• Title/Summary/Keyword: Synoptic observation

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Numerical Study on Characteristics of Turbulence Scheme in Planetary Boundary Layer (난류 모수화 방법에 따른 대기경계층 수치모의 특성에 관한 연구)

  • Jeon, Won-Bae;Lee, Hwa-Woon;Lee, Soon-Hwan
    • Journal of Environmental Science International
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    • v.19 no.2
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    • pp.137-148
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    • 2010
  • This paper investigates the characteristics of turbulence schemes. Turbulence closures are fundamental for modeling the atmospheric diffusion, transport and dispersion in the boundary layer. In particular, in non-homogeneous conditions, a proper description of turbulent transport in planetary boundary layer is fundamental aspect. This study is based on the Regional Atmospheric Modeling System (RAMS) and combines four different turbulence schemes to assess if the different schemes have a impact on simulation results of vertical profiles. Two of these schemes are Isotropc Deformation scheme (I.Def) and Anisotropic deformation scheme (A.Def) that are simple local scheme based on Smagorinsky scheme. The other two are Mellor-Yamada scheme (MY2.5) and Deardorff TKE scheme (D.TKE) that are more complex non-local schemes that include a prognostic equation for turbulence kinetic energy. The simulated potential temperature, wind speed and mixing ratio are compared against radiosonde observations from the study region. MY2.5 shows consistently reasonable vertical profile and closet to observation. D.TKE shows good results under relatively strong synoptic condition especially, mixing ratio simulation. Validation results show that all schemes consistently underestimated wind speed and mixing ratio but, potential temperature was somewhat overestimated.

On the occurrence of yellow sand and atmospheric loadings (황사의 사례분석과 한반도 유입량)

  • 정용승;윤마병
    • Journal of Korean Society for Atmospheric Environment
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    • v.10 no.4
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    • pp.233-244
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    • 1994
  • The phenomenon of yellow sand (dust clouds) occurred in Korea during the spring of 1993 and 1994 is studied in detail. In total 6 cases including 15 days of yellow sand were observed in 1993 and the annual number of these events was found to increased. Examinations in this study include meteorological charts satellite imagery, pilot reports (PIREP) of Korea Air Force, and air concentrations of total suspended particulates(TSP). We present on estimation of total atmospheric loadings based on the observation and theory. According to the PIREP, in general the dust clouds travelled in the lower troposphere up to the level 5km. The visibility within the clouds was in the range of 3-8km The area covered by yellow sand in an event exceeded 0.4 M $\textrm{km}^2$ . According to trajectory analyses, dust clouds invaded Korea in April and May 1993 were landed in the sink area after 2~4 days travelling for 2,000~3,000km from a source region. Estimates of total atmospheric loadings of a dust cloud for April 23~24 in 1993 were 1.5 M ton. In addition, 7 dust storms were also reported in synoptic observations in NW China and Mongolia during the spring in 1994. The yellow sand was not reported with meteorological observations in Korea, however pilots reported significant dust clouds over the Yellow Sea on 8 and 13 April and 20 May 1994.

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A study on changes in runoff characteristics through period classification of SSP scenarios (SSP 시나리오의 기간 구분을 통한 유출 특성 변화 연구)

  • Nam Ki Moon;Dong Hyeok Park;Sang Woo Yim;Jaehyun Ahn
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.393-393
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    • 2023
  • 최근 기후변화에 대한 관심이 높아짐에 따라 전 세계적으로 미래 기후변화 예측 전망에 대한 다양한 연구들이 수행되었으며, 특히 IPCC(Intergovernmental Panel on Climate Change)의 기후변화 6차 보고서에 채택된 SSP(Shared Socio-economic Pathway) 시나리오를 이용한 연구가 활발한 상황이다. 이들 연구에서는 미래 기후변화의 양상 비교를 위한 기간 구분은 통상적으로 F1(2011-2040), F2(2041-2070), F3(2071-2100)으로 구성된다. 하지만 이는 단순하게 동일한 기간으로 나누어 설정한 것으로, 통계적 근거가 부족할 뿐만 아니라 변화 추이를 확인하기 위한 수단으로 사용하기에 부족할 수 있다는 한계점이 존재한다. 이 연구에서는 기후변화 패턴에 대한 기존 연구의 한계, 특히 미래 기후변화를 비교하기 위해 사용되는 기간 분류와 관련하여 한계점을 보완하고자 한다. SSP 시나리오 모델 중 UKESM1 모델을 활용하여 ASOS(Automated Synoptic Observation System) 기상관측소 기준 59개 지점에서 추출한 강수량 데이터를 분석하였다. 이후, 기후변화 비교를 위한 최적의 분류를 결정하기 위해 장마철인 6월부터 9월까지의 강수 데이터에 대해 통계분석 및 Pettitt 검정을 수행해 최적 기간을 산정하였다. 이를 통해 기존의 F1, F2, F3 분류 방식과 통계분석을 통해 도출한 최적 시기의 유출 특성 분석결과의 변화양상을 비교하였으며, 각 방법에 대한 비교를 통해 기후변화 추이에 대한 이해를 제공할 수 있을 것으로 판단하였다. 결과적으로 이 연구는 기후변화 시나리오를 활용하는 연구 수행 시 기간 구분에 대한 발전된 접근 방식을 제시하고자 한다.

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Application of machine learning for merging multiple satellite precipitation products

  • Van, Giang Nguyen;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.134-134
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    • 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.

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Evaluation of Precipitation Variability using Grid-based Rainfall Data Based on Satellite Image (위성영상 기반 격자형 강우자료를 활용한 강수량 변동성 평가)

  • Park, Gwang-Su;Nam, Won-Ho;Mun, Young-Sik;Yang, Mi-Hye;Lee, Hee-Jin
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.330-330
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    • 2022
  • 우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

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Analysis of Optical Characteristic Near the Cloud Base of Before Precipitation Over the Yeongdong Region in Winter (영동지역 겨울철 스캔라이다로 관측된 강수 이전 운저 인근 수상체의 광학 특성 분석)

  • Nam, Hyoung-Gu;Kim, Yoo-Jun;Kim, Seon-Jeong;Lee, Jin-Hwa;Kim, Geon-Tea;An, Bo-Yeong;Shim, Jae-Kwan;Jeon, Gye-hak;Choi, Byoung-Choel;Kim, Byung-Gon
    • Korean Journal of Remote Sensing
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    • v.34 no.2_1
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    • pp.237-248
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    • 2018
  • The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.

An analysis of Characteristics of Heavy Rainfall Events over Yeongdong Region Associated with Tropopause Folding (대류권계면 접힘에 의한 영동지방 집중호우사례의 특성분석)

  • Lee, Hye-Young;Ko, Hye-Young;Kim, Kyung-Eak;Yoon, Ill-Hee
    • Journal of the Korean earth science society
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    • v.31 no.4
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    • pp.354-369
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    • 2010
  • The synoptic and kinematic characteristics of a heavy rainfall that occurred in Gangneung region on 22 to 24 October 2006 were investigated using weather maps, infrared images, AWS observation data and NCEP global final analyses data. The total amount of rainfall observed in the region for the period was 316.5 mm, and the instanteneous maximum wind speed was $63.7m\;s^{-1}$. According to the analysis of weather maps, before the starting of the heavy rainfall, an extratropical low pressure system was developed in the middle region of the Korean Peninsula, and an inverted trough was formed in the northern region of the peninsula. In addition, a jet stream on the upper charts of 300 hPa was located over the Yellow Sea and the southern boundary of the peninsula. A cutoff low in the cyclonic shear side of the upper jet streak, which was linked to an anomaly of isentropic potential vorticity, was developed over the northwestern part of the peninsula. And there are analyzed potential vorticity and wind, time-height cross section of potential vorticity, vertical air motion, maximums of the divergence and convergence and vertical distribution of potential temperature in Gangneung region. The analyzed results of the synoptic conditions and kinematic processes strongly suggest that the tropopause folding made a significant role of initializing the heavy rainfall.

Estimation of Monthly Precipitation in North Korea Using PRISM and Digital Elevation Model (PRISM과 상세 지형정보에 근거한 북한지역 강수량 분포 추정)

  • Kim, Dae-Jun;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.13 no.1
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    • pp.35-40
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    • 2011
  • While high-definition precipitation maps with a 270 m spatial resolution are available for South Korea, there is little information on geospatial availability of precipitation water for the famine - plagued North Korea. The restricted data access and sparse observations prohibit application of the widely used PRISM (Parameter-elevation Regressions on Independent Slopes Model) to North Korea for fine-resolution mapping of precipitation. A hybrid method which complements the PRISM grid with a sub-grid scale elevation function is suggested to estimate precipitation for remote areas with little data such as North Korea. The fine scale elevation - precipitation regressions for four sloping aspects were derived from 546 observation points in South Korea. A 'virtual' elevation surface at a 270 m grid spacing was generated by inverse distance weighed averaging of the station elevations of 78 KMA (Korea Meteorological Administration) synoptic stations. A 'real' elevation surface made up from both 78 synoptic and 468 automated weather stations (AWS) was also generated and subtracted from the virtual surface to get elevation difference at each point. The same procedure was done for monthly precipitation to get the precipitation difference at each point. A regression analysis was applied to derive the aspect - specific coefficient of precipitation change with a unit increase in elevation. The elevation difference between 'virtual' and 'real' surface was calculated for each 270m grid points across North Korea and the regression coefficients were applied to obtain the precipitation corrections for the PRISM grid. The correction terms are now added to the PRISM generated low resolution (~2.4 km) precipitation map to produce the 270 m high resolution map compatible with those available for South Korea. According to the final product, the spatial average precipitation for entire territory of North Korea is 1,196 mm for a climatological normal year (1971-2000) with standard deviation of 298 mm.

Climate Change Impact on the Flowering Season of Japanese Cherry (Prunus serrulata var. spontanea) in Korea during 1941-2100 (기후변화에 따른 벚꽃 개화일의 시공간 변이)

  • Yun Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.8 no.2
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    • pp.68-76
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    • 2006
  • A thermal time-based two-step phenological model was used to project flowering dates of Japanese cherry in South Korea from 1941 to 2100. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. Daily maximum and minimum temperature are used to calculate daily chill units until a pre-determined chilling requirement for rest release is met. After the projected rest release date, daily heat units (growing degree days) are accumulated until a pre-determined heating requirement for flowering is achieved. Model calculations using daily temperature data at 18 synoptic stations during 1955-2004 were compared with the observed blooming dates and resulted in 3.9 days mean absolute error, 5.1 days root mean squared error, and a correlation coefficient of 0.86. Considering that the phonology observation has never been fully standardized in Korea, this result seems reasonable. Gridded data sets of daily maximum and minimum temperature with a 270 m grid spacing were prepared for the climatological years 1941-1970 and 1971-2000 from observations at 56 synoptic stations by using a spatial interpolation scheme for correcting urban heat island effect as well as elevation effect. A 25km-resolution temperature data set covering the Korean Peninsula, prepared by the Meteorological Research Institute of Korea Meteorological Administration under the condition of Inter-governmental Panel on Climate Change-Special Report on Emission Scenarios A2, was converted to 270 m gridded data for the climatological years 2011-2040, 2041-2070 and 2071-2100. The model was run by the gridded daily maximum and minimum temperature data sets, each representing a climatological normal year for 1941-1970, 1971-2000, 2011-2040, 2041-2070, and 2071-2100. According to the model calculation, the spatially averaged flowering date for the 1971-2000 normal is shorter than that for 1941-1970 by 5.2 days. Compared with the current normal (1971-2000), flowering of Japanese cherry is expected to be earlier by 9, 21, and 29 days in the future normal years 2011-2040, 2041-2070, and 2071-2100, respectively. Southern coastal areas might experience springs with incomplete or even no Japanese cherry flowering caused by insufficient chilling for breaking bud dormancy.

The Distribution of Total Ozone Amounts and Intercomparison of their characteristics Derived from the TOVS Observations over the Korean Peninsula (TOVS로 부터 도출한 한반도 부근의 전오존량 분포 및 그 특성 비교)

  • 정효상;주상원
    • Korean Journal of Remote Sensing
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    • v.11 no.3
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    • pp.23-31
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    • 1995
  • The International TOVS(TIROS Operational Vertical Sounders) Process Package(ITPP-VI), which has been installed at Korea Meteorological Administration(KMA), is only for a global usage to need a surface data to generate atmospheric soundings and total ozone amount. If the initial input process in the ITTP-VI is not modified, it takes climatic surface data for producing sounding data and total ozone amount in general. KMA is trying to improve the quality of TOVS total ozone amount using real-time synoptoc observation in various ways instead of climatological data because this retrieved data in the new scheme for total ozone presently used at the KMA may critically provide to analyze the long-term trend of ozone structure over the Korean peninsula. Two cases in this study show that TOVS retrieved total ozone amounts used by synoptic surface observations can delineate more detailed ozone structures rather than those used by climate surface data. The distribution of TOVS retrieved ozone amount fields with the synoptic surface analyzed data(TOVS-GPV) show more in detail relatively than those with the climate data(TOVS-CLIMAT) as expected. In addition, the collocated inter-comparisons of TOVS-GPV with TOVS-CLIMAT, TOMS observations and Dobsometer observations are performed statistically. TOVS-GPV fields with TOMS observations show smaller bias relatively than TOVS-CLIMAT and also reduce the differences.