regions lacking spatially and temporally resolved precipitation data.

• Geomechanics and Engineering
• /
• v.33 no.1
• /
• pp.65-75
• /
• 2023

Recycled concrete aggregate (RCA) is widely used as a construction material in road construction, concrete structures, embankments, etc. However, it has been reported that calcite (CaCO₃) precipitation from RCA can be a cause of clogging when used in drainage applications. An accelerated calcite precipitation (ACP) procedure has been devised to evaluate the long-term geochemical performance of RCA in subsurface drainage systems. While the ACP procedure was useful for the French Drain application, there remained opportunities for improvement. In this study, key factors that control the formation of calcite precipitation were quantitatively evaluated, and the results were used to improve the current prototype ACP method. A laboratory parametric study was carried out by investigating the effects of reaction temperature and time on the formation of calcite precipitation of RCA, with determining an optimum reaction temperature and time which maximizes calcite precipitation. The improved ACP procedure was then applied to RCA samples that were graded for Type I Underdrain application, to compare the calcite precipitation. Two key findings are (1) that calcite precipitation can be maximized with the optimum heating temperature (75℃) and time (17 hours), and (2) the potential for calcite precipitation from RCA is not as significant as for limestone. With the improved ACP procedure, the total amount of calcite precipitation from RCAs within the life cycle of a drain system can be determined when RCAs from different sources are used as pipe backfill materials in a drain system.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.134-134
• /
• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.