Journal of Power and Energy Engineering, 2013, 1, 1-9
http://dx.doi.org/10.4236/jpee.2013.13003 Published Online August 2013 (http://www.scirp.org/journal/jpee)
1
Estimation of Global Solar Radiation for Four Selected
Sites in Nepal Using Sunshine Hours, Temperature and
Relative Humidity
Krishna R. Adhikari1*, Binod K. Bhattarai1, Shekhar Gurung2
1Institute of Engineering, Tribhuvan University, Kathmandu, Nepal; 2Central Department of Physics, Tribhuvan University, Kath-
mandu, Nepal.
Email: *adhikari.krishnaraj@gmail.com
Received August 9th, 2013; revised August 23rd, 2013; accepted August 30th, 2013
Copyright © 2013 Krishna R. Adhikari et al. This is an open access article distributed under the Creative Commons Attribution Li-
cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Rational and accurate solar energy databases, essential for designing, sizing and performing the solar energy systems in
any part of the world, are not easily accessible in different localities of Nepal. In this study, daily global solar radiation,
sunshine hours and meteorological data for Biratnagar, Kathmandu, Pokhara and Jumla have been used to derive the
regression constants. The linear regression technique has been used to develop a model for Biratnagar, Kathmandu,
Pokhara and Jumla. The model has calculated the global solar radiation for these locations. The values of global solar
radiation estimated by the model are found to be in close agreement with measured values of respective sites. The esti-
mated values were compared with Angstrom-Prescott model and examined using the root mean square error (RMSE),
mean bias error (MBE), mean percentage error (MPE), coefficient of regression (R), coefficient of determinant (R2) and
correlation coefficient (CC) statistical techniques. Thus, the resultant correlations and linear regression relations may be
then used for the locations of similar meteorological/geographical characteristics and also can be used to estimate the
missing data of solar radiation for the respective site.
Keywords: Global Solar Radiation; Clearness Index; Sunshine Hours; Linear Regression Relation; Model
1. Introduction
Nepal is a land-locked mountainous country with a large
area of beautiful landscape situated between 26˚22' to
30˚27' North latitude and 80˚40' to 80˚12' East longitude
within a span of 200 km from south to north and about
800 km from east to west [1]. The total area of the coun-
try is 147,181 square kilometers and is divided into five
physiographic regions: High Himal, High Mountain,
Middle Mountain, Siwalik (the Chure Range) and the
Terai [2].
Nepal has more than 6000 rivers with all river systems
draining north to south towards the Ganges [2] and its
theoretical, technical and economically feasible hydro-
power potential has been estimated at about 83,000 MW,
45,000 MW and 42,000 MW respectively [1]. The cur-
rent installed capacity of power plants connected to the
national grid is 689 MW whereas peak demand of power
for the year of 2011 was 946.10 MW and projection of
power demand for 2012/2013 was 1163.2 MW [3]. The
electricity consumption and the number of consumers
increase at a rate of approximately 9% per year [4]
whereas generation of additional power plant is almost in
stagnant situation. This gap between supply and demand
in power sector forces Nepal Electricity Authority into
load-shedding from 4 hours to 16 hours per day in spring
and dry season respectively [5].
With the rapid use and depletion of fossil fuel reserves
[6] in the world, they create negative impact on economy
and environment [7]. The construction period for new
power generation projects and new import transmission
capacities is very long, therefore, a rapid improvement of
energy supply cannot be expected. An urgent supply of
power through diesel power plants is impracticable be-
cause of the high power generation costs. The power
supply crisis affects public life and especially economic
development negatively [4]. Moreover, biomass tech-
nology does not work well enough on the comparatively
cold high altitude and small hydro turbines need special
*Corresponding author.
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
2
topographical conditions [1] to be established and run.
All the above facts demand a shift of the emphasis to the
new and clean alternative energy sources to replace
costly and unrealistic sources and ensure sustainable de-
velopment of the country.
In the year of 2008/2009, total energy consumption in
Nepal was 401 million GJ, out of 87% of total energy
consumption was derived from traditional resources (also
called biomass energy resources), 12% from commercial
sources (coal, grid electricity, and petroleum products)
and less than 1% from the alternative sources (biogas,
solar power, wind and micro/pico level hydropower) [1].
The average global solar radiation in Nepal varies from
3.6 - 6.2 kWh/m2·day; the sun shines for about 300 days
a year, the national average sunshine duration is 6.8
hours/day and average insolation intensity about 4.7
kWhm2·day1 (=16.92 MJ/m2·day) [1], it is greater than
the 15.8 MJ/m2·day measured by Solar Energy Research
Laboratory, Department of Physics, Silpakorn University,
Thailand for Lao PDR [7]. The data is based on one
year’s several sites of Nepal. With the consideration of
12% efficiency of PV module and 4.7 kWh/m2·day1 of
insolation intensity, the total energy generation potential
of the country will be 83,000 GWh/day = 18.36 TW.
This is more than present energy demand (13 TW) of the
world [1]. Under this circumstance, the development of
solar energy technology in many parts of the country and
especially in rural sectors is desirable and favorable
where there is no viable alternative to the solar electricity
[1].
Choice of solar energy, in countries like Nepal, is the
best and ultimate option among the different energy in-
cluding alternative energy sources. If we think of com-
plete solution of rural electrification in Nepal, we have to
plan to link up micro-hydro/pico-hydro with solar energy
exploitation. Thus, an accurate knowledge and database
of solar radiation at a particular place and selected sites
are important for the development of many solar devices,
the establishment of solar plant at the proposed site and
for estimation of their performance [8].
The radiation reaching the earth surface is modified
significantly by clouds [9], water vapor, ice, aerosols,
and atmospheric constituents in its intensity and the sun-
shine duration. The beam radiation (radiation coming
directly from the solar disk) is attenuated by the presence
of cloud in its path, as well as by the various atmospheric
elements. The depletion of the direct beam by the cloud
depends on the type of clouds, their thickness and the
number of layers [10]. The radiation scattered by the
atmospheric constituents is called diffuse radiation where
a portion of this radiation goes back by about 6% of the
incident radiation to space, and a portion, about 20% of
the incident radiation, reaches the earth surface [11]. The
sum of direct and diffuse radiation on the earth surface is
known as global/total radiation which is very important
for the design of certain solar energy applications [10].
In developing countries like Nepal, the facility of
ground-based measurement of solar radiation is available
only at selected sites whereas meteorological and hydro-
logical data are available at different parts of the country.
Obviously the best way of knowing the amount of global
solar radiation at the site of consideration is to install
pyranometer at many locations in the given region and
look after their day-to-day maintenance and recording,
which is a very expensive venture. The alternative ap-
proach is to correlate the global radiation with the mete-
orological parameters where the data can be collected.
The resultant correlation may then be used for locations
of similar meteorological characteristics [12]. Thus, de-
veloping the empirical model to estimate the global solar
radiation using easily available parameters such as sun-
shine duration, maximum and minimum temperature,
relative humidity, rainfall and geographical location, etc.,
is an essential assignment for countries like Nepal, which
will be a vigorous scientific research. So far, various
models have been developed by a number of researchers
with different regression coefficients using linear regres-
sion techniques [13] for various countries and for differ-
ent locations to estimate solar radiation. The most and
commonly used model in most of the countries including
Nepal is Angstrom-Prescott model which is based on
correlation of global solar radiation with sunshine hours.
Available literatures show that there is a very few and
limited study done in Nepal to develop the model and to
calculate the regression coefficients. This may be due to
inadequacy of existing solar energy data and lacking sense
of necessity to develop solar energy techniques. Either the
researchers may have been satisfied with the available data
or our research culture may be such that the research
works are not well tied up with our ground reality.
Empirical models which have been used to calculate
solar radiation are usually based on astronomical factors,
geographical factors, geometric factors, physical factors
and meteorological factors [14].
In the present study, annual radiation, meteorological/
hydrological data have been used to derive the regression
coefficients b, c, d and intersection constant a to develop
a model based on linear regression technique to estimate
the monthly average daily global solar radiation for four
sites of Nepal, and to compare the values with the esti-
mations derived from sunshine-based Angstrom-Prescott
model. The linear regression relation of the model is
ln
mav
OM
d
HnT
abcd RH
HNT

 


(1)
where m
H
is measured monthly mean daily solar ra-
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
3
diation on horizontal surface in MJ/m2·day, O
H
monthly mean daily extraterrestrial radiation on horizon-
tal surface in MJ/m2·day, n monthly mean daily sun-
shine hours, d
N monthly average maximum possible
daily hours of sunshine or the day length, av
T and
M
T
are monthly mean of daily mean and monthly mean daily
maximum temperature in Kelvin scale, RH monthly
mean daily relative humidity, ln natural logarithm and a,
b, c, d are constants obtained by the linear regression
analysis.
2. Material and Method
The primary data of daily solar radiation on horizontal
surface for Biratnagar, Kathmandu, Pokhara and Jumla
were collected from the archives of the Department of
Hydrology and Meteorology, government of Nepal
(DHM/GoN) and Solar Radiation and Aerosol in Hima-
layan Region (SAHR) project of Institute of Engineering,
Tribhuvan University, Nepal. Daily sunshine duration,
temperature and relative humidity data for these sites
were obtained from Department of Hydrology and Mete-
orology (DHM)/GoN. The data obtained covered a pe-
riod of years from 2007 to 2012 for Biratnagar (latitude
26.483˚, longitude 87.266˚ and altitude 72 m), Kath-
mandu (latitude 27.7˚, longitude 86.366˚ and altitude
1337 m), Pokhara (latitude 28.216˚, longitude 84˚ and
altitude 827 m) and two years 2011 to 2012 years for
Jumla (latitude 29.283˚, longitude 82.166˚ and altitude
2300 m). The most widely used ORIGIN/Microsoft Of-
fice Excel softwares have been used for the data analysis.
2.1. Theory
The acquired data were processed in Microsoft Office
Excel to obtain useful form i.e., daily extraterrestrial so-
lar radiation in MJ/m2, daily global radiation in MJ/m2,
the ratio of daily mean of maximum and minimum tem-
perature to daily maximum temperature in Kelvin scale
and natural logarithm of average value of daily relative
humidity data of the year 2007-2012 for Biratnagar,
Kathmandu and Pokhara and those of 2011-2012 data for
Jumla.
The proposed linear regression relation (empirical mo-
del) to estimate global solar radiation is given below:

ln
mav
OM
d
HnT
abcd RH
HNT

 


where, a, b, c, and d are regression constants, the ratio
m
O
H
H
is clearness parameter or cloudiness index,
d
n
N



fraction of sunshine hours, and
O
H
is the monthly average daily extraterrestrial radia-
tion on the horizontal surface given by Iqbal (1983) as
follows:
sin si
24 π
π18 ncoscosi
0sn
Oossc
s
HIE
 
(2)
where,
21
13673600 MJ mh
10 ·
00000
sc
x
I (3)
is the solar constant,
360
10.33cos
365
o
N
E (4)
is the eccentricity correction,
N is the day number of the year (DoY)/Julian day (1
Jan, N = 1 and 31st December, N = 365), ϕ is the latitude
of the site,
360 284
23.45sin 365
N
(5)
is the solar declination,
1
costan tan
s

 (6)
is the hour angle,

1
22
costan tan
15 15
ds
N
 
(7)
is the maximum possible sunshine hours.
2.2. Developing a Model
The data presented in Table 1 has been used to evaluate
the regression constants a, b, c and d for the year men-
tioned in the table and the same technique used for other
years too. Three years’ values were averaged to derive
the final regression constants presented in Table 2.
To analyze these data further, the first order linear re-
gression equation was employed as given below:
T
abxcydz K
 (8)
It is an equation of least square line [15] or first order
regression [16] where, KT (= Hm/Ho) is a dependent vari-
able called clearness index, a, b, c, d are regression con-
stants, and

,,ln
av
dM
T
n
x
yzR
NT
 

 

 H
are independent variables and the earlier explained me-
teorological parameters.
To perform the regression analysis of least square line,
both sides of the Equation (8) have to be multiplied by 1,
x, and z successively and summing both sides to obtain: y
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
Copyright © 2013 SciRes. JPEE
4
Table 1. One year sum of different metrological parameters for four sites in Nepal to derive regression constants and used
meteorological data of the years.
Locations n/Nd Tav/TM ln (RH) KT = Hm/HO Used 1 Year Data Data of Years
Biratnagar 188.722 358.554 1579.288 171.751 2010, 365 days 2007, 2008, 2010
Kathmandu 198.129 356.3063 1574.593 175.878 2010, 365 days 2007, 2008, 2010
Pokhara 202.645 358.0092 1561.1 197.246 2010, 365 days 2008, 2010, 2012
Jumla 221.566 354.8842 1487.16 227.936 2011, 365 days 2011, 2012
Table 2. Regression constants, comparison of errors and regression coefficient for different models and sites.
Regression constants RMSE MBE MPE% R R² CC
SN Locations
a b c d Ang NewAngNew AngNewAng New Ang NewNew
1 Biratnagar 2 E07 0.1621.032 0.168 1.940.860.873 0.10 6.310.790.81 0.956 0.66 0.9140.96
2 Kathmandu 1 E04 0.3240.09 0.08 4.15 1.1972.32 0.866 11.520.340.70.948 0.44 0.8980.93
3 Pokhara 8 E06 0.3370.21 0.120 2.820.7500.6 0.14 2.351.02480.61 0.97 0.37 0.940.99
4 Jumla 1.4 E06 0.3840.40 0.001 4.401.6 2.350.425 10.52.640.49 0.87 0.24 0.750.86
T
aNbx cy dzK
 
(9)
2
T
axbx cxydxzKx 
  (10)
2
T
aybyxcydyz Ky
  (11)
2
T
azbzxczydz Kz 
  (12)
These four Equations (9) to (12) were used to evaluate
the regression constants a, b, c and d of three years for
Biratnagar (BRT), Kathmandu (KTM), and Pokhara (PKR)
separately and calculate the average value of respective
parameters and the same was done for Jumla (JUM) by
using the data of the 2 years.
2.3. Data Analysis
The accuracy of the estimated values was tested by using
the statistical techniques for the Angstrom-Prescott mo-
del and for the new proposed model based on the defini-
tion devised by Iqbal (1983) which is as below:


12
2
n
1em
RMSEH Hn


(13)

1
n
em
M
BEH Hn

(14)
1100
nme
m
HH
M
PE n
H



(15)





12
2
ememmm
eme mmm
HHH H
CC
HHH H



2
(16)
where n is the total numbers of observations, e
H
and
m
H
are monthly mean measured and estimated values
and mm
H
and me
H
are mean of measured and esti-
mated values respectively. Calculated values of different
parameters in organized form with coefficient of regres-
sion, R and coefficient of determinant, R2 derived from
the plots for the statistical analysis are presented in the
Table 2.
The above mentioned statistical indicators are used to
examine the performance of the model of solar radiation
estimation. In general, low values of root mean square
error (RMSE), mean bias (MBE) and mean percentage
error (MPE) are desirable. RSME test provides informa-
tion on the short-term performance whereas MBE and
MPE test provide information on the long-term perform-
ance. The positive MBE points out the overestimation
and negative MBE shows the underestimation [17] of the
radiations. Ideally correlation coefficient (CC), coeffi-
cient of regression (R) and coefficient of determinant (R2)
should be 1 for the best performance.
3. Result and Discussion
One year’s input parameters and three/two years data
were used to evaluate the regression constants, to de-
velop the linear regressions equations and hence estimate
monthly mean daily solar radiation
e
H
at four se-
lected sites in Nepal as presented in Table 1. Table 3
presents the three years’ monthly mean daily extraterres-
trial solar radiation, clearness index, fraction of sunshine
duration, ratio of average to maximum temperature and
natural logarithm of average humidity at four locations in
Nepal.
From the Table 3, it is manifested that clearness index
and sunshine hours vary with period of the year, condi-
tion of the sky and the location. Clearness index ob-
served minimum in July (Biratnagar 0.31, Kathmandu
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
5
Table 3. Monthly mean of daily solar and meteorological data.
O
H
T
K
d
nN av M
TT
L
NRH
BRT KTM PKR JUM BRT KTM PKR JUMBRTKTMPKR JUMBRT KTM PKR JUM BRT KTM PKRJUM
Jan 23.4 22.7 22.4 21.7 0.32 0.42 0.55 0.690.450.620.650.810.98 0.97 0.98 0.97 4.4 4.36 4.333.95
Feb 27.8 27.2 27 26.3 0.35 0.42 0.54 0.630.560.670.650.690.98 0.97 0.98 0.97 4.3 4.29 4.253.95
May 33.6 33.2 33.1 32.6 0.41 0.4 0.48 0.690.640.6 0.590.740.980.97 0.97 0.96 4.13 4.17 4.133.87
Apr 38.9 38.7 38.7 38.4 0.4 0.42 0.48 0.590.640.640.60.560.98 0.97 0.97 0.97 4.12 4.04 4.09 3.95
May 42.2 42.2 42.3 42.3 0.41 0.37 0.49 0.60.590.520.560.530.98 0.98 0.97 0.97 4.22 4.19 4.213.99
Jun 43.4 43.6 43.7 43.8 0.38 0.34 0.46 0.570.430.440.430.390.990.98 0.97 0.97 4.38 4.28 4.364.05
Jul 42.8 42.9 43 43.1 0.31 0.31 0.4 0.460.340.3 0.330.280.990.990.98 0.97 4.44 4.4 4.44.12
Aug 40.3 40.2 40.1 40.1 0.32 0.31 0.44 0.480.4 0.280.360.280.99 0.99 0.98 0.97 4.43 4.42 4.44.14
Sep 35.6 35.2 35 34.9 0.35 0.38 0.49 0.590.460.440.480.540.990.980.97 0.97 4.43 4.4 4.44.09
Oct 29.6 29.1 28.7 28.4 0.42 0.48 0.62 0.710.610.640.730.820.98 0.98 0.97 0.97 4.37 4.37 4.323.95
Nov 24.4 23.7 24.1 22.8 0.44 0.5 0.63 0.730.7 0.690.790.840.98 0.97 0.97 0.96 4.33 4.39 4.283.88
Dec 22 21.3 21 20.3 0.43 0.47 0.56 0.70.620.6 0.70.820.98 0.97 0.98 0.96 4.38 4.41 4.313.86
0.31, Pokhara 0.4 and Jumla 0.46) and August indicating
the overcast/cloud covered skies and more aerosols and
maximum value was observed in November (Biratnagar
0.44, Kathmandu 0.5, Pokhara 0.63 and Jumla 0.73) and
October suggesting the more clear skies with fewer
aerosols. Similarly high values of sunshine hours were
observed in November at all sites and among them high-
est value (0.84) was at Jumla (latitude 29.283˚, and alti-
tude 2300 m) and the least of maximum values (0.69)
was at Kathmandu (latitude 27.7˚, and altitude 1337 m)
because of high clearness index/sunshine hours. The
values are minimum in July and August due to less clear-
ness index/sunshine hours. Unexpected least values at
Kathmandu indicate the more hazy and pollutant par-
ticulates in the atmosphere above the Kathmandu valley.
Table 4 presents the measured and estimated monthly
mean daily global solar radiation at four different sites of
Nepal where their altitude varies from 72 m to 2300 m
above the sea level. These values were estimated by us-
ing the Angstrom-Prescott model and by the new pro-
posed model.
The minimum measured and estimated monthly mean
daily radiation on the horizontal surfaces for all sites
were observed in January characterized by more cloudy/
foggy days. And maximum values were observed in May
at Biratnagar, Pokhara and Jumla and in April at Kath-
mandu which is characterized by more clear skies and
less aerosols. Among four sites, maximum radiation
(measured m
H
= 25.21 MJ/m2·day and estimated e
H
= 25.25 MJ/m2·day) was observed at Jumla (2300 m
above the sea level) and minimum radiation (measured
m
H
= 7.508 MJ/m2·day and estimated e
H
= 7.97 MJ/
m2·day) was observed at Biratnagar (72 m above the sea
level). The result showed the altitude and location de-
pendency of the radiation. The table also shows the close
agreement of the measured and estimated values by the
new proposed model.
The least values of root mean square error RMSE,
mean bias error MBE and mean percentage error MPE
indicate the best linear regression relations to estimate
global solar radiation at Biratnagar, Kathmandu, Pokhara
and Jumla in Nepal.
In this study, three additional statistical indicators
were used to evaluate the accuracy and performance of
new proposed model. The highest value of R (=0.97 at
Pokhara) and minimum value of R (=0.87 at Jumla), the
higher correlation coefficient CC (0.86 at Jumla to 0.99
at Pokhara) and the Figures from 1-5 of the plots of
global solar radiations estimated by the Angstrom-Pres-
cott and new proposed model proved the higher per-
formance of the new proposed model in comparison to
Angstrom-Prescott model and the value estimated by
Poudyal, et al. [18].
4. Conclusions
Rational and accurate solar energy databases, essential
for designing, sizing and performing the solar energy
systems in any part of the world, are not easily accessible
in different localities of Nepal. The database of the solar
radiation at any locations is very useful for that particular
locality as well as for the broader world community [14]
for a sustainable future energy.
Important finding of this work is the linear regres-
sion analysis of the global solar radiation, sunshine
durations, temperature and relative humidity data
through least square technique that lead to the devel-
opment of this new proposed model showing the best
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
6
Table 4. Monthly mean daily measured and estimated global solar radiation.
Months Biratnagar Radiation Kathmandu Radiation Pokhara Radiation Jumla Radiation
m
H
eAng
H eNew
H m
H
eAng
HeNew
Hm
H
eAng
H eNew
H m
H
eAng
H eNew
H
JAN 7.51 6.90 7.97 9.54 11.32 10.30 12.31 13.40 11.95 15.04 16.56 15.15
FEB 9.82 10.36 10.41 11.35 14.93 12.71 14.5 16.16 14.15 16.75 17.00 17.16
MAR 13.92 14.41 13.98 13.21 16.02 14.40 15.93 17.93 16.24 22.38 22.71 21.98
APR 15.59 16.85 16.45 16.39 20.24 16.95 18.56 21.33 18.94 22.81 20.29 23.44
MAY 17.19 16.77 16.91 15.53 17.33 17.18 20.9 21.72 20.72 25.21 20.9 25.26
JUN 16.61 12.19 15.27 15.01 15.06 16.99 20.06 17.48 20.31 24.97 16.00 24.08
JUL 13.12 9.42 14.15 13.41 9.6 15.16 17.25 12.95 18.62 19.99 11.08 21.92
AUG 12.92 10.51 13.71 12.57 8.48 14.07 17.8 13.24 17.81 19.23 10.16 20.3
SEP 12.46 10.83 12.43 13.40 12.4 14.13 17.16 15.62 17.06 20.54 17.5 21.08
OCT 12.54 12.18 11.26 13.89 15.16 13.46 17.7 19.27 16.13 20.03 21.75 20.05
NOV 10.51 11.49 9.61 11.67 13.26 11.36 15.21 17.48 13.9 16.73 17.97 16.25
DEC 9.39 9.12 8.17 10.04 10.36 9.66 11.67 13.49 11.504 14.31 15.60 14.21
(a) (b)
(c) (d)
Figure 1. (a) Variation of radiation with months for Biratnaga; (b) Variation of radiation with months for Kathmandu; (c)
Variation of radiation with months for Pokhara; (d) Variation of radiation with months for Jumla.
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
7
Figure 2. Measured
m
H
versus estimation global solar radiation
e
H by Angstrom-Prescott model and new model for
Biratnagar.
Figure 3. Measured
m
H
versus estimation global solar radiation
e
H by Angstrom-Prescott model and new model for
Kathmandu.
correlation for Biratnagar, Kathmandu, Pokhara and
Jumla (from east to west) between measured and esti-
mated values in Nepal. The linear regression relations to
estimate/predict the global solar radiation on the hori-
zontal surface of Biratnagar, Kathmandu, Pokhara and
Jumla are as below:


2070.162
1.032 0.168ln
m
Od
av
M
Hn
E
HN
TRH
T

 





(17)


1040.324
0.09 0.08ln
m
Od
av
M
Hn
E
HN
TRH
T

 





(18)


8060.337
0.21 0.12ln
m
Od
av
M
Hn
E
HN
TRH
T







(19)
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
8
Figure 4. Measured
m
H
versus estimation global solar radiation
e
H by Angstrom-Prescott model and new model for
Pokhara.
Figure 5. Measured
m
H
versus estimation global solar radiation
e
H by Angstrom-Prescott model and new model for
Jumla.


1.407 0.384
0.400.001ln
m
Od
av
M
H
E
H
TRH
T

 





n
N
(20)
respectively.
Excellent agreement has been found between meas-
ured and estimated global solar radiation predicted by
linear regression equations (new proposed model). The
statistical/error analysis techniques/examination also con-
firm the better performance of the model at those sites;
they cover almost all parts of Nepal.
Jumla (high altitude location) is the place where high
potential of global solar radiation was observed and least
value of radiation was observed at Biratnagar (low alti-
tude location). But it is also obvious that ample solar
radiation is observed at all sites in Nepal. The new pro-
posed model may then be used to estimate daily and
monthly mean daily solar radiation for the locations of
similar geographical/meteorological characteristics and
also can be used to estimate the missing daily/monthly
mean daily solar radiation at the respective site. This
study recommends that Pokhara, Jumla and places hav-
ing similar altitude/geographical/meteorological parame-
ters, rather than terai region, are suitable for solar farm-
Copyright © 2013 SciRes. JPEE
Estimation of Global Solar Radiation for Four Selected Sites in Nepal Using Sunshine Hours,
Temperature and Relative Humidity
9
ing activities in Nepal.
5. Acknowledgements
Authors gratefully express sincere thanks to University
Grant Commission, Nepal for providing assistance in the
form of scholarship and assistantship for this research
work and are indebted to Solar Radiation and Aerosol in
Himalaya Region (SAHR) project, Pulchowk, Nepal and
Department of Hydrology and Meteorology/GoN for mak-
ing the data available.
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Copyright © 2013 SciRes. JPEE