• 제목/요약/키워드: Satellite Retrievals

검색결과 39건 처리시간 0.023초

RAINFALL ESTIMATION OVER THE TAIWAN ISLAND FROM TRMM/TMI DATA DURING THE TYPHOON SEASON

  • Chen, W-J;Tsai, M-D;Wang, J-L;Liu, G-R;Hu, J-C;Li, C-C
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.930-933
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    • 2006
  • A new algorithm for satellite microwave rainfall retrievals over the land of Taiwan using TMI (TRMM Microwave Imager) data on board TRMM (Tropical Rainfall Measuring Mission) satellite is described in this study. The scattering index method (Grody, 1991) was accepted to develop a rainfall estimation algorithm and the measurements from Automatic Rainfall and Meteorological Telemetry System (ARMTS) were employed to evaluate the satellite rainfall retrievals. Based on the standard products of 2A25 derived from TRMM/PR data, the rainfall areas over Taiwan were divided into convective rainfall area and stratiform rainfall areas with/without bright band. The results of rainfall estimation from the division of rain type are compared with those without the division of rain type. It is shown that the mean rainfall difference for the convective rain type is reduced from -6.2mm/hr to 1.7mm/hr and for the stratiform rain type with bright band is decreased from 10.7 mm/hr to 2.1mm/hr. But it seems not significant improvement for the stratiform rain type without bright band.

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자료동화 토양수분 데이터를 활용한 동아시아지역 수동형 위성 토양수분 데이터 보정: SMOS (MIRAS), GCOM-W1 (AMSR2) 위성 및 GLDAS 데이터 활용 (Revising Passive Satellite-based Soil Moisture Retrievals over East Asia Using SMOS (MIRAS) and GCOM-W1 (AMSR2) Satellite and GLDAS Dataset)

  • 김형록;김성균;정재환;신인철;신진호;최민하
    • 한국습지학회지
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    • 제18권2호
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    • pp.132-147
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    • 2016
  • 동아시아 지역의 위성 토양수분 데이터 활용을 위해 Soil Moisture Ocean Salinity (SMOS) 위성에 탑재된 Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) 센서와 Global Change Observation Mission-Water (GCOM-W1) 위성에 탑재된 Advanced Microwave Scanning Radiometer 2 (AMSR2) 센서 기반 토양수분 데이터를 자료동화 데이터인 Global Land Data Assimilation System (GLDAS)를 기준 값으로 Cumulative Distribution Function (CDF) 기법과 회귀식을 활용하여 보정하는 연구를 수행하였다. 동아시아 지역에서 발생하는 전파간섭의 영향을 고려하여 토양수분 산출에 적합하다고 판단되는 Radio Frequency Interference (RFI), Data Quality indeX (DQX) 한계값과, 합성일수를 제시하였다. 보완된 위성 토양수분 데이터를 지점 토양수분 데이터와 비교한 결과 상관계수가 평균 27%, 11% 증가하였고, Root Mean Square Deviation (RMSD, 평균제곱근 편차)는 평균 61%, 57% 감소하였다. 추가적으로, 보정된 위성데이터를 GLDAS 토양수분 데이터와 비교했을 때, 보정된 MIRAS 및 AMSR2 데이터는 한반도의 80% 및 90%의 지역에서 상관계수가 증가하였으며, 한반도 전역에서 RMSD가 감소하였다. 본 연구를 통해 향후 MIRAS 및 AMSR2 위성 데이터를 융합하여 각 위성의 토양수분 데이터를 보완 할 수 있는 가능성을 제시하였다.

Improving streamflow prediction with assimilating the SMAP soil moisture data in WRF-Hydro

  • Kim, Yeri;Kim, Yeonjoo
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2021년도 학술발표회
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    • pp.205-205
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    • 2021
  • Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

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OMI 구름 측정 자료들의 비교 분석과 그에 따른 오존 측정에 미치는 영향 평가 (Analyses of the OMI Cloud Retrieval Data and Evaluation of Its Impact on Ozone Retrieval)

  • 최수환;박주선;김재환;백강현
    • 대기
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    • 제25권1호
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    • pp.117-127
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    • 2015
  • The presences of clouds significantly influence the accuracy of ozone retrievals from satellite measurements. This study focuses on the influence of clouds on Ozone Monitoring instrument (OMI) ozone profile retrieval based on an optimal estimation. There are two operational OMI cloud products; OMCLDO2, based on absorption in $O_2-O_2$ at 477 nm, and OMCLDRR, based on filling in Fraunhofer lines by rotational Raman scattering (RRS) at 350 nm. Firstly, we characterize differences between $O_2-O_2$ and RRS effective cloud pressures using MODIS cloud optical thickness (COT), and then compare ozone profile retrievals with different cloud input data. $O_2-O_2$ cloud pressures are significantly smaller than RRS by ~200 hPa in thin clouds, which corresponds to either low COT or cloud fraction (CF). On the other hand, the effect of Optical centroid pressure (OCP) on ozone retrievals becomes significant at high CF. Tropospheric ozone retrievals could differ by up to ${\pm}10$ DU with the different cloud inputs. The layer column ozone below 300 hPa shows the cloud-induced ozone retrieval error of more than 20%. Finally, OMI total ozone is validated with respect to Brewer ground-based total ozone. A better agreement is observed when $O_2-O_2$ cloud data are used in OMI ozone profile retrieval algorithm. This is distinctly observed at low OCP and high CF.

An Improved Estimation of Outgoing Longwave Radiation Based on Geostationary Satellite

  • Kim, Hyunji;Seo, Minji;Seong, Noh-hun;Lee, Kyeong-sang;Choi, Sungwon;Jin, Donghyun;Huh, Morang;Han, Kyung-Soo
    • 대한원격탐사학회지
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    • 제35권1호
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    • pp.195-201
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    • 2019
  • The Outgoing Longwave Radiation (OLR) is an important satellite-driven variable for understanding the Earth's energy budget balance. The geostationary OLR retrievals require angular and spectral integration using an empirical equation for irradiance flux-to-OLR from a regression analysis, which determines the accuracy of the narrowband satellite-based OLR. We selected homogeneous pixels which is satisfied less temporal-spatial variability of cloud, on three infrared channels (6.7, 10.8, $12.0{\mu}m$) of the first multipurpose geostationary satellite in Korea, namely the Communication, Ocean and Meteorological Satellite/Meteorological Imager (COMS/MI). Multiple regression analysis was performed to retrieve OLR with improved accuracy using selected parameters based on theoretical and physical significance. This algorithm yielded retrieval with higher accuracy than broadband-based OLR retrieval: RMSE of 10.54 to $3.81W\;m^{-2}$, and bias of -8.49 to $-0.07W\;m^{-2}$.

EFFECTS OF ATMOSPHERIC WATER AND SURFACE WIND ON PASSIVE MICROWAVE RETRIEVALS OF SEA ICE CONCENTRATION: A SIMULATION STUDY

  • Shin, Dong-Bin;Chiu, Long S.;Clemente-Colon, Pablo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.892-895
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    • 2006
  • The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors are examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water and water vapor and surface wind on surface emissivity on the microwave signatures. A plane parallel radiative transfer model is used to compute brightness temperatures at SSM/I frequencies over surfaces that contain open water, first-year (FY) ice and multi-year (MY) ice and their combinations. Synthetic retrievals in this study use the NASA Team (NT) algorithm for the estimation of sea ice concentrations. This study shows that if the satellite sensor’s field of view is filled with only FY ice the retrieval is not much affected by the atmospheric conditions due to the high contrast between emission signals from FY ice surface and the signals from the atmosphere. Pure MY ice concentration is generally underestimated due to the low MY ice surface emissivity that results in the enhancement of emission signals from the atmospheric parameters. Simulation results in marginal ice areas also show that the atmospheric and surface effects tend to degrade the accuracy at low sea ice concentration. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. In particular, our results suggest that strong surface wind is more important than atmospheric water in contributing to the retrieval errors of total ice concentrations over marginal ice zones.

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복사전달모델을 이용한 GEMS 일산화브로민 산출 민감도 시험 (GEMS BrO Retrieval Sensitivity Test Using a Radiative Transfer Model)

  • 정희성;김준;정욱교;박상서;홍재민;안다현;차혜지;이원진;이혜정
    • 대한원격탐사학회지
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    • 제37권6_1호
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    • pp.1491-1506
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    • 2021
  • GEMS의 복사 실측 자료로부터 일산화브로민(BrO) 전량 농도를 산출하기에 앞서, 복사전달모델로부터 생성된 모의자료를 이용하여 민감도 시험을 수행하였다. 산출 오차가 갖는 월간 및 일내 변동성을 고려하기 위해, 2013년 7월-2014년 6월 기간 매달 첫째 날의 00-07 UTC에 대해 한 시간 간격의 모의자료를 구성하였다. 최적추정법을 통해 계산된 산출물의 해답 오차는 대기질량인자 증가에 따라 감소하는 반비례 경향을 주로 보였지만, 대기질량인자 값이 5 이상으로 크게 나타나는 범위에서는 비례 경향을 보였다. BrO와 포름알데히드(HCHO) 흡수선 간의 중첩으로 인해 발생하는 BrO 산출물의 간섭 오차는 BrO의 대기질량인자가 작을수록 크게 나타났다. 해답 오차와 간섭 오차의 추정치를 결합하여 계산한 산출물 최종 오차의 평균값은 모든 데이터 샘플에 대해 26.74±30.18%로, 80° 이상의 태양천정각을 갖는 샘플에 대해 60.39±133.78%로 나타났다. 본 연구에서 고려되지 않은 간섭 스펙트럼 및 복사 측정의 오차로 인해, 실제 GEMS의 BrO 산출물이 갖게 될 오차는 추정치와 절대값의 차이를 나타낼 가능성이 있다. 그러나 본 연구에서 제시한 오차 요소들의 변동 특성들은 실제 산출물에서도 나타날 것이다.

해양수색 위성자료의 검.보정 (Calibration and Validation of Ocean Color Satellite Imagery)

  • 서영상;;장이현;이삼근;유신재
    • 한국환경과학회지
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    • 제10권6호
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    • pp.431-436
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    • 2001
  • Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer In the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentration of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll_a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDl. We studied In find out the relationship between the measured chlorophyll_a from the ship and the estimated chlorophyll_a from the SeaWiFs satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) In the northern part of the East China Sea. Chlorophyll_a =0.121Ln(X) + 0.504, R²= 0.73 (1) We also determined total suspended sediment mass (55) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-.situ data and the ratio (L/sub WN/(490 ㎚)L/sub WN/(555 ㎚) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS = -0.703 Ln(X) + 2.237, R²= 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMl, Terra/MODIS and Orbview/SeaWiFS.

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미계측지역의 위성강우 기반 가뭄감시 평가 (Evaluation of Drought Monitoring Using Satellite Precipitation for Un-gaged Basins)

  • 장상민;윤선권;이성규;이태화;박경원
    • 한국농공학회논문집
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    • 제60권2호
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    • pp.55-63
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    • 2018
  • This study analyzed the applications of near real-time drought monitoring using satellite rainfall for the Korean Peninsula and un-gaged basins. We used AWS data of Yongdam-Dam, Hoengseong-Dam in Korea area, the meteorological station of Nakhon Rachasima, Pak chong for test-bed to evaluate the validation and the opportunity for un-gaged basins. In addition, we calculated EDI (Effective doought index) using the stations and co-located PERSIANN-CDR, TRMM (Tropical Rainfall Measurement Mission) TMPA (The TRMM Multisatellite Precipitation Analysis), GPM IMERG (the integrated Multi-satellitE Retrievals for GPM) rainfall data and compared the EDI-based station data with satellite data for applications of drought monitoring. The results showed that the correlation coefficient and the determination coefficient were 0.830 and 0.914 in Yongdam-dam, and 0.689 and 0.835 in Hoengseng-Dam respectively. Also, the correlation coefficient were 0.830, 0.914 from TRMM TMPA datasets and compasion with 0.660, 0.660 based on PERSIANN-CDR and TRMM data in nakhon and pakchong station. Our results were confirmed possibility of near real-time drought monitoring using EDI with daily satellite rainfall for un-gaged basins.

기상 입력장 오차에 대한 자외선 오존 프로파일 산출 알고리즘 민감도 분석 (Sensitivity Analysis of Satellite BUV Ozone Profile Retrievals on Meteorological Parameter Errors)

  • 신대근;박주선;김재환
    • 대한원격탐사학회지
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    • 제34권3호
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    • pp.481-494
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    • 2018
  • 자외선 관측 자료로부터 최적 추정법을 이용해 오존 프로파일을 산출하기 위해서는 복사모델을 이용한 정확한 복사모의가 매우 중요하다. 복사모델 입력 변수는 복사 모의의 정확도를 결정하는 중요한 요소이며, 특히 온도와 지면 기압과 같은 기상 입력 변수는 각각 오존 흡수 계수와 레일리 산란을 계산하는데 사용되어 복사 스펙트럼 모의에 직접적인 영향을 준다. 따라서 그 영향을 평가하기 위해, 복사전달 모델을 이용하여 온도와 지면 기압에 대한 자외선 오존 프로파일 산출 민감도 검사가 수행되었다. 지면 기압은 기상 수치 예보모델 기반의 일 자료와 월 기후 자료에서 100 hPa 미만의 평균 오차를 보였으며, 해당 오차에 대해 계산된 오존 산출 오차는 각 층에 대해 약 0.2 DU 미만이다. 한편, 온도는 일 자료와 월 기후 자료에 대해서 지점과 고도에 따라 1~7K의 오차를 보였으며, 이에 대해 계산된 오존 산출 오차는 층별로 약 4 DU으로 나타났다. 이 같은 결과들은 위성 관측 값으로부터 산출된 연직 오존 정보를 이해하는데 도움이 될 뿐만 아니라, 알고리즘의 현업화 과정에서 기상 입력 자료의 선택 및 시스템 설계 방향 수립에 효과적으로 활용 가능할 것으로 기대된다.