scholarly journals Correction: Ferreira, P.M., et al. A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature. Sensors 2012, 12, 15750–15777

Sensors ◽  
2013 ◽  
Vol 13 (7) ◽  
pp. 9547-9548
Author(s):  
Pedro Ferreira ◽  
João Gomes ◽  
Igor Martins ◽  
António Ruano
Keyword(s):  
Neural Network ◽  
Solar Radiation ◽  
Air Temperature ◽  
Temperature Sensors

scholarly journals Outdoor Air Temperature Measurement: A Semi-Empirical Model to Characterize Shelter Performance

Climate ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 26
Author(s):  
Jérémy Bernard ◽  
Pascal Kéravec ◽  
Benjamin Morille ◽  
Erwan Bocher ◽  
Marjorie Musy ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Response Time ◽  
Air Temperature ◽  
Empirical Model ◽  
Regression Coefficient ◽  
Radiation Sensitivity ◽  
Temperature Sensors ◽  
Outdoor Air ◽  
The One ◽  
Semi Empirical

Shelters used to protect air temperature sensors from solar radiation induce a measurement error. This work presents a semi-empirical model based on meteorological variables to evaluate this error. The model equation is based on the analytical solution of a simplified energy balance performed on a naturally ventilated shelter. Two main physical error causes are identified from this equation: one is due to the shelter response time and the other is due to its solar radiation sensitivity. A shelter intercomparison measurement campaign performed by the World Meteorological Organization (WMO) is used to perform a non-linear regression of the model coefficients. The regression coefficient values obtained for each shelter are found to be consistent with their expected physical behavior. They are then used to simply classify shelters according to their response time and radiation sensitivity characteristics. Finally, the ability of the model to estimate the temperature error within a given shelter is assessed and compared to the one of two existing models (proposed by Cheng and by Nakamura). For low-response-time shelters, our results reduce the root mean square error by about 15% (0.07 K) on average when compared with other compensation schemes.

scholarly journals Errors of Naturally Ventilated Air Temperature Measurements in a Spatial Observation Network

2008 ◽  
Vol 25 (11) ◽  
pp. 2145-2151 ◽  
Author(s):  
Matthias Mauder ◽  
R. L. Desjardins ◽  
Zhiling Gao ◽  
Ronald van Haarlem
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Agricultural Land ◽  
Sensible Heat Flux ◽  
Temperature Sensors ◽  
Radiative Heating ◽  
Temperature Measurements ◽  
Observation Network ◽  
Temporal Averaging ◽  
Radiation Shields

Abstract A spatial network of 25 air temperature sensors was deployed over an area of 3.5 km × 3.5 km of agricultural land, aiming to calculate the sensible heat flux by spatial averaging instead of temporal averaging. Since temperature sensors in naturally ventilated solar radiation shields were used for these measurements, a correction for radiative heating had to be applied. In this study, the approach of Anderson and Baumgartner was adapted to the cube-shaped HOBO solar radiation shields. This semiempirical correction depends on the shield’s area normal to the sun in addition to solar radiation and wind speed. The required correction coefficients, which can be universally applied for this type of shield, were obtained through comparison with fan-aspirated temperature measurements at one site. The root-mean-square error of the HOBO temperature measurements was reduced from 0.49° to 0.15°C after applying this radiation correction.

scholarly journals Solar radiation exposure of shielded air temperature sensors and measurement error evaluation in an urban environment: a preliminary study in Florence, Italy

2009 ◽  
Vol 3 (1) ◽  
pp. 9-12 ◽  
Author(s):  
M. Petralli ◽  
L. Massetti ◽  
S. Orlandini
Keyword(s):  
Solar Radiation ◽  
Radiation Exposure ◽  
Air Temperature ◽  
Urban Areas ◽  
Thermal Conditions ◽  
Surface Characteristics ◽  
Temperature Sensors ◽  
Island Effect ◽  
Synoptic Conditions ◽  
Solar Radiation Exposure

Abstract. Particularly in summer, thermal conditions in urban areas are influenced by solar radiation and human health can be strongly affected by the higher temperature regime increased by the Urban Heat Island effect (UHI). Many studies have been carried out to estimate the temperature distribution in urban areas and some of these use or are based on data collected by meteorological instruments placed within the cities. At microscale, temperature collected by sensors can be influenced by the underlying surface characteristics and the closeness to warm surfaces. The aim of this study is to investigate how different exposure to solar radiation can affect air temperature measurement in streets and gardens. The study was carried out on two different areas in Florence during summer 2007. Shielded air temperature sensors were placed in a street of a high density built-up area and in a green area. Each area was monitored by two sensors, sited in different solar radiation exposure: one in a sunny area and the other in a shaded one. A preliminary data analysis showed a difference in every site between the air temperature values collected by the two sensors especially from the morning to the afternoon. The relationship between air temperature differences and synoptic meteorological conditions were also analyzed. In conclusion, the solar radiation exposure of a monitoring station is an important parameter that must be considered both during the instruments siting and the analysis of data collected by sensors previously placed. The result of this study shows that during particular synoptic conditions, data collected by the two sensors of the same area can be different.

scholarly journals A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

Sensors ◽  
2012 ◽  
Vol 12 (11) ◽  
pp. 15750-15777 ◽  
Author(s):  
Pedro Ferreira ◽  
João Gomes ◽  
Igor Martins ◽  
António Ruano
Keyword(s):  
Neural Network ◽  
Solar Radiation ◽  
Air Temperature

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

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