Seasonal Variations of Atmospheric Clearness Numbers for Use in Solar Radiation Modelling

1981 ◽  
Vol 5 (3) ◽  
pp. 185-187 ◽  
Author(s):  
D. Y. Goswami ◽  
D. E. Klett ◽  
E. K. Stefanakos ◽  
T.K. Goswami
Keyword(s):  
Solar Radiation ◽  
Seasonal Variations ◽  
Radiation Modelling

scholarly journals Correcting solar radiation from Reanalysis and Analysis datasets with systematic and seasonal variations

2021 ◽  
pp. 100933
Author(s):  
Zia ul Rehman Tahir ◽  
Muhammad Asim ◽  
Muhammad Azhar ◽  
Ghulam Moeenuddin ◽  
Muhammad Farooq
Keyword(s):  
Solar Radiation ◽  
Seasonal Variations

scholarly journals The effects of daily meteorological perturbation on pregnancy outcome: follow-up of a cohort of young women undergoing IVF treatment

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Mingpeng Zhao ◽  
Haoyang Zhang ◽  
Tarah H. B. Waters ◽  
Jacqueline Pui Wah Chung ◽  
Tin Chiu Li ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Time Series Analysis ◽  
Subgroup Analysis ◽  
Seasonal Variations ◽  
Multiple Logistic Regression Analysis ◽  
Human Reproduction ◽  
Mixed Effect ◽  
Series Analysis ◽  
Patient Consent

Abstract Background Human reproduction follows a seasonal pattern with respect to spontaneous conception, a phenomenon wherein the effect of meteorological fluctuations might not be unique. However, the effect of seasonal variations on patients who underwent in vitro fertilization (IVF) treatment is unclear. We aimed to evaluate the effects of meteorological variation on the pregnancy rate in a cohort undergoing IVF treatment by performing multivariable analyses. Methods We conducted a cohort study in a sub-tropical region with prominent seasonal variations (2005–2016). Women aged < 35 years who were treated with a long ovarian stimulation protocol and underwent fresh embryo transfer (ER) were included. Data on gonadotropin administration (CYCL), oocyte retrieval (OR), ER, and pregnancy outcomes were prospectively recorded. For each patient, the daily average of meteorological data (temperature, humidity, sunlight duration, solar radiation) was recorded from the date of CYCL to ER. Multiple logistic regression analysis adjusted for age, fertilization method, year of the cycle, gonadotropin dose, and transferred embryo grade was performed to determine the relationship between the meteorological parameters and clinical pregnancy. Patients with one successful cycle and one failed cycle were subtracted for a case-control subgroup analysis through mixed effect logistics regressions. Time-series analysis of data in the epidemic level was conducted using the distributed lag linear and non-linear models (DLNMs). Results There were 1029 fresh cycles in 860 women (mean age 31.9 ± 2.0 years). Higher mean temperature from CYCL to OR (adjusted odds ratio [aOR] 1.04; 95% confidence interval [CI] 1.01–1.07, P = 0.01) increased the odds of pregnancy, while OR to ER did not show any statistical significance. Compared to that in winter, the odds of becoming pregnant were higher during higher temperature seasons, summer and autumn (aOR 1.47, 95%CI 0.97–2.23, P = 0.07 (marginally significant) and aOR 1.73, 95%CI 1.12–2.68, P = 0.02, respectively). Humidity, sunlight duration, and solar radiation had no effect on the outcome. The subgroup analysis confirmed this finding. The time-series analysis revealed a positive association between temperature and relative risk for pregnancy. Conclusions In IVF treatment, the ambient temperature variation alters the pregnancy rates; this aspect must be considered when obtaining patient consent for assisted conception.

scholarly journals Evaluation of Solar Radiation Transposition Models for Passive Energy Management and Building Integrated Photovoltaics

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 702 ◽  
Author(s):  
Carlos Toledo ◽  
Ana Maria Gracia Amillo ◽  
Giorgio Bardizza ◽  
Jose Abad ◽  
Antonio Urbina
Keyword(s):  
Solar Radiation ◽  
Horizontal Plane ◽  
Architectural Design ◽  
Operating Conditions ◽  
Geographical Information ◽  
Medium Temperature ◽  
Building Integrated Photovoltaics ◽  
Wide Range ◽  
Radiation Modelling ◽  
Winter Time

Incident solar radiation modelling has become of vital importance not only in architectural design considerations, but also in the estimation of the energy production of photovoltaic systems. This is particularly true in the case of buildings with integrated photovoltaics (PV) systems having a wide range of orientations and inclinations defined by the skin of the building. Since solar radiation data at the plane of interest is hardly ever available, this study presents the analysis of two of the most representative transposition models used to obtain the in-plane irradiance using as input data the global and diffuse irradiation on the horizontal plane, which can be obtained by satellite-based models or ground measurements. Both transposition models are validated with experimental measurements taken in Murcia (southeast of Spain) and datasets provided by the photovoltaic geographical information system (PVGIS) and the National Renewable Energy Laboratory (NREL) for vertical surfaces facing the four cardinal points. For the validation, the mean bias deviation, root mean square error and forecasted skill were used as indicators. Results show that the error rate decreases slightly for clear days. Better results are also obtained by dismissing data with low solar elevation angles so as to avoid shadowing effects from the surroundings in the early and late hours of the day, which affects mainly the performance of the transposition models for west and east surfaces. The results highlight the potential of equator-facing façades in winter time when the received irradiation can be twice as much as the one collected by the horizontal plane. It is also noteworthy that the operating conditions of all façades are mainly low irradiance and medium temperature at these locations.

Predicting the spectral and broadband aerosol transmittance in the atmosphere for solar radiation modelling

1997 ◽  
Vol 12 (3) ◽  
pp. 259-279 ◽  
Author(s):  
B.E. Psiloglou ◽  
M. Santamouris ◽  
D.N. Asimakopoulos
Keyword(s):  
Solar Radiation ◽  
Radiation Modelling
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