• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.92-97
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• 2001

The intra-annual and interannual variations of total, high, middle, low clouds, and cloud forcing net solar radiation flux, cloud forcing net long-wave radiation flux, and SSTs over the tropical oceans are investigated with the use of ISCP D2, NCEP/NCAR Reanalysis for January 1983-December 1993. The intra-annual variation of total cloudiness is dominated by high and middle clouds in the western Pacific and central tropical oceans, the interannual variation of total cloudiness is also dominated by high and middle clouds in the central Pacific and Atlantic. The dominant intra-annual and interannual EOFs of total cloudiness have spatially coherent link with those SSTs. For the interannual EOFs, total cloudiness and SSTs are related to E1 nino-Southern Oscillation(ENSO). The second most important intra-annual EOFs of total cloudiness are related to Inter Tropical Convergence Zone(ITCZ). The third most important intra-annual EOFs show coherent relation in the western Pacific. The correlation analysis between cloud radiative effects and SSTs show spatially coherent relation over the tropical oceans even though cloud forcing cooling effect is much higher than heating effect.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.1-12
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• 1997

The western equatorial Pacific Ocean, where sea surface temperature is the warmest on the globe, is characterized by numerous convective systems and large annual precipitation. In this region, the cloudiness data with tops higher than 8km level obtained from the GMS-IR data are used to investigate the diurnal variation of cloudiness. The amplitude and phase of diurnal and semi-diurnal cycles are mainly investigated to examine details on the temporal and spatial structure of clouds. Cloudiness variation has typical cycles and each cycle is associated with the air-sea interactive phenomena. Spectral analysis on the cloudiness time series data indicates that 30-60 day, 17-20day, 7-8 day, diurnal and semi diurnal cycle are peaked. During Northern Winter and Southern Summer, the large cloudiness exsists over New Guinea, the adjacent seas of North Australia, and the open oceanic regions east of $160^{\circ}$E. Cloudiness diurnal variability over the lands and their adjacent seas is about 2.0 times larger than that over the open sea regions. That may be due to the difference of specific heat between the land and sea. The maximum and minimum cloudiness appeared at 18:00 and 09:00 hours over the land, and at noon and 21:00 hours over the sea, respectively. The amplitude of diurnal component over the land is 4,7 times larger than that of semi-diurnal component, and 1.5 times over the sea.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.415-431
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• 2019

The satellite-viewed cloudiness, a ratio of cloudy pixels to total pixels ($C_{sat,\;prev}$), inevitably differs from the "ground-viewed" cloudiness ($C_{grd}$) due to different viewpoints. Here we develop an algorithm to retrieve the satellite-viewed, but adjusted cloudiness to $C_{grd} (C_{sat,\;adj})$. The key process of the algorithm is to convert the cloudiness projected on the plane surface into the cloudiness on the celestial hemisphere from the observer. For this conversion, the supplementary satellite retrievals such as cloud detection and cloud top pressure are used as they provide locations of cloudy pixels and cloud base height information, respectively. The algorithm is tested for Himawari-8 level 1B data. The $C_{sat,\;adj}$ and $C_{sat,\;prev}$ are retrieved and validated with $C_{grd}$ of SYNOP station over Korea (22 stations) and China (724 stations) during only daytime for the first seven days of every month from July 2016 to June 2017. As results, the mean error of $C_{sat,\;adj}$ (0.61) is less that than that of $C_{sat,\;prev}$ (1.01). The percent of detection for 'Cloudy' scenario of $C_{sat,\;adj}$ (73%) is higher than that of $C_{sat,\;prev}$ (60%) The percent of correction, the accuracy, of $C_{sat,\;adj}$ is 61%, while that of $C_{sat,\;prev}$ is 55% for all seasons. For the December-January-February period when cloudy pixels are readily overestimated, the proportion of correction of $C_{sat,\;adj$ is 60%, while that of $C_{sat,\;prev}$ is 56%. Therefore, we conclude that the present algorithm can effectively get the satellite cloudiness near to the ground-viewed cloudiness.

• KCID journal
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• v.19 no.1
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• pp.87-96
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• 2012

Information of local solar radiation is essential for many field, including water resources management, crop yield estimation, crop growth model, solar energy systems and irrigation and drainage design. Unfortunately, solar radiation measurements are not easily available due to the cost and maintenance and calibration requirements of the measuring equipment and station. Therefore, it is important to elaborate methods to estimate the solar radiation based on readily available meteorological data. In this study, two empirical equations are employed to estimate daily solar radiation using Cheongju Regional Meteorological Office data. Two scenarios are considered: (a) sunshine duration data are available for a given location, or (b) only daily cloudiness index records exist. Simple linear regression with daily sunshine duration and cloudiness index as the dependent variable accounted for 91% and 80%, respectively of the variation of solar radiation(H) at 2011. Daily global solar radiation is highly correlated with sunshine duration. In order to indicate the performance of the models, the statistical test methods of the mean bias error(MBE), root mean square error(RMSE) and correlation coefficient(r) are used. Sunshine duration and cloudiness index can be easily and reliably measured and data are widely available.

• Atmosphere
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• v.16 no.4
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• pp.333-342
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• 2006

The long-term trends of global solar irradiance, air temperature, specific humidity and cloudiness measured at King Sejong station, Antarctica, during the period of 1988-2004, have been investigated. A statistically insignificant decrease, -0.21 $Wm^{-2}yr^{-1}$ (-0.26 %$yr^{-1}$, P<0.5) in global solar irradiance was found in an analysis from the time series of the monthly mean values, except for the increasing trends only in two months of January and June. The trends in irradiance are directly and inversely associated with the cloudiness trends in annual and monthly means. The trends in surface air temperature show a slight warming, $0.03^{\circ}Cyr^{-1}$ (1.88 %$yr^{-1}$, P<0.5) on the annual average, with cooling trend in the summer months and the warming in the winter. The exact relationship, if any, between the irradiance and temperature trends is not known. No significant tendency was found in specific humidity for the same periods. Recent (1996-2004) erythermal ultraviolet irradiance shows decreasing trend in annual mean, -0.15 $mWm^{-2}yr^{-1}$ (-1.18 %$yr^{-1}$, P<0.1) which is about five times the trends of global solar irradiance. The ratio of erythermal ultraviolet to global solar irradiance shows remarkable seasonal variations with annual mean value of 0.01 % and a peak in October and November, showing the increase of ultraviolet irradiance resulting from the Antarctic ozone hole. The sensitivity of global solar irradiance to the change in cloudiness is roughly $13%oktas^{-1}$ which is about twice of the value at the South Pole due to the difference in the average surface reflectance between the two stations. Much more sensitive values of $59%oktas^{-1}$ was found for erythermal UV irradiance than for the global solar irradiance.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.93-102
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• 2017

Interpretation of relevance between long-wave radiation and meteorological elements is recognized as an essential element for understanding the underlying mechanism of urban thermal environment formation. In this study, we analyzed relation between three elements : long-wave radiation, temperature, and lower-middle class cloudiness. The correlation was analyzed through field observations. The results are as follows. (1) Temperatures and long-wave radiation increased from January to March. This phenomenon has been confirmed in urban and suburban areas. (2) Long-wave radiations showed a tendency to increase clearly with increasing cloudiness.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.41-52
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• 2019

The purpose of the work is to develop a simple solar irradiance prediction model using a deep learning method, the LSTM (long term short term memory). Other than existing prediction models, the proposed one uses only the cloudiness among the information forecasted from the national meterological forecast center. The future cloudiness is generally announced with four categories and for three-hour intervals. In this work, a daily irradiance pattern is used as an input vector to the LSTM together with that cloudiness information. The proposed model showed an error of 5% for learning and 30% for prediction. This level of error has lower influence on the load prediction in typical building cases.

• Atmosphere
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• v.27 no.3
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• pp.291-300
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• 2017

The monthly-mean irradiance of ultra violet (UV)-B and UV-A observed from 2005 to 2014 and 2012 to 2014, respectively, at noon in Gosan, Jeju, South Korea are analyzed. We compare cloudiness, total ozone, visibility, and relative humidity with an emphasis on the four months from May to August (MJJA), which shows the largest UV radiation. While the incoming UV-B radiation at the top of the atmosphere in Gosan is the largest in June due to the small solar zenith angle, the observed surface UV-B shows an unexpected smaller value in June than those in May, July or August. In June, the meteorological conditions affecting Gosan are completely dominated by cloudiness and thus, frequent overcast seems to determine the minimum UV-B. Another important UV-determining factor is the total ozone, which exhibits a monotonic decrease during MJJA without agreeing to the characteristic feature of UV. The ratio of UV-B to UV-A is not generally influenced by cloudiness. Thus, the ratio is a useful indicator of atmospheric turbidity showing larger values for increasing visibility, except in June. A simple model has been used to estimate surface UV by using the observed ozone and visibility in the cloudless condition. The result shows that UV has the lowest value in June with small variation during MJJA. Model estimation also shows that the different characteristic features observed in July between surface UV-B and UV-A is the result of less absorption of UV-B by ozone than that of UV-A by a smaller amount of total ozone.

• Atmosphere
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• v.19 no.3
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• pp.243-253
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• 2009

In other to interpret the long-term variations of sunshine duration, cloud lifetime, and precipitation intensity observed in and around Seoul and Busan for the period from 1986 to 2005, aerosol indirect effect was employed and applied. For the identification of long-term trend of aerosol concentration, observed visibility and AOT of AERONET sunphotometer data were also used over the same regions. The result showed that the time series of visibility was decreased and those of AOT increased, especially trends were remarkable in 2000s. In both regions, occurrence frequencies of observed cloudiness (cloud amount ${\leq}6/10$) and strong precipitation (rain rate > $0.5mmhour^{-1}$) have been steadily increased while those of cloudiness (cloud amount > 7/10) and weak precipitation (rain rate ${\leq}0.2mmhour^{-1}$) decreased. These results are corresponding to the trend of both visibility and AERONET data, implying the aerosol indirect effect that makes size of cloud droplet reduce, cloud life-time longer and precipitation efficiency decreased. Our findings demonstrate that, although these phenomena are not highly significant, weather and climate system over Korean urban area have been changed toward longer lifetime of small cloudiness and increasing precipitation intensity as a result of increased aerosol indirect effect.

• Atmosphere
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• v.18 no.1
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• pp.1-14
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• 2008

The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.