• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1359-1361
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• 2003

A set of microwave remote sensing data collected with the newly developed UMass Imaging Wind and Rain Airborne Profiler (IWRAP) during the 2002 Atlantic Hurricane Season was analyzed to further our understanding of the effect of precipitation on scatterometer wind vector retrieval. Coincident surface wind speed and precipitation measurements were provided by the UMass Simultaneous Frequency Microwave Radiometer (SFMR). The differences between the wind estimations from IWRAP and SFMR under precipitation conditions of 0-100mm/hr and wind speed of 0-60m/s was calculated, from which the effect of precipitation on the wind vector retrieval using scatterometry is analyzed qualitatively.

• Water Engineering Research
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• v.4 no.1
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• pp.31-43
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• 2003

The impacts of climate change on soil moisture in sub - Arctic watershed simulated by using the hydrologic model. A range of arbitrary changes in temperature and precipitation are applied to the runoff model to study the sensitivity of soil moisture due to potential changes in precipitation and temperature. The sensitivity analysis indicates that changes in precipitation are always amplified in soil moisture with the amplification factor for flow. The change in precipitation has effect on the soil moisture in the catchment. The percentage change in soil moisture levels can be greater than the percentage change in precipitation. Compared to precipitation, temperature increases or decreases alone have impacts on the soil moisture. These results show the potential for climate change to bring about soil moisture that may require a significant planning response. They are also indicative of the fact that hydrological impacts affecting water supply may be important in consider-ing the cost and benefits of potential climate change.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.25-28
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• 2016

Recently, because of the weather forecasts through the low-resolution data has been limited, the demand of the high-resolution data is sharply increasing. Therefore, in this study, we restore the ultra-high resolution synthetic precipitation and temperature data for 2000-2014 due to small-scale topographic effect using the QPM (Quantitative Precipitation Model)/QTM (Quantitative Temperature Model). First, we reproduce the detailed precipitation and temperature data with 1km resolution using the distribution of Automatic Weather System (AWS) data and Automatic Synoptic Observation System (ASOS) data, which is about 10km resolution with irregular grid over South Korea. Also, we recover the precipitation and temperature data with 1km resolution using the MERRA reanalysis data over North Korea, because there are insufficient observation data. The precipitation and temperature from restored current climate reflect more detailed topographic effect than irregular AWS/ASOS data and MERRA reanalysis data over the Korean peninsula. Based on this analysis, more detailed prospect of regional climate is investigated.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.24-24
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• 2019

This study investigates variations in the Western Pacific Subtropical High (WPSH) and its impact on South Korean precipitation in late summer during the period between 1958 and 2017. Composite analysis reveals that precipitation occurrence is directly linked to the displacement of the WPSH western ridge, a single, large-scale feature of the atmosphere in the Pacific Ocean. When WPSH ridging is located northwest (NW) of its climatological mean position, excessive precipitation is expected in late summer due to enhanced moisture transport. On the other hand, a precipitation deficit is frequently observed when the western ridge is located in the southeast (SE). Different phases of the WPSH are associated with lagged patterns of Pacific and Atlantic atmospheric and oceanic variability, introducing the potential to predict variability in the WPSH western ridge and its climate over northern East Asia by one month. Based on the identified SST patterns, a simple statistical model is developed and improvement in the ability to predict is confirmed through a cross-validation framework. Finally, the potential for further improvements in WPSH-based predictions is addressed.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.738-739
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• 2015

The main objective of this study, "Spatial Downscaling of Precipitation from GCMs for Assessing Climate Change over Han River and Imjin River Watersheds", is to carry out over Han River and Imjin River watersheds. To this end, a statistical regression method with MOS (Model Output Statistics) corrections at every downscaling step was developed and applied for downscaling the spatially-coarse Global Climate Model Projections (GCMPs) from CCSM3 and CSIRO with respect to precipitation into 0.1 degree (about 11 km) spatial grid over study regions. The spatially archived hydro-climate data sets such as Willmott, GsMap and APHRODITE datasets were used for MOS corrections by means of monthly climatology between observations and downscaled values. Precipitation values downscaled in this study were validated against ground observations and then future climate simulation results on precipitation were evaluated for the projections.

• Journal of Environmental Science International
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• v.15 no.12
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• pp.1125-1139
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• 2006

The cluster analysis of diurnal precipitation patterns is performed by using daily precipitation of 59 stations in South Korea from 1973 to 1996 in four seasons of each year. Four seasons are shifted forward by 15 days compared to the general ones. Number of clusters are 15 in winter, 16 in spring and autumn, and 26 in summer, respectively. One of the classes is the totally dry day in each season, indicating that precipitation is never observed at any station. This is treated separately in this study. Distribution of the days among the clusters is rather uneven with rather low area-mean precipitation occurring most frequently. These 4 (seasons)$\times$2 (wet and dry days) classes represent more than the half (59 %) of all days of the year. On the other hand, even the smallest seasonal clusters show at least $5\sim9$ members in the 24 years (1973-1996) period of classification. The cluster analysis is directly performed for the major $5\sim8$ non-correlated coefficients of the diurnal precipitation patterns obtained by factor analysis In order to consider the spatial correlation. More specifically, hierarchical clustering based on Euclidean distance and Ward's method of agglomeration is applied. The relative variance explained by the clustering is as high as average (63%) with better capability in spring (66%) and winter (69 %), but lower than average in autumn (60%) and summer (59%). Through applying weighted relative variances, i.e. dividing the squared deviations by the cluster averages, we obtain even better values, i.e 78 % in average, compared to the same index without clustering. This means that the highest variance remains in the clusters with more precipitation. Besides all statistics necessary for the validation of the final classification, 4 cluster centers are mapped for each season to illustrate the range of typical extremities, paired according to their area mean precipitation or negative pattern correlation. Possible alternatives of the performed classification and reasons for their rejection are also discussed with inclusion of a wide spectrum of recommended applications.

• Journal of the Korean earth science society
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• v.24 no.1
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• pp.22-29
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• 2003

Temporal and spatial variability of precipitation (P), evaporation (E), and moisture balance (P-E; precipitation minus evaporation) has been investigated over the tropical ocean during the period from January 1998 to July 2001. Our data were analyzed by the EOF method using the satellite P and E observations made by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and the Special Sensor Microwave/Imager (SSM/I). This analysis has been performed for two three-year periods as follow; The first period which includes the El Ni${\tilde{n}}$o in early 1998 ranges from January 1998 to December 2000, and the second period which includes the La Ni${\tilde{n}}$o events in the early 1999 and 2000 (without El Ni${\tilde{n}}$o) ranges from August 1998 to July 2001. The areas of maxima and high variability in the precipitation and in the P-E were displaced from the tropical western Pacific and the ITCZ during the La Ni${\tilde{n}}$o to the tropical middle Pacific during the El Ni${\tilde{n}}$o, consistent with those in previous P studies. Their variations near the Korean Peninsula seem to exhibit a weakly positive correlation with that in the tropical Pacific during the El Ni${\tilde{n}}$o. The evaporation, out of phase with the precipitation, was reduced in the tropical western Pacific due to humid condition in boreal summer, but intensified in the Kuroshio and Gulf currents due to windy condition in winter. The P-E variability was determined mainly by the precipitation of which the variability was more localized but higher by 2-3 times than that of evaporation. Except for the ITCZ (0-10$^{\circ}$N), evaporation was found to dominate precipitation by ${\sim}$2 mm/day over the tropical Pacific. Annual and seasonal variations of P, E, and P-E were discussed.

• Journal of Wetlands Research
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• v.15 no.2
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• pp.233-250
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• 2013

Gradually or radically change how the characteristics of the climate characteristic using change point analysis for the precipitation indicators were investigated. Significantly the amount, extreme and frequency were separated by precipitation indicators, each indicator RIA(Rainfall Index for Amount), RIE(Rainfall Index for Extremes) and RIF(Rainfall Index for Frequency) was defined. Bayesian Change Point was applied to investigate changing over time of precipitation indicators calculated. As the result of analysis, precipitation indicators in South Korea was found to recently increase all indicators except for the annual precipitation days and 200-yr precipitation. RIA revealed that there was a very clear point of significance for the change in Ulleungdo, Relatively significant results for RIE were identified in Gumi, Jecheon and Seogwipo. Also, since the 1990s, an increase in the number of variation points, and the horizontal width of the fluctuation point was being relatively wider. Based on these results, rethink the precipitation on the assumption of stationarity was judged necessary.

• Journal of Korea Water Resources Association
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• v.44 no.8
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• pp.683-694
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• 2011

To analyze the regional impact of air temperature increase and precipitation variation on water resources, the variability of precipitation-effectiveness (P-E) ratio which is estimated using precipitation and air temperature data of 59 weather stations operated by the Korean Meteorological Administration (KMA) during 1973~2009 was analyzed. Also runoff data resulting from the Precipitation-Runoff Modelling System (PRMS) modelling were analyzed during 1966~2007. The overall spatio-temporal variability of P-E ratio and runoff data in South Korea is corresponding to the variability of precipitation amount. However some region shows that the P-E ratio decreases even though the trend of precipitation amount increases which may be caused by the air temperature increase. Runoff trend is similar to that of P-E ratio. Precipitation and P-E ratio have decreased all seasons except summer season and it means the reduction of available water resources during those seasons. These variability should be reflected in the spring, fall, and winter water supply strategy.

• Atmosphere
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• v.28 no.1
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• pp.85-97
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• 2018

This study evaluates the performance of the Weather Research and Forecasting (WRF) model in reproducing the present-day (1981~2005) precipitation over Far East Asia and South Korea. The WRF model is configured with 25-km horizontal resolution within the context of the COordinated Regional climate Downscaling Experiment (CORDEX) - East Asia Phase 2. The initial and lateral boundary forcing for the WRF simulation are derived from European Centre for Medium-Range Weather Forecast Interim reanalysis. According to our results, WRF model shows a reasonable performance to reproduce the features of precipitation, such as seasonal climatology, annual and inter-annual variabilities, seasonal march of monsoon rainfall and extreme precipitation. In spite of such model's ability to simulate major features of precipitation, systematic biases are found in the downscaled simulation in some sub-regions and seasons. In particular, the WRF model systematically tends to overestimate (underestimate) precipitation over Far East Asia (South Korea), and relatively large biases are evident during the summer season. In terms of inter-annual variability, WRF shows an overall smaller (larger) standard deviation in the Far East Asia (South Korea) compared to observation. In addition, WRF overestimates the frequency and amount of weak precipitation, but underestimates those of heavy precipitation. Also, the number of wet days, the precipitation intensity above the 95 percentile, and consecutive wet days (consecutive dry days) are overestimated (underestimated) over eastern (western) part of South Korea. The results of this study can be used as reference data when providing information about projections of fine-scale climate change over East Asia.