• Title/Summary/Keyword: precipitation verification

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The Precipitation Climate of South Korea and the Dichotomous Categorical Verification Indices (남한 강수 기후와 이분 범주 예보 검증 지수)

  • Lim, Gyu-Ho
    • Atmosphere
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    • v.29 no.5
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    • pp.615-626
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    • 2019
  • To find any effects of precipitation climate on the forecast verification methods, we processed the hourly records of precipitation over South Korea. We examined their relationship between the climate and the methods of verification. Precipitation is an intermittent process in South Korea, generally less than an hour or so. Percentile ratio of precipitation period against the entire period of the records is only 14% in the hourly amounts of precipitation. The value of the forecast verification indices heavily depends on the climate of rainfall. The direct comparison of the index values might force us to have a mistaken appraisal on the level of the forecast capability of a weather forecast center. The size of the samples for verification is not crucial as long as it is large enough to satisfy statistical stability. Our conclusion is still temporal rather than conclusive. We may need the amount of precipitation per minute for the confirmation of the present results.

Verification of Precipitation Forecast Model and Application of Hydrology Model in Kyoungan-chun Basin (경안천 유역에 대한 강수예보모델의 검증 및 수문모형활용)

  • Choi, Ji-Hye;Kim, Young-Hwa;Nam, Kyung-Yeub;Oh, Sung-Nam
    • Journal of Korea Water Resources Association
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    • v.39 no.3 s.164
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    • pp.215-226
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    • 2006
  • In this study, we performed verification of VSRF (Very Short Range Forecast of precipitation) model and application of NWSPC (National Weather Service PC) rainfall-runoff model in Kyoungan-chun basin. We used two methods for verification of VSRF model. The first method is a meteorological verification that evaluates the special quality feature for rain amount between AWS and VSRF model over Kyoungan-chun basin, while second method is a hydrological verification that compares the calculated Mean Area Precipitation (MAP) between AWS and VSRF Quantitatively. This study examines the usefulness of VSRF precipitation forecasting model data in NWSPC hydrological model. As a result, correlation coefficient is over 0.6 within 3 hour lead time. It represents that the forecast results from VSRF are useful for water resources application.

Statistical Verification of Precipitation Forecasts from MM5 for Heavy Snowfall Events in Yeongdong Region (영동대설 사례에 대한 MM5 강수량 모의의 통계적 검증)

  • Lee, Jeong-Soon;Kwon, Tae-Yong;Kim, Deok-Rae
    • Atmosphere
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    • v.16 no.2
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    • pp.125-139
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    • 2006
  • Precipitation forecasts from MM5 have been verified for the period 1989-2001 over Yeongdong region to show a tendency of model forecast. We select 57 events which are related with the heavy snowfall in Yeongdong region. They are classified into three precipitation types; mountain type, cold-coastal type, and warm type. The threat score (TS), the probability of detection (POD), and the false-alarm rate (FAR) are computed for categorical verification and the mean squared error (MSE) is also computed for scalar accuracy measures. In the case of POD, warm, mountain, and cold-coastal precipitation type are 0.71, 0.69, and 0.55 in turn, respectively. In aspect of quantitative verification, mountain and cold-coastal type are relatively well matched between forecasts and observations, while for warm type MM5 tends to overestimate precipitation. There are 12 events for the POD below 0.2, mountain, cold-coastal, warm type are 2, 7, 3 events, respectively. Most of their precipitation are distributed over the East Sea nearby Yeongdong region. These events are also shown when there are no or very weak easterlies in the lower troposphere. Even in the case that we use high resolution sea surface temperature (about 18 km) for the boundary condition, there are not much changes in the wind direction to compare that with low resolution sea surface temperature (about 100 km).

Generation and Verification on the Synthetic Precipitation/Temperature Data

  • Oh, Jai-Ho;Kang, Hyung-Jeon
    • 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.

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Evaluation of GPM IMERG Applicability Using SPI based Satellite Precipitation (SPI를 활용한 GPM IMERG 자료의 적용성 평가)

  • Jang, Sangmin;Rhee, Jinyoung;Yoon, Sunkwon;Lee, Taehwa;Park, Kyungwon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.3
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    • pp.29-39
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    • 2017
  • In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

Performance tests and uncertainty analysis of precipitation types (강수량계 종류별 성능시험 및 불확도 분석)

  • Hong, Sungtaek;Park, Byungdon;Kim, Jonglib;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.7
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    • pp.935-942
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    • 2018
  • Precipitation has a wide range of applications, such as the management and operation of dams and rivers, supply of dranking water for urban and industrial complex, farming and fishing, forest greening, and safety management. In order to prepare for disasters and to obtain economical effects in case of flood damage, it is necessary to measure accurate precipitation. In this study, we carried out the characteristics tests for various types of rainfall gauge using integrated verification system, which can analyze the performance of collective type rainfall gauge. The uncertainty for tipping bucket rain gauge was 0.0041 mm, where weight type and surface tension type was 0.0045 mm and 0.0039 mm respectively. Therefore, the uncertainty according to the type and characteristics of the precipitation system is not significantly different. The uncertainty is also influenced greatly by the resolution.

Verification of Core/Shell Structure of Poly(glycidyl methacrylate-co-divinyl benzene) Microspheres

  • Jin, Jeong-Min;Choi, Jin-Young;Lee, Kang-Seok;Choe, Soon-Ja
    • Macromolecular Research
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    • v.17 no.5
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    • pp.339-345
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    • 2009
  • The core/shell type structure of the highly crosslinked poly(glycidylmetharylate-co-divinylbenzene) microspheres prepared in the precipitation polymerization in acetonitrile was thoroughly verified by means of swelling, $^1H$ NMR, XPS, TEM and TGA measurements. In the XPS measurement, the higher the GMA content, the higher the oxygen content was observed, implying that the higher content of GMA is observed in the particle surface. The further verification of the core/shell structure of the poly(GMA-co-DVB) particles was carried out using $^1H$ NMR and TEM techniques, resulting in the poly(GMA-co-DVB) particles with the GMA rich-phase and DVB rich-phase. In overall, the poly(GMA-co-DVB) microspheres consist of a highly crosslinked DVB rich-phase in the core and slightly or non-crosslinked GMA rich-phase in the shell part due to the different reaction ratios between two monomers and self-crosslinking density of DVB.

WRF-Based Short-Range Forecast System of the Korea Air Force : Verification of Prediction Skill in 2009 Summer (WRF 기반 공군 단기 수치 예보 시스템 : 2009년 하계 모의 성능 검증)

  • Byun, Ui-Yong;Hong, Song-You;Shin, Hyeyum;Lee, Ji-Woo;Song, Jae-Ik;Hahm, Sook-Jung;Kim, Jwa-Kyum;Kim, Hyung-Woo;Kim, Jong-Suk
    • Atmosphere
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    • v.21 no.2
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    • pp.197-208
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    • 2011
  • The objective of this study is to describe the short-range forecast system of the Korea Air Force (KAF) and to verificate its performace in 2009 summer. The KAF weather prediction model system, based on the Weather Research and Forecasting (WRF) model (i.e., the KAF-WRF), is configured with a parent domain overs East Asia and two nested domains with the finest horizontal grid size of 2 km. Each domain covers the Korean peninsula and South Korea, respectively. The model is integrated for 84 hour 4 times a day with the initial and boundary conditions from National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data. A quantitative verification system is constructed for the East Asia and Korean peninsula domains. Verification variables for the East Asia domain are 500 hPa temperature, wind and geopotential height fields, and the skill score is calculated using the difference between the analysis data from the NCEP GFS model and the forecast data of the KAF-WRF model results. Accuracy of precipitation for the Korean penisula domain is examined using the contingency table that is made of the KAF-WRF model results and the KMA (Korea Meteorological Administraion) AWS (Automatic Weather Station) data. Using the verification system, the operational model and parallel model with updated version of the WRF model and improved physics process are quantitatively evaluated for the 2009 summer. Over the East Aisa region, the parallel experimental model shows the better performance than the operation model. Errors of the experimental model in 500 hPa geopotential height near the Tibetan plateau are smaller than errors in the operational model. Over the Korean peninsula, verification of precipitation prediction skills shows that the performance of the operational model is better than that of the experimental one in simulating light precipitation. However, performance of experimental one is generally better than that of operational one, in prediction.

Evaluation of Predictability of Global/Regional Integrated Model System (GRIMs) for the Winter Precipitation Systems over Korea (한반도 겨울철 강수 유형에 따른 전지구 수치모델(GRIMs) 예측성능 검증)

  • Yeon, Sang-Hoon;Suh, Myoung-Suk;Lee, Juwon;Lee, Eun-Hee
    • Atmosphere
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    • v.32 no.4
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    • pp.353-365
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    • 2022
  • This paper evaluates precipitation forecast skill of Global/Regional Integrated Model system (GRIMs) over South Korea in a boreal winter from December 2013 to February 2014. Three types of precipitation are classified based on development mechanism: 1) convection type (C type), 2) low pressure type (L type), and 3) orographic type (O type), in which their frequencies are 44.4%, 25.0%, and 30.6%, respectively. It appears that the model significantly overestimates precipitation occurrence (0.1 mm d-1) for all types of winter precipitation. Objective measured skill scores of GRIMs are comparably high for L type and O type. Except for precipitation occurrence, the model shows high predictability for L type precipitation with the most unbiased prediction. It is noted that Equitable Threat Score (ETS) is inappropriate for measuring rare events due to its high dependency on the sample size, as in the case of Critical Success Index as well. The Symmetric Extreme Dependency Score (SEDS) demonstrates less sensitivity on the number of samples. Thus, SEDS is used for the evaluation of prediction skill to supplement the limit of ETS. The evaluation via SEDS shows that the prediction skill score for L type is the highest in the range of 5.0, 10.0 mm d-1 and the score for O type is the highest in the range of 1.0, 20.0 mm d-1. C type has the lowest scores in overall range. The difference in precipitation forecast skill by precipitation type can be explained by the spatial distribution and intensity of precipitation in each representative case.

Prolactin Monomeric Polyethylene Glycol Measurement Method and Study of Reference Value Verification

  • Dong Hyuk Ha;Hwa-Jin Ryu;Hyun-Su Cho;Sun-Young Shin
    • The Korean Journal of Nuclear Medicine Technology
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    • v.27 no.2
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    • pp.133-136
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    • 2023
  • Purpose: Prolactin in the blood is separated into three types, and over 90% of prolactin presents as a double monomer (23 KDa). Rarely, it can exist in the size of big prolactin (150 KDa), which is called macroprolactin and is known as an autoantibody complex. When macroprolactin accounts for more than 60% of prolactin in the blood, it is called macroprolactinemia. The presence of such macroprolactin was first reported in a patient with hyperprolactinemia but without typical symptoms. Macroprolactinemia is emerging as an important cause of idiopathic hyperprolactinemia. The polyethylene glycol (PEG) precipitation method using the property of precipitating large-molecular-weight proteins is simple and recently has been widely used as a screening test. The results are in good agreement with the results of gel chromatography. The purpose of this study was to confirm the measurement method and reference value verification of monomeric prolactin in blood prolactin using the PEG precipitation method. Materials and Methods: For 40 examinees who visited the Gangnam Center of Seoul National University Hospital in 2021, the prolactin level was verified using radioimmunoassay (RIA). For macroprolactinemia PEG precipitation method, 25% PEG (molecular weight 6000kDa) solution and serum were mixed in equal amounts in a test tube, then left at room temperature for 20 minutes and centrifuged at 4℃ for 30 minutes (1500g). The prolactin level was measured in the supernatant. Results : After confirming that more than 90% of the 40 tested samples within the reference range <25 ng/mL, the same value as the reference value for prolactin was applied. Since the concentration of monomeric prolactin in serum from which macroprolactin has been removed from blood is diluted 1:1 with PEG, our laboratory is currently reporting the result by multiplying the result by a dilution factor of 2. Conclusion: Radioimmunoassay using PEG precipitation method using the property of precipitating large molecular weight proteins is simple and effective for quantitative measurement of monomeric prolactin in blood prolactin.