• Journal of information and communication convergence engineering
• /
• v.3 no.3
• /
• pp.146-151
• /
• 2005

This paper represents an attempt to bring together and analyses the measurement data measured by the Satellite Signal Monitoring Center in Korea and the Korea Meteorological Administration/Korea Meteorological Research Institute in close cooperation with this study team. This paper presents the signal characteristic of GEO satellite operating in frequency range 1 to 20GHz associated with Asian Sand Dust (the so-called Yellow Sand Dust). The downlink signal power (dBm) for L-, S-, C-, Ku-, and Ka-band frequencies from GEO satellites were measured in a clear weather and in Asian Sand Dust weather by the Satellite Signal Monitoring Center. The measured signal power(dBm) were compared to the total number concentration and size distribution of Sand Dust that were measured by the Korea Meteorological Administration/Korea Meteorological Research Institute and the possible correlation between these sets data were analyzed. The results demonstrate that the downlink signal level (dBm) of GEO satellite is attenuated by Asian Sand Dust. Hitherto, merger information has been reported as to the influence of sand dust on satellite communications operating in regions affected by sand dust.

• Korean Journal of Remote Sensing
• /
• v.16 no.2
• /
• pp.117-133
• /
• 2000

We studied the sea level variations at Kerguelen island in the South Indian Ocean with ARGOS data and meteorological data during about 1 year(May 1993~April 1994) through using filter, spectral analysis, coherency and phase, and found characteristics for the two oceanic signal levels(detided oceanic signal level, h$_{detided}$ and seasonal oceanic level, h$_{corr.ib}$). The forms of atmospheric pressure variations are good agreed to between ARGOS data and meteorological data in the observed periods. This Kerguelen area shows the inflow of an air temperature(gain of a radiant heat) into the sea water and the stagnation of high atmospheric pressure bands in summer, and the outflow of a sea water temperature(loss of sensible and latent heat) toward the atmosphere and the stagnation of low atmospheric pressure bands in winter. The seasonal difference of sea level between summer and winter is about 1.6cm. Both the detided oceanic signal level(h$_{detided}$) variation and the inverted barometer level(h$_{ib}$) variation have a strong correlation for T>1day period bands. The characteristics of h$_{detided}$ variation are not decided by the influence of any meteorological distributions (atmospheric pressure), but the influence of other factors(bottom water temperature) for T>2days periods bands. h$_{corr.ib}$ plays a very important role of sea level variation in the observed periods (especially T>about 180days period bands).

• Journal of Astronomy and Space Sciences
• /
• v.25 no.3
• /
• pp.267-282
• /
• 2008

The GNSS (Global Navigation Satellite System) signal is delayed by the neutral atmosphere at the troposphere, so that the delay is one of major error sources for GNSS precise positioning. The tropospheric delay is an integrated refractive index along the path of GNSS signal. The refractive index is empirically related to standard meteorological variables, such as pressure, temperature and water vapor partial pressure, therefore the tropospheric delay could be calculated from them. In this paper, it is presented how to generate meteorological data where observation cannot be performed. KASI(Korea Astronomy & Space Science Institute) has operated 9 GPS (Global Positioning System) permanent stations equipped with co-located MET3A, which is a meteorological sensor. Meteorological data are generated from observations of MET3A by Ordinary Kriging. To compensate a blank of observation data, simple models which consider periodic characteristics for meteorological data, are employed.

• Atmosphere
• /
• v.17 no.1
• /
• pp.27-44
• /
• 2007

The purpose of this study is to investigate predictability of the seasonal simulation by the METRI (Meteorological Research Institute) AGCM (Atmospheric General Circulation Model), which is a long-term prediction model for the METRI 3-month prediction system. We examine the performance skill of climate simulation and predictability by the analysis of variance of the METRI AGCM, focusing on the precipitation, 850 hPa temperature, and 500 hPa geopotential height. According to the result, the METRI AGCM shows systematic errors with seasonal march, and represents large errors over the equatorial region, compared to the observation. Also, the response of the METRI AGCM by the variation of the sea surface temperature is obvious for the wintertime and springtime. However, the METRI AGCM does not show the significant ENSO-related signal in autumn. In case of prediction over the east Asian region, errors between the prediction results and the observation are not quite large with the lead-time. However, in the predictability assessment using the analysis of variance method, longer lead-time makes the prediction better, and the predictability becomes better in the springtime.

• Atmosphere
• /
• v.16 no.3
• /
• pp.215-223
• /
• 2006

Among observational, local-environmental, and large-scale factors causing significant changes in climate records, the site relocations and the replacement of the instruments are well-known nonclimatic factors for the analysis of climatic trends, climatic variability, and for the detection of anthropogenic climate change such as heat-island effect and global warming. Using dataset that were contaminated by these nonclimatic factors can affect seriously the assessment of climatic trends and variability, and the detection of the climatic change signal. In this paper, the inhomogeneities, which have been caused by relocation of the observation site, in the climate data of Korea Meteorological Administration (KMA) were examined using two-phase regression model. The observations of pan evaporation and wind speed are more sensitive to site relocations than those of other meteorological elements, such as daily mean, maximum and minimum temperatures, with regardless to region.

• Current Optics and Photonics
• /
• v.2 no.1
• /
• pp.7-14
• /
• 2018

As a sophisticated detection technology, LIDAR has been widely employed to probe low-altitude windshear. Due to the drawbacks of the traditional ramp algorithm, the alarm accuracy of the LIDAR has not been satisfactory. Aiming at settling this matter, a novel method is proposed on the basis of improved signal smoothing and second windshear detection, which essentially acts as a combination of ramp algorithm and segmentation approach, involving the human factor as well as signal fluctuations. Experiments on the real and artificial signals verify our approach.

• Proceedings of the KSRS Conference
• /
• 2000.04a
• /
• pp.13-18
• /
• 2000

We observed sea level variation of the long time at Kerguelen island in the South Indian Ocean with ARGOS data and meteorological data during about 1 year(May 1993~March 1994) through using filter, spectral analysis, coherency and phase, and found characteristics for the two oceanic signal levels(detided oceanic signal level, h$_{detided}$ and seasonal oceanic level, h$_{corr.ib}$). The forms of variations are very well agreed to between ARGOS data and meteorological data for atmospheric pressure in the observed periods. The seasonal difference of sea level between Summer and Winter is about 1.6cm. Both the detided oceanic signal level(h$_{detided}$) variation and the inverted barometer level(h$_{ib}$) variation have a strong correlation for T>1day period bands. Characteristics of h$_{detided}$ variation are decided not by the influence of any meteorological distributions (pressure, winds, etc), but the influence of another factors(temperature, salinity, etc.) for T>2days periods bands. h$_{corr.ib}$ plays an very important role of sea level variation of the long time term(especially T>about 180days period bands).

• Atmosphere
• /
• v.34 no.1
• /
• pp.55-67
• /
• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.

• Journal of Satellite, Information and Communications
• /
• v.5 no.2
• /
• pp.19-24
• /
• 2010

The COMS (Communication Ocean Meteorological Satellite) is a hybrid geostationary satellite including communication, ocean, and meteorological payloads. The COMS includes the MODCS (Meteorological and Ocean Data Communication Subsystem) which provides transmitting the raw data collected by meteorological payload called MI (Meteorological Imager) and ocean payload named GOCI (Geostationary Ocean Color Imager) to the ground station, and relaying the meteorological data processed on the ground to the end-user stations. Here, for the L-band transmit antenna transmitting SD (Sensor Data) signal and the processed signal, from the system point of view, it is required to estimate the combined antenna gain when the L-band transmit is placed with MI and GOCI payloads on the earth panel of COMS. First of all, the L-band transmit horn is designed and analyzed for the requirements given, and then after placing it on the earth panel, the combined gain analysis is performed using three different analysis methods. It's shown that the obtained gain patterns are very similar among three different analysis methods. Finally the antenna gain degradation of less than 0.5 dB is estimated.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.377-380
• /
• 2006

본 논문에서는 통신해양기상위성의 지상국에 구축된 고 출력증폭기에 대한 특성 모델링 및 이에 따른 입력신호에 따른 출력 신호의 상호 간섭에 대한 결과가 정리되어 있다. 고 출력증폭기는 지상국에서 위성으로 신호를 전송할 때 필요한 장비로써 비선형 특성으로 인해 입력된 신호에 대한 다양한 하모닉 성분이 발생된다. 특히 통신해양 기상위성의 지상국의 경우에는 하나의 고 출력증폭기에 대해 두개의 서로 다른 주파수의 신호를 입력해야 하는 것을 고려해야 하기 때문에 이에 대한 영향은 사전에 반드시 분석되어야 한다. 본 논문에서는 고출력증폭기의 P1dB 특성곡선에 의해 특성 모델링을 수행한 결과 및 이러한 모델을 검증하기 위해 이미 정의된 두 신호에 대한 간섭의 양을 확인하였다. 특히 고 출력 증폭기의 전단에 속하는 상향 주파수 변환기의 특성을 고려한 신호를 사용하여 실제의 통신해양기상위성으로 데이터를 전송할 때의 결과를 얻는데 중점을 두었다. 그 결과 상호간의 간섭에 의해 발생되는 신호는 실제 보내고자 하는 신호의 대역과 매우 가깝게 있으며 그 크기는 보내고자 하는 신호의 특성에 따라 달라지는 것을 확인 할 수 있었다.