• 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).

• Ocean and Polar Research
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• v.26 no.3
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• pp.439-451
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• 2004

Total solar irradiance (750), total UV irradiunce (TUV) and erythemal UV irradiance (EUV) measured at King Sejong station $(62.22^{\circ}S,\;58.78^{\circ}W)$ in west Antarctica have been used together with total ozone, cloud amount and snow cover to examine the effects of ozone, cloud and snow surface on these surface solar inadiunce over the period of 1998-2003. The data of three solar components for each scan were grouped by cloud amount, n in oktas $(0{\leq}n<3,\;3{\leq}n<4,\;4{\leq}n<5,\;5{\leq}n<6,\;6{\leq}n<7\;and\;7{\leq}n<8)$ and plotted against solar zenith angle (SZA) over the range of $45^{\circ}\;to\;75^{\circ}$. The radiation amplification factor (RAE) is used to quantify ozone effect on EUV. RAF of EUV decreases from 1.51 to 0.94 under clear skies but increases from 0.94 to 1.85 under cloudy skies as SZA increases, and decreases from 1.51 to 1.01 as cloud amount increases. The effects of cloud amount and snow surface on EUV are estimated as a function of SZA and cloud amount after normalization of the data to the reference total ozone of 300 DU. In order to analyse the transmission of solar radiation by cloud, regression analyses have been performed for the maximum values of solar irradiance on clear sky conditions $(0{\leq}n<3)$ and the mean values on cloudy conditions, respectively. The maximum regression values for the clear sky cases were taken to represent minimum aerosol conditions fur the site and thus appropriate for use as a normalization (reference) factor for the other regressions. The overall features for the transmission of the three solar components show a relatively high values around SZAs of $55^{\circ}\;and\;60^{\circ}$ under all sky conditions and cloud amounts $4{\leq}n<5$ and $5{\leq}n<6$. The transmission is, in general, the largest in TUV and the smallest in EUV among the three components of the solar irradiance. If the ground is covered with snow on partly cloudy days $(6{\leq}n<7)$, EUV increases by 20 to 26% compared to snow-free surface around SZA $60^{\circ}-65^{\circ}$, due to multiple reflections and scattering between the surface and the clouds. The relative difference between snow surface and snow-free surface slowly increases from 9% to 20% as total ozone increases from 100 DU to 400 DU under partly cloud conditions $(3{\leq}n<6)$ at SZA $60^{\circ}$. The snow effects on TUV and TSO are relatively high with 32% and 34%, respectively, under clear sky conditions, while the effects changes to 36% and 20% for TUV and TSO, respectively, as cloud amount increases.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.433-442
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• 2016

In this study, we examine future changes in surface radiation associated with cloud amount and aerosol emission over East Asia. Data in this study is HadGEM2-CC (Hadley Centre Global Environmental Model version 2, Carbon Cycle) simulations of the Representative Concentration Pathways (RCPs) 2.6/4.5/8.5. Results show that temperature and precipitation increase with rising of the atmosphere $CO_2$. At the end of $21^{st}$ century (2070~2099) relative to the end of $20^{st}$ century (1981~2005), changes in temperature and precipitation rate are expected to increase by $+1.85^{\circ}C/+6.6%$ for RCP2.6, $+3.09^{\circ}C/+8.5%$ for RCP4.5, $+5.49^{\circ}C/10%$ for RCP8.5. The warming results from increasing Net Down Surface Long Wave Radiation Flux (LW) and Net Down Surface Short Wave Radiation Flux (SW) as well. SW change increases mainly from reduced total Aerosol Optical Depth (AOD) and low-level cloud amount. LW change is associated with increasing of atmospheric $CO_2$ and total cloud amount, since increasing cloud amounts are related to absorb LW radiation and remit the energy toward the surface. The enhancement of precipitation is attributed by increasing of high-level cloud amount. Such climate conditions are favorable for vegetation growth and extension. Expansion of C3 grass and shrub is distinct over East Asia, inducing large latent heat flux increment.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.663-670
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• 2013

Total Vertical Column Density (VCD) of $NO_2$, a key component in air quality and tropospheric chemistry was measured using a ground-based instrument, Pandora, in Seoul from March 2012 to October 2013. The $NO_2$ measurements using Pandora were compared with those obtained by satellite remote sensing from Ozone Monitoring Instrument (OMI) where the intercomparison characteristics were analyzed as a function of measurement geometry, cloud amount and aerosol loading. The negative biases of the OMI $NO_2$ VCD were larger when cloud amount and Aerosol Optical Depth (AOD) were higher. The correlation coefficient between $NO_2$ VCDs from Pandora and OMI was 0.53 for the entire measurement period, whereas the correlation coefficient between the two was 0.74 when the cloud amount and AOD were low (cloud amount<3, AOD<0.4). The low bias of OMI data was associated with the shielding effect of the cloud and the aerosols.

• Journal of Korea Water Resources Association
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• v.31 no.5
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• pp.621-635
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• 1998

The feasibility of cloud seeding in Korea is presented from analyses of precipitation, cloud amount, satellite data, and upper air data. The daily mean precipitation over Dae-Kwan-Ryong is the largest(~4.5 mm/day), while the intensity of precipitation (amount of yearly rainfall divided by the frequency of rain days) over Southern area is above 14 mm/day, which shows the largest in Korea. Both the daily mean and the intensity of precipitation over Andong area are the smallest with values of ~2.7 mm/day and ~11 mm/day, respectively. In the meanwhile, the occurrence frequency of appropriate cloud top temperature (-10'~-30') for cloud seeding over the region has a large value (~130 days/year). The precipitation patterns of the region vary with wind direction and intensity calculated from 43 AWSs(Automatic Weather Station) and the additional 7 rain guages which were installed along Northern and Southern part of the Sobaek mountain. The Sc(Stratocumulus) cloud type over Andong is frequently observed, and Cirrus and Altostratus next. From the results, it is estimated that the feasibility of cloud seeding over the area would be high if a proper strategy of cloud seeding is set up. LCL (Lifting Condensation Level) and CCL (Convective Condensation Level) have the most frequency in 1000-950 hPa being occupied 4/9 of total analysis period and in 400-500 hPa, respectively, with both small variations from season to season. The correlation between vapor mixing ratio and CCL is the highest in Summer and the lowest in Winter. It means that the height of cumulus in Summer is high with an abundant water vapor but vice versa in Winter, and that the strategy of cloud seeding should be different with seasons.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.701-718
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• 2006

The average ratio of the daily UV-B to total solar (75) irradiance at Busan (35.23$^{\circ}$N, 129.07$^{\circ}$E) in Korea is found as 0.11%. There is also a high exponential relationship between hourly UV-B and total solar irradiance: UV-B=exp (a$\times$(75-b))(R$^2$=0.93). The daily variation of total ozone is compared with the UV-B irradiance at Pohang (36.03$^{\circ}$N, 129.40$^{\circ}$E) in Korea using the Total Ozone Mapping Spectrometer (TOMS) data during the period of May to July in 2005. The total ozone (TO) has been maintained to a decreasing trend since 1979, which leading to a negative correlation with the ground-level UV-B irradiance doting the given period of cloudless day: UV-B=239.23-0.056 TO (R$^2$=0.52). The statistical predictions of daily total ozone are analyzed by using the data of the Brewer spectrophotometer and TOMS in East Asia including the Korean peninsula. The long-term monthly averages of total ozone using the multiplicative seasonal AutoRegressive Integrated Moving Average (ARIMA) model are used to predict the hourly mean UV-B irradiance by interpolating the daily mean total ozone far the predicting period. We also can predict the next day's total ozone by using regression models based on the present day's total ozone by TOMS and the next day's predicted maximum air temperature by the Meteorological Mesoscale Model 5 (MM5). These predicted and observed total ozone amounts are used to input data of the parameterization model (PM) of hourly UV-B irradiance. The PM of UV-B irradiance is based on the main parameters such as cloudiness, solar zenith angle, total ozone, opacity of aerosols, altitude, and surface albedo. The input data for the model requires daily total ozone, hourly amount and type of cloud, visibility and air pressure. To simplify cloud effects in the model, the constant cloud transmittance are used. For example, the correlation coefficient of the PM using these cloud transmissivities is shown high in more than 0.91 for cloudy days in Busan, and the relative mean bias error (RMBE) and the relative root mean square error (RRMSE) are less than 21% and 27%, respectively. In this study, the daily variations of calculated and predicted UV-B irradiance are presented in high correlation coefficients of more than 0.86 at each monitoring site of the Korean peninsula as well as East Asia. The RMBE is within 10% of the mean measured hourly irradiance, and the RRMSE is within 15% for hourly irradiance, respectively. Although errors are present in cloud amounts and total ozone, the results are still acceptable.

• Atmosphere
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• v.29 no.4
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• pp.463-480
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• 2019

This study classified heavy rain types from K-means clustering for the hourly relationship between rainfall intensity and cloud top height over the Korean peninsula, and then examined their statistical characteristics for the period of June~August 2013~2018. Total rainfall amount of warm-type events was 2.65 times larger than that of the cold-type, whereas the lightning frequency divided by total rainfall for the warm-type was only 46% of the cold-type. Typical cold-type cases exhibited high cloud top height around 16 km, large reflectivity in the upper layer, and frequent lightning flashes under convectively unstable condition. Phenomenally, the cold-type cases corresponded to cloud cluster or multi-cell thunderstorms. However, two warm-type cases related to Changma and typhoon were characterized by heavy rainfall due to long duration, relatively low cloud top height and upper-level reflectivity, and the absence of lightning under the convectively neutral and extremely humid conditions. This study further confirmed that the forecast skill of rainfall could be improved by applying correction factor with the overestimation for cold-type and underestimation for warm-type cases in the Local Data Assimilation and Prediction System (LDAPS) operational model (e.g., BIAS score was improved by 5%).

• Atmosphere
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• v.31 no.4
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• pp.445-459
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• 2021

This study uses a cloud-resolving storm simulator (CReSS) to understand the individual effect of determinant meteorological factors on snowfall characteristics in the Yeongdong region based on the rawinsonde soundings for two snowfall cases that occurred on 23 February (Episode 1) and 13 December (Episode 2) 2016; one has a single-layered cloud and the other has two-layered cloud structure. The observed cloud and precipitation (snow crystal) features were well represented by a CReSS model. The first ideal experiment with a decrease in low-level temperature for Episode 1 indicates that total precipitation amount was decreased by 19% (26~27% in graupel and 53~67% in snow) compared with the control experiment. In the ideal experiment that the upper-level wind direction was changed from westerly to easterly, although total precipitation was decreased for Episode 1, precipitation was intensified over the southwestern side (specifically in terrain experiment) of the sounding point (128.855°E, 37.805°N). In contrast, the precipitation for Episode 2 was increased by 2.3 times greater than the control experiment under terrain condition. The experimental results imply that the low-level temperature and upper-level dynamics could change the location and characteristics of precipitation in the Yeongdong region. However, the difference in precipitation between the single-layered experiment and control (two-layered) experiment for Episode 2 was negligible to attribute it to the effect of upper-level cloud. The current results could be used for the development of guidance of snowfall forecast in this region.

• Journal of the Korean earth science society
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• v.38 no.2
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• pp.129-140
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• 2017

Global solar radiation was calculated in this research using ground-base measurement data, meteorological satellite data, and GWNU (Gangneung-Wonju National University) solar radiation model. We also analyzed the accuracy of the GWNU model by comparing the observed solar radiation according to the total cloud cover. Our research was based on the global solar radiation of the GWNU radiation site in 2012, observation data such as temperature and pressure, humidity, aerosol, total ozone amount data from the Ozone Monitoring Instrument (OMI) sensor, and Skyview data used for evaluation of cloud mask and total cloud cover. On a clear day when the total cloud cover was 0 tenth, the calculated global solar radiations using the GWNU model had a high correlation coefficient of 0.98 compared with the observed solar radiation, but root mean square error (RMSE) was relatively high, i.e., $36.62Wm^{-2}$. The Skyview equipment was unable to determine the meteorological condition such as thin clouds, mist, and haze. On a cloudy day, regression equations were used for the radiation model to correct the effect of clouds. The correlation coefficient was 0.92, but the RMSE was high, i.e., $99.50Wm^{-2}$. For more accurate analysis, additional analysis of various elements including shielding of the direct radiation component and cloud optical thickness is required. The results of this study can be useful in the area where the global solar radiation is not observed by calculating the global solar radiation per minute or time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.571-577
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• 2019

Since the introduction of digital cameras in an aerial-photogrammetry field on 2006, the technological paradigm related to the photogrammetry has been shifting from the analog types to digital types. However, current construction standard cost for the aerial-photogrammetry and the digital mapping are being mixed with analog-based concepts and digital-based methods. In the current standard cost, the monthly weather table is closely related to the calculation of the number of flying days in a taking of aerial photograph. The current monthly weather table uses the results calculated from the observation data of total cloud amount from 1999 to 2007. In this study, the monthly weather table was calculated using the total cloud data during ten years from 2009 to 2018. As a result, the newly calculated number of clear days for 29 stations was analyzed as 44 days decreased by 6 days. The maximum number of clear days decreased in Jinju as 23 days, and the highest decreased clearing days was February.