The Experts below are selected from a list of 222 Experts worldwide ranked by ideXlab platform
S. Soulayman - One of the best experts on this subject based on the ideXlab platform.
-
Comments on “Optimum tilt angle for flat plate collectors all over the World – A Declination dependence formula and comparisons of three Solar radiation models”, by Stanciu, C. and Stanciu, D. [Energy Convers. Manage. 81 (2014) 133–143]
Energy Conversion and Management, 2015Co-Authors: S. SoulaymanAbstract:Abstract Stanciu and Stanciu [1] mentioned that when using the Hottel and Woertz model for estimating the incident Solar radiation, the daily optimum tilt angle B opt,d for a flat plate collector could be computed as simplest as B opt,d = L − δ function on the latitude, L , and Solar Declination, δ , with emphasizing that this equation is applicable all over the world from 0° latitude to 80° and the novelty of their work consists in finding this global optimum instead of “local” ones for which monthly adjustment is required. The present comments are focused on these statements and the novelty of this work.
-
Comments on "optimum tilt angle for flat plate collectors all over the World - A Declination dependence formula and comparisons of three Solar radiation models", by Stanciu, C. and Stanciu, D. [Energy Convers. Manage. 81 (2014) 133-143]
Energy Conversion and Management, 2015Co-Authors: S. SoulaymanAbstract:Stanciu and Stanciu [1] mentioned that when using the Hottel and Woertz model for estimating the incident Solar radiation, the daily optimum tilt angle Bopt,dfor a flat plate collector could be computed as simplest as Bopt,d= L - δ function on the latitude, L, and Solar Declination, δ, with emphasizing that this equation is applicable all over the world from 0° latitude to 80° and the novelty of their work consists in finding this global optimum instead of "local" ones for which monthly adjustment is required. The present comments are focused on these statements and the novelty of this work.
Abdoulaye Ouedraogo - One of the best experts on this subject based on the ideXlab platform.
-
Correlation of Global Solar Radiation of Eight Synoptic Stations in Burkina Faso Based on Linear and Multiple Linear Regression Methods
Journal of Solar Energy, 2016Co-Authors: Ousmane Coulibaly, Abdoulaye OuedraogoAbstract:We utilize the multiple linear regression method to analyse meteorological data for eight cities in Burkina Faso. A correlation between the monthly mean daily global Solar radiation on a horizontal surface and five meteorological and geographical parameters, which are the mean daily extraterrestrial Solar radiation intensity, the average daily ratio of sunshine duration, the mean daily relative humidity, the mean daily maximum air temperature, and the sine of the Solar Declination angle, was examined. A second correlation is established for the entire country, using, this time, the monthly mean global Solar radiation on a horizontal surface and the following climatic variables: the average daily ratio of sunshine duration, the latitude, and the longitude. The results show that the coefficients of correlation vary between 0.96 and 0.99 depending on the station while the relative errors spread between −3.16% (Po) and 3.65% (Dedougou). The maximum value of the RMSD which is 312.36 kJ/m2 is obtained at Dori, which receives the strongest radiation. For the entire cities, the values of the MBD are found to be in the acceptable margin.
-
Correlation of Global Solar Radiation of Eight Synoptic Stations in Burkina Faso Based on Linear and Multiple Linear Regression Methods
Journal of Solar Energy, 2016Co-Authors: Ousmane Coulibaly, Abdoulaye OuedraogoAbstract:We utilize the multiple linear regression method to analyse meteorological data for eight cities in Burkina Faso. A correlation between the monthly mean daily global Solar radiation on a horizontal surface and five meteorological and geographical parameters, which are the mean daily extraterrestrial Solar radiation intensity, the average daily ratio of sunshine duration, the mean daily relative humidity, the mean daily maximum air temperature, and the sine of the Solar Declination angle, was examined. A second correlation is established for the entire country, using, this time, the monthly mean global Solar radiation on a horizontal surface and the following climatic variables: the average daily ratio of sunshine duration, the latitude, and the longitude. The results show that the coefficients of correlation vary between 0.96 and 0.99 depending on the station while the relative errors spread between −3.16% (Pô) and 3.65% (Dédougou). The maximum value of the RMSD which is 312.36 kJ/m 2 is obtained at Dori, which receives the strongest radiation. For the entire cities, the values of the MBD are found to be in the acceptable margin.
Joonas Kiviranta - One of the best experts on this subject based on the ideXlab platform.
-
An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin-SMR measurements
Atmospheric Chemistry and Physics, 2018Co-Authors: Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, Donal P. MurtaghAbstract:Abstract. Nitric oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin sub-millimeter radiometer (SMR) to build an empirical model that links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K index, Solar Declination, and the F10.7 cm flux, as well as two newly devised indices that take the planetary K index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 and 115 km and between 80 ∘ S and 80 ∘ N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31 %–70 % of the variance of the measured datasets near the magnetic poles, and between 16 % and 73 % near the magnetic equator. The corresponding values for NOEM are 12 %–38 % and 7 %–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA span over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only cover 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days that can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as a priori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se (last access: 15 September 2018).
-
Empirical Modeling of Solar Induced Variations of Nitric Oxide in the Upper Mesosphere and Lower Thermosphere
2018Co-Authors: Joonas KivirantaAbstract:Nitric Oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This thesis uses measurements of NO taken between 2004 and 2016 by the Odin Sub Millimetre Radiometer (SMR) to build an empirical model which links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K-index, Solar Declination, and the F10.7cm flux, and two newly devised indices which take the planetary K-index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the previously mentioned indices to estimate NO between 85 km-115 km and 80◦ S-80◦ N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR-dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31-70% of the variance of the measured datasets near the magnetic poles, and between 16-73% near the magnetic equator. The corresponding values for NOEM are 12-38% and 7-40%, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for the entire latitude range was on average 20% larger for SANOMA, and 78% larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA spans over 12 years covering more than one Solar cycle, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only covers two years (1998-2000). Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days which can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical climate models, as apriori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments.
-
An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin-SMR measurements
2018Co-Authors: Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, Donal P. MurtaghAbstract:Abstract. Nitric Oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin Sub Millimetre Radiometer (SMR) to build an empirical model which links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K-index, Solar Declination, and the F10.7cm flux, and two newly devised indices which take the planetary K-index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 km–115 km and 80° S–80° N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR-dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31–70 % of the variance of the measured datasets near the magnetic poles, and between 16–73 % near the magnetic equator. The corresponding values for NOEM are 12–38 % and 7–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA spans over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only covers 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days which can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as apriori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se.
-
An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin SMR measurements
Copernicus Publications, 2018Co-Authors: Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, Donal P. MurtaghAbstract:Nitric oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin sub-millimeter radiometer (SMR) to build an empirical model that links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K index, Solar Declination, and the F10.7 cm flux, as well as two newly devised indices that take the planetary K index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 and 115 km and between 80° S and 80° N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31 %–70 % of the variance of the measured datasets near the magnetic poles, and between 16 % and 73 % near the magnetic equator. The corresponding values for NOEM are 12 %–38 % and 7 %–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA span over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only cover 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days that can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as a priori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se (last access: 15 September 2018).
Donal P. Murtagh - One of the best experts on this subject based on the ideXlab platform.
-
An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin-SMR measurements
Atmospheric Chemistry and Physics, 2018Co-Authors: Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, Donal P. MurtaghAbstract:Abstract. Nitric oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin sub-millimeter radiometer (SMR) to build an empirical model that links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K index, Solar Declination, and the F10.7 cm flux, as well as two newly devised indices that take the planetary K index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 and 115 km and between 80 ∘ S and 80 ∘ N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31 %–70 % of the variance of the measured datasets near the magnetic poles, and between 16 % and 73 % near the magnetic equator. The corresponding values for NOEM are 12 %–38 % and 7 %–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA span over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only cover 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days that can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as a priori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se (last access: 15 September 2018).
-
An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin-SMR measurements
2018Co-Authors: Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, Donal P. MurtaghAbstract:Abstract. Nitric Oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin Sub Millimetre Radiometer (SMR) to build an empirical model which links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K-index, Solar Declination, and the F10.7cm flux, and two newly devised indices which take the planetary K-index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 km–115 km and 80° S–80° N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR-dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31–70 % of the variance of the measured datasets near the magnetic poles, and between 16–73 % near the magnetic equator. The corresponding values for NOEM are 12–38 % and 7–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA spans over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only covers 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days which can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as apriori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se.
-
An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin SMR measurements
Copernicus Publications, 2018Co-Authors: Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, Donal P. MurtaghAbstract:Nitric oxide (NO) is produced by Solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin sub-millimeter radiometer (SMR) to build an empirical model that links the prevailing Solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K index, Solar Declination, and the F10.7 cm flux, as well as two newly devised indices that take the planetary K index and the Solar Declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 and 115 km and between 80° S and 80° N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31 %–70 % of the variance of the measured datasets near the magnetic poles, and between 16 % and 73 % near the magnetic equator. The corresponding values for NOEM are 12 %–38 % and 7 %–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA span over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only cover 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days that can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as a priori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se (last access: 15 September 2018).
Ousmane Coulibaly - One of the best experts on this subject based on the ideXlab platform.
-
Correlation of Global Solar Radiation of Eight Synoptic Stations in Burkina Faso Based on Linear and Multiple Linear Regression Methods
Journal of Solar Energy, 2016Co-Authors: Ousmane Coulibaly, Abdoulaye OuedraogoAbstract:We utilize the multiple linear regression method to analyse meteorological data for eight cities in Burkina Faso. A correlation between the monthly mean daily global Solar radiation on a horizontal surface and five meteorological and geographical parameters, which are the mean daily extraterrestrial Solar radiation intensity, the average daily ratio of sunshine duration, the mean daily relative humidity, the mean daily maximum air temperature, and the sine of the Solar Declination angle, was examined. A second correlation is established for the entire country, using, this time, the monthly mean global Solar radiation on a horizontal surface and the following climatic variables: the average daily ratio of sunshine duration, the latitude, and the longitude. The results show that the coefficients of correlation vary between 0.96 and 0.99 depending on the station while the relative errors spread between −3.16% (Po) and 3.65% (Dedougou). The maximum value of the RMSD which is 312.36 kJ/m2 is obtained at Dori, which receives the strongest radiation. For the entire cities, the values of the MBD are found to be in the acceptable margin.
-
Correlation of Global Solar Radiation of Eight Synoptic Stations in Burkina Faso Based on Linear and Multiple Linear Regression Methods
Journal of Solar Energy, 2016Co-Authors: Ousmane Coulibaly, Abdoulaye OuedraogoAbstract:We utilize the multiple linear regression method to analyse meteorological data for eight cities in Burkina Faso. A correlation between the monthly mean daily global Solar radiation on a horizontal surface and five meteorological and geographical parameters, which are the mean daily extraterrestrial Solar radiation intensity, the average daily ratio of sunshine duration, the mean daily relative humidity, the mean daily maximum air temperature, and the sine of the Solar Declination angle, was examined. A second correlation is established for the entire country, using, this time, the monthly mean global Solar radiation on a horizontal surface and the following climatic variables: the average daily ratio of sunshine duration, the latitude, and the longitude. The results show that the coefficients of correlation vary between 0.96 and 0.99 depending on the station while the relative errors spread between −3.16% (Pô) and 3.65% (Dédougou). The maximum value of the RMSD which is 312.36 kJ/m 2 is obtained at Dori, which receives the strongest radiation. For the entire cities, the values of the MBD are found to be in the acceptable margin.
