• Atmosphere
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• v.22 no.4
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• pp.437-447
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• 2012

There is still large uncertainty in estimating aerosol indirect effect despite ever-escalating efforts and virtually exponential increase in published studies concerning aerosol-cloud-precipitation interactions (CAPI). Probably most uncertainty comes from a wide range of observational scales and different platforms inappropriately used, and inherent complex chains of CAPI. Therefore, well-designed field campaigns and data analysis are required to address how to attribute aerosol signals along with clouds and precipitation to the microphysical effects of aerosols. Basically, aerosol influences cloud properties at the microphysical scales, "process scale", but observations are generally made of bulk properties over a various range of temporal and spatial resolutions, "analysis scale" (McComiskey & Feingold, 2012). In the most studies, measures made within the wide range of scales are erroneously treated as equivalent, probably resulting in a large uncertainty in associated with CAPI. Therefore, issues associated with the disparities of the observational resolution particular to CAPI are briefly discussed. In addition, the dependence of CAPI on the cloud environment such as stability and adiabaticity, and observation characteristics with varying situations of CAPI are also addressed together with observation framework optimally designed for the Korean situation. Properly designed and observation-based CAPI studies will likely continue to accumulate new evidences of CAPI, to further help understand its fundamental mechanism, and finally to develop improved parameterization for cloud-resolving models and large scale models.

• Korean Journal of Remote Sensing
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• v.6 no.2
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• pp.153-164
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• 1990

A statistical correlation between cloud thickness and brightness is shown by regression analysis using the least-square method. Cloud thicknesses are obtained from radiosonde observation. Brightness values are obtained from GMS visible channel. Regression analyses are preformed on both thickness data used in conjunction with brightness data for summer season. The results are shown by the regression curve relating thickness and brightness accounting for 79% of variance. And the relationship between thickness and precipitable water in the cloud layers is analyzed. The thickness shows a positive correlation with precipitable water in cloudy layers.

• Atmosphere
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• v.24 no.1
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• pp.39-48
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• 2014

This study provides a comparative analysis of cloud top heights observed by a Ka-band cloud radar and the Communication, Ocean and Meteorological Satellite (COMS) at Boseong National Center for Intensive Observation of severe weather (NCIO) from May 25, 2013 (1600 UTC) to May 27. The rainfall duration is defined as the period of rainfall from start to finish, and the no rainfall duration is defined as the period other than the rainfall duration. As a result of the comparative analysis, the cloud top heights observed by the cloud radar have been estimated to be lower than that observed by the COMS for the rainfall duration due to the signal attenuation caused by raindrops. The stronger rainfall intensity gets, the more the difference grows. On the other hand, the cloud top heights observed by the cloud radar have been relatively similar to that observed by the COMS for the no rainfall duration. In this case, the cloud radar can effectively detect cloud top heights within the range of its observation. The COMS indicates the cloud top heights lower than the actual ones due to the upper thin clouds under the influence of ground surface temperature. As a result, the cloud radar can be useful in detecting cloud top heights when there are no precipitation events. The COMS data can be used to correct the cloud top heights when the radar gets beyond the valid range of observation or there are precipitation events.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.716-723
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• 2019

It is crucial to understand the characteristics of cloud occurrence frequency for development of high precision guided missile using infrared imaging sensor. In this paper, we investigated the vertical structure of cloud for altitude using upper-air observation data. We find that cloud occurrence frequency is high at altitudes of 1.3 km and 9.5 km. Theses features have seasonal and temporal dependency. In the summer, cloud often occur more than average regardless of altitude. In the winter, low clouds occur frequently, and high clouds do not occur well. In temporal characteristics, clouds occur more frequently in daytime than in nighttime regardless of altitude. Many of clouds exist in single layer or double layers in the air. We also find that the 40 % of cloud occurrence frequency at high altitude when low clouds under altitude of 2 km cover entire sky.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• Journal of Astronomy and Space Sciences
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• v.33 no.2
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• pp.137-146
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• 2016

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

• Journal of the Korean earth science society
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• v.36 no.4
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• pp.330-340
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• 2015

For this study, we developed an algorithm to estimate the total amount of clouds using sky image data from the Skyviewer equipped with CCD camera. Total cloud amount is estimated by removing mask areas of RGB (Red Green Blue) images, classifying images according to frequency distribution of GBR (Green Blue Ratio), and extracting cloud pixels from them by deciding RBR (Red Blue Ratio) threshold. Total cloud amount is also estimated by validity checks after removing sunlight area from those classified cloud pixels. In order to verify the accuracy of the algorithm that estimates total cloud amount, the research analyzed Bias, RMSE, and correlation coefficient compared to records of total cloud amount earned by human observation from the Gangwon Regional Meteorological Administration, which is in the closest vicinity of the observation site. The cases are selected four daily data from 0800 LST to 1700 LST for each season. The results of analysis showed that the Bias in total cloud amount estimated by the Skyviewer was an average of -0.8 tenth, and the RMSE was 1.6 tenths, indicating the difference in total cloud amount within 2 tenths. Also, correlation coefficient was very high, marking an average of over 0.91 in all cases, despite the distance between the two observation sites (about 4 km).

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1027-1039
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• 2021

In this study, we investigated the optimal meteorological conditions for cloud seeding using aircraft over the Korean Peninsula. The weather conditions were analyzed using various data sources such as a weather chart, upper air observation, aircraft observation, and a numerical model for cloud seeding experiments conducted from 2018 to 2019 by the National Institute of Meteorological Sciences, Korea Meteorological Administration. Cloud seeding experiments were performed in the seasons of autumn (37.0%) and winter (40.7%) in the West Sea and Gangwon-do. Silver iodide (70.4%) and calcium chloride (29.6%) were used as cloud seeding materials for the experiments. The cloud seeding experiments used silver iodide in cold clouds. Aircraft observation revealed relatively low temperatures, low liquid water content, and strong wind speeds in clouds with a weak updraft. In warm clouds, the cloud seeding experiments used calcium chloride. Observations included relatively high temperatures, high liquid water content, and weak wind speeds in clouds with a weak updraft. Based upon these results, we determined the comprehensive meteorological conditions for cloud seeding experiments using aircraft over the Korean Peninsula. The understanding of optimal weather conditions for cloud seeding gained from this study provide information critical for performing successful cloud seeding and rain enhancement.

• Korean Journal of Remote Sensing
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• v.29 no.3
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• pp.293-306
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• 2013

Hydrometeor type and Drop Size Distribution (DSD) in cloud are the fundamental properties that may help explain the rain formation processes and determine the parameters of radar meteorology. This study presents a preliminary analysis of hydrometeor types and DSD data of cloud measured with a PARSIVEL (PARticle SIze and VELocity) optical disdrometer at the site of Cloud Physics Observation System (CPOS, $37^{\circ}41^{\prime}N$, $128^{\circ}45^{\prime}E$, 843 m from sea level) in Daegwallyeong mountainside of Korea. The method has been validated by comparing the observed rainfall rates with the computed ones from the fitted distribution, using the physical data such as DSD, terminal velocity, and rain intensity which were measured by a Micro-Rain Radar (MRR) and a PARSIVEL optical disdrometer. The analysis period started in three cases: on rainy days with light rain (15.5 mm), moderate rain (76 mm), and heavy rain (121 mm), from March to November 2007, respectively.

• Current Optics and Photonics
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• v.4 no.3
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• pp.174-185
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• 2020

Multiscattering occurs when a laser transmits into dense atmosphere targets (e.g. fogs, smoke or clouds), which can cause depolarization effects even though the scattering particles are spherical. In addition, multiscattering effects have additional information about microphysical properties of scatterers. Thus, multiscattering can be utilized to study the microphysical properties of the liquid water cloud. In this paper, a Monte Carlo method was used to simulate multi-scattering transmission properties of Lidar signals in the cloud. The results showed the slope of the degree of linear polarization (SLDLP) can be used to invert the extinction coefficient, and then the cloud effective size (CES) and the liquid water content (LWC) may be easily obtained by using the extinction coefficient and saturation of the degree of linear polarization (SADLP). Based on calculation results, a microphysical properties inversion method for a liquid cloud was presented. An innovative multiscattering polarization Lidar (MSPL) system was constructed to measure the LWC and CES of the liquid cloud, and a new method based on the polarization splitting ratio of the Polarization Beam Splitter (PBS) was developed to calibrate the polarization channels of MSPL. By analyzing the typical observation data of MSPL observation in the northern suburbs of Nanjing, China, the LWC and CES of the liquid water cloud were obtained. Comparisons between the results from the MSPL, MODIS and the Microwave radar data showed that, the microphysical properties of liquid cloud could be retrieved by combining our MSPL and the inversion method.