• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.149-157
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• 2008

If we use the microwave of SAR, we can observe ocean in spite of severe weather or night time. The sea surface image of SAR has numerous information about atmospheric phenomena related to surface wind field. The extracted wind information from SAR can be used diversely. In order to extract sea wind speed from SAR image, a generated wind direction from SAR and sigma nought should be input into wind model. Therefore, wind speed can be obtained by input wind direction into CMOD5 Model. Azimuth angle using CMOD5 Model is generated by added $90^{\circ}$ to Look angle which is extracted from SAR data file. A gained wind direction spectrum from SAR image has $180^{\circ}$ ambiguity because of 2D-FFT. This ambiguity should decide to use the location of land, wind direction in field or the result of numerical model. Consequently, wind direction using 2D-FFT is $3^{\circ}{\sim}7^{\circ}$ differences with actual surveying data. Wind speed by CMOD5 model is similar to actual surveying data as below 2m/s.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.57-73
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• 1997

This paper is related to the correction of radiometric distortions induced by topographic relief. RADARSAT SAR image data were obtained over the mountainous area near southern part of Seoul. Initially, the SAR data was geometrically corrected and registered to plane rectangular coordinates so that each pixel of the SAR image has known topographic parameters. The topographic parameters (slope and aspect) at each pixel position were calculated from the digital elevation model (DEM) data having a comparable spatial resolution with the SAR data. Local incidence angle between the incoming microwave and the surface normal to terrain slope was selected as a primary geometric factor to analyze and to correct the radiometric distortions. Using digital maps of forest stands, several fields of rather homogeneous forest stands were delineated over the SAR image. Once the effects of local incidence angle on the radar backscatter were defined, the radiometric correction was performed by an empirical fuction that was derived from the relationship between the geometric parameters and mean radar backscatter. The correction effects were examined by ground truth data.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.80-80
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• 2016

GPS로 대표되는 위성항법시스템(GNSS : Global Navigation Satellite System)은 지구 주위를 돌면서 연속적으로 항법신호를 보내고 있다. 그 중 지구표면으로부터 반사되는 항법신호를 수신하고 해석함으로써 지구표면에 관한 정보를 취득할 수가 있다. GPS로 대표되는 항법신호는 L밴드를 사용하기 때문에 토양수분의 변화 등에 대한 반사강도의 감도가 비교적 높다고 알려져 있으며, 토양수분 측정 등에 사용할 수 있다. 뿐만 아니라 경량화, 소형화하기 쉬운 점, 능동적 마이크로웨이브 리모트센싱시스템(Active Microwave Remote Sensing System)과 달리 스스로 신호를 발사하지 않기 때문에 관측의 스텔스성(Stealth)dl 뛰어난 점 등의 장점을 가지고 있다. 또한 향후 10년 이내에 준천정위성(QZSS), Galileo, COMPAS, IRNSS 등 많은 위성항법시스템이 본격 운용되어 GPS와 함께 120기 정도의 항법위성이 항법신호를 송신할 예정이므로 이용 가능성은 크게 늘어날 것으로 기대된다.한편, 항법위성을 이용한 바이스테이틱 리모트센싱은 반사파의 강도가 상당히 미약하기 때문에 정량적 계측모델의 구축은 미미한 상태이다. 즉, 지상 타워에서의 관측, 항공기에서의 관측, 소형 위성에서의 관측 등이 수행되고 있으나, 타워관측과 같이 지상의 거의 동일한 장소를 계속적으로 관측하는 경우를 제외한 기존의 연구에서는 토지의 피복상황이나 토양수분 등의 상관관계를 제시하는 수준으로써 정량적인 계측방법은 아직 확립되어 있지 않다. 이러한 관점에서 본 연구에서는 GPS위성으로부터의 항법신호를 이용하여 지구표면에 관한 정보를 얻는 바이스테이틱 리모트센싱(Bi-static Remote Sensing) 기술을 바탕으로 육지면과 해면의 판별에 신호특성이 어떻게 유효한가를 실험적으로 밝혔다. 이러한 기술은 토양수분 측정 등 수자 원인자를 추출하는데 유용할 뿐만 아니라 수면의 고도 측정, 해상풍 산출 등에도 응용 가능하다.

• Atmosphere
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• v.29 no.3
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• pp.241-255
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• 2019

Bias correction (BC) and quality control (QC) are essential steps for the proper use of satellite observations in data assimilation (DA) system. BC should be calculated over quality controlled observation. And also QC should be performed for bias corrected observation. In the Korea Institute of Atmospheric Prediction Systems (KIAPS) Package for Observation Processing (KPOP), we adopted an adaptive BC method that calculates the BC coefficients with background at the analysis time rather than using static BC coefficients. In this study, we have developed an iterative QC-BC method for Advanced Microwave Sounding Unit-A (AMSU-A) to reduce the negative feedback from the interaction between BC and QC. The new iterative QC-BC is evaluated in the KIAPS 3-dimensional variational (3DVAR) DA cycle for January 2016. The iterative QC-BC method for AMSU-A shows globally significant benefits for error reduction of the temperature. The positive impacts for the temperature were predominant at latitudes of $30^{\circ}{\sim}90^{\circ}$ of both hemispheres. Moreover, the background warm bias across the troposphere is decreased. Even though AMSU-A is mainly designed for atmospheric temperature sounding, the improvement of AMSU-A pre-processing module has a positive impact on the wind component over latitudes of $30^{\circ}S$ near upper-troposphere, respectively. Consequently, the 3-day-forecast-accuracy is improved about 1% for temperature and zonal wind in the troposphere.

• Atmosphere
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• v.32 no.4
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• pp.395-409
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• 2022

A new soil moisture initialization scheme is applied to the Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6). It is designed to ingest the microwave soil moisture retrievals from Soil Moisture Active Passive (SMAP) radiometer using the Local Ensemble Transform Kalman Filter (LETKF). In this technical note, we describe the procedure of the newly-adopted initialization scheme, the change of soil moisture states by assimilation, and the forecast skill differences for the surface temperature and precipitation by GloSea6 simulation from two preliminary experiments. Based on a 4-year analysis experiment, the soil moisture from the land-surface model of current operational GloSea6 is found to be drier generally comparing to SMAP observation. LETKF data assimilation shows a tendency toward being wet globally, especially in arid area such as deserts and Tibetan Plateau. Also, it increases soil moisture analysis increments in most soil levels of wetness in land than current operation. The other experiment of GloSea6 forecast with application of the new initialization system for the heat wave case in 2020 summer shows that the memory of soil moisture anomalies obtained by the new initialization system is persistent throughout the entire forecast period of three months. However, averaged forecast improvements are not substantial and mixed over Eurasia during the period of forecast: forecast skill for the precipitation improved slightly but for the surface air temperature rather degraded. Our preliminary results suggest that additional elaborate developments in the soil moisture initialization are still required to improve overall forecast skills.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Journal of the Korean earth science society
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• v.21 no.5
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• pp.503-524
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• 2000

Intercomparisons between four kinds of data have been done to estimate the accuracy of satellite observations and model reanalysis for middle and lower tropospheric thermal state over regional oceans. The data include the Microwave Sounding Units (MSU) Channel 2 (Ch2) brightness temperatures of NOAA satellites and the vertically weighted corresponding temperature of ECMWF GCM (1980-93). The satellite data for midtropospheric temperatures are MSU2 (1980-98) in nadir direction and SC2 (1980-97) in multiple scans, and for lower tropospheric temperature SC2R (1980-97). MSU2 was derived in this study while SC2 and SC2R were described in Spencer and Christy (1992a, 1992b). Temporal correlations between the above data were high (r${\ge}$0.90) in the middle and high latitudes, but low(r${\sim}$0.65) over the low latitude and more convective regions. Their values with SC2R which included the noises due to hydrometeors and surface emission were conspicuously low. The reanalysis shows higher correlation with SC2 than with MSU2 partially because of the hydrometeors screening. SC2R in monthly climatological anomalies was more sensitive to surface thermal condition in northern hemisphere than MSU2 or SC2. The first EOF mode for the monthly mean data of MSU and ECMWF shows annual cycle over most regions except the tropics. The mode in MSU2 over the Pacific suggests the east-west dipole due to the Walker circulation, but this tendency is not clear in other data. In the first and second modes for the Ch2 anomalies over most regions, the MSU and ECMWF data commonly indicate interannual variability due to El Ni${\tilde{n}$o and La Ni${\tilde{n}$a. The substantial disagreement between observations and model reanalysis occurs over the equatorial upwelling region of the western Pacific, suggesting uncertainties in the model parameterization of atmosphere-ocean interaction.

• Journal of the Korean earth science society
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• v.21 no.5
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• pp.525-540
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• 2000

Global temperature trends of middle and upper tropospheres have been investigated using the data of satellite-observed Microwave Sounding Unit (MSU) channels 2-3(Ch2, Ch3) during the period of 1980-97 and three GCM (NCEP, ECMWF, GEOS) reanalyses during 1981-93. The global, hemispheric and tropical anomalies, computed from the data during the common period, have been intercompared in the following regions; ocean, land, and both ocean and land. The correlation with MSU in midtropospheric temperatures is the best (r=0.81${\sim}$0.95) in ECMWF, particularly over the tropics. The correlations in upper troposphere are lower (r=0.06${\sim}$0.34) due to poor quality of MSU Ch3 data consistent with previous result. The midtropospheric trends during 1981-93, obtained from MSU and three GCMs, show the global warming of 0.01${\sim}$0.18K decade$^{-1}$. The warmest years have been 1987 and 1991 in El Ni${\tilde{n}$o while the coolest 1993 and 1994 in La Ni${\tilde{n}$a. The warming (0.12${\sim}$0.13K decade$^{-1}$) in MSU over global ocean is similar to that over global land. The largest discrepancy in upper troposphere between MSU and GCMs has been found in the transition period (1984. 12-1985. 1) from NOAA 9 to 10, because of a sizable error in the MSU Ch3. The midtropospheric trends near the Korean peninsula during 1981-93 are almost negligible(-0.02K decade$^{-1}$) in MSU, but indicate significant warming (0.25-0.43K decade$^{-1}$) in GCMs. The trends are crosschecked and discussed with other two independent MSU data of Spencer and Christy (1992a, 1992b).

• Journal of the Korean earth science society
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• v.21 no.2
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• pp.137-158
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• 2000

The correlation and Empirical Orthogonal Function (EOF) analyses over the globe have been applied to intercompare lower-stratospheric (${\sim}$70hPa) temperature obtained from satellite data and two model reanalyses. The data is the19 years (1980-98) Microwave Sounding Unit (MSU) channel 4 (Ch4) brightness temperature, and the reanalyses are GCM (NCEP, 1980-97; GEOS, 1981-94) outputs. In MSU monthly climatological anomaly, the temperature substantially decreases by ${\sim}$21k in winter over southern polar regions, and its annual cycle over tropics is weak. In October the temperature and total ozone over the area south of Australia remarkably increase together. High correlations (r${\ge}$0.95) between MSU and reanalyses occur in most global areas, but they are lower (r${\sim}$O.75) over the 20-3ON latitudes, northern America and southern Andes mountains. The first mode of MSU and reanalyses for monthly-mean Ch4 temperature shows annual cycle, and the lower-stratospheric warming due to volcanic eruptions. The analyses near the Korean peninsula show that lower-stratospheric temperature, out of phase with that for troposphere, increases in winter and decreases in summer. In the first mode for anomaly over the tropical Pacific, MSU and reanalyses indicate lower-stratospheric warming due to volcanic eruptions. In the second mode MSU and GEOS present Quasi-Biennial Oscillation (QBO) while NCEP, El Ni${\tilde{n}}$o. Volcanic eruption and QBO have more impact on lower-stratospheric thermal state than El Ni${\tilde{n}}$o. The EOF over the tropical Atlantic is similar to that over the Pacific, except a negligible effect of El Ni${\tilde{n}}$o. This study suggests that intercomparison of satellite data with model reanalyses may estimate relative accuracy of both data.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.