• Title/Summary/Keyword: NOAA-11

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The Analysis of Typhoon Center Location and Intensity from NOAA Satellite Microwave Data (NOAA/MUS 자료를 이용한 태풍 중심의 위치및 강도 분석)

  • 신도식;서애숙;김용상;이미선
    • Korean Journal of Remote Sensing
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    • v.11 no.2
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    • pp.29-42
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    • 1995
  • A typhoon center location and its intensity from the 54.96GMz channel of Microwave Sounding Unit(MSU) on board the NOAA satellite is analyzed. NOAA satellite MSU channel 3 data may delineate the development and dissipation of the upper tropospheric warm core associated with a typhoon. The typhoon warm core is related to microwave imagery of 250hPa temperature field (54.96GMz). The typhoon center intensity, surface center pressure and maximum wind speed at the eye well, correlate to horozontal Laplacian of an upper tropospheric temperature field. The typhoon center is found from the analysis of 250hPa temperature field. The excellent correlation is found between the horizontal Laplacian of an tropospheric temperature field and surface maximum wind speed, another correlation is found between the warm temperature anomaly and surface pressure anomaly.

EXTENDED KALMAN FILTERING OF SATELLITE DOPPLER TRACKING DATA AND IT'S APPLICATION TO ORBIT DETERMINATION PROBLEMS (확장칼만필터를 이용한 인공위성 도플러 추적자료의 처리와 궤도 결정)

  • 김동규;최규홍
    • Journal of Astronomy and Space Sciences
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    • v.12 no.1
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    • pp.143-156
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    • 1995
  • Using a directional antenna, the Doppler effect of satellites can be detected and the orbital elements can be obtained by the Extended Kalman Filter with the observed frequency shift data. We obtained the orbital elements of NOAA-11 by the application of the Extended Kalman Filter type algorithm to the Doppler shift data of NOAA-11d and discussed the accuracy and the credibility of this algorithm.

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Korean Vegetation Types Using NOAA/AVHRR Data (인공위성(NOAA/AVHRR) 영상자과에 의한 한반도 식생분포에 관한 연구)

  • 김동실
    • Journal of the Korean Geographical Society
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    • v.35 no.1
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    • pp.39-51
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    • 2000
  • 본 연구는 원격탐사 기법을 이용하여 북한 지역을 포함한 한반도 전지역을 대상으로 식생활력도(vegetation activity)의 시계열적 변화를 모니터링하고, 식생지수의 연중변화 특성을 이용하여 한반도의 식생 분포도를 작성하는데 그 목적이 있다. 1997년 4월부터 11월까지 8개월 동안 NOAA-14 위성에서 수신된 AVHRR 자료를 수집하여 정규 식생지수(Nomalized Difference Vegetation Index)를 구하고 이들을 MVC(Maximum Value Composite) 방법으로 조합하여 월별 NDVI 합성도를 작성하여 식생활력도의 시계열 변화를 고찰하였다. 또한 식물의 생장시기인 5월부터 10월까지의 NDVI를 무감독 분류하여 한반도의 식생분포 유형을 도시.나대지가 4.49%, 초지 4.49%, 경작지 27.54%, 활엽수림 25.61%, 침엽수림 38.22%로 나타났다.

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Extraction of Snow Cover Area and Depth Using NOAA/AVHRR Images (NOAA/AVHRR 위성영상을 이용한 적설분포 및 적설심 추출)

  • Kang Su Man;Lim Hyuk Jin;Kwon Hyung Joong;Kim Seong Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.948-952
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    • 2005
  • 본 연구는 우리나라 강원도 북동부 산지유역의 봄철 하천유출량에 영향을 주는 융설에 관련하여, 장기 유출 모형의 융설 모의시 융설 관련 매개변수 추정 및 정량화에 기본이 피는 적설 분포 지역 및 적설심 추출기법을 제시하였다. NOAA/AVHRR 위성영상을 이용하여 소양강 유역에 대하여 2002년 11월부터 2003년 3월까지의 적설분포를 추출한 후, 추출 결과와 유역 인근 7개 기상관측소의 최심적설심 자료와의 중첩을 통하여 적설심을 추출하였다.

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Adjoint-Based Observation Impact of Advanced Microwave Sounding Unit-A (AMSU-A) on the Short-Range Forecast in East Asia (수반 모델에 기반한 관측영향 진단법을 이용하여 동아시아 지역의 단기예보에 AMSU-A 자료 동화가 미치는 영향 분석)

  • Kim, Sung-Min;Kim, Hyun Mee
    • Atmosphere
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    • v.27 no.1
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    • pp.93-104
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    • 2017
  • The effect of Advanced Microwave Sounding Unit-A (AMSU-A) observations on the short-range forecast in East Asia (EA) was investigated for the Northern Hemispheric (NH) summer and winter months, using the Forecast Sensitivity to Observations (FSO) method. For both periods, the contribution of radiosonde (TEMP) to the EA forecast was largest, followed by AIRCRAFT, AMSU-A, Infrared Atmospheric Sounding Interferometer (IASI), and the atmospheric motion vector of Communication, Ocean and Meteorological Satellite (COMS) or Multi-functional Transport Satellite (MTSAT). The contribution of AMSU-A sensor was largely originated from the NOAA 19, NOAA 18, and MetOp-A (NOAA 19 and 18) satellites in the NH summer (winter). The contribution of AMSU-A sensor on the MetOp-A (NOAA 18 and 19) satellites was large at 00 and 12 UTC (06 and 18 UTC) analysis times, which was associated with the scanning track of four satellites. The MetOp-A provided the radiance data over the Korea Peninsula in the morning (08:00~11:30 LST), which was important to the morning forecast. In the NH summer, the channel 5 observations on MetOp-A, NOAA 18, 19 along the seaside (along the ridge of the subtropical high) increased (decreased) the forecast error slightly (largely). In the NH winter, the channel 8 observations on NOAA 18 (NOAA 15 and MetOp-A) over the Eastern China (Tibetan Plateau) decreased (increased) the forecast error. The FSO provides useful information on the effect of each AMSU-A sensor on the EA forecasts, which leads guidance to better use of AMSU-A observations for EA regional numerical weather prediction.

A Study on Comparison of Satellite-Tracked Drifter Temperature with Satellite-Derived Sea Surface Temperature of NOAA/NESDIS

  • Park, Kyung-Ae;Chung, Joug-Yul;Kim, Kuh;Choi, Byung-Ho
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.83-107
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    • 1994
  • Sea surface temperatures (SSTs) estimated by using the operational SST derivation equations of NOAA/NESDIS were compared with satellite-tracked drifter temperatures. As a result of eliminating cloud-filled or contaminated pixels through several cloud tests, 69 matchup points between the drifter temperatures and the SSTs estimated with NOAA satellite 9, 10. 11 and 12 data from August, 1993 to July, 1994 were collected. Multi-channel sea surface temperature(MCSST) using a split window technique showed an approximately $1.0{\circ}C$ rms error as compared with the drifting buoy temperatures for 69 coincidences. Accuracies for satellete-derived sea surface temperatures were evaluated for only NOAA-11 AVHRR data which had relatively large matchups of 35points as compared with other satellites. For the comparison of the oberved temperatures with the calculated SSTs, linear MCSST and nonlinear cross product sea surface temperature(CPSST) algorithms by the split, the dual and the triple window technique were used respectively. As a result, the split window CPSSTs showed the smallest rms error of $0.72{\circ}C$. Defferences between the split window SSTs and the drifter temperatures appeared th have a linear tendency against the drifter temperatures and also against the differences between AVHRR channel 4 and 5 brighness temperatures. This indicates some possibilities that satelite-derived SSTs operationally calculated from the NOAA/NESDIS equation in the seas around Korea have been underestimated as compared with actural SSTs in case sea water temperature is relatively low or the atmosphere over the sea surface is very dry like in winter, while overstimated in case of high temperature or very moist atmospheric equations based on local sea measurements around Korea instead of global measurements should be derived.

Study on the Southern Coastal Waters of Korea by NOAA Image (NOAA영상자료에 의한 한국 남해안연안수 조사연구)

  • 김복기
    • Korean Journal of Remote Sensing
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    • v.5 no.1
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    • pp.57-67
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    • 1989
  • This study on the southern coastal waters of Korea has been made by analysis of NOAA image and oceanographic observation data from October 1987 to August 1988. The results obtained from the study are as follow: Horizontal distributions of water temperature in different layers in winter ranged from 6.07 to 18.62$^{\circ}C$ at 0m layer, 6.02 to 18.54$^{\circ}C$ at 30m layer and 7.19 to 18.69$^{\circ}C$ at 50m layer. Consequently its vertical distribution showed homogeneity. Horizontal water temperature gradients were 0.28$^{\circ}C$/mile between the coastal waters and Tsushima warm waters. In summer, its horizontal distribution varied from 19.37 to 29.92$^{\circ}C$ at 0m layer, 13.26 to 27.11$^{\circ}C$ at 30m layer and 7.36 to 26.6$0^{\circ}C$ at 50m layer, and its vertical profile showed stratified structure. Vertical water temperature gradients were 0.44$^{\circ}C$/m between 30 and 50m layers. It was remarkable that distribution of southern coastal water system analysed by NOAA image coincided with relatively the oceanographic observation data but SST from NOAA image seemed to be 2-4$^{\circ}C$ lower in winter and 4-6$^{\circ}C$ lower in summer than the oceanographic data.

Analysis of Cloud Types and Low-Level Water Vapor Using Infrared Split-Window Data of NOAA/AVHRR (NOAA/AVHRR 적외 SPLIT WINDOW 자료를 이용한 운형과 하층수증기 분석)

  • 이미선;이희훈;서애숙
    • Korean Journal of Remote Sensing
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    • v.11 no.1
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    • pp.31-45
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    • 1995
  • The values of brightness temperature difference (BTD) between 11um and 12um infrared channels may reflect amounts of low-level water vapor and cloud types due to the different absorptivity for water vapor between two channels. A simple method of classifying cloud types at night was proposed. Two-dimensional histograms of brightness temperature of the 11um channel and the BTD between the split window data over subareas around characteristic clouds such as Cb(cumulonimbus), Ci(cirrus), and Sc(stratocumulus) was constructed. Cb, Ci and Sc can be classified by seleting appropriate thresholds in the two-dimensional histograms. And we can see amounts of low-level water vapor in clear area as well as cloud types in cloudy area in the BTD image. The map of cloud types and low-level water vapor generated by this method was compared with 850hPa and 1000hPa relative humidity(%) of numerical analysis data and nephanalysis chart. The comparisons showed reasonable agreement.

A Study on the Estimation of the Sea Surface Temperature from AVHRR CH4 data of NOAA-9 (극궤도 기상위성 NOAA-9호의 AVHRR CH4 data로 부터 해수면온도 산출과정에 관한 연구)

  • 이희훈;서애숙
    • Korean Journal of Remote Sensing
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    • v.3 no.1
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    • pp.41-54
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    • 1987
  • Accurate determination of Sea Surface Temperature (SST) is essential for ocean and climate studies. This paper estimated SST in the sea region around the Korea from the Advenced Very High Resolution Radiometer(AVHRR) channel 4 data on board NOAA-9 satellite. The processing procedure used to derive SSTs utilized: 1) Ascending node prediction of satellite orbit 2) Geometric correction 3) Radiometric calibration and radiance to temperature conversion look up table 4) Removing cloudy area. SST product results are displayed as colored video and hardcopy. In this processing, geometric correction is derived from equator crossing time, ascending time and subpoint coordinate information. Also, normalized response function of infrared 10.5-11.5$\mu\textrm{m}$ wavelength is used for temperature conversion. The SST derived from this processing is relatively similar to the measurements made by ship data, but because of water vapor attenuation SST from satellite are in general 2$^{\circ}$- $^{\circ}C$ lower than the ship data.

Extraction of Snowmelt Factors using NOAA Satellite Images and Meteorological Data (NOAA위성영상 및 기상자료를 이용한 융설 관련 매개변수 추출)

  • Kang, Su-Man;Shin, Hyung-Jin;Kwon, Hyung-Joong;Kim, Seong-Joon
    • Journal of Korea Water Resources Association
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    • v.39 no.10 s.171
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    • pp.845-854
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    • 2006
  • Establishment of snowmelt factors is necessary to simulate stream flow using snowmelt models during snowmelt periods. The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. The objective of this study was to extract snowmelt factors using RS, GIS technique and meteorological data. Snow cover maps were derived from NOAA/AVHRR images for the winter seasons from 1997 to 2003. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation station. Depletion curves of snowmelt area were described from the linear regression equations of each year between the average temperature and snow cover area in Soyanggang-dam and chungju-dam watershed.