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Asia-Pac. J. Atmos. Sci. pISSN 1976-7633 / eISSN 1976-7951
DOI:10.1007/s13143-014-0047-0
Development of GWNU (Gangneung-Wonju National University) One-Layer
Transfer Model for Calculation of Solar Radiation Distribution of the Korean
Peninsula
Il-Sung Zo1, Joon-Bum Jee2, and Kyu-Tae Lee1
1Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University, Gangneung, Korea
2Weather Information Service Engine, Center for Atmospheric sciences and Earthquake Research, Seoul, Korea
(Manuscript received 24 October 2013; accepted 28 July 2014)
© The Korean Meteorological Society and Springer 2014
Abstract: Gangneung-Wonju National University (GWNU) one-
layer solar radiation model is developed in order to resolve the lack
of the vertical structure of atmospheric components and fast
calculation with high horizontal spatial resolution. GWNU model is
based on IQBAL and NREL methods and corrected by precise multi-
layer Line-By-Line (LBL) model. Further, the amount of solar
radiation reaching the surface by using 42 types of vertical atmos-
pheric data as input data was compared with detailed models and
one-layer models. One-layer solar radiation models were corrected
depending on sensitivity of each input data (i.e., total precipitable
water, ozone, mixed gas, and solar zenith angle). Global solar radiation
was calculated by corrected GWNU solar model with satellites
(MODIS, OMI and MTSAT-2), KLAPS model prediction data in
Korea peninsula in 2010, and the results were compared to surface
solar radiation observed by 22 KMA solar radiation sites. Calculated
solar radiation annually accumulated showed highest solar radiation
distribution in Andong, Daegu, and Jinju regions, meanwhile the
observation data showed lower solar radiation in Daegu region
compared to model result values.
Key words: One-layer solar radiation model, line-by-line model,
correction, global solar radiation, vertical atmospheric data
1. Introduction
Solar radiation reaching the surface of the earth not only
serves as a crucial role in climate change of global atmosphere
but also is extensively used for industrial activity of human
beings. In particular, as solar energy, one of clean energy
resources, is attenuated by 65% when radiant energy (65,700
TW/year) released from the sun passes atmosphere, the
amount reaching the surface of the earth is about 23,000 TW/
year, a more amount compared to other types of energy
sources (Perez and Perez, 2008). Thus, many countries in the
world show their great interest and have heavily invested in
energy power projects using solar energy. Germany Trade &
Invest(GTAI), a leader in photovoltaic generation, reported that
a growing trend of Germany's annual solar radiation capacity
reached 7.6 GW in 2012, and approximately 180,000 photo-
voltaic systems were newly operated for a year, which proves
photovoltaic generation sharply increases.
The U. S. Department of Energy's National Renewable En-
ergy Laboratory (NREL) developed the Climatological Solar
Radiation (CSR) model in 1995 to calculate daily accumulated
solar radiation (George and Maxwell, 1999). A solar energy
map was produced at 10 km ×10 km spatial resolution by
using the State University of New York (SUNY)'s Satellite
Radiation Model (Perez et al., 2002) developed by NREL and
Perez, and was analyzed by using the US Climate Reference
Network (USCRN) data and the Typical Meteorological Year
(TMY) Ver.3 model. The German Weather Service (Deutscher
Wetterdienst, DWD) completed a solar energy map for the first
time in 1999 by using observation data on monthly and annual
average solar radiation daily accumulated from 1981 to 1998,
and a solar energy map using a solar radiation model was
developed by using relevant meteorological and meteorological
satellite observation data based on Kerschgens et al. (1978)'s
two-stream method. Further, a solar energy map was produced
by using the European Center for Midrange Weather Forecasts
(ECMWF) data and the Model Output Statics (MOS) method,
and additional studies that calculate photovoltaic power gener-
ation are being conducted. Recently, new technic, research
actively conducted using the neural network method (Takenaka
et al., 2011).
Solar energy that is released from the sun and reaches the
surface of the earth changes with astronomical conditions (i.e.,
location change of the sun and the earth), distribution of the
earth's atmospheric components (e.g., water vapor, mixed gas,
aerosol, cloud, etc., Yeom et al., 2012; Lee et al., 2013), and
the earth's surface conditions (i.e., geography and topography).
It is important to consider multiple scattering between sub-
strates by dividing atmosphere into multiple layers and input-
ting observation data by altitude. However, as stations ob-
serving the atmosphere's vertical structure are limited, and
observation for calculating radiation characteristics does not
exist except for specific observation, calculation for high-
resolution solar radiation requires a one-layer solar radiation
model that assumes atmosphere as a one-layer to calculate.
Therefore, this study herein corrects the existing Gangneung-
Wonju National University (GWNU; hereafter GWNU) one-
Corresponding Author: Joon-Bum Jee, Weather Information Service
Engine, SAIT Tower 12 Fl., 434 Worldcupbukro, Mapo-gu, Seoul
121-835, Korea
E-mail: rokmcjjb717@gmail.com
ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
layer solar radiation model's calculation process on transmit-
tance and solar radiation by comparing results derived from a
multiple-layer solar radiation model. The input data for solar
radiation model operation calculated a correction equation by
using the atmosphere's 42 types of vertical data. The correction
equation calculated solar energy distribution of the Korean
peninsula by applying the GWNU one-layer solar radiation
model, and was analyzed by comparing observation data. The
research results will resolve deficiency of input data to calculate
solar radiation models and will be used for super resolution
and accurate solar energy calculation in an efficient manner.
2. Solar radiation model
Solar radiation released from the sun and reaching the surface
are classified as direct and diffuse solar radiation by physical
process, and these elements can be observed in a separate
manner (i.e., direct, diffuse and global solar radiation) on the
surface. In other words, the solar radiations reaching the
surface are observed and attenuated by clouds, aerosol, and gas
components in the atmosphere, which are varied by wavelength
(see Fig. 1). The ozone layer in the stratosphere absorbs some
parts of visible and ultraviolet ray areas at 0.4 µm or less,
while water vapor and carbon dioxide absorb infrared wave-
length regions at 0.75 µm or more.
a. Multi-layer line-by-line solar radiation model
Solar radiation energy entering at top of atmosphere is
absorbed, diffused, and reflected by gas components, clouds,
and aerosol in the atmosphere, and the surface. Under the
assumption of a plane-parallel atmosphere, provided that the
definition of solar zenith angle (θ), azimuth (φ), and µ≡cosθ
on radiation process directions is used, a general solar
radiation transfer equation is as follows (Dave, 1974).
.(1)
In this equation,τλ stands for optical thickness by wavelength
and Jλ stands for a source function.
In atmosphere, although solar radiation transfer equation can
be simplified by neglecting the Planck function, it is not easy
to find accurate values with the equation if multiple scattering
is included, resulting from many layers and the surface of the
earth. However, provided that a phase function (Pv) does not
change depending on azimuth (φ), downward flux of radiation
in a τ layer can be specified as follows.
F↓(τ)= . (2)
Herein, F0 stands for solar radiation flux entered in atmos-
phere, and as solar radiation calculated in this equation
drastically changes by wavelength, the Line-by-Line (LBL)
method that calculates by densely dividing wavelength spacing
was used to accurately calculate transfer equation values for
solar radiation, meanwhile Stamnes et al. (1988)'s discrete
ordinate approximation was used for transmission and diffusion
calculation by atmospheric components.
This method is based on Chandrasekhar (1960), and with it,
a multiple scattering process of layer was included to calcu-
lation by Stamnes et al. For absorption line data, as intervals
by wavelength are not constant and are arranged in a random
manner, band models for the equation (2)'s transmission
function calculation produce errors in some parts. For a range
of solar radiation wavelength, coefficient by wavelength was
calculated at 0.002 cm−1 intervals from HITRAN2k absorption
line data (Rothman et al., 2003).
b. One-layer solar radiation model
The intensity (Iλ) of solar energy reaching the surface of the
earth can be written as follows based on Beer's law (Siegel and
Howell, 1981).
Igλ=Idλcosθ+Isλ.(3)
Herein, λ stands for wavelength, global solar radiation (Igλ)
can be divided into direct components (Idλ) and diffuse
components (ISλ), and provided that atmosphere is a one layer,
direct solar energy reaching the surface is calculated as the
following equation (4).
Idλ=I0λexp(−τλ). (4)
Herein, I0λ and τλ, respectively, stand for extraterrestrial radi-
ation and optical thickness resulting from absorption gas, and
atmospheric transmittance can be specified as tλ=exp(−τλ).
For absorption gas and particles, the following empirical
equations were used to obtain each transmittance ratio of
optical thickness on air molecule, aerosol, ozone, water vapor,
and mixed gas.
toλ= exp(−koλ lmo), (5)
µdIλτλµφ,,()
dτ
--------------------------- Iλτλµφ,,()Jλτλµφ,,()–=
vd
∫2πIλ
0
1–
∫τvµ,()µdµµ
0
+πF0eτµ
0
⁄–
Fig. 1. A comparison of the extraterrestrial spectrum with the diffuse,
direct, and global radiation (W m−2 µm−1) on June 15.
Il-Sung Zo et al.
twaλ= exp[−0.2385kwaλωmr/ (1 + 20.07kwaλωmr)0.45], (6)
trλ= exp(−0.008735maλ−4.08), (7)
taλ= exp[−β(λ/0.55)
−αmr], (8)
tgλ= exp[−1.41kgλma/ (1 + 118.93kgλma)0.45]. (9)
Herein, koλ, kgλ and kwaλ stand for classified wavelength ab-
sorption coefficient on ozone, mixed gas, and water vapor.
Provided that aerosol is less than 0.5 µm, α is 1.027, mean-
while 1.206 is used for others, and l and ω, respectively, stand
for vertical concentration and total precipitable water. Further,
mr, ma, and mo, respectively, stand for relative optical mass,
pressure-corrected value, and relative optical mass on ozone.
Diffuse solar radiation (Isλ) on the surface is changed by air
molecule, aerosol, and multiple scattering at the surface, which
can be calculated as follows.
Isλ= Irλ+Iaλ+Igλ. (10)
From the above equation, solar radiation diffused by Rayleigh
(Irλ), aerosol (Iaλ), and atmosphere (Igλ) is calculated by
empirical equations as follows.
Irλ=I0λE0cosθτ
oλτgλτwaλ [0.5(1 −τrλ)τaλ], (11)
Iaλ=I0λE0cosθτ
oλτgλτwaλ [Fcω0(1 −τ
aλ)τrλ], (12)
Igλ=Qλ[(ρgλ)/(1−ρgλ)], (13)
Qλ=(Irλ+Iaλ)+Idλ, (14)
=τoλτgλτwaλ[0.5(1 −τrλ)τaλ+(1−Fc)ω0(1 −τ
aλ)τrλ]. (15)
Herein, E0 stands for eccentricity, and Fc stands for a ratio of
forward scattering on the total energy scattering, meanwhile
1−Fc stands for backward scattering. ω0 stands for a single
scattering albedo. and ρgλ, respectively, stand for multiple
scattering by all the absorption gases in atmosphere and
surface albedo.
The GWNU model used for this study was based on the
IQBAL model, which is a solar radiation model corrected by
using a multiple solar radiation model after adapting and
applying the NREL's aerosol process method. The IQBAL
model was produced on a basis of Iqbal's theory (Iqbal, 1983)
and the NREL model is a one-layer model Bird and Riordan
(1986) produced by the National Renewable Energy Labora-
tory (NREL) for development and to compare observed values,
and the two above-stated models are a spectrum model calcu-
lating solar radiation by wavelength. Further, BIRD (Bird and
Hulstrom, 1981) stands for a one-layer solar radiation model to
develop wavelength ranges of solar radiation as a one band.
3. Correction of one-layer solar radiation model
The τλ of the equation (4) in section 2.b stands for optical
thickness, which is a function of absorption coefficients (e.g.,
koλ, kgλ, kwaλ, etc.) of pressure components, and basically, a
function of altitude or pressure, but the GWNU one-layer solar
radiation model does not include change in altitude or pressure
of absorption coefficient because atmosphere was assumed as
a single layer to save calculation time and calculation re-
solution. Therefore, for this study, methods correcting one-
layer solar radiation models of the equations from (3) to (15),
were used by comparing detailed solar radiation models
including altitude or pressure effects by dividing atmosphere
into multiple layer.
To operate accurate solar radiation models, vertical atmos-
pheric distribution data require input data, and reference atmos-
phere data (i.e., standard atmosphere data by latitude) are
mostly used. To compare calculation results of radiation
models, Garand et al. (2001)'s 42 types of vertical atmospheric
data were used for this study. The 42 types of vertical
atmospheric data include not only 6 standard atmospheres (i.e.,
standard, tropical, middle latitude summer, middle latitude
winter, sub-arctic summer, and sub-arctic winter) but also
distribution by altitude observed at many stations of the earth.
ρaλ
′ρaλ
′
ρaλ
′
ρaλ
′
Fig. 2. Global solar radiation of LBL solar radiation model (black point) and error between GWNU and LBL solar radiation
model for transmittance (red triangle) with total precipitable water (a) and total ozone amount (b).
ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
For total precipitable water, total ozone amount and mixed
gas, the results and the error of transmittance derived from the
LBL model were shown by using 42 types of vertical
atmospheric data. Total precipitation water (a) and total ozone
amount (b) of Fig. 2 showed that solar radiation and the error
of transmittance decreased depending on change in the amount
of input data, indicating that the one-layer model calculates
transmittance more depending on the amount of absorber
compared to detailed models. In other words, for the amount
of gas absorbed in the same atmosphere, the one-layer model
calculates less transmittance compared to detailed models.
Therefore, transmittance calculated in the one-layer model
should be corrected by the amount of gas absorption so that
transmittance derived from total precipitable water and total
ozone amount can be decreased to the same amount of detailed
models. Transmittance was corrected by using a third-degree
polynomial to obtain the amount of total precipitable water as
the fluctuation of its error is large compared to total ozone
amount, meanwhile a second-degree polynomial was used to
obtain the amount of total ozone amount.
Further, the mixed gas of Fig. 3 was calculated on the
assumption that the mixture ratio in atmosphere is constant.
And as the amount of solar radiation change resulting from the
amount of mixed gas is not large, the relationship of global
solar radiation and temperature of the surface was examined.
As a result, correlation coefficient showed a relatively high
correlation as 0.97. Therefore, for correction derived from the
amount of mixed gas, transmittance was corrected by surface
temperature by applying a second-degree polynomial, which is
the same method applied to total precipitable water and total
ozone amount. When it comes to correction of global solar
radiation depending on solar zenith angle, as shown in Table 1
below, surface albedo was each corrected at 0.1 interval of
cosine the solar zenith angle by using the rate of global solar
radiation. The interaction between atmosphere and the ground
surface is sensitive to change in solar zenith angle, and the
LBL model and the error increase as solar zenith angle
increases. This is caused by while the LBL model considers a
mixture ratio by altitude and accumulates calculated values to
calculate, the one-layer solar radiation model considers multiple
scattering and path length of absorption gas by considering a
one-layer to calculate the amount of solar radiation. At a part
with small solar zenith angle, although solar radiation corrected
Fig. 3. Same as Fig. 2 except for surface air temperature (K).
Tabl e 1 . The error correction equation between GWNU and LBL
solar radiation model for global solar radiation with cosine of solar
zenith angle.
Solar zenith angle Equation (quadratic polynomial)
0.0 y = 1.0083 + (−0.0062/x) + (−2.8119e −5/x2)
0.1 y = 1.0080 + (−0.0063/x) + (−2.6584e −5/x2)
0.2 y = 1.0077 + (−0.0063/x) + (−2.4944e −5/x2)
0.3 y = 1.0074 + (−0.0064/x) + (−2.3077e −5/x2)
0.4 y = 1.0071 + (−0.0065/x) + (−2.1002e −5/x2)
0.5 y = 1.0067 + (−0.0066/x) + (−1.8675e −5/x2)
0.6 y = 1.0063 + (−0.0067/x) + (−1.6053e −5/x2)
0.7 y = 1.0059 + (−0.0068/x) + (−1.3253e −5/x2)
0.8 y = 1.0054 + (−0.0069/x) + (−9.8984e −6/x2)
0.9 y = 1.0049 + (−0.0070/x) + (−6.1025e −6/x2)
Table 2. Surface solar radiation (W m−2) by solar radiation models with surface albedo and mid-latitude summer atmosphere. And differences (%)
between LBL and solar radiation models.
Surface albedo
Multi-layer
LBL model
(W m−2)
Difference(%)
Multi-layer One-layer
Band model Spectral model Band model
NASA IQBAL NREL GWNU BIRD
0.0 1060.1 −0.121 −2.274 −1.654 −1.654 −0.812
0.1 1067.7 −0.078 −2.308 −1.613 −0.211 0.512
0.2 1075.5 −0.031 −2.344 −1.547 −0.217 1.031
0.3 1083.7 0.019 −2.383 −1.453 −0.215 1.822
0.4 1091.4 0.074 −2.425 −1.329 −0.216 2.585
0.5 1101.0 0.133 −2.470 −1.174 −0.210 3.412
0.6 1110.3 0.196 −2.519 −0.986 −0.208 4.051
0.7 1119.9 0.265 −2.573 −0.761 −0.211 4.717
0.8 1130.1 0.339 −2.632 −0.498 −0.209 5.581
0.9 1140.8 0.419 −2.697 −0.132 −0.213 6.833
Il-Sung Zo et al.
Fig. 4. Global solar radiation (W m−2) by LBL model and box-plots of differences (%) between solar radiation models and
LBL model with atmospheres from Garand et al. (2001).
ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
Fig. 5. Monthly accumulated surface solar radiations (unit: MJ m−2) calculated by GWNU model with 1 km ×1km
resolution (Jan. to Dec., 2010).
Il-Sung Zo et al.
is small, a second-degree polynomial regression equation was
applied as errors radically occur when the solar zenith angle is
big. As shown in Fig. 2 and 3, and Table 1, the GWNU model
was established for this study as a conclusive solar radiation
model, by including corrected regression equation to solar
radiation models of the equations (3)-(9) depending on ab-
sorption gas and surface albedo.
Out of calculation results derived from the multi-layer LBL
radiation model, the multi-layer band model (Chou and Suarez,
1999; hereafter NASA), and 4 types of one-layer solar radi-
ation model (e.g., IQBAL, NREL, and BIRD) including the
GWNU model, results of mid-latitude summer atmosphere
were shown in Table 2. Surface temperature of mid-latitude
summer atmosphere is 294.2 K, total precipitable water is 2.91
cm, total ozone amount is 330.5 DU, and solar zenith angle is
0o, and the flux of extraterrestrial solar radiation used 1366.05
Wm
−2. Results showed that the amount of solar radiation on
the surface increased by surface albedo, and the GWNU was
the most similar model out of one-layer models, and the Bird
model, one-layer band model, showed the biggest difference.
When surface albedo is 0.0, the value of solar radiation
calculated on the surface and the difference between NASA,
IQBAL, NREL, and GWNU were shown in Fig. 4 as box-plot
after changing the cosine value of solar zenith angle into 1.0,
0.8, 0.6, and 0.4. It is analyzed that the values calculated in the
LBL model were calculated dependently on amounts of ozone
and total precipitable water that are input data, and the smallest
difference showed in NASA, followed by GWNU, NREL and
IQBAL. Comparing with calculation results derived from the
LBL model showed that while the error increased in the
GWNU as albedo increased, and the error was below 0.50%
on average. The error of IQBAL and NREL model, similar
kinds, was 2% or more. Further, the error of one-layer solar
radiation model increased as solar zenith angle increased
(cosine values decreased). This occurs when the increasing
ratio on length of optical path is bigger in the one-layer model,
and the amount of absorber in layer equally increases.
4. Results
The GWNU model, a corrected one-layer solar radiation
model, calculated surface solar radiation by inputting real
atmospheric conditions obtained from model forecasting and
satellite observations data of the Korean peninsula. To calculate
the amount of solar radiation reaching the surface of the earth,
required are amounts of gas absorbing solar radiation such as
water vapor (or total precipitable water), ozone, etc., aerosol,
and cloud cover data, and also surface pressure and altitude at
calculation spots and surface albedo data. Out of these data, for
data on pressure and the amount of water vapor, etc., the Korea
Local Analysis and Prediction System (KLAPS), a regional
forecast model of the Korea Meteorological Administration
(KMA; hereafter KMA), was used, for the amount of ozone,
Fig. 6. Monthly accumulated cloud amounts (unit: okta) observation by 22 KMA solar sites (Jun. to Aug. 2010).
Fig. 7. KMA 22 solar radiation sites on Korea peninsula.
ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
the Ozone Monitoring Instrument (OMI) sensor data (daily
average; when missing use to month average data) at 1o×1o
resolution was used, and for aerosol, showing very strong
characteristics in size, shape, and region, MODIS satellite data
(daily average; when missing use to month average data) at
1o×1o resolution were used. Further, for surface albedo data,
used were MODIS's high resolution (0.05o×0.05o resolution)
data, and for the digital elevation model, used were 3-second
data (about 90 m resolution) of NASA's Shuttle Radar Topo-
graphy Mission (SRTM) from United State Geological Survey
(USGS). For cloud data, one of the most important factors
attenuating solar radiation energy reaching the surface, MTSAT-
2 satellite data were processed by a method used in Kawamura
et al. (1998) and Communication, Ocean and Meteorological
Satellite Data Processing System (Korea Meteorological Ad-
ministration, 2009). Cloud data (hereafter cloud factor) using
visible and infrared spin scan radiometer data supplied by the
MTSAT-2 satellite and solar zenith angle. Cloud factor is the
observation and calculation (in clear sky) on cloudy pixel. And
look up table of cloud factor is calculated by Gauss-Jordan
elimination (Gilbert, 2003) and multiple regression (Cohen et
al., 2003) methods with 1o of solar zenith angle and visible
albedo, respectively. The above-stated data were used in a way
of interpolation scheme in accordance with 1 km ×1km
resolution regarding the Korean peninsula, research area.
Analysis was conducted from January 2010 to December
2010, and spatial distribution of monthly accumulated solar
radiation calculated by the GWNU model, which was cor-
Fig. 8. Monthly accumulated surface solar radiations (unit: MJ m−2) observation by 22 KMA solar radiation sites in 2010.
Il-Sung Zo et al.
rected, was shown in Fig. 5. For monthly solar radiation
distribution of the Korean peninsula, seasonal and regional
distribution characteristics were distinctively shown by the
effect of cloud, solar zenith angle, aerosol, and the amount of
water vapor. In particular, as the solar zenith angle is small
during summer season, the solar radiation of surface is expected
to be strong. However, due to frequent clouds, monthly maxi-
mum accumulated solar radiation was shown in June, early
summer. That is, the reason that surface solar radiation is
strong compared to mid-summer (July to August) is that
although the sun's altitude was lower in June compared to mid-
summer season, the amount of clouds, the most important
factor in the attenuation effect, was less in June compared to
July and August, mid-summer season (5.75 okta in June, 7.34
okta in July, 6.88 okta in August, See Fig. 6). Further, the
lowest month of the year was December in the amount of
average monthly solar radiation, about 27% compared to June,
the highest month, analyzed that it is due to the solar zenith
angle is large and much cloud amount in Dec.. Fig. 7 indicates
that 22 solar radiation sites operated by the KMA, and out of
monthly accumulated data observed in the sites, main months
of season was shown in Fig. 8. Although the distribution of
solar radiation was similar with model calculation values in
Fig. 5, it partially shows a difference, which is resulting from
that as model calculation results are calculated at one-hour
intervals while observation data are hourly accumulated. How-
ever, this will be resolved, provided that collection intervals
are shortened on input data of solar radiation models including
cloud.
Further, Fig. 9 stands for calculation of the GWNU model
on the amount of solar radiation annually accumulated and
solar radiation observation data provided by the KMA's 22
sites. The amount of average solar radiation on the Korean
peninsula's calculated solar radiation was 4,800 MJ m−2, and
the average value of 22 observatories' data was 4,932 MJ m−2.
Results of model calculation showed that solar radiation annu-
ally accumulated was relatively less in the Korean peninsula's
western coast area as the area has more amount of cloud
compared to other regions, while the intensity of solar energy
was strong as Andong, Daegu, and Jinju show little amount of
cloud related to downwind location of Sobaek mountainous
areas. During the same period, although the KMA's solar
radiation shows a similar tendency, Daegu showed relatively
lower solar radiation compared to the model. This difference
can be analyzed and described through environment investiga-
tion of solar radiation observatories and comparative obser-
vation of pyranometer.
5. Summary
The one-layer solar radiation model was developed to resolve
deficiency of vertical atmospheric data and improve high-
resolution computing speed. The GWNU solar radiation model
was developed on a basis of the IQBAL and NREL theories, a
Fig. 9. Annual accumulated global solar radiations (unit: MJ m−2) of calculation by GWNU model (a) and observation by 22 KMA
solar radiation sites (b) in 2010.
ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
one-layer solar radiation model, and the LBL was selected as a
reference model to improve accuracy. Further, the amount of
solar radiation reaching the surface of the earth by using 42
types of vertical atmospheric data as input data was compared
with detailed models and one-layer models. One-layer solar
radiation models were corrected depending on sensitivity of
each input data (i.e., total precipitable water, ozone, mixed gas,
and solar zenith angle). Analysis results derived from the
GWNU solar radiation model showed that a difference showed
0.5% or less compared to the LBL model, which is a similar
value with the NASA model, a multi-layer model, and the
error increased by solar zenith angle, which was lower com-
pared to other one-layer solar radiation models.
By using satellite and numerical model data as input data,
calculated was solar radiation reaching the surface in the
Korean peninsula for one year in 2010, which were compared
with surface observation data. The results showed a similar
distribution with observation data, partially showing a differ-
ence, which was caused by a time difference between model
and observation data. This is analyzed as an error occurring,
resulting from that the observation data are accumulated by
time meanwhile the model is calculated at hourly intervals. As
a factor affecting the most is cloud, June least affected by
cloud during summer showed high solar radiation compared to
July and August of mid-summer, due to change in cloud.
Calculated solar radiation annually accumulated showed hig-
hest solar radiation distribution in Andong, Daegu, and Jinju
regions, meanwhile the observation data showed lower solar
radiation in Daegu region compared to model result values.
This difference can be analyzed and described through com-
parative observation conducted by solar radiation observation
stations on environment investigation and pyranometer.
In conclusion, the one-layer solar radiation model developed
herein in this study can partially resolve problems occurring in
input data of solar radiation models, and can be applied to
high-resolution calculation requiring much computation. Fur-
ther, it is considered that the one-layer solar radiation model
can be basic research for further renewable energy and
photovoltaic generation studies.
Acknowledgments. This work is funded by the Korea Meteor-
ological Administration Research and Development Program
under the Weather Information Service Engine (WISE) project
(Grant No. 153-3100-3133-302-350).
Edited by: Tadahiro Hayasaka
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