• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.9-17
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• 2003

Typhoon RUSA, which caused serious damage was passed over in Korea peninsula during 30 August to 1 September, 2002. We estimated tropospheric wet delay using GPS data and meteorological data during this period. Integrated Water Vapor(IWV) gives the total amount of water vapor from tropospheric wet delay and Precipitable Water Vapor(PWV) is calculated the IWV scaled by the density of water. We obtained GPS PWV at 13th GPS permanent stations(Seoul, Wonju. Seosan, Sangju, Junju, Cheongju, Taegu, Wuljin, Jinju, Daejeon, Mokpo, Sokcho, Jeju). We retrieve GPS data hourly and use Gipsy-Oasis II software and we compare PWV and precipitation. GPS observed PWV time series demonstrate that PWV is, in general, high before and during the occurrence of the typhoon RUSA, and low after the typhoon RUSA. GPS PWV peak time at each station is related to the progress of a typhoon RUSA. We got very near result as we compare GMS Satellite image with tomograph using GPS PWV and we could present practical use possibility by numerical model for weather forecast.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.2
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• pp.215-222
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• 2002

As the GPS signals propagate from the GPS satellites to the receivers on the ground, they are delayed by the atmosphere. The tropospheric delay consists of two components. The hydrostatic (or "dry") component that is dependent on the dry air gasses in the atmosphere and accounts for approximately 90% of the delay. And the "wet" component that depends on the moisture content of the atmosphere and accounts for the remaining effect of the delay. The Zenith Hydrostatic Delay (ZHD) can be calculated from the local surface pressure. The Total Zenith Delay (TZD) will be estimated and the wet component extracted later. Integrated water Vapor (IWV) gives the total amount of water vapor that a signal from the zenith direction would encounter. Precipitable Water Vapor (PWV) is the IWV scaled by the density of water. The quality of this PWV has been verified by comparison with radiosonde data(at Osan). We processed data for JULY 2 and JULY 14, 1999 from four stations(Cheju, Kwangju, Suwon, Daegu). We found the coincidence between PWV of the estimations using GPS and PWV of pressing the radiosonde data. The average of the difference between PWV using GPS and PWV using radiosonde was 3.77 mm(Std. ＝ $\pm$0.013 mm) and 2.70 mm(Std. = $\pm$0.0011 mm) at Suwon & Kwangju.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.535-544
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• 2009

Signals from the Global Positioning System(GPS) satellite are used to retrieve the integrated amount of water vapor or the precipitable water vapor(PWV) along the path between a transmitting satellite and ground-based receiver. In order to retrieve the PWV from GPS signal delay in the troposphere, the actual zenith wet delay, which can be derived by extracting the zenith total delay and subtracting the actual zenith hydrostatic delay computed using surface pressure observing, will be needed. Since it has been not co-located between GPS permanent station and automated weather station, the air-pressure on the mean sea level has been used to determine the actual zenith hydrostatic delay. The directly use of this air-pressure has been caused the dilution of precision on GPS PWV retrieval. In this study, Korean reverse sea level correction method of air-pressure was suggested for the improving of GPS PWV retrieval capability and the accuracy of water vapor estimated by GPS was evaluated through a comparison with radiosonde PWV.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1591-1604
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• 2023

In ocean color remote sensing, atmospheric correction is a vital process for ensuring the accuracy and reliability of ocean color products. Furthermore, in recent years, the remote sensing community has intensified its requirements for understanding errors in satellite data. Accordingly, research is currently addressing errors in remote sensing reflectance (R_rs) resulting from inaccuracies in meteorological variables (total ozone, pressure, wind field, and total precipitable water) used as auxiliary data for atmospheric correction. However, there has been no investigation into the error in R_rs caused by the variability of the water vapor profile, despite it being a recognized error source. In this study, we used the Second Simulation of a Satellite Signal Vector version 2.1 simulation to compute errors in water vapor transmittance arising from variations in the water vapor profile within the GOCI-II observation area. Subsequently, we conducted an analysis of the associated errors in ocean color products. The observed water vapor profile not only exhibited a complex shape but also showed significant variations near the surface, leading to differences of up to 0.007 compared to the US standard 62 water vapor profile used in the GOCI-II atmospheric correction. The resulting variation in water vapor transmittance led to a difference in aerosol reflectance estimation, consequently introducing errors in R_rs across all GOCI-II bands. However, the error of R_rs in the 412-555 nm due to the difference in the water vapor profile band was found to be below 2%, which is lower than the required accuracy. Also, similar errors were shown in other ocean color products such as chlorophyll-a concentration, colored dissolved organic matter, and total suspended matter concentration. The results of this study indicate that the variability in water vapor profiles has minimal impact on the accuracy of atmospheric correction and ocean color products. Therefore, improving the accuracy of the input data related to the water vapor column concentration is even more critical for enhancing the accuracy of ocean color products in terms of water vapor absorption correction.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.264-277
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• 2021

This study analyzed the relationship between the total precipitable water vapor in the atmosphere and the moving speed of recent typhoons. This study used ground observation data of air temperature, precipitation, and wind speed from the Korea Meteorological Administration (KMA) as well as total rainfall data and Red-Green-Blue (RGB) composite images from the U.S. Meteorological and Satellite Research Institute and the KMA's Cheollian Satellite 2A (GEO-KOMPSAT-2A). Using the typhoon location and moving speed data provided by the KMA, we compared the moving speeds of typhoon Bavi, Maysak, and Haishen from 2020, typhoon Tapah from 2019, and typhoon Kong-rey from 2018 with the average typhoon speed by latitude. Tapah and Kong-rey moved at average speed with changing latitude, while Bavi and Maysak showed a significant decrease in moving speed between approximately 25°N and 30°N. This is because a water vapor band in the atmosphere in front of these two typhoons induced frontogenesis and prevented their movement. In other words, when the water vapor band generated by the low-level jet causes frontogenesis in front of the moving typhoon, the high pressure area located between the site of frontogenesis and the typhoon develops further, inducing as a blocking effect. Together with the tropical night phenomenon, this slows the typhoon. Bavi and Maysak were accompanied by copious atmospheric water vapor; consequently, a water vapor band along the low-level jet induced frontogenesis. Then, the downdraft of the high pressure between the frontogenesis and the typhoon caused the tropical night phenomenon. Finally, strong winds and heavy rains occurred in succession once the typhoon landed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.53-62
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• 2015

The water vapor including latent heat is the important component in an atmospheric circulation and in a monitoring of the Earth's climate changes, as well as in the weather forecast improvement. In this study, to establish the Algerian weighted mean temperature model, a linear regression method had been developed under 5 radiosonde observations for a total 24,694 profiles from 2004 to 2013. An weighted mean temperature is a key parameter in the processing of PWV from GNSS tropospheric delays. The result from the study has expected to provide an useful model to demonstrate the realization and utility of using the ground-based GNSS meteorology technique that will bring improvements in weather forecasting, climate monitoring in Algeria.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.331-337
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• 2016

Water vapor is main absorption factor of outgoing longwave radiation. So, it is essential to monitoring the changes in the amount of water vapor and to understanding the causes of such changes. In this study, we monitor temporal variability of Total Precipitable Water (TPW) which observed by satellite. Among climate variables, precipitation play an important part to analyze temporal variability of water vapor because it is produced by water vapor. And El $Ni{\tilde{n}}o$ is one of climate variables which appear regularly in comparison with the others. Through them, we analyze relationship between temporal variability of TPW and climate variable. In this study, we analyzed long-term change of TPW from Moderate-Resolution Imaging Spectroadiometer (MODIS) data and change of precipitation in middle area of Korea peninsula quantitatively. After these analysis, we compared relation of TPW and precipitation with El $Ni{\tilde{n}}o$. The aim of study is to research El $Ni{\tilde{n}}o$ has an impact on TPW and precipitation change in middle area of Korea peninsula. First of all, we calculated TPW and precipitation from time series analysis quantitatively, and anomaly analysis is performed to analyze their correlation. As a result, TPW and precipitation has correlation mostly but the part had inverse correlation was found. This was compared with El $Ni{\tilde{n}}o$ of anomaly results. As a result, TPW and precipitation had inverse correlation after El $Ni{\tilde{n}}o$ occurred. It was found that El $Ni{\tilde{n}}o$ have a decisive effect on change of TPW and precipitation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.233-242
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• 2019

ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.195-200
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• 2016

Water vapor leading various scale of atmospheric circulation and accounting for about 60% of the naturally occurring warming effect is important climate variables. Using the Total Precipitable Water (TPW) from Moderate Resolution Imaging Spectroradiometer (MODIS) operating on both Terra and Aqua, we study long-term Variation of TPW and define relationship among TPW and climatic parameters such as temperature and precipitation to quantitatively demonstrate the impact on climate change over East Asia focusing on the Korea peninsula. In this study, we used linear regression analysis to detect the correlation of TPW and temperature/precipitation and harmonic analysis to analyze changeable aspects of periodic characteristics. A result of analysis using linear regression analysis between TPW and climate elements, TPW shows a high determination coefficient ($R^2$) with temperature and precipitation (determination coefficient between TPW and temperature: 0.94, determination coefficient between TPW anomaly and temperature anomaly: 0.8, determination coefficient between TPW and precipitation: 0.73, determination coefficient between TPW anomaly and precipitation anomaly: 0.69). A result of harmonic analysis of TPW and precipitation of two-year to five-year cycle, amplitude contribution ratio of 3.5-year cycle are much higher and two phases are similar in 3.5-year cycle.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.309-324
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• 2008

In this study the retrieval algorithms have been developed to retrieve total precipitable water (TPW) from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) infrared measurements using a physical iterative retrieval method and a split-window technique over East Asia. Retrieved results from these algorithms were validated against Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) over ocean and radiosonde observation over land and were analyzed for investigating the key factors affecting the accuracy of results and physical processes of retrieval methods. Atmospheric profiles from Regional Data Assimilation and Prediction System (RDAPS), which produces analysis and prediction field of atmospheric variables over East Asia, were used as first-guess profiles for the physical retrieval algorithm. We used RTTOV-7 radiative transfer model to calculate the upwelling radiance at the top of the atmosphere. For the split-window technique, regression coefficients were obtained by relating the calculated brightness temperature to the paired radiosonde-estimated TPW. Physically retrieved TPWs were validated against SSM/I and radiosonde observations for 14 cases in August and December 2004 and results showed that the physical method improves the accuracy of TPW with smaller bias in comparison to TPWs of RDAPS data, MODIS products, and TPWs from split-window technique. Although physical iterative retrieval can reduce the bias of first-guess profiles and bring in more accurate TPWs, the retrieved results show the dependency upon initial guess fields. It is thought that the dependency is due to the fact that the water vapor absorption channels used in this study may not reflect moisture features in particular near surface.