• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.747-755
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• 1999

Effects of precipitation and cloud cover on high ozone days are examined by investigating the precipitation and average cloud cover before the ozone peak time within a day. High ozone days above 100 ppb in the Greater Seoul Area(GSA) for the ozone season from May to September are chosen for the analyses in terms of the surface meteorological data during 1990~1997. The result shows that the effect of precipitation on the rise of ozone concentration is definitely negative so that ozone concentration could not rise above 100ppb immediately after precipitation. But, the effect of cloud cover is associated with the variations of other meteorological parameters. The number of high ozone days with "zero" cloud cover is rather less than that with cloud cover of 1 to 4 since temperature is usually lower in "zero" cloud cover days. Furthermore, ozone concentration can rise above 100ppb even with full cloud cover when the wind is weak and the temperature is high.temperature is high.

• Journal of the Korean Solar Energy Society
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• v.30 no.3
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• pp.1-9
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• 2010

Since the horizontal global radiation and cloud cover are a main factor for designing any solar photovoltaic system, it is necessary to evaluate its characteristics all over the country. The work presented here are the investigation of horizontal global radiation and cloud cover in Korea. The data utilized in the investigation consist of horizontal global radiation and cloud cover collected for 27 years(1982. 12~2008. 12) at measuring stations across the country. The analysis shows that the annual-average daily horizontal global radiation is $3.61\;kWh/m^2$ and the annual-average daily cloud cover is 5.1 in Korea. We also constructed the contour map of cloud cover in Korea by interpolating actually measured data across the country.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.124-129
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• 2011

Since the horizontal global radiation and cloud cover are a main factor for designing any solar energy system, it is necessary to evaluate its characteristics all over the country. The work presented here are the investigation of horizontal global radiation and cloud cover in Korea. The data utilized in the investigation consist of horizontal global radiation and cloud cover collected for 27 years(1982.12~2008.12) at measuring stations across the country. The analysis shows that the annual-average daily horizontal global radiation is $3.61kWh/m^2$ and the annual-average daily cloud cover is 5.1 in Korea. We also constructed the contour map of cloud cover in Korea by interpolating actually measured data across the country.

• Journal of Environmental Science International
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• v.4 no.1
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• pp.13-18
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• 1995

In order to examine the effect on the insolation of cloud cover, we analyzed the data of the insolation, cloud cover and surface air pressure in Pusan during the period of 1991. 10 - 1993.1. At first, we investigate the atmospheric transmissivity A(t) using the Beer's law at clear skies. The atmospheric transmissivity is characterized by cold season high and warn season low. From this atmospheric transmissivity, the empirical formula that shows the variation of the insolation due to the cloud cover is obtained. The result formula is I : l0 A(tn)·( 0.7-0.05×m ). 1 is the insolation that reaches the surface when cloud cover is m and to is solar constant. Although the result is some rough it seems meaningful that the estimation of insolation can be made only from the routine data.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.507-519
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• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• Journal of Institute of Convergence Technology
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• v.6 no.2
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• pp.29-33
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• 2016

Recently, the authors of this paper proposed newly the correlation model to calculate the horizontal global solar radiation in Korea based the Zhang-Huang (ZH) model proposed in 2002 for China. Previous study was pronounced the correlation with a new term of the duration of sunshine proved as being closely related with the hourly solar radiation in Korea into ZH model. And then another modified correlation for the regions without measuring cloud cover was proposed and evaluated the accuracy and validity for those regions. So, this study was performed to propose modified correlation to calculate the horizontal global solar irradiance of non-measuring cloud-cover regions. Finally, this study proposed the new correlation that could well predict hourly and daily total solar radiation for all regions, various seasons, and various weather conditions including overcast and clear, with higher accuracy and lower error than other models proposed ever before in Korea for non-measuring cloud-cover regions.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.26-29
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• 2005

In order to compute cloud coverage statistics over Asian region, an operational scheme for masking cloud-contaminated pixels in Advanced Very High Resolution Radiometer (AVHRR) daytime data was developed, evaluated and presented. Dynamic thresholding was used with channell, 2 and 3 to automatically create a cloud mask for a single image. Then the IO-day cloud coverage imagery was generated over the whole Asian region along with cloud-free composite imagery. Finally the monthly based statistics were computed based on the derived cloud coverage imagery in terms of land cover and country. As a result, it was found that 20-day is required to acquire the cloud free data over the whole Asia using NOAA AVHRR. The to-day cloud coverage and cloud-free composite imagery derived in this research is available via the web-site http://webpanda.iis.u-tokyo.ac.jp/CloudCover/.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.387-392
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests were performed to see how cloud cover and sun glint affect the priority determined by pigment concentration distributions, and consequently to minimize their seasonal effects upon the data collection planning.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.5
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• pp.296-303
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• 2010

An experimental study was carried out to investigate performance characteristics of the hybrid solar system during spring season. The system operating condition, each load, and heat pump performance were analyzed with the cloud cover. As a results, the collector heat, solar fraction, and hot water load were decreased with a rise of the cloud. The heating load was considerably effected by the ambient temperature regardless of the cloud cover. Besides, the temperature of hot water increased with the solar radiation. The COP of the heat pump was significantly influenced by the ambient temperature, that was 2.09~2.46 for gray day and 1.94~2.71 for fair day, respectively.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.259-276
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• 2011

Short-term land cover changes, such as forest fire scar and crop harvesting, can be detected by high temporal resolution satellite imagery like MODIS and AVHRR. Because these optical satellite images are often obscured by clouds, the static cloud-free composite methods (maximum NDVI, minblue, minVZA, etc.) has been used based on non-overlapping composite period (8-day, 16-day, or a month). Due to relatively long time lag between successive images, these methods are not suitable for observing short-term land cover changes in near-real time. In this study, we suggested a new dynamic cloud-free composite algorithm that uses cut-and-patch method of cloud-masked daily MODIS data using MOD35 products. Because this dynamic composite algorithm generates daily cloud-free MODIS images with the most recent information, it can be used to monitor short-term land cover changes in near-real time. The dynamic composite algorithm also provides information on the date of each pixel used in compositing, thereby makes accurately identify the date of short-term event.