• Title/Summary/Keyword: total cloud mixing ratio

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Cloud Forecast using Numerical Weather Prediction (수치 예보를 이용한 구름 예보)

  • Kim, Young-Chul
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.15 no.3
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    • pp.57-62
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    • 2007
  • In this paper, we attempted to produce the cloud forecast that use the numerical weather prediction(NWP) MM5 for objective cloud forecast. We presented two methods for cloud forecast. One of them used total cloud mixing ratio registered to sum(synthesis) of cloud-water and cloud-ice grain mixing ratio those are variables related to cloud among NWP result data and the other method that used relative humidity. An experiment was carried out period from 23th to 24th July 2004. According to the sequence of comparing the derived cloud forecast data with the observed value, it was indicated that both of those have a practical use possibility as cloud forecast method. Specially in this Case study, cloud forecast method that use total cloud mixing ratio indicated good forecast availability to forecast of the low level clouds as well as middle and high level clouds.

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Bulk-Type Cloud Microphysics Parameterization in Atmospheric Models (대기 모형에서의 벌크형 미세구름물리 모수화 방안)

  • Lim, Kyo-Sun Sunny
    • Atmosphere
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    • v.29 no.2
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    • pp.227-239
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    • 2019
  • This paper reviews various bulk-type cloud microphysics parameterizations (BCMPs). BCMP, predicting the moments of size distribution of hydrometeors, parameterizes the grid-resolved cloud and precipitation processes in atmospheric models. The generalized gamma distribution is mainly applied to represent the hydrometeors size distribution in BCMPs. BCMP can be divided in three different methods such as single-moment, double-moment, and triple-moment approaches depending on the number of prognostic variables. Single-moment approach only predicts the hydrometeors mixing ratio. Double-moment approach predicts not only the hydrometeors mixing ratio but also the hydrometeors number concentration. Triple-moment approach predicts the dispersion parameter of hydrometeors size distribution through the prognostic reflectivity, together with the number concentrations and mixing ratios of hydrometeors. Triple-moment approach is the most time expensive method because it has the most number of prognostic variables. However, this approach can allow more flexibility in representing hydrometeors size distribution relative to single-moment and double-moment approaches. At the early stage of the development of BMCPs, warm rain processes were only included. Ice-phase categories such as cloud ice, snow, graupel, and hail were included in BCMPs with prescribed properties for densities and sedimentation velocities of ice-phase hydrometeors since 1980s. Recently, to avoid fixed properties for ice-phase hydrometeors and ad-hoc category conversion, the new approach was proposed in which rimed ice and deposition ice mixing ratios are predicted with total ice number concentration and volume.

A Study on Feasibility of Cloud Seeding in Korea (한반도에서의 인공증우 가능성에 대한 연구)

  • Chung, Kwan-Young;Eom, Won-Geun;Kim, Min-Jeong;Jung, Young-Sun
    • Journal of Korea Water Resources Association
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    • v.31 no.5
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    • pp.621-635
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    • 1998
  • The feasibility of cloud seeding in Korea is presented from analyses of precipitation, cloud amount, satellite data, and upper air data. The daily mean precipitation over Dae-Kwan-Ryong is the largest(~4.5 mm/day), while the intensity of precipitation (amount of yearly rainfall divided by the frequency of rain days) over Southern area is above 14 mm/day, which shows the largest in Korea. Both the daily mean and the intensity of precipitation over Andong area are the smallest with values of ~2.7 mm/day and ~11 mm/day, respectively. In the meanwhile, the occurrence frequency of appropriate cloud top temperature (-10'~-30') for cloud seeding over the region has a large value (~130 days/year). The precipitation patterns of the region vary with wind direction and intensity calculated from 43 AWSs(Automatic Weather Station) and the additional 7 rain guages which were installed along Northern and Southern part of the Sobaek mountain. The Sc(Stratocumulus) cloud type over Andong is frequently observed, and Cirrus and Altostratus next. From the results, it is estimated that the feasibility of cloud seeding over the area would be high if a proper strategy of cloud seeding is set up. LCL (Lifting Condensation Level) and CCL (Convective Condensation Level) have the most frequency in 1000-950 hPa being occupied 4/9 of total analysis period and in 400-500 hPa, respectively, with both small variations from season to season. The correlation between vapor mixing ratio and CCL is the highest in Summer and the lowest in Winter. It means that the height of cumulus in Summer is high with an abundant water vapor but vice versa in Winter, and that the strategy of cloud seeding should be different with seasons.

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Application of Seasonal AERI Reference Spectrum for the Improvement of Cloud data Filtering Method (계절별 AERI 기준 스펙트럼 적용을 통한 구름에 영향을 받은 스펙트럼 자료 제거방법 개선)

  • Cho, Joon-Sik;Goo, Tae-Young;Shin, Jinho
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.409-419
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    • 2015
  • The Atmospheric Emitted Radiance Interferometer (AERI) which is the Fourier Transform InfraRed (FTIR) spectrometer has been operated by the National Institute of Meteorological Research (NIMR) in Anmyeon island, South Korea since June 2010. The ground-based AERI with similar hyper-spectral infrared sensor to satellite could be an alternative way to validate satellite-based remote sensing. In this regard, the NIMR has focused on the improvement of Cloud data Filtering Method (CFM) which employed only one reference spectrum of clear sky in winter season. This study suggests Seasonal-Cloud data Filtering Method (S-CFM) which applied seasonal AERI reference spectra. For the comparison of applied S-CFM and CFM, the methane retrievals (surface volume mixing ratio) from AERI spectra are used. The quality of AERI methane retrieval applied S-CFM was significantly more improved than that of CFM. The positive result of S-CFM is similar pattern with the seasonal variation of methane from ground-based in-situ measurement, even if the summer season's methane is retrieved over-estimation. In addition, the comparison of vertical total column of methane from AERI and GOSAT shows good result except for the summer season.

The Study on the Frontal Thunderstorm during Winter Time in the Korean Peninsula (우리나라 동계 전선성 뇌우에 관한 연구)

  • Kim, Jong-Seok;Park, Sang Hwan;Ham, Sook Jung;Ban, Ki-Song;Choi, Young Jean;Chang, Dong-Eon;Chung, Hyo-Sang
    • Atmosphere
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    • v.16 no.4
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    • pp.351-358
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    • 2006
  • The structure of frontal thunderstorm in winter time is different from that of in summer time over the Korean peninsula, due to dry tongue and upward motion. The dry tongue, that is propagation of dry zone from upper level to lower level, was formed after front passage and the upward motion is intensified by the strengthened low level jet. Since this mechanism makes the structure more unstable, thunderstorm occurs at relatively low cloud top height. This study suggests a forecast guidance of winter time frontal thunderstorm that thunderstorms develop when one of the following conditions are satisfied: 1) total totals (TT) >40, 2) K index >-10, 3) mixing ratio ${\geq}$ 3.5 g/kg.

Development of Raman LIDAR System to Measure Vertical Water Vapor Profiles and Comparision of Raman LIDAR with GNSS and MWR Systems (수증기의 연직 분포 측정을 위한 라만 라이다 장치의 개발 및 GNSS, MWR 장비와 상호 비교연구)

  • Park, Sun-Ho;Kim, Duk-Hyeon;Kim, Yong-Gi;Yun, Mun-Sang;Cheong, Hai-Du
    • Korean Journal of Optics and Photonics
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    • v.22 no.6
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    • pp.283-290
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    • 2011
  • A Raman LIDAR system has been designed and constructed for quantitative measurement of water vapor mixing ratio. The comparison with commercial microwave radiometer and global navigation satellite system(GNSS) was performed for the precipitable water vapor(PWV) profile and total PWV. The result shows that the total GNSS-PWV and LIDAR-PWV have good correlation with each other. But, there is small difference between the two methods because of maximum measurement height in LIDAR and the GNSS method. There are some significant differences between Raman and MWR when the water vapor concentration changes quickly near the boundary layer or at the edge of a cloud. Finally we have decided that MWR cannot detect spatial changes but LIDAR can measure spatial changes.