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Performance analysis of daily global solar radiation models in peru by regression analysis

Mohammadi, Babak LU orcid and Moazenzadeh, Roozbeh (2021) In Atmosphere 12(3).
Abstract

Solar radiation (Rs) is one of the main parameters controlling the energy balance at the Earth’s surface and plays a major role in evapotranspiration and plant growth, snow melting, and environmental studies. This work aimed at evaluating the performance of seven empirical models in estimating daily solar radiation over 1990–2004 (calibration) and 2004–2010 (validation) at 13 Peruvian meteorological stations. With the same variables used in empirical models (temperature) as well as two other parameters, namely precipitation and relative humidity, new models were developed by multiple linear regression analysis (proposed models). In calibration of empirical models with the same variables, the lowest estimation errors were 227.1 and 236.3... (More)

Solar radiation (Rs) is one of the main parameters controlling the energy balance at the Earth’s surface and plays a major role in evapotranspiration and plant growth, snow melting, and environmental studies. This work aimed at evaluating the performance of seven empirical models in estimating daily solar radiation over 1990–2004 (calibration) and 2004–2010 (validation) at 13 Peruvian meteorological stations. With the same variables used in empirical models (temperature) as well as two other parameters, namely precipitation and relative humidity, new models were developed by multiple linear regression analysis (proposed models). In calibration of empirical models with the same variables, the lowest estimation errors were 227.1 and 236.3 J∙cm−2∙day−1 at Tacna and Puno stations, and the highest errors were 3958.4 and 3005.7 at San Ramon and Junin stations, respectively. The poorest‐performing empirical models greatly overestimated Rs at most stations. The best performance of a proposed model (in terms of percentage of error reduction) was 73% compared to the average of all empirical models and 93% relative to the poorest result of empirical models, both at San Ramon station. According to root mean square errors (RMSEs) of proposed models, the worst and the best results are achieved at San Martin station (RMSE = 508.8 J∙cm−2∙day−1) and Tacna station (RMSE = 223.2 J∙cm−2∙day−1 ), respectively.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Hydrometeorology, Peru, Regression models, Renewable energy, Solar radiation, Temperature‐based models
in
Atmosphere
volume
12
issue
3
article number
389
publisher
MDPI AG
external identifiers
  • scopus:85103457291
ISSN
2073-4433
DOI
10.3390/atmos12030389
language
English
LU publication?
yes
id
21d8dd68-b285-44c2-bda5-5990dbd8e31c
date added to LUP
2021-04-12 10:06:53
date last changed
2024-01-24 11:03:49
@article{21d8dd68-b285-44c2-bda5-5990dbd8e31c,
  abstract     = {{<p>Solar radiation (Rs) is one of the main parameters controlling the energy balance at the Earth’s surface and plays a major role in evapotranspiration and plant growth, snow melting, and environmental studies. This work aimed at evaluating the performance of seven empirical models in estimating daily solar radiation over 1990–2004 (calibration) and 2004–2010 (validation) at 13 Peruvian meteorological stations. With the same variables used in empirical models (temperature) as well as two other parameters, namely precipitation and relative humidity, new models were developed by multiple linear regression analysis (proposed models). In calibration of empirical models with the same variables, the lowest estimation errors were 227.1 and 236.3 J∙cm<sup>−2</sup>∙day<sup>−1</sup> at Tacna and Puno stations, and the highest errors were 3958.4 and 3005.7 at San Ramon and Junin stations, respectively. The poorest‐performing empirical models greatly overestimated Rs at most stations. The best performance of a proposed model (in terms of percentage of error reduction) was 73% compared to the average of all empirical models and 93% relative to the poorest result of empirical models, both at San Ramon station. According to root mean square errors (RMSEs) of proposed models, the worst and the best results are achieved at San Martin station (RMSE = 508.8 J∙cm<sup>−2</sup>∙day<sup>−1</sup>) and Tacna station (RMSE = 223.2 J∙cm<sup>−2</sup>∙day<sup>−1</sup> ), respectively.</p>}},
  author       = {{Mohammadi, Babak and Moazenzadeh, Roozbeh}},
  issn         = {{2073-4433}},
  keywords     = {{Hydrometeorology; Peru; Regression models; Renewable energy; Solar radiation; Temperature‐based models}},
  language     = {{eng}},
  number       = {{3}},
  publisher    = {{MDPI AG}},
  series       = {{Atmosphere}},
  title        = {{Performance analysis of daily global solar radiation models in peru by regression analysis}},
  url          = {{http://dx.doi.org/10.3390/atmos12030389}},
  doi          = {{10.3390/atmos12030389}},
  volume       = {{12}},
  year         = {{2021}},
}