Modeling the relationship between photosynthetically active radiation and global horizontal irradiance using singular spectrum analysis

Zempila, Μ. Μ.; Taylor, Michael; Bais, A. F.; Kazadzis, Stelios

doi:10.1016/j.jqsrt.2016.06.003

Cited by 20 publications

(12 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other empirical models include these parameters and others but involving a more complicated formulation. Moreover, small improvements of non‐linear models over linear models have been detected (Zempila et al , ).…”

Section: Resultsmentioning

confidence: 99%

“…Thus, the most adequate variables to model Q p are θ and k t . Zempila et al () developed and assessed the performance of linear regression, multiple linear regression and non‐linear neural networks to calculate Q p from R s measurements using also information about θ , the columnar perceptible water vapour and the aerosol optical depth. Jacovides et al () also used ANN models for estimating daily solar global UV, Q p and broadband radiant fluxes in an Eastern Mediterranean site.…”

Section: Resultsmentioning

confidence: 99%

“…Other empirical models include these parameters and others but involving a more complicated formulation. Moreover, small improvements of non-linear models over linear models have been detected (Zempila et al, 2016). Table 3 shows the results obtained for each station including the coefficient of determination R 2 -the fraction of experimental data variance explained by the model -the slope b, and the intercept a of the linear regression of estimated Q p versus measured values.…”

Section: Performance Of Modelmentioning

confidence: 99%

See 2 more Smart Citations

A new conventional regression model to estimate hourly photosynthetic photon flux density under all sky conditions

Foyo-Moreno

Alados

Alados-Arboledas

2017

Intl Journal of Climatology

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Performance Of Modelmentioning

confidence: 99%

See 1 more Smart Citation

A new conventional regression model to estimate hourly photosynthetic photon flux density under all sky conditions

Foyo-Moreno

Alados

Alados-Arboledas

2017

Intl Journal of Climatology

View full text Add to dashboard Cite

“…Another alternative method for estimating solar radiation is using different artificial intelligence (AI) techniques. Recently, artificial neural networks (ANNs), M5 model tree (M5Tree), adaptive neuro‐fuzzy inference systems (ANFIS) and Genetic programming approaches have been successfully used in a wide range of scientific applications including surface energy budget, hydrometeorology and ecology (Lopez et al , ; Bhardwaj et al , ; Kumar et al , ; Zempila et al , ). One of the major advantages of AI methods is that they do not require any input assumptions (Moghaddamnia et al , ).…”

Section: Introductionmentioning

confidence: 99%

Prediction of diffuse photosynthetically active radiation using different soft computing techniques

Wang

Kisi

et al. 2017

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

Knowledge of diffuse photosynthetically active radiation (PARd) is important for many applications dealing with climate change, environmental engineering and terrestrial productivity. It is necessary to estimate the PARd using different techniques due to the absence of direct observations of this radiometric flux in most parts of the world. In this study, Adaptive Neuro‐Fuzzy Inference Systems (ANFIS) with grid partition (ANFIS‐GP), ANFIS with subtractive clustering (ANFIS‐SC) and M5 model tree (M5Tree) are optimized and applied for predicting hourly PARd in different ecosystems. Hourly climatic variables at six stations from the AmeriFlux network are used for training, validating and testing the above models. It is observed that the mean bias error (MBE) values range −11 to +18%, −16 to +9% and −10 to +9% for ANFIS‐GP, ANFIS‐SC and M5Tree models, respectively; root mean square errors (RMSE) range 25–44%, 22–41% and 29–51%, respectively for different stations in the testing period. The results show that the ANFIS‐SC model can generally bring more accurate estimations than other models, and the statistical indices (MBE and RMSE) at CA_Gro stations (mixed forests) are lower than other stations for each model. The models underestimate some high PARd values (>900 µmol m−2 s−1) for some stations, which may due to the differences of data ranges and distributions. This study will lay the foundation for accurately mapping regional and global distributions of PARd and its associated ecological applications.

show abstract

“…Mizoguchi et al (2014) provided an empirical model for calculating PAR based on measured solar radiation, atmospheric pressure, air temperature and relative humidity (RH). Recently, artificial intelligence techniques have been successfully used in estimating PAR (Kumar et al, 2015;Zempila et al, 2016). However, previous study results indicated that both semi-physical and empirical estimation methods should be recalibrated according to local conditions (Gonzalez and Calbo, 2002;Hu et al, 2007;Wang et al, 2015a).…”

mentioning

confidence: 99%

Trends of photosynthetically active radiation over China from 1961 to 2014

Tang

Liu

et al. 2018

Intl Journal of Climatology

View full text Add to dashboard Cite

The aim of this study was to reveal the long‐term variation properties of photosynthetically active radiation (PAR) over China. A series of reliable empirical PAR estimation equations suitable for all‐sky conditions were developed using data measured in situ from 2005 to 2014, which were obtained from the Chinese Ecosystem Research Network (CERN). These equations were then combined with a hybrid model to reconstruct the PAR from 1961 to 2014 for 724 weather stations belonging to the China Meteorological Administration (CMA). There was a decreasing linear trend in the PAR (with an amplitude of −0.009 mol m−2 day−1 year−1) from 1961 to 1981 and a steady low level of −0.003 mol m−2 day−1 year−1 during 1981–2014 for all of China. The PAR over the Tibetan Plateau (TP) region increased from 1961 to 1984; then, this linear trend slightly changed. The breakpoint years for the northwest China (NWC), southwest China (SWC), north China (NC), northeast China (NEC) and east China (EC) regions were 1985, 1981, 1996, 1998 and 1979, respectively. In addition, the aerosol optical depth, ozone column concentration, cloud cover and water vapour content attenuated the PAR that would otherwise have reached the earth’s surface by approximately 7.59, 1.12, 18.13 and 6.20%, respectively.

show abstract

Modeling the relationship between photosynthetically active radiation and global horizontal irradiance using singular spectrum analysis

Cited by 20 publications

References 79 publications

A new conventional regression model to estimate hourly photosynthetic photon flux density under all sky conditions

A new conventional regression model to estimate hourly photosynthetic photon flux density under all sky conditions

Prediction of diffuse photosynthetically active radiation using different soft computing techniques

Trends of photosynthetically active radiation over China from 1961 to 2014

Contact Info

Product

Resources

About