scholarly journals Statistical Analysis and InterComparison of Solar UV and Global Radiation for Athalassa and Larnaca,Cyprus.

2017 ◽  
Vol 2 (2) ◽  
pp. 1-16
Author(s):  
Pashiardis S ◽  
Kalogirou SA ◽  
Pelengaris A
Keyword(s):  
Statistical Analysis ◽  
Global Radiation ◽  
Solar Uv

Statistical analysis of solar UVB and global radiation in Kuwait

Energy ◽  
2013 ◽  
Vol 60 ◽  
pp. 23-34 ◽  
Author(s):  
Adel A. Ghoneim ◽  
Ibrahim M. Kadad ◽  
Majida S. Altouq
Keyword(s):  
Statistical Analysis ◽  
Global Radiation

scholarly journals Modelling of UV radiation variations at different time scales

2008 ◽  
Vol 26 (3) ◽  
pp. 441-446 ◽  
Author(s):  
J. L. Borkowski
Keyword(s):  
Uv Radiation ◽  
Time Scales ◽  
Time Scale ◽  
Global Radiation ◽  
Regression Method ◽  
Ozone Content ◽  
Explanatory Variables ◽  
Solar Uv ◽  
Solar Global Radiation ◽  
Different Time Scales

Abstract. Solar UV radiation variability in the period 1976–2006 is discussed with respect to the relative changes in the solar global radiation, ozone content, and cloudiness. All the variables were decomposed into separate components, representing variations of different time scales, using wavelet multi-resolution decomposition. The response of the UV radiation to the changes in the solar global radiation, ozone content, and cloudiness depends on the time scale, therefore, it seems reasonable to model separately the relation between UV and explanatory variables at different time scales. The wavelet components of the UV series are modelled and summed to obtain the fit of observed series. The results show that the coarser time scale components can be modelled with greater accuracy than fine scale components and the fitted values calculated by this method are in better agreement with observed values than values calculated by the regression method, in which variables were not decomposed. The residual standard error in the case of modelling with the use of wavelets is reduced by 14% in comparison to the regression method without decomposition.

scholarly journals European UV DataBase (EUVDB) as a repository and quality analyser for solar spectral UV irradiance monitored in Sodankylä

2016 ◽  
Vol 5 (2) ◽  
pp. 333-345 ◽  
Author(s):  
Anu Heikkilä ◽  
Jussi Kaurola ◽  
Kaisa Lakkala ◽  
Juha Matti Karhu ◽  
Esko Kyrö ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Statistical Analysis ◽  
Quality Indicators ◽  
Uv Spectra ◽  
Measured Data ◽  
Uv Irradiance ◽  
Atmospheric Data ◽  
Solar Uv

Abstract. Databases gathering atmospheric data have great potential not only as data storages but also in serving as platforms for coherent quality assurance (QA). We report on the flagging system and QA tools designed for and implemented in the European UV DataBase (EUVDB; http://uv.fmi.fi/uvdb/) for measured data on solar spectral UV irradiance. We confine the study on the data measured by Brewer #037 MkII spectroradiometer in Sodankylä (67.37° N, 26.63° E) in 1990–2014. The quality indicators associated with the UV irradiance spectra uploaded into the database are retrieved from the database and subjected to a statistical analysis. The study demonstrates the performance of the QA tools of the EUVDB. In addition, it yields an overall view of the availability and quality of the solar UV spectra recorded in Sodankylä over a quarter of a century. Over 90 % of the four main quality indicators are flagged as GREEN, indicating the highest achievable quality. For the BLACK flags, denoting data not meeting the pre-defined requirements, the percentages for all the indicators remain below 0.12 %.

scholarly journals Long-term solar UV radiation reconstructed by ANN modelling with emphasis on spatial characteristics of input data

2008 ◽  
Vol 8 (12) ◽  
pp. 3107-3118 ◽  
Author(s):  
U. Feister ◽  
J. Junk ◽  
M. Woldt ◽  
A. Bais ◽  
A. Helbig ◽  
...  
Keyword(s):  
Uv Radiation ◽  
Input Data ◽  
Global Radiation ◽  
Small Scale ◽  
Ann Model ◽  
Solar Uv Radiation ◽  
Solar Uv ◽  
Global Dimming ◽  
Column Ozone

Abstract. Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Special emphasis will be given to the discussion of small-scale characteristics of input data to the ANN model. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980/1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

scholarly journals Long-term solar UV radiation reconstructed by Artificial Neural Networks (ANN)

2008 ◽  
Vol 8 (1) ◽  
pp. 453-488 ◽  
Author(s):  
U. Feister ◽  
J. Junk ◽  
M. Woldt
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Uv Radiation ◽  
Global Radiation ◽  
Ann Model ◽  
Solar Uv Radiation ◽  
Solar Uv ◽  
Artificial Neural ◽  
Global Dimming

Abstract. Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980–1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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