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Range limit check for sunshine duration

Angstrom-Prescott model. R/Ro = a + b (S/So). Clearness index. K = R/Ro. S.Valentino alla Mutta. INMS Solar Network. Dobbiaco. M.Paganella. Pian Rosà. Udine. Treviso. Novara. Trieste. Milano. Verona. Torino. Piacenza. Solar radiation and sunshine duration. Cervia. M.Cimone.

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Range limit check for sunshine duration

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  1. Angstrom-Prescott model R/Ro = a + b (S/So) Clearness index K = R/Ro S.Valentino alla Mutta INMS Solar Network Dobbiaco M.Paganella Pian Rosà Udine Treviso Novara Trieste Milano Verona Torino Piacenza Solar radiation and sunshine duration Cervia M.Cimone C.Mele Sunshine duration Pisa Solar Radiation I.Elba Grosseto M.Terminillo Viterbo Termoli Vigna di Valle Ciampino M.S.Angelo Campobasso Pratica di Mare Ro(X,D) Amendola Grazzanise I.Ponza Brindisi C.Caccia UB UB and LB carry out a noteworthy restriction of the admissible area for each couple of measures (S(X,D),R(X,D)) C.Palinuro C.Bellavista S.M.Leuca Decimomannu M.Scuro Cagliari Elmas (S(X,D),R(X,D)) Global solar radiation (MJ/m2) I.Ustica Messina LB Trapani Catania Gela I. Pantelleria Cozzo Spadaro Sunshine duration (hours) So(X,D) References A. Angstrom, Solar and terrestrial radiation. Quatern. J. Roy. Meteorol. Soc., 50,(1924)121-125. J.A. Prescott, J.N. Black, C.W. Bonython, Solar radiationand the duration of sunshine. Q. J. R. Meteorol. Soc. 84 (1954), pp. 231–235. J.A. Duffie, W.A. Beckman, Solar Engineering of Thermal Processes, 2nd Ed. Wiley-Interscience, New York. (1991). WMO No. 485, Manual on the Global Data-Processing System. Ed. 1992. WMO No. 8, Guide to meteorological instruments and methods of observation. Ed. 2006. Improvements of the quality control system for solar radiation and sunshine duration data at the Centre of Meteorological Experimentations (ReSMA) of the Italian Air Force National Met Service (INMS) S. Vergari, F. Foti, E. Vuerich, P. Cucchiarelli and T. Iorio ReSMA - Centre of Meteorological Experimentations, via Braccianese Claudia Km 20.100, 00062 Bracciano, Italy. Tel. +39 06 9988 7701; Fax +39 06 9987 297 E-mail: stefania.vergari@aeronautica.difesa.it; {vergari, foti, vuerich}@meteoam.it Introduction Solar radiation and sunshine duration are two of the most important variables in the energy budget of the Earth. They play a fundamental role in the performance estimation of renewable energy systems and in many other applications (ecological building designs, agriculture, human healthy). An effective system of quality control therefore need to ensure that only acceptable data could be collectedanddata meet the quality requirements for the intended application. In order to improve quality control checks for global solar radiation and sunshine duration data of the INMS network, we implemented two different quality controls. A range limit check, applied to both variables separately, concerns the respect of variables’ physical limits and has been improved varying physical limits in agreement to the latitude and the season. An internal consistency check, applied for the first time in 2009, provides a physically real area when both measures are available simultaneously. From the climatic history of each site, by applying the linear form of the Angstrom-Prescott model, the atmospheric clearness index has been monthly calculated. Then an upper and a lower bound for a value of solar radiation are defined as linear functions of this index and the sunshine duration. The Centre of Meteorological Experimentation of Vigna di Valle (42°04’49” N; 12°12’41” E; 266 m a.s.l.), collects solar data from the INMS solar network.Solar radiation and sunshine duration data is checked by a quality control system and delivered to the World Radiation Data Center (WRDC) of St. Petersburg (Russia). R : amount of measured daily solar radiation Ro : extraterrestrial daily solar radiation S : number of sunshine hours daily recorded So : maximum day length a,b: regression constants monthly determined CM 11 K&Z Method Results Range limit check for sunshine duration Year: 2009 If S(X,D) = sunshine duration (hours) of the day D at the meteorological station X Amount of daily data checked: ~ 18000 0 ≤ S(D,X) ≤ So(X,D) where So(X,D) = maximum day length of day D at the latitude of X Detected errors: 1.8% Range limit check for global solar radiation Corrections done: 0.5% If R(X,D) = Global solar radiation (MJ/m2) of the day D at the meteorological station X Erased data*: 1.2% 0 ≤ R(D,X) < Ro(X,D) False detections: 0.1% where Ro(X,D) = extraterrestrial radiation for day D at the latitude of X *Data recovery not achievable because of mainly concerns solar radiation data corrupted by instrumentation breakdown. Internal consistency check Given S(X,D) LB(K, S(X,D)) ≤ R(D,X) < UB(K, S(X,D)) Where functions LB(K, S(X,D)) and UB(K, S(X,D)) depend on the clearness index K (monthly determined site by site) which aims to consider the availability of solar radiation incoming in the atmosphere. In UB, K lessens the extraterrestrial upper limit Ro(X,D), according to the hours of sunshine duration recorded. In LB, K heightens the lower limit of direct solar irradiance equal to 120 W/m2 multiplied by the hours of sunshine duration recorded. In the graphical example 2 errors detected UB that, at manual inspection on row data, resulted LB 2 real errors on sunshine duration values The control quality system is implemented by a MATLAB code: it takes as input daily or hourly values for both variables and gives as output monthly reports of detected errors (graphics production is optional). A table of clearness indexes K, monthly computed for each solar station, is also required in order to compute UB and LB. Regression constants of the Angstrom-Prescott model, needed to compute K, are derived from historical series of solar variables. Slopes ofUB and LB vary both site by site and monthly Conclusions and future work The purpose of this work is to realize a selective quality control for global solar radiation and sunshine duration data, involving a range limit check together with an internal consistency check working on both hourly and daily data. The aim is to perform a finer control on data reducing as much as possible the number of false errors detected. In the near future, the increasing number of automatic weather station, provided with high performance instrumentation, will imply a quickly grow of the amount of data to manage; a finer automatic quality control system is therefore needful to ensure, to the scientific communities, the respect of international quality standards.

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