• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.386-389
• /
• 2006

The sea surface wind speed (SSWS) derived by microwave radiometer can be contaminated by change of microwave brightness temperature owing to the angle between the sensor azimuth and the wind direction (Relative Wind Direction). We attempt to correct the contamination to the SSWS derived by Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing Satellite II (ADEOS-II), by applying the method proposed by Konda and Shibata (2004). The improvement of accuracy of the SSWS estimation amounts to roughly 60% of the error caused by the RWD effect.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.456-461
• /
• 1999

It is very important for monitoring the interannual variability of sea ice extents in the Okhotsk Sea because the global warming has firstly appeared around the Okhotsk Sea, locating around the southernmost region of sea ice cover in the Northern Hemisphere. In order to develop the sea ice concentration algorithm by microwave sensors onboard satellite, electromagnetic properties of sea ice in the Okhotsk Sea, therefore, were observed by airborne microwave radiometer (AMR), which has the same frequencies as AMSR (Advanced Microwave Scanning Radiometer), ADEOS-II, launching on November, 2000. On this study, it is discussed how to make the image of AMR-EFOV and the video image with nadir angle under flight at the same time, and superimpose the brightness temperature data by AMR-EFOV on the video mosaiced images. For comparing SPOT image, it is clearly that the variation of brightness temperature is small in 89GHz V-pol without the sea ice types and increase at the lower frequency-band.

• Korean Journal of Remote Sensing
• /
• v.27 no.2
• /
• pp.131-140
• /
• 2011

In this study, temporal variations of the Advanced Microwave Scanning Radiometer E (AMSR-E) soil moisture products were evaluated using ground based measurements from the Haenam flux monitoring network site for two years (2004 and 2006). Even if there were major comparison issues including spatial resolutions, AMSR-E soil moisture production showed a great potential to replicate temporal variability patterns with ground based measurements. Additional intensive validation efforts should be conducted at a variety of field conditions including vegetation type for better utilization of remotely sensed soil moisture and understanding of the land surface-atmosphere interactions in the view of hydrometeorology.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.146-149
• /
• 2006

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m $s^{-1}$ and $20^{\circ}$, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. The wind speed observed by AMSR also exhibited reasonable agreement with the buoy data in general with rms difference of 1.2 m $s^{-1}$. Systematic bias which was observed in earlier versions of the AMSR winds has been removed by algorithm refinements. Intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits also shows good agreements. Global wind speed histograms of the SeaWinds data and European Centre for Medium-range Weather Forecasts (ECMWF) analyses agree precisely with each other, while that of the AMSR wind shows slight deviation from them.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.705-708
• /
• 2004

The spatial variability of the L- and C- band large scale remotely sensed soil moisture data, obtained during tire Southern Great Plain 1999 (SGP'99), was characterized. The results demonstrate that soil moisture data using L-band show the break in statistical symmetry (multiscaling behavior) with the variation of scale of observation, which is similar to that of the soil property such as sand content. Also, soil moisture data using C-band show single scaling behavior with the variation of scale of observation, which Is similar to that of the vegetation condition.

• Journal of Coastal Disaster Prevention
• /
• v.4 no.3
• /
• pp.133-137
• /
• 2017

The Arctic region remains surrounded by sea ice during most of the period of the year. In the Arctic Ocean the Northern Sea Route (NSR) has been used as an important route for shipping. The arctic sea ice is decreasing since 1979; hence needs to be monitored. In this research work sea ice concentration in the recent years and sea ice concentration anomalies of few months with long term sea ice concentration are studied. The climatology of long term ice concentration data from various satellites, and the recent sea ice concentration data from Advanced Microwave Scanning Radiometer 2 (AMSR2) were used. The results show that sea ice concentration and sea ice extent in the Arctic region decreased by around 5% from 2015 to 2016, but in 2017 increased again in smaller amount in some areas like around Novaya Zemlya, and parts of the sea in between Greenland and Longyearbyen, and around Banks Island. The percentages of sea ice area in NSR for July 7 in 2015 to 2017 were 37%, 39% and 33%, respectively, indicating a large area (around ten thousand $km^2$) become ice free in 2017 compared to the previous year.

• Journal of Wetlands Research
• /
• v.18 no.2
• /
• pp.132-147
• /
• 2016

In this study the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) sensor onboard the Soil Moisture Ocean Salinity (SMOS) and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission-Water (GCOM-W1) based soil moisture retrievals were revised to obtain better accuracy of soil moisture and higher data acquisition rate over East Asia. These satellite-based soil moisture products are revised against a reference land model data set, called Global Land Data Assimilation System (GLDAS), using Cumulative Distribution Function (CDF) matching and regression approach. Since MIRAS sensor is perturbed by radio frequency interferences (RFI), the worst part of soil moisture retrieval, East Asia, constantly have been undergoing loss of data acquisition rate. To overcome this limitation, the threshold of RFI, DQX, and composite days were suggested to increase data acquisition rate while maintaining appropriate data quality through comparison of land surface model data set. The revised MIRAS and AMSR2 products were compared with in-situ soil moisture and land model data set. The results showed that the revising process increased correlation coefficient values of SMOS and AMSR2 averagely 27% 11% and decreased the root mean square deviation (RMSD) decreased 61% and 57% as compared to in-situ data set. In addition, when the revised products' correlation coefficient values are calculated with model data set, about 80% and 90% of pixels' correlation coefficients of SMOS and AMSR2 increased and all pixels' RMSD decreased. Through our CDF-based revising processes, we propose the way of mutual supplementation of MIRAS and AMSR2 soil moisture retrievals.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.332-332
• /
• 2022

적설은 지구 기후시스템과 수문순환 과정에서 중요한 역할을 하고 있으며, 겨울철의 적설은 봄철에 녹으면서 식생과 수자원 제공에 큰 영향을 주는 인자로 알려져 있다. 동아시아가 위치한 북반구는 적설량의 90%가 관찰되고 토지의 약 42%가 긴 시간동안 눈으로 덮여 있어 지표 에너지와 물 균형에 영향을 주고, 특히 수자원 관리를 위한 유출이나 토양수분과 같은 수문 인자에 큰 영향을 미친다. 따라서 적설을 정확하게 예측하는 것은 수자원 관리에 있어 매우 중요한 일이다. 한편, 이러한 수문 순환을 정확히 예측하기 위해 수문 분야에서는 지면모형(Land Surface Model, LSM)을 많이 사용하고 있다. 지면모형은 지표면과 대기 사이의 상호작용을 모의하기 위해 개발되었고, 에너지, 수증기, 이산화탄소 등의 다양한 인자들의 교환에 대하여 해석하며, 토양수분, 유출량 등의 수자원 분야의 주요 인자들을 산출하여 수자원 관리에 적극적으로 활용되고 있다. 이에 본 연구에서는 National Center for Atmospheric Research(NCAR)에서 개발한 Community Land Model(CLM)을 사용하여 2001년부터 2016년까지 25km의 공간해상도로 동아시아 지역의 적설 모의를 평가하였다. CLM의 적설 모의 평가 인자는 Snow depth, Snow water equivalent의 2가지 인자를 대상으로 수행하였고, 모의 성능 평가를 위한 관측 자료로 NASA Aqua와 JAXA GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer(AMSR) 센서에서 제공하는 위성 관측 자료와 Defense Meteorological Satellite Program(DMSP) 위성의 Special Sensor Microwave/Imager(SSM/I) 센서와 Nimbus-7 위성의 Scanning Multichannel Microwave Radiometer(SMMR) 센서에서 제공하는 위성 관측 자료를 기반으로 지상 기상 관측소 자료와 조합하여 재생성한 European Space Agency Global Snow Monitoring for Climate Research (ESA GlobSnow)의 자료를 사용하였다. 그 결과 CLM의 적설 모의는 과대 추정하는 것을 알 수 있었으며, 본 연구의 결과는 동아시아 적설 모의 개선을 위해 자료 동화를 사용하는 후속 연구의 기초자료로 사용할 수 있다.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.138-141
• /
• 2006

In developing algorithms to retrieve the sea surface temperature (SST) and sea surface wind speed from the Advanced Microwave Scanning Radiometer (AMSR) aboard the AQUA and the Advanced Earth Observation Satellite-II (ADEOS-II), data from the SeaWinds aboard ADEOS-II were helpful. Since features of the ocean microwave emission (Tb) related with ocean wind are not well understood, in case of using only AMSR data, combination of AMSR and SeaWinds revealed pronounced features about the ocean Tb. Two results from combinations of the two sensors were shown in this paper. One result was obtained at wind speeds over about 6m/s, in which the ocean Tb varies with the air-sea temperature difference, even though the SeaWinds wind speed is fixed at the same values. The ocean Tb increases as the air-sea temperature difference becomes negative, i.e., the boundary condition becomes unstable. This result indicates that the air temperature should be included in AMSR SST algorithm. The second result was obtained from comparison of two wind speeds between AMSR and SeaWinds. There is a small difference of two wind speeds, which might be related with several mechanisms, such as evaporation and plankton.

• Journal of Korea Water Resources Association
• /
• v.49 no.5
• /
• pp.423-429
• /
• 2016

This study aims at assessing the quality of the Advanced Microwave Scanning Radiometer 2 (AMSR2) soil moisture products onboard GCOM-W1 satellite based on Land Parameter Retrieval Model (LPRM) soil moisture retrieval algorithm with field measurements in South Korea from March to September, 2014. Results of mean bias and root mean square error between AMSR2 LPRM soil moisture products (X-band) and ground measurements showed reasonable value of 0.03 and 0.16. Also, the maximum of the Pearson correlation coefficients was 0.67, which showed good agreement in terms of temporal variability with ground measurements. By comparing AMSR2 soil moisture with in-situ measurement according to the overpass time and band frequency, X-band products on the ascending time outperformed than those of C1-band and C2-band. Furthermore, this study offers an insight into the applicability of the AMSR2 soil moisture products for monitoring various natural disasters at a large scale such as drought and flood.