• Title, Summary, Keyword: Precipitation

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The Characteristics of the Anomaly Level and Variability of the Monthly Precipitation in Kyeongnam, Korea (경남지방의 월강수량의 변동율과 Anomaly Level의 출현특성)

  • 박종길;이부용
    • Journal of Environmental Science International
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    • v.2 no.3
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    • pp.179-191
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    • 1993
  • This paper aims to know the characteristics of occurrence of the anomaly level and variability of the monthly precipitation in Kyeongnam, Korea. For this study, it was investigated 주e distribution of the annual and cont비y mean precipitation, the precipitation variability and its annual change, and the characteristics of occurrence of the anomaly level in Kyeongnam area the results were summarized as follows : 1) she mean of annual total precipitation averaged over Kyeongnam area is 1433.3mm. I'he spatial distribution of the annual total precipitation shows that in Kyeongnam area, the high rainfall area locates in the southwest area and south coast and the low rainfall area in an inland area. 2) Monthly mean precipitation in llyeongnam area was the highest in July(266.4mm) 각lowed by August(238.0mm), June(210.2mm) in descending order. In summer season, rainfall was concentrated and accounted for 49.9 percent of the annual total precipitation. Because convergence of the warm and humid southwest current which was influenced by Changma and typhoon took place well in this area. 3) The patterns of annual change of precipitaion variability can be divided into two types; One is a coast type and the other an inland type. The variability of precipitation generally appears low in spring and summer season and high in autumn and winter season. This is in accord with the large and small of precipitation. 4) The high frequency of anomaly level was N( Normal)-level and the next was LN( Low Informal) -level and 25(Extremely Subnormal)-level was not appeared in all stations. The occurrence frequency of N level was high in high rainfall area and distinguish성 in spring and summer season but the low rainfall area was not. hey Words : anomaly level, variability, precipitation, coast type, inland type.

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Spatial Distribution of Precipitation Trends According to Geographical and Topographical Conditions (지리지형적 조건에 따른 강수량 추세 분포)

  • Rim, Chang-Soo
    • Journal of Korea Water Resources Association
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    • v.42 no.5
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    • pp.385-396
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    • 2009
  • The spatial distribution of precipitation trends according to urbanization, geographical and topographical conditions have been studied. In this study, precipitation data from 1973 to 2006 were analyzed for 56 climatological stations including the Seoul metropolis in South Korea. In addition to annual average daily precipitation, monthly average daily precipitation in April, July, October and January were analyzed, considering seasonal effect. The geographical and topographical characteristics of these sites were examined using GIS analysis. Land use status of the study area was also examined to estimate the extent of urbanization. The study results indicate that annual average precipitation increased, and monthly average precipitation in April and October decreased, while those in January and July increased. Considering urbanization effect, annual average precipitation and monthly average precipitation in July increased; however, monthly average precipitation in January, April and October decreased. Furthermore, compared with urbanization rate and proximity to coast, average elevation of study area appeared to be the most close correlation with annual and monthly averages of precipitation trends.

The Analysis of the Correlation between Groundwater Level and the Moving Average of Precipitation in Kum River Watershed (금강유역에서의 지하수위와 강수량 이동평균의 상관관계 분석)

  • Yang, Jeong-Seok;Ahn, Tae-Yeon
    • The Journal of Engineering Geology
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    • v.18 no.1
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    • pp.1-6
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    • 2008
  • Precipitation and groundwater level data sets from Kum river watershed were analyzed and compared. The correlation between groundwater level and the moving average of precipitation was analyzed. Moving averaging technique is stochastic method and that was used to consider the effect of precipitation events on groundwater level fluctuation. Groundwater level generally follows seasonal precipitation pattern and low level occurs from early December to late April. Relatively high groundwater level is appeared in wet spell (July and August). The correlation between groundwater level and the moving average of precipitation to consider precedent precipitation events was analyzed with minimum two-year data sets. When the precipitation and groundwater level data set pair was selected the precipitation gauge station is closely located to groundwater level gauge station in the upstream direction to minimize the non-homogeneous precipitation distribution effect. The maximum correlation was occurred when the averaging periods were from 10 days to 150 days with Kum river watershed data. The correlation coefficients are influenced by data quality, missing data periods, or snow melt effect, etc. The maximum coefficient was 0.8886 for Kum river watershed data.

Impact of Horizontal Resolution of Regional Climate Model on Precipitation Simulation over the Korean Peninsula (지역 기후 모형을 이용한 한반도 강수 모의에서 수평 해상도의 영향)

  • Lee, Young-Ho;Cha, Dong-Hyun;Lee, Dong-Kyou
    • Atmosphere
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    • v.18 no.4
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    • pp.387-395
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    • 2008
  • The impact of horizontal resolution on a regional climate model was investigated by simulating precipitation over the Korean Peninsula. As a regional climate model, the SNURCM(Seoul National University Regional Climate Model) has 21 sigma layers and includes the NCAR CLM(National Center for Atmospheric Research Community Land Model) for land-surface model, the Grell scheme for cumulus convection, the Simple Ice scheme for explicit moisture, and the MRF(Medium-Range Forecast) scheme for PBL(Planetary Boundary Layer) processing. The SNURCM was performed with 20 km resolution for Korea and 60 km resolution for East Asia during a 20-year period (1980-1999). Although the SNURCM systematically underestimated precipitation over the Korean Peninsula, the increase of model resolution simulated more precipitation in the southern region of the Korean Peninsula, and a more accurate distribution of precipitation by reflecting the effect of topography. The increase of precipitation was produced by more detailed terrain data which has a 10 minute terrain in the 20 km resolution model compared to the 30 minute terrain in the 60 km resolution model. The increase in model resolution and more detailed terrain data played an important role in generating more precipitation over the Korean Peninsula. While the high resolution model with the same terrain data resulted in increasing of precipitation over the Korean Peninsula including the adjoining sea, the difference of the terrain data resolution only influenced the precipitation distribution of the mountainous area by increasing the amount of non-convective rain. In conclusion, the regional climate model (SNURCM) with higher resolution simulated more precipitation over the Korean Peninsula by reducing the systematic underestimation of precipitation over the Korean Peninsula.

Precipitation Change in Korea due to Atmospheric $CO_2$ Increase (대기중 $CO_2$ 증가에 따른 한반도 강수량 변화)

  • 오재호;홍성길
    • Water for future
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    • v.28 no.3
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    • pp.143-157
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    • 1995
  • A precipitation change in Korea due to atmospheric $CO_2$ doubling has been estimated with a mixed method(Robinson and Finkelstein, 1991) to represent regional precipitation distribution from the simulated precipitation data by three GCM(general circulation model) (CCC, UI, and GFDL GCM) experiments. As a result of this analysis, the precipitation change by atmospheric $CO_2$ doubling can be summarized as follows: The precipitation increases as much as 25mm/yr during spring season and more than 50mm/yr during summer and autumn. However, it decreases as much as 13mm/yr during winter. In terms of percentage with respect to current precipitation climatology, we may have more rain as much as 10%, 13% and 24%, respectively, for spring, summer and autumn than current precipitation. However, we may have less winter precipitation than current climatological average.

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Precipitation Behavior of Laves Phase in 10%Cr Ferrite System Alloy (10%Cr 페라이트계 합금에서 라베스상의 석출거동에 관한 연구)

  • Kim, I.S.;Kang, C.Y.;Bae, D.S.
    • Journal of the Korean Society for Heat Treatment
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    • v.12 no.1
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    • pp.21-30
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    • 1999
  • The present study were investigated changes of precipitation behaviour of laves phase in ferrite single phase and ferrite-martensite dual phase and precipitation of laves phase under stress. Hardness changes in ferrite phase appeared two hardness peaks by precipitation of initial fine precipitator and laves phase in 3Mo-0.3Si and 3Mo-0.3Si-C specimens, respectively. Hardness changes in martensite phase of 3Mo-0.3Si-C specimen was lower in the initial stage of aging by carbide precipitation and after this, increased by re-hardening due to precipitation of laves phase. In the ferrite phase, laves phase was mainly precipitated, whereas in the martensite phase, carbide was preferentially formed during the initial stage of aging and with increasing aging time, laves phase and carbide were simultaneously precipitated by precipitation of laves phase at around carbide. In the ferrite-martensite interface, laves phase was mainly precipitated and carbide was mainly formed at boundary of lath martensite than grain boundary. Adding the stress in aging, fine precipitator of inital precipitation of laves phase precipitated in (100) of perpendicular to tensile direction and has grown to only followed<010>direction and also, volume fraction of laves phase increased. Consequently, the stress added was accelerated initial precipitation of laves phase.

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Design of Optimized Type-2 Fuzzy RBFNN Echo Pattern Classifier Using Meterological Radar Data (기상레이더를 이용한 최적화된 Type-2 퍼지 RBFNN 에코 패턴분류기 설계)

  • Song, Chan-Seok;Lee, Seung-Chul;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.6
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    • pp.922-934
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    • 2015
  • In this paper, The classification between precipitation echo(PRE) and non-precipitation echo(N-PRE) (including ground echo and clear echo) is carried out from weather radar data using neuro-fuzzy algorithm. In order to classify between PRE and N-PRE, Input variables are built up through characteristic analysis of radar data. First, the event classifier as the first classification step is designed to classify precipitation event and non-precipitation event using input variables of RBFNNs such as DZ, DZ of Frequency(DZ_FR), SDZ, SDZ of Frequency(SDZ_FR), VGZ, VGZ of Frequency(VGZ_FR). After the event classification, in the precipitation event including non-precipitation echo, the non-precipitation echo is completely removed by the echo classifier of the second classifier step that is built as Type-2 FCM based RBFNNs. Also, parameters of classification system are acquired for effective performance using PSO(Particle Swarm Optimization). The performance results of the proposed echo classifier are compared with CZ. In the sequel, the proposed model architectures which use event classifier as well as the echo classifier of Interval Type-2 FCM based RBFNN show the superiority of output performance when compared with the conventional echo classifier based on RBFNN.

Interdecadal Variability and Future Change in Spring Precipitation over South Korea (한반도 봄철 강수량의 장기변동과 미래변화)

  • Kim, Go-Un;Ok, Jung;Seo, Kyong-Hwan;Han, Sang-Dae
    • Atmosphere
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    • v.22 no.4
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    • pp.449-454
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    • 2012
  • This study presents the long-term variability of spring precipitation over the Korean peninsula. It is found that the significant interdecadal change in the spring precipitation has occurred around year 1991. Over the Korean peninsula the precipitation for the post-1991 period increased by about 30 mm per year in CMAP and station-measured data compared to the precipitation prior to year 1991. Due to an increased baroclinicity during the later period, the low-level negative pressure anomaly has developed with its center over northern Japan. Korea is situated at the western end of the negative pressure anomaly, receiving moisture from westerly winds and producing more precipitation. Also, we estimate the change in the near future (years 2020~2040) spring precipitation using six best performing Coupled Model Intercomparison Project 3 (CMIP3) models. These best model ensemble mean shows that spring precipitation is anticipated to increase by about 4% due to the strengthened westerlies accompanied by the northwestern enhancement of the North Pacific subtropical high.

Development of Auto-Empting Type Weighing Precipitation Gauge and Performance Test on Rainfall Measurement (자동배수형 무게식 강수량계 개발 및 강우량 측정 성능검사)

  • Kim, Sang-Jo;Son, Top
    • Atmosphere
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    • v.22 no.2
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    • pp.279-285
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    • 2012
  • The weighing precipitation gauge with auto-empting capability was developed in the R&D project organized by the Research Agency for Climate Science (RACS) and supported by the Korea Meteorological Administration (KMA). This project was initiated in line with the KMA's plan executed since 2010 to introduce the weighing precipitation gauges partly into of their Automatic Weather Station (AWS) network in order to upgrade the quality of precipitation data. The innovative feature of this research is that the auto-empting in weighing precipitation gauge is realized by abrupt rotation of receiving container. The prototype was tested in compliance with the relevant standards of KMA. The results of performance test on rainfall measurement in laboratory verified that the accuracies for 20 mm and 100 mm reference rainfall amount were 0.1 mm and 0.4 mm, respectively in both conditions of auto-empting and no-empting. During the rotation of container for auto-empting, the data was extrapolated smoothly by applying the same precipitation intensity of the previous 10 sec. Consequently, it was found that the auto-empting precipitation gauge developed in this research is quite enough to be used for the operational purpose of accurate measurement with 0.1 mm resolution, regardless of the precipitation intensity.

Bias Correction of Satellite-Based Precipitation Using Convolutional Neural Network

  • Le, Xuan-Hien;Lee, Gi Ha
    • Proceedings of the Korea Water Resources Association Conference
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    • pp.120-120
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    • 2020
  • Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

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