• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.319-322
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• 1999

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability. Especially, snow, soil moisture, surface temperature, vegetation and rain are the key parameters which should be observed in the global scale. In this paper, new algorithms for these land surface hydrological parameters have been developed by introducing frequency and polarization dependencies of these parameters in the microwave radiative-transfer equations. The algorithms were applied to the TRMM Microwave Radiometer. (TMI) and validated by using the ground data obtained in the Tibetan Plateau. The estimated snow, soil moisture, surface temperature, water content of vegetation and rain patterns corresponded reasonably to the observed ones.

• Proceedings of the KSRS Conference
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• v.1
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• pp.142-145
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• 2006

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the NOAA HWind wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

• Proceedings of the KSRS Conference
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• v.2
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• pp.1015-1018
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• 2006

The use of passive microwave data for estimating sea-ice thickness is limited by strong dependence of emissivity on near-surface brine. However, this particular characteristic becomes a basis for an algorithm to estimate thickness of thin sea-ice if a thickness-salinity-emissivity relationship is established. This study aims at developing an algorithm to estimate sea ice thickness on the basis of this relationship. In order to establish a thickness-salinity-emissivity relationship, we have conducted multi-platform synchronous observations in the Sea of Okhotsk. We note a positive relationship between thickness and brightness temperature. From observations, we also establish an empirical relationship between salinity and emissivity, thus between thickness and brightness temperature. The derived relationship is qualitatively similar to the one based on Hoekstra and Cappillino's formulation. Our results suggest that for thin sea-ice in the winter period there is potential to develop an algorithm to estimate sea-ice thickness.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.19-28
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• 2005

Passive microwave remote sensing technique have shown great potential for mon monitoring regional/global surface soil moisture. Given a single measurement at dual polarization/single frequency/single view angle, a strategic approach to artificially generating multiple microwave brightness temperatures is presented. And then the statistically generated microwave brightness temperature data are applied to the inverse algorithm, which mainly relies on a physically based microwave emission model and an advanced single-criterion multi-parameter optimization technique, to simultaneously retrieve soil moisture and vegetation characteristics. . The procedure is tested with dual polarized Tropical Rainfall Measurement Mission Microwave Imager (TRMM/TMI) over two different cover sites in Oklahoma and Beltsville field experimental data. The retrieval results are analyzed and show excellent performance.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.47-55
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• 2004

We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced by global data centers, to our knowledge, this is the first attempt to process 10-minute long direct-broadcast (DB) data. We found that the processor designed for a granule needs modification to apply to the DB data. The modification includes the correction to path number, the selection of land mask and the manipulation of dummy scans. Pixel-to-pixel comparison with a reference indicates the difference in brightness temperature of about 0.2 K rms and less than 0.05 K mean. The difference comes from the different length of data between 50-minute granule and about 10-minute DB data. In detail, due to the short data length, DB data do not always have correct cold sky mirror count. The DB processing system is automated to enable the near-real time generation of brightness temperatures within 5 minutes after downlink. Through this work, we would be able to enhance the use of AMSR-E data, thus serving the objective of direct-broadcast.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.9
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• pp.900-907
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• 2013

The development processes of a L-band microwave radiometer for remote sensing of water surface salinity are described in this paper. Achieving the development aim of the measurement accuracy within 2 psu for water surface salinity of 0~40 psu, the requirements and specifications of the microwave radiometer and its receiver are drawn. The receiver with high gain, high sensitivity is designed and implemented to satisfy these requirements and specifications. The receiver has the bandwidth of 45 MHz, the system gain of 47 dB and the sensitivity of 0.41 K at 1,390 MHz. The effectiveness of the developed L-band microwave radiometer for remote sensing of water surface salinity is demonstrated experimentally. The results show the microwave radiometer can detect water surface salinity for 10~28 psu within the accuracy of 1.4 psu.

• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.53-59
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• 2003

The passive microwave remote sensing has progressed considerably in recent years Important earth surface parameters are detected and monitored by airborne and space born radiometers. However the spatial resolution of real aperture measurements is constrained by the antenna aperture size available on orbiting platforms and on the ground. The inverse problem technique is researched in order to improve the spatial resolution of microwave scanning radiometer. We solve a two-dimensional (surface) temperature-imaging problem with a major intention to develop high-resolution methods. In this paper, the scenario for estimation of both radiometer point spread function (PSF) and target configuration is explained. The PSF of the radiometer is assumed to be unknown and estimated from the observations. The configuration and brightness temperature of targets are also estimated. To do this, we deal with the parametric modeling of observation scenario. The performance of developed algorithms is illustrated on two-dimensional experimental data obtained by the water vapor radiometer.

• Proceedings of the KSRS Conference
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• v.1
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• pp.150-152
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• 2006

The DISCOVER Project (${\underline{D}}istributed$ ${\underline{I}}nformation$ ${\underline{S}}ervices$ for ${\underline{C}}limate$ and ${\underline{O}}cean$ products and ${\underline{V}}isualizations$ for ${\underline{E}}arth$ ${\underline{R}}esearch$) is a NASA funded Earth Science REASoN project that strives to provide highly accurate, carefully calibrated, long-term climate data records and near-real-time ocean products suitable for the most demanding Earth research applications via easy-to-use display and data access tools. A key element of DISCOVER is the merging of data from the multiple sensors on multiple platforms into geophysical data sets consistent in both time and space. The project is a follow-on to the SSM/I Pathfinder and Passive Microwave ESIP projects which pioneered the simultaneous retrieval of sea surface temperature, surface wind speed, columnar water vapor, cloud liquid water content, and rain rate from SSM/I and TMI observations. The ocean products available through DISCOVER are derived from multi-sensor observations combined into daily products and a consistent multi-decadal climate time series. The DISCOVER team has a strong track record in identifying and removing unexpected sources of systematic error in radiometric measurements, including misspecification of SSM/I pointing geometry, the slightly emissive TMI antenna, and problems with the hot calibration source on AMSR-E. This in-depth experience with inter-calibration is absolutely essential for achieving our objective of merging multi-sensor observations into consistent data sets. Extreme care in satellite inter-calibration and commonality of geophysical algorithms is applied to all sensors. This presentation will introduce the DISCOVER products currently available from the web site, http://www.discover-earth.org and provide examples of the scientific application of both the diurnally corrected optimally interpolated global sea surface temperature product and the 4x-daily global microwave water vapor product.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.9
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• pp.1107-1115
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• 2012

This paper presents the development processes of a microwave radiometer for remote sensing of water surface temperature. Achieving the measurement accuracy within $2^{\circ}C$ for water surface temperature of $5{\sim}30^{\circ}C$, the requirements and specifications of the microwave radiometer and its receiver are drawn. The receiver with high gain, high sensitivity is designed and implemented. The receiver has the bandwidth of 50 MHz, the system gain of 45.2 dB and the sensitivity of 0.56K at 5.02 GHz. The effectiveness of the developed microwave radiometer in the measurement of water surface temperature is demonstrated experimentally. The results show the microwave radiometer can detect water surface temperature for $7.5{\sim}18^{\circ}C$ within the accuracy of $0.45^{\circ}C$.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.378-381
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• 2007

Analyses of Tropical Rainfall Measuring Mission (TRMM) microwave radiometer (TMI) and precipitation radar (PR) data show that the rainfall inhomogeneity, represented by the coefficient of variation, decreases as rain rate increases at the low resolution (the footprint size of TMI 10 GHz channel). The rainfall inhomogeneity, however, is relatively constant for all rain rates at the high resolution (the footprint size of TMI 37 GHz channel). Consequently, radiometric signatures at lower spatial resolutions are characterized by larger dynamic range and smaller variability than those at higher spatial resolution. Based on the observed characteristics, this study develops a low-resolution (${\sim}40{\times}40$ km) rainfall retrieval algorithm utilizing realistic rainfall distributions in the a-priori databases. The purpose of the low-resolution rainfall algorithm is to make more reliable climatological rainfalls from various microwave sensors, including low-resolution radiometers.